A comparison of two sampling approaches for assessing the urban forest canopy cover from aerial photography.

Science.gov (United States)

Ucar Zennure; Pete Bettinger; Krista Merry; Jacek Siry; J.M. Bowker

2016-01-01

Two different sampling approaches for estimating urban tree canopy cover were applied to two medium-sized cities in the United States, in conjunction with two freely available remotely sensed imagery products. A random point-based sampling approach, which involved 1000 sample points, was compared against a plot/grid sampling (cluster sampling) approach that involved a...

'Intelligent' approach to radioimmunoassay sample counting employing a microprocessor controlled sample counter

International Nuclear Information System (INIS)

Ekins, R.P.; Sufi, S.; Malan, P.G.

1977-01-01

The enormous impact on medical science in the last two decades of microanalytical techniques employing radioisotopic labels has, in turn, generated a large demand for automatic radioisotopic sample counters. Such instruments frequently comprise the most important item of capital equipment required in the use of radioimmunoassay and related techniques and often form a principle bottleneck in the flow of samples through a busy laboratory. It is therefore particularly imperitive that such instruments should be used 'intelligently' and in an optimal fashion to avoid both the very large capital expenditure involved in the unnecessary proliferation of instruments and the time delays arising from their sub-optimal use. The majority of the current generation of radioactive sample counters nevertheless rely on primitive control mechanisms based on a simplistic statistical theory of radioactive sample counting which preclude their efficient and rational use. The fundamental principle upon which this approach is based is that it is useless to continue counting a radioactive sample for a time longer than that required to yield a significant increase in precision of the measurement. Thus, since substantial experimental errors occur during sample preparation, these errors should be assessed and must be releted to the counting errors for that sample. It is the objective of this presentation to demonstrate that the combination of a realistic statistical assessment of radioactive sample measurement, together with the more sophisticated control mechanisms that modern microprocessor technology make possible, may often enable savings in counter usage of the order of 5-10 fold to be made. (orig.) [de

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Directory of Open Access Journals (Sweden)

Ling-Yu Duan

2010-01-01

Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Directory of Open Access Journals (Sweden)

Tian Yonghong

2010-01-01

Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

A double-loop adaptive sampling approach for sensitivity-free dynamic reliability analysis

International Nuclear Information System (INIS)

Wang, Zequn; Wang, Pingfeng

2015-01-01

Dynamic reliability measures reliability of an engineered system considering time-variant operation condition and component deterioration. Due to high computational costs, conducting dynamic reliability analysis at an early system design stage remains challenging. This paper presents a confidence-based meta-modeling approach, referred to as double-loop adaptive sampling (DLAS), for efficient sensitivity-free dynamic reliability analysis. The DLAS builds a Gaussian process (GP) model sequentially to approximate extreme system responses over time, so that Monte Carlo simulation (MCS) can be employed directly to estimate dynamic reliability. A generic confidence measure is developed to evaluate the accuracy of dynamic reliability estimation while using the MCS approach based on developed GP models. A double-loop adaptive sampling scheme is developed to efficiently update the GP model in a sequential manner, by considering system input variables and time concurrently in two sampling loops. The model updating process using the developed sampling scheme can be terminated once the user defined confidence target is satisfied. The developed DLAS approach eliminates computationally expensive sensitivity analysis process, thus substantially improves the efficiency of dynamic reliability analysis. Three case studies are used to demonstrate the efficacy of DLAS for dynamic reliability analysis. - Highlights: • Developed a novel adaptive sampling approach for dynamic reliability analysis. • POD Developed a new metric to quantify the accuracy of dynamic reliability estimation. • Developed a new sequential sampling scheme to efficiently update surrogate models. • Three case studies were used to demonstrate the efficacy of the new approach. • Case study results showed substantially enhanced efficiency with high accuracy

Species richness in soil bacterial communities: a proposed approach to overcome sample size bias.

Science.gov (United States)

Youssef, Noha H; Elshahed, Mostafa S

2008-09-01

Estimates of species richness based on 16S rRNA gene clone libraries are increasingly utilized to gauge the level of bacterial diversity within various ecosystems. However, previous studies have indicated that regardless of the utilized approach, species richness estimates obtained are dependent on the size of the analyzed clone libraries. We here propose an approach to overcome sample size bias in species richness estimates in complex microbial communities. Parametric (Maximum likelihood-based and rarefaction curve-based) and non-parametric approaches were used to estimate species richness in a library of 13,001 near full-length 16S rRNA clones derived from soil, as well as in multiple subsets of the original library. Species richness estimates obtained increased with the increase in library size. To obtain a sample size-unbiased estimate of species richness, we calculated the theoretical clone library sizes required to encounter the estimated species richness at various clone library sizes, used curve fitting to determine the theoretical clone library size required to encounter the "true" species richness, and subsequently determined the corresponding sample size-unbiased species richness value. Using this approach, sample size-unbiased estimates of 17,230, 15,571, and 33,912 were obtained for the ML-based, rarefaction curve-based, and ACE-1 estimators, respectively, compared to bias-uncorrected values of 15,009, 11,913, and 20,909.

An 'intelligent' approach to radioimmunoassay sample counting employing a microprocessor-controlled sample counter

International Nuclear Information System (INIS)

Ekins, R.P.; Sufi, S.; Malan, P.G.

1978-01-01

The enormous impact on medical science in the last two decades of microanalytical techniques employing radioisotopic labels has, in turn, generated a large demand for automatic radioisotopic sample counters. Such instruments frequently comprise the most important item of capital equipment required in the use of radioimmunoassay and related techniques and often form a principle bottleneck in the flow of samples through a busy laboratory. It is therefore imperative that such instruments should be used 'intelligently' and in an optimal fashion to avoid both the very large capital expenditure involved in the unnecessary proliferation of instruments and the time delays arising from their sub-optimal use. Most of the current generation of radioactive sample counters nevertheless rely on primitive control mechanisms based on a simplistic statistical theory of radioactive sample counting which preclude their efficient and rational use. The fundamental principle upon which this approach is based is that it is useless to continue counting a radioactive sample for a time longer than that required to yield a significant increase in precision of the measurement. Thus, since substantial experimental errors occur during sample preparation, these errors should be assessed and must be related to the counting errors for that sample. The objective of the paper is to demonstrate that the combination of a realistic statistical assessment of radioactive sample measurement, together with the more sophisticated control mechanisms that modern microprocessor technology make possible, may often enable savings in counter usage of the order of 5- to 10-fold to be made. (author)

Approach-Induced Biases in Human Information Sampling.

Directory of Open Access Journals (Sweden)

Laurence T Hunt

2016-11-01

Full Text Available Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here, we investigated a potential role for Pavlovian approach in biasing which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled ("positive evidence approach", the selection of which information to sample ("sampling the favorite", and the interaction between information sampling and subsequent choices ("rejecting unsampled options". The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in the amount of information gathered are a stable trait across multiple gameplays and can be related to demographic measures, including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.

Calculating Confidence, Uncertainty, and Numbers of Samples When Using Statistical Sampling Approaches to Characterize and Clear Contaminated Areas

Energy Technology Data Exchange (ETDEWEB)

Piepel, Gregory F.; Matzke, Brett D.; Sego, Landon H.; Amidan, Brett G.

2013-04-27

This report discusses the methodology, formulas, and inputs needed to make characterization and clearance decisions for Bacillus anthracis-contaminated and uncontaminated (or decontaminated) areas using a statistical sampling approach. Specifically, the report includes the methods and formulas for calculating the • number of samples required to achieve a specified confidence in characterization and clearance decisions • confidence in making characterization and clearance decisions for a specified number of samples for two common statistically based environmental sampling approaches. In particular, the report addresses an issue raised by the Government Accountability Office by providing methods and formulas to calculate the confidence that a decision area is uncontaminated (or successfully decontaminated) if all samples collected according to a statistical sampling approach have negative results. Key to addressing this topic is the probability that an individual sample result is a false negative, which is commonly referred to as the false negative rate (FNR). The two statistical sampling approaches currently discussed in this report are 1) hotspot sampling to detect small isolated contaminated locations during the characterization phase, and 2) combined judgment and random (CJR) sampling during the clearance phase. Typically if contamination is widely distributed in a decision area, it will be detectable via judgment sampling during the characterization phrase. Hotspot sampling is appropriate for characterization situations where contamination is not widely distributed and may not be detected by judgment sampling. CJR sampling is appropriate during the clearance phase when it is desired to augment judgment samples with statistical (random) samples. The hotspot and CJR statistical sampling approaches are discussed in the report for four situations: 1. qualitative data (detect and non-detect) when the FNR = 0 or when using statistical sampling methods that account

State of the art of environmentally friendly sample preparation approaches for determination of PBDEs and metabolites in environmental and biological samples: A critical review.

Science.gov (United States)

Berton, Paula; Lana, Nerina B; Ríos, Juan M; García-Reyes, Juan F; Altamirano, Jorgelina C

2016-01-28

Green chemistry principles for developing methodologies have gained attention in analytical chemistry in recent decades. A growing number of analytical techniques have been proposed for determination of organic persistent pollutants in environmental and biological samples. In this light, the current review aims to present state-of-the-art sample preparation approaches based on green analytical principles proposed for the determination of polybrominated diphenyl ethers (PBDEs) and metabolites (OH-PBDEs and MeO-PBDEs) in environmental and biological samples. Approaches to lower the solvent consumption and accelerate the extraction, such as pressurized liquid extraction, microwave-assisted extraction, and ultrasound-assisted extraction, are discussed in this review. Special attention is paid to miniaturized sample preparation methodologies and strategies proposed to reduce organic solvent consumption. Additionally, extraction techniques based on alternative solvents (surfactants, supercritical fluids, or ionic liquids) are also commented in this work, even though these are scarcely used for determination of PBDEs. In addition to liquid-based extraction techniques, solid-based analytical techniques are also addressed. The development of greener, faster and simpler sample preparation approaches has increased in recent years (2003-2013). Among green extraction techniques, those based on the liquid phase predominate over those based on the solid phase (71% vs. 29%, respectively). For solid samples, solvent assisted extraction techniques are preferred for leaching of PBDEs, and liquid phase microextraction techniques are mostly used for liquid samples. Likewise, green characteristics of the instrumental analysis used after the extraction and clean-up steps are briefly discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Performance of local information-based link prediction: a sampling perspective

Science.gov (United States)

Zhao, Jichang; Feng, Xu; Dong, Li; Liang, Xiao; Xu, Ke

2012-08-01

Link prediction is pervasively employed to uncover the missing links in the snapshots of real-world networks, which are usually obtained through different kinds of sampling methods. In the previous literature, in order to evaluate the performance of the prediction, known edges in the sampled snapshot are divided into the training set and the probe set randomly, without considering the underlying sampling approaches. However, different sampling methods might lead to different missing links, especially for the biased ways. For this reason, random partition-based evaluation of performance is no longer convincing if we take the sampling method into account. In this paper, we try to re-evaluate the performance of local information-based link predictions through sampling method governed division of the training set and the probe set. It is interesting that we find that for different sampling methods, each prediction approach performs unevenly. Moreover, most of these predictions perform weakly when the sampling method is biased, which indicates that the performance of these methods might have been overestimated in the prior works.

Validity of the reduced-sample insulin modified frequently-sampled intravenous glucose tolerance test using the nonlinear regression approach.

Science.gov (United States)

Sumner, Anne E; Luercio, Marcella F; Frempong, Barbara A; Ricks, Madia; Sen, Sabyasachi; Kushner, Harvey; Tulloch-Reid, Marshall K

2009-02-01

The disposition index, the product of the insulin sensitivity index (S(I)) and the acute insulin response to glucose, is linked in African Americans to chromosome 11q. This link was determined with S(I) calculated with the nonlinear regression approach to the minimal model and data from the reduced-sample insulin-modified frequently-sampled intravenous glucose tolerance test (Reduced-Sample-IM-FSIGT). However, the application of the nonlinear regression approach to calculate S(I) using data from the Reduced-Sample-IM-FSIGT has been challenged as being not only inaccurate but also having a high failure rate in insulin-resistant subjects. Our goal was to determine the accuracy and failure rate of the Reduced-Sample-IM-FSIGT using the nonlinear regression approach to the minimal model. With S(I) from the Full-Sample-IM-FSIGT considered the standard and using the nonlinear regression approach to the minimal model, we compared the agreement between S(I) from the Full- and Reduced-Sample-IM-FSIGT protocols. One hundred African Americans (body mass index, 31.3 +/- 7.6 kg/m(2) [mean +/- SD]; range, 19.0-56.9 kg/m(2)) had FSIGTs. Glucose (0.3 g/kg) was given at baseline. Insulin was infused from 20 to 25 minutes (total insulin dose, 0.02 U/kg). For the Full-Sample-IM-FSIGT, S(I) was calculated based on the glucose and insulin samples taken at -1, 1, 2, 3, 4, 5, 6, 7, 8,10, 12, 14, 16, 19, 22, 23, 24, 25, 27, 30, 40, 50, 60, 70, 80, 90, 100, 120, 150, and 180 minutes. For the Reduced-Sample-FSIGT, S(I) was calculated based on the time points that appear in bold. Agreement was determined by Spearman correlation, concordance, and the Bland-Altman method. In addition, for both protocols, the population was divided into tertiles of S(I). Insulin resistance was defined by the lowest tertile of S(I) from the Full-Sample-IM-FSIGT. The distribution of subjects across tertiles was compared by rank order and kappa statistic. We found that the rate of failure of resolution of S(I) by

Inverse Reliability Task: Artificial Neural Networks and Reliability-Based Optimization Approaches

OpenAIRE

Lehký , David; Slowik , Ondřej; Novák , Drahomír

2014-01-01

Part 7: Genetic Algorithms; International audience; The paper presents two alternative approaches to solve inverse reliability task – to determine the design parameters to achieve desired target reliabilities. The first approach is based on utilization of artificial neural networks and small-sample simulation Latin hypercube sampling. The second approach considers inverse reliability task as reliability-based optimization task using double-loop method and also small-sample simulation. Efficie...

Pi sampling: a methodical and flexible approach to initial macromolecular crystallization screening

International Nuclear Information System (INIS)

Gorrec, Fabrice; Palmer, Colin M.; Lebon, Guillaume; Warne, Tony

2011-01-01

Pi sampling, derived from the incomplete factorial approach, is an effort to maximize the diversity of macromolecular crystallization conditions and to facilitate the preparation of 96-condition initial screens. The Pi sampling method is derived from the incomplete factorial approach to macromolecular crystallization screen design. The resulting ‘Pi screens’ have a modular distribution of a given set of up to 36 stock solutions. Maximally diverse conditions can be produced by taking into account the properties of the chemicals used in the formulation and the concentrations of the corresponding solutions. The Pi sampling method has been implemented in a web-based application that generates screen formulations and recipes. It is particularly adapted to screens consisting of 96 different conditions. The flexibility and efficiency of Pi sampling is demonstrated by the crystallization of soluble proteins and of an integral membrane-protein sample

A novel approach for small sample size family-based association studies: sequential tests.

Science.gov (United States)

Ilk, Ozlem; Rajabli, Farid; Dungul, Dilay Ciglidag; Ozdag, Hilal; Ilk, Hakki Gokhan

2011-08-01

In this paper, we propose a sequential probability ratio test (SPRT) to overcome the problem of limited samples in studies related to complex genetic diseases. The results of this novel approach are compared with the ones obtained from the traditional transmission disequilibrium test (TDT) on simulated data. Although TDT classifies single-nucleotide polymorphisms (SNPs) to only two groups (SNPs associated with the disease and the others), SPRT has the flexibility of assigning SNPs to a third group, that is, those for which we do not have enough evidence and should keep sampling. It is shown that SPRT results in smaller ratios of false positives and negatives, as well as better accuracy and sensitivity values for classifying SNPs when compared with TDT. By using SPRT, data with small sample size become usable for an accurate association analysis.

Inferring the demographic history from DNA sequences: An importance sampling approach based on non-homogeneous processes.

Science.gov (United States)

Ait Kaci Azzou, S; Larribe, F; Froda, S

2016-10-01

In Ait Kaci Azzou et al. (2015) we introduced an Importance Sampling (IS) approach for estimating the demographic history of a sample of DNA sequences, the skywis plot. More precisely, we proposed a new nonparametric estimate of a population size that changes over time. We showed on simulated data that the skywis plot can work well in typical situations where the effective population size does not undergo very steep changes. In this paper, we introduce an iterative procedure which extends the previous method and gives good estimates under such rapid variations. In the iterative calibrated skywis plot we approximate the effective population size by a piecewise constant function, whose values are re-estimated at each step. These piecewise constant functions are used to generate the waiting times of non homogeneous Poisson processes related to a coalescent process with mutation under a variable population size model. Moreover, the present IS procedure is based on a modified version of the Stephens and Donnelly (2000) proposal distribution. Finally, we apply the iterative calibrated skywis plot method to a simulated data set from a rapidly expanding exponential model, and we show that the method based on this new IS strategy correctly reconstructs the demographic history. Copyright © 2016. Published by Elsevier Inc.

Sample Entropy-Based Approach to Evaluate the Stability of Double-Wire Pulsed MIG Welding

Directory of Open Access Journals (Sweden)

Ping Yao

2014-01-01

Full Text Available According to the sample entropy, this paper deals with a quantitative method to evaluate the current stability in double-wire pulsed MIG welding. Firstly, the sample entropy of current signals with different stability but the same parameters is calculated. The results show that the more stable the current, the smaller the value and the standard deviation of sample entropy. Secondly, four parameters, which are pulse width, peak current, base current, and frequency, are selected for four-level three-factor orthogonal experiment. The calculation and analysis of desired signals indicate that sample entropy values are affected by welding current parameters. Then, a quantitative method based on sample entropy is proposed. The experiment results show that the method can preferably quantify the welding current stability.

Using machine learning to accelerate sampling-based inversion

Science.gov (United States)

Valentine, A. P.; Sambridge, M.

2017-12-01

In most cases, a complete solution to a geophysical inverse problem (including robust understanding of the uncertainties associated with the result) requires a sampling-based approach. However, the computational burden is high, and proves intractable for many problems of interest. There is therefore considerable value in developing techniques that can accelerate sampling procedures.The main computational cost lies in evaluation of the forward operator (e.g. calculation of synthetic seismograms) for each candidate model. Modern machine learning techniques-such as Gaussian Processes-offer a route for constructing a computationally-cheap approximation to this calculation, which can replace the accurate solution during sampling. Importantly, the accuracy of the approximation can be refined as inversion proceeds, to ensure high-quality results.In this presentation, we describe and demonstrate this approach-which can be seen as an extension of popular current methods, such as the Neighbourhood Algorithm, and bridges the gap between prior- and posterior-sampling frameworks.

Variable screening and ranking using sampling-based sensitivity measures

International Nuclear Information System (INIS)

Wu, Y-T.; Mohanty, Sitakanta

2006-01-01

This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables

ON SAMPLING BASED METHODS FOR THE DUBINS TRAVELING SALESMAN PROBLEM WITH NEIGHBORHOODS

Directory of Open Access Journals (Sweden)

Petr Váňa

2015-12-01

Full Text Available In this paper, we address the problem of path planning to visit a set of regions by Dubins vehicle, which is also known as the Dubins Traveling Salesman Problem Neighborhoods (DTSPN. We propose a modification of the existing sampling-based approach to determine increasing number of samples per goal region and thus improve the solution quality if a more computational time is available. The proposed modification of the sampling-based algorithm has been compared with performance of existing approaches for the DTSPN and results of the quality of the found solutions and the required computational time are presented in the paper.

Sensitivity based reduced approaches for structural reliability analysis

Indian Academy of Sciences (India)

captured by a safety-factor based approach due to the intricate nonlinear ... give the accounts of extensive research works which have been done over ... (ii) simulation based methods, for example, importance sampling (Bucher 1988; Mahade-.

A scalable method for parallelizing sampling-based motion planning algorithms

KAUST Repository

Jacobs, Sam Ade; Manavi, Kasra; Burgos, Juan; Denny, Jory; Thomas, Shawna; Amato, Nancy M.

2012-01-01

This paper describes a scalable method for parallelizing sampling-based motion planning algorithms. It subdivides configuration space (C-space) into (possibly overlapping) regions and independently, in parallel, uses standard (sequential) sampling-based planners to construct roadmaps in each region. Next, in parallel, regional roadmaps in adjacent regions are connected to form a global roadmap. By subdividing the space and restricting the locality of connection attempts, we reduce the work and inter-processor communication associated with nearest neighbor calculation, a critical bottleneck for scalability in existing parallel motion planning methods. We show that our method is general enough to handle a variety of planning schemes, including the widely used Probabilistic Roadmap (PRM) and Rapidly-exploring Random Trees (RRT) algorithms. We compare our approach to two other existing parallel algorithms and demonstrate that our approach achieves better and more scalable performance. Our approach achieves almost linear scalability on a 2400 core LINUX cluster and on a 153,216 core Cray XE6 petascale machine. © 2012 IEEE.

A scalable method for parallelizing sampling-based motion planning algorithms

KAUST Repository

Jacobs, Sam Ade

2012-05-01

This paper describes a scalable method for parallelizing sampling-based motion planning algorithms. It subdivides configuration space (C-space) into (possibly overlapping) regions and independently, in parallel, uses standard (sequential) sampling-based planners to construct roadmaps in each region. Next, in parallel, regional roadmaps in adjacent regions are connected to form a global roadmap. By subdividing the space and restricting the locality of connection attempts, we reduce the work and inter-processor communication associated with nearest neighbor calculation, a critical bottleneck for scalability in existing parallel motion planning methods. We show that our method is general enough to handle a variety of planning schemes, including the widely used Probabilistic Roadmap (PRM) and Rapidly-exploring Random Trees (RRT) algorithms. We compare our approach to two other existing parallel algorithms and demonstrate that our approach achieves better and more scalable performance. Our approach achieves almost linear scalability on a 2400 core LINUX cluster and on a 153,216 core Cray XE6 petascale machine. © 2012 IEEE.

A Fault Sample Simulation Approach for Virtual Testability Demonstration Test

Institute of Scientific and Technical Information of China (English)

ZHANG Yong; QIU Jing; LIU Guanjun; YANG Peng

2012-01-01

Virtual testability demonstration test has many advantages,such as low cost,high efficiency,low risk and few restrictions.It brings new requirements to the fault sample generation.A fault sample simulation approach for virtual testability demonstration test based on stochastic process theory is proposed.First,the similarities and differences of fault sample generation between physical testability demonstration test and virtual testability demonstration test are discussed.Second,it is pointed out that the fault occurrence process subject to perfect repair is renewal process.Third,the interarrival time distribution function of the next fault event is given.Steps and flowcharts of fault sample generation are introduced.The number of faults and their occurrence time are obtained by statistical simulation.Finally,experiments are carried out on a stable tracking platform.Because a variety of types of life distributions and maintenance modes are considered and some assumptions are removed,the sample size and structure of fault sample simulation results are more similar to the actual results and more reasonable.The proposed method can effectively guide the fault injection in virtual testability demonstration test.

On-site sampling and sample-preparation approach with a portable sampler based on hollow-fiber/graphene bars for the microextraction of nitrobenzene compounds in lake water.

Science.gov (United States)

Xing, Rongrong; Hu, Shuang; Chen, Xuan; Bai, Xiaohong; Feng, Meiqin

2015-02-01

A novel on-site sampling and sample-preparation approach was developed and evaluated in the present work. In this procedure, hollow-fiber/graphene bars (HF/GBs) were used for sampling and sample preparation. A handheld battery-operated electric egg beater was utilized to support the HF/GBs and stir the sample solution to facilitate extraction at the sampling site. Four nitrobenzene compounds (nitrobenzene, o-nitrophenol, m-nitrophenol, and p-nitrophenol) were used as model compounds. Several factors affecting performance, including types and amount of graphene used and extraction and desorption times, were investigated and optimized in the laboratory. Under optimized conditions, the enrichment factors of the four nitrobenzene compounds ranged from 46 to 69. Good linearities of 0.01-10 μg/mL with regression coefficients between 0.9917 and 0.9973 were obtained for all analytes. The LOD of the method was 0.3 ng/mL. Satisfactory recoveries (98-102%) and precision (1.0-5.8%) were also achieved. The ultrastructures and extraction mechanism of the HF/GBs were characterized and analyzed. The proposed approach coupled with high-performance liquid chromatography was successfully applied in the extraction and determination of trace nitrobenzene compounds in lake water. Experimental results showed that the approach is simple, convenient, rapid, and practical for routine environmental monitoring. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Variational Approach to Enhanced Sampling and Free Energy Calculations

Science.gov (United States)

Valsson, Omar; Parrinello, Michele

2014-08-01

The ability of widely used sampling methods, such as molecular dynamics or Monte Carlo simulations, to explore complex free energy landscapes is severely hampered by the presence of kinetic bottlenecks. A large number of solutions have been proposed to alleviate this problem. Many are based on the introduction of a bias potential which is a function of a small number of collective variables. However constructing such a bias is not simple. Here we introduce a functional of the bias potential and an associated variational principle. The bias that minimizes the functional relates in a simple way to the free energy surface. This variational principle can be turned into a practical, efficient, and flexible sampling method. A number of numerical examples are presented which include the determination of a three-dimensional free energy surface. We argue that, beside being numerically advantageous, our variational approach provides a convenient and novel standpoint for looking at the sampling problem.

An Integrated Approach Using Chaotic Map & Sample Value Difference Method for Electrocardiogram Steganography and OFDM Based Secured Patient Information Transmission.

Science.gov (United States)

Pandey, Anukul; Saini, Barjinder Singh; Singh, Butta; Sood, Neetu

2017-10-18

This paper presents a patient's confidential data hiding scheme in electrocardiogram (ECG) signal and its subsequent wireless transmission. Patient's confidential data is embedded in ECG (called stego-ECG) using chaotic map and the sample value difference approach. The sample value difference approach effectually hides the patient's confidential data in ECG sample pairs at the predefined locations. The chaotic map generates these predefined locations through the use of selective control parameters. Subsequently, the wireless transmission of the stego-ECG is analyzed using the Orthogonal Frequency Division Multiplexing (OFDM) system in a Rayleigh fading scenario for telemedicine applications. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through the statistical and clinical performance measures. Statistical measures comprise of Percentage Root-mean-square Difference (PRD), Peak Signal to Noise Ratio (PSNR), and Kulback-Leibler Divergence (KL-Div), etc. while clinical metrics includes wavelet Energy Based Diagnostic Distortion (WEDD) and Wavelet based Weighted PRD (WWPRD). The various channel Signal-to-Noise Ratio scenarios are simulated for wireless communication of stego-ECG in OFDM system. The proposed method over all the 48 records of MIT-BIH arrhythmia database resulted in average, PRD = 0.26, PSNR = 55.49, KL-Div = 3.34 × 10 -6 , WEDD = 0.02, and WWPRD = 0.10 with secret data size of 21Kb. Further, a comparative analysis of proposed method and recent existing works was also performed. The results clearly, demonstrated the superiority of proposed method.

Sampling in interview-based qualitative research: A theoretical and practical guide

OpenAIRE

Robinson, Oliver

2014-01-01

Sampling is central to the practice of qualitative methods, but compared with data collection and analysis, its processes are discussed relatively little. A four-point approach to sampling in qualitative interview-based research is presented and critically discussed in this article, which integrates theory and process for the following: (1) Defining a sample universe, by way of specifying inclusion and exclusion criteria for potential participation; (2) Deciding upon a sample size, through th...

Adaptive Rate Sampling and Filtering Based on Level Crossing Sampling

Directory of Open Access Journals (Sweden)

Saeed Mian Qaisar

2009-01-01

Full Text Available The recent sophistications in areas of mobile systems and sensor networks demand more and more processing resources. In order to maintain the system autonomy, energy saving is becoming one of the most difficult industrial challenges, in mobile computing. Most of efforts to achieve this goal are focused on improving the embedded systems design and the battery technology, but very few studies target to exploit the input signal time-varying nature. This paper aims to achieve power efficiency by intelligently adapting the processing activity to the input signal local characteristics. It is done by completely rethinking the processing chain, by adopting a non conventional sampling scheme and adaptive rate filtering. The proposed approach, based on the LCSS (Level Crossing Sampling Scheme presents two filtering techniques, able to adapt their sampling rate and filter order by online analyzing the input signal variations. Indeed, the principle is to intelligently exploit the signal local characteristics—which is usually never considered—to filter only the relevant signal parts, by employing the relevant order filters. This idea leads towards a drastic gain in the computational efficiency and hence in the processing power when compared to the classical techniques.

Sample vial inserts: A better approach for sampling heterogeneous slurry samples in the SRS Defense Waste Processing Facility

International Nuclear Information System (INIS)

Coleman, C.J.; Goode, S.R.

1996-01-01

A convenient and effective new approach for analyzing DWPF samples involves the use of inserts with volumes of 1.5--3 ml placed in the neck of 14 ml sample vials. The inserts have rims that conform to the rim of the vials so that they sit straight and stable in the vial. The DWPF tank sampling system fills the pre-weighed insert rather than the entire vial, so the vial functions only as the insert holder. The shielded cell operator then removes the vial cap and decants the insert containing the sample into a plastic bottle, crucible, etc., for analysis. Inert materials such as Teflon, plastic, and zirconium are used for the insert so it is unnecessary to separate the insert from the sample for most analyses. The key technique advantage of using inserts to take DWPF samples versus filling sample vials is that it provides a convenient and almost foolproof way of obtaining and handling small volumes of slurry samples in a shielded cell without corrupting the sample. Since the insert allows the entire sample to be analyzed, this approach eliminates the errors inherent with subsampling heterogeneous slurries that comprise DWPF samples. Slurry samples can then be analyzed with confidence. Analysis times are dramatically reduced by eliminating the drying and vitrification steps normally used to produce a homogeneous solid sample. Direct dissolution and elemental analysis of slurry samples are achieved in 8 hours or less compared with 40 hours for analysis of vitrified slurry samples. Comparison of samples taken in inserts versus full vials indicate that the insert does not significantly affect sample composition

Small sample approach, and statistical and epidemiological aspects

NARCIS (Netherlands)

Offringa, Martin; van der Lee, Hanneke

2011-01-01

In this chapter, the design of pharmacokinetic studies and phase III trials in children is discussed. Classical approaches and relatively novel approaches, which may be more useful in the context of drug research in children, are discussed. The burden of repeated blood sampling in pediatric

Phobos Sample Return: Next Approach

Science.gov (United States)

Zelenyi, Lev; Martynov, Maxim; Zakharov, Alexander; Korablev, Oleg; Ivanov, Alexey; Karabadzak, George

The Martian moons still remain a mystery after numerous studies by Mars orbiting spacecraft. Their study cover three major topics related to (1) Solar system in general (formation and evolution, origin of planetary satellites, origin and evolution of life); (2) small bodies (captured asteroid, or remnants of Mars formation, or reaccreted Mars ejecta); (3) Mars (formation and evolution of Mars; Mars ejecta at the satellites). As reviewed by Galimov [2010] most of the above questions require the sample return from the Martian moon, while some (e.g. the characterization of the organic matter) could be also answered by in situ experiments. There is the possibility to obtain the sample of Mars material by sampling Phobos: following to Chappaz et al. [2012] a 200-g sample could contain 10-7 g of Mars surface material launched during the past 1 mln years, or 5*10-5 g of Mars material launched during the past 10 mln years, or 5*1010 individual particles from Mars, quantities suitable for accurate laboratory analyses. The studies of Phobos have been of high priority in the Russian program on planetary research for many years. Phobos-88 mission consisted of two spacecraft (Phobos-1, Phobos-2) and aimed the approach to Phobos at 50 m and remote studies, and also the release of small landers (long-living stations DAS). This mission implemented the program incompletely. It was returned information about the Martian environment and atmosphere. The next profect Phobos Sample Return (Phobos-Grunt) initially planned in early 2000 has been delayed several times owing to budget difficulties; the spacecraft failed to leave NEO in 2011. The recovery of the science goals of this mission and the delivery of the samples of Phobos to Earth remain of highest priority for Russian scientific community. The next Phobos SR mission named Boomerang was postponed following the ExoMars cooperation, but is considered the next in the line of planetary exploration, suitable for launch around 2022. A

Sample preparation with solid phase microextraction and exhaustive extraction approaches: Comparison for challenging cases.

Science.gov (United States)

Boyacı, Ezel; Rodríguez-Lafuente, Ángel; Gorynski, Krzysztof; Mirnaghi, Fatemeh; Souza-Silva, Érica A; Hein, Dietmar; Pawliszyn, Janusz

2015-05-11

In chemical analysis, sample preparation is frequently considered the bottleneck of the entire analytical method. The success of the final method strongly depends on understanding the entire process of analysis of a particular type of analyte in a sample, namely: the physicochemical properties of the analytes (solubility, volatility, polarity etc.), the environmental conditions, and the matrix components of the sample. Various sample preparation strategies have been developed based on exhaustive or non-exhaustive extraction of analytes from matrices. Undoubtedly, amongst all sample preparation approaches, liquid extraction, including liquid-liquid (LLE) and solid phase extraction (SPE), are the most well-known, widely used, and commonly accepted methods by many international organizations and accredited laboratories. Both methods are well documented and there are many well defined procedures, which make them, at first sight, the methods of choice. However, many challenging tasks, such as complex matrix applications, on-site and in vivo applications, and determination of matrix-bound and free concentrations of analytes, are not easily attainable with these classical approaches for sample preparation. In the last two decades, the introduction of solid phase microextraction (SPME) has brought significant progress in the sample preparation area by facilitating on-site and in vivo applications, time weighted average (TWA) and instantaneous concentration determinations. Recently introduced matrix compatible coatings for SPME facilitate direct extraction from complex matrices and fill the gap in direct sampling from challenging matrices. Following introduction of SPME, numerous other microextraction approaches evolved to address limitations of the above mentioned techniques. There is not a single method that can be considered as a universal solution for sample preparation. This review aims to show the main advantages and limitations of the above mentioned sample

Automated Generation of OCL Constraints: NL based Approach vs Pattern Based Approach

Directory of Open Access Journals (Sweden)

IMRAN SARWAR BAJWA

2017-04-01

Full Text Available This paper presents an approach used for automated generations of software constraints. In this model, the SBVR (Semantics of Business Vocabulary and Rules based semi-formal representation is obtained from the syntactic and semantic analysis of a NL (Natural Language (such as English sentence. A SBVR representation is easy to translate to other formal languages as SBVR is based on higher-order logic like other formal languages such as OCL (Object Constraint Language. The proposed model endows with a systematic and powerful system of incorporating NL knowledge on the formal languages. A prototype is constructed in Java (an Eclipse plug-in as a proof of the concept. The performance was tested for a few sample texts taken from existing research thesis reports and books

A Variational Approach to Enhanced Sampling and Free Energy Calculations

Science.gov (United States)

Parrinello, Michele

2015-03-01

The presence of kinetic bottlenecks severely hampers the ability of widely used sampling methods like molecular dynamics or Monte Carlo to explore complex free energy landscapes. One of the most popular methods for addressing this problem is umbrella sampling which is based on the addition of an external bias which helps overcoming the kinetic barriers. The bias potential is usually taken to be a function of a restricted number of collective variables. However constructing the bias is not simple, especially when the number of collective variables increases. Here we introduce a functional of the bias which, when minimized, allows us to recover the free energy. We demonstrate the usefulness and the flexibility of this approach on a number of examples which include the determination of a six dimensional free energy surface. Besides the practical advantages, the existence of such a variational principle allows us to look at the enhanced sampling problem from a rather convenient vantage point.

Generating samples for association studies based on HapMap data

Directory of Open Access Journals (Sweden)

Chen Yixuan

2008-01-01

Full Text Available Abstract Background With the completion of the HapMap project, a variety of computational algorithms and tools have been proposed for haplotype inference, tag SNP selection and genome-wide association studies. Simulated data are commonly used in evaluating these new developed approaches. In addition to simulations based on population models, empirical data generated by perturbing real data, has also been used because it may inherit specific properties from real data. However, there is no tool that is publicly available to generate large scale simulated variation data by taking into account knowledge from the HapMap project. Results A computer program (gs was developed to quickly generate a large number of samples based on real data that are useful for a variety of purposes, including evaluating methods for haplotype inference, tag SNP selection and association studies. Two approaches have been implemented to generate dense SNP haplotype/genotype data that share similar local linkage disequilibrium (LD patterns as those in human populations. The first approach takes haplotype pairs from samples as inputs, and the second approach takes patterns of haplotype block structures as inputs. Both quantitative and qualitative traits have been incorporated in the program. Phenotypes are generated based on a disease model, or based on the effect of a quantitative trait nucleotide, both of which can be specified by users. In addition to single-locus disease models, two-locus disease models have also been implemented that can incorporate any degree of epistasis. Users are allowed to specify all nine parameters in a 3 × 3 penetrance table. For several commonly used two-locus disease models, the program can automatically calculate penetrances based on the population prevalence and marginal effects of a disease that users can conveniently specify. Conclusion The program gs can effectively generate large scale genetic and phenotypic variation data that can be

Screen Space Ambient Occlusion Based Multiple Importance Sampling for Real-Time Rendering

Science.gov (United States)

Zerari, Abd El Mouméne; Babahenini, Mohamed Chaouki

2018-03-01

We propose a new approximation technique for accelerating the Global Illumination algorithm for real-time rendering. The proposed approach is based on the Screen-Space Ambient Occlusion (SSAO) method, which approximates the global illumination for large, fully dynamic scenes at interactive frame rates. Current algorithms that are based on the SSAO method suffer from difficulties due to the large number of samples that are required. In this paper, we propose an improvement to the SSAO technique by integrating it with a Multiple Importance Sampling technique that combines a stratified sampling method with an importance sampling method, with the objective of reducing the number of samples. Experimental evaluation demonstrates that our technique can produce high-quality images in real time and is significantly faster than traditional techniques.

A New Approach To Soil Sampling For Risk Assessment Of Nutrient Mobilisation.

Science.gov (United States)

Jonczyk, J. C.; Owen, G. J.; Snell, M. A.; Barber, N.; Benskin, C.; Reaney, S. M.; Haygarth, P.; Quinn, P. F.; Barker, P. A.; Aftab, A.; Burke, S.; Cleasby, W.; Surridge, B.; Perks, M. T.

2016-12-01

Traditionally, risks of nutrient and sediment losses from soils are assessed through a combination of field soil nutrient values on soil samples taken over the whole field and the proximity of the field to water courses. The field average nutrient concentration of the soil is used by farmers to determine fertiliser needs. These data are often used by scientists to assess the risk of nutrient losses to water course, though are not really `fit' for this purpose. The Eden Demonstration Test Catchment (http://www.edendtc.org.uk/) is a research project based in the River Eden catchment, NW UK, with the aim of cost effectively mitigating diffuse pollution from agriculture whilst maintaining agricultural productivity. Three instrumented focus catchments have been monitored since 2011, providing high resolution in-stream chemistry and ecological data, alongside some spatial data on soils, land use and nutrient inputs. An approach to mitigation was demonstrated in a small sub-catchment, where surface runoff was identified as the key drivers of nutrient losses, using a suite of runoff attenuation features. Other issues identified were management of hard- standings and soil compaction. A new approach for evaluating nutrient losses from soils is assessed in the Eden DTC project. The Sensitive Catchment Integrated Modelling and Prediction (SCIMAP) model is a risk-mapping framework designed to identify where in the landscape diffuse pollution is most likely to be originating (http://www.scimap.org.uk) and was used to look at the spatial pattern of erosion potential. The aim of this work was to assess if erosion potential identified through the model could be used to inform a new soil sampling strategy, to better assess risk of erosion and risk of transport of sediment-bound phosphorus. Soil samples were taken from areas with different erosion potential. The chemical analysis of these targeted samples are compared to those obtained using more traditional sampling approaches

Design-based estimators for snowball sampling

OpenAIRE

Shafie, Termeh

2010-01-01

Snowball sampling, where existing study subjects recruit further subjects from amongtheir acquaintances, is a popular approach when sampling from hidden populations.Since people with many in-links are more likely to be selected, there will be a selectionbias in the samples obtained. In order to eliminate this bias, the sample data must beweighted. However, the exact selection probabilities are unknown for snowball samplesand need to be approximated in an appropriate way. This paper proposes d...

The role of graphene-based sorbents in modern sample preparation techniques.

Science.gov (United States)

de Toffoli, Ana Lúcia; Maciel, Edvaldo Vasconcelos Soares; Fumes, Bruno Henrique; Lanças, Fernando Mauro

2018-01-01

The application of graphene-based sorbents in sample preparation techniques has increased significantly since 2011. These materials have good physicochemical properties to be used as sorbent and have shown excellent results in different sample preparation techniques. Graphene and its precursor graphene oxide have been considered to be good candidates to improve the extraction and concentration of different classes of target compounds (e.g., parabens, polycyclic aromatic hydrocarbon, pyrethroids, triazines, and so on) present in complex matrices. Its applications have been employed during the analysis of different matrices (e.g., environmental, biological and food). In this review, we highlight the most important characteristics of graphene-based material, their properties, synthesis routes, and the most important applications in both off-line and on-line sample preparation techniques. The discussion of the off-line approaches includes methods derived from conventional solid-phase extraction focusing on the miniaturized magnetic and dispersive modes. The modes of microextraction techniques called stir bar sorptive extraction, solid phase microextraction, and microextraction by packed sorbent are discussed. The on-line approaches focus on the use of graphene-based material mainly in on-line solid phase extraction, its variation called in-tube solid-phase microextraction, and on-line microdialysis systems. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sampling Key Populations for HIV Surveillance: Results From Eight Cross-Sectional Studies Using Respondent-Driven Sampling and Venue-Based Snowball Sampling.

Science.gov (United States)

Rao, Amrita; Stahlman, Shauna; Hargreaves, James; Weir, Sharon; Edwards, Jessie; Rice, Brian; Kochelani, Duncan; Mavimbela, Mpumelelo; Baral, Stefan

2017-10-20

In using regularly collected or existing surveillance data to characterize engagement in human immunodeficiency virus (HIV) services among marginalized populations, differences in sampling methods may produce different pictures of the target population and may therefore result in different priorities for response. The objective of this study was to use existing data to evaluate the sample distribution of eight studies of female sex workers (FSW) and men who have sex with men (MSM), who were recruited using different sampling approaches in two locations within Sub-Saharan Africa: Manzini, Swaziland and Yaoundé, Cameroon. MSM and FSW participants were recruited using either respondent-driven sampling (RDS) or venue-based snowball sampling. Recruitment took place between 2011 and 2016. Participants at each study site were administered a face-to-face survey to assess sociodemographics, along with the prevalence of self-reported HIV status, frequency of HIV testing, stigma, and other HIV-related characteristics. Crude and RDS-adjusted prevalence estimates were calculated. Crude prevalence estimates from the venue-based snowball samples were compared with the overlap of the RDS-adjusted prevalence estimates, between both FSW and MSM in Cameroon and Swaziland. RDS samples tended to be younger (MSM aged 18-21 years in Swaziland: 47.6% [139/310] in RDS vs 24.3% [42/173] in Snowball, in Cameroon: 47.9% [99/306] in RDS vs 20.1% [52/259] in Snowball; FSW aged 18-21 years in Swaziland 42.5% [82/325] in RDS vs 8.0% [20/249] in Snowball; in Cameroon 15.6% [75/576] in RDS vs 8.1% [25/306] in Snowball). They were less educated (MSM: primary school completed or less in Swaziland 42.6% [109/310] in RDS vs 4.0% [7/173] in Snowball, in Cameroon 46.2% [138/306] in RDS vs 14.3% [37/259] in Snowball; FSW: primary school completed or less in Swaziland 86.6% [281/325] in RDS vs 23.9% [59/247] in Snowball, in Cameroon 87.4% [520/576] in RDS vs 77.5% [238/307] in Snowball) than the snowball

Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms

KAUST Repository

Fidel, Adam; Jacobs, Sam Ade; Sharma, Shishir; Amato, Nancy M.; Rauchwerger, Lawrence

2014-01-01

Motion planning, which is the problem of computing feasible paths in an environment for a movable object, has applications in many domains ranging from robotics, to intelligent CAD, to protein folding. The best methods for solving this PSPACE-hard problem are so-called sampling-based planners. Recent work introduced uniform spatial subdivision techniques for parallelizing sampling-based motion planning algorithms that scaled well. However, such methods are prone to load imbalance, as planning time depends on region characteristics and, for most problems, the heterogeneity of the sub problems increases as the number of processors increases. In this work, we introduce two techniques to address load imbalance in the parallelization of sampling-based motion planning algorithms: an adaptive work stealing approach and bulk-synchronous redistribution. We show that applying these techniques to representatives of the two major classes of parallel sampling-based motion planning algorithms, probabilistic roadmaps and rapidly-exploring random trees, results in a more scalable and load-balanced computation on more than 3,000 cores. © 2014 IEEE.

Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms

KAUST Repository

Fidel, Adam

2014-05-01

Motion planning, which is the problem of computing feasible paths in an environment for a movable object, has applications in many domains ranging from robotics, to intelligent CAD, to protein folding. The best methods for solving this PSPACE-hard problem are so-called sampling-based planners. Recent work introduced uniform spatial subdivision techniques for parallelizing sampling-based motion planning algorithms that scaled well. However, such methods are prone to load imbalance, as planning time depends on region characteristics and, for most problems, the heterogeneity of the sub problems increases as the number of processors increases. In this work, we introduce two techniques to address load imbalance in the parallelization of sampling-based motion planning algorithms: an adaptive work stealing approach and bulk-synchronous redistribution. We show that applying these techniques to representatives of the two major classes of parallel sampling-based motion planning algorithms, probabilistic roadmaps and rapidly-exploring random trees, results in a more scalable and load-balanced computation on more than 3,000 cores. © 2014 IEEE.

An inversion-relaxation approach for sampling stationary points of spin model Hamiltonians

International Nuclear Information System (INIS)

Hughes, Ciaran; Mehta, Dhagash; Wales, David J.

2014-01-01

Sampling the stationary points of a complicated potential energy landscape is a challenging problem. Here, we introduce a sampling method based on relaxation from stationary points of the highest index of the Hessian matrix. We illustrate how this approach can find all the stationary points for potentials or Hamiltonians bounded from above, which includes a large class of important spin models, and we show that it is far more efficient than previous methods. For potentials unbounded from above, the relaxation part of the method is still efficient in finding minima and transition states, which are usually the primary focus of attention for atomistic systems

Cross validation of two partitioning-based sampling approaches in mesocosms containing PCB contaminated field sediment, biota, and activated carbon amendment

DEFF Research Database (Denmark)

Nørgaard Schmidt, Stine; Wang, Alice P.; Gidley, Philip T

2017-01-01

with multiple thicknesses of silicone and in situ pre-equilibrium sampling with low density polyethylene (LDPE) loaded with performance reference compounds were applied independently to measure polychlorinated biphenyls (PCBs) in mesocosms with (1) New Bedford Harbor sediment (MA, USA), (2) sediment and biota......, and (3) activated carbon amended sediment and biota. The aim was to cross validate the two different sampling approaches. Around 100 PCB congeners were quantified in the two sampling polymers, and the results confirmed the good precision of both methods and were in overall good agreement with recently...... published silicone to LDPE partition ratios. Further, the methods yielded Cfree in good agreement for all three experiments. The average ratio between Cfree determined by the two methods was factor 1.4±0.3 (range: 0.6-2.0), and the results thus cross-validated the two sampling approaches. For future...

Exploring hadronic tau identification with DC1 datat samples a track based approach

CERN Document Server

Richter-Was, Elzbieta; Tarrade, F

2004-01-01

In this note we discuss the identification of hadronic $\\tau$s. We propose an algorithm, tauID, which starts from a reconstructed, relatively high pT track and then collects calorimetric energy deposition in a fixed cone seeded by the track eta and phi at the vertex. With the proposed algorithm we explore exclusive features of the hadronic $\\tau$ decays and we indicate also the possibility of using an energy-flow based approach for defining the energy scale of the reconstructed tau-candidates. The results presented here are limited to the barrel region (|eta| < 1.5) and are based on the DC1 events simulated without pile-up and electronic noise. We compare the performances of the proposed algorithm and of the base-line tauRec algorithm and draw some conclusions for further studies.

Evaluating the effect of disturbed ensemble distributions on SCFG based statistical sampling of RNA secondary structures

Directory of Open Access Journals (Sweden)

Scheid Anika

2012-07-01

Full Text Available Abstract Background Over the past years, statistical and Bayesian approaches have become increasingly appreciated to address the long-standing problem of computational RNA structure prediction. Recently, a novel probabilistic method for the prediction of RNA secondary structures from a single sequence has been studied which is based on generating statistically representative and reproducible samples of the entire ensemble of feasible structures for a particular input sequence. This method samples the possible foldings from a distribution implied by a sophisticated (traditional or length-dependent stochastic context-free grammar (SCFG that mirrors the standard thermodynamic model applied in modern physics-based prediction algorithms. Specifically, that grammar represents an exact probabilistic counterpart to the energy model underlying the Sfold software, which employs a sampling extension of the partition function (PF approach to produce statistically representative subsets of the Boltzmann-weighted ensemble. Although both sampling approaches have the same worst-case time and space complexities, it has been indicated that they differ in performance (both with respect to prediction accuracy and quality of generated samples, where neither of these two competing approaches generally outperforms the other. Results In this work, we will consider the SCFG based approach in order to perform an analysis on how the quality of generated sample sets and the corresponding prediction accuracy changes when different degrees of disturbances are incorporated into the needed sampling probabilities. This is motivated by the fact that if the results prove to be resistant to large errors on the distinct sampling probabilities (compared to the exact ones, then it will be an indication that these probabilities do not need to be computed exactly, but it may be sufficient and more efficient to approximate them. Thus, it might then be possible to decrease the worst

A New Acoustic Emission Sensor Based Gear Fault Detection Approach

Directory of Open Access Journals (Sweden)

Junda Zhu

2013-01-01

Full Text Available In order to reduce wind energy costs, prognostics and health management (PHM of wind turbine is needed to ensure the reliability and availability of wind turbines. A gearbox is an important component of a wind turbine. Therefore, developing effective gearbox fault detection tools is important to the PHM of wind turbine. In this paper, a new acoustic emission (AE sensor based gear fault detection approach is presented. This approach combines a heterodyne based frequency reduction technique with time synchronous average (TSA and spectrum kurtosis (SK to process AE sensor signals and extract features as condition indictors for gear fault detection. Heterodyne technique commonly used in communication is first employed to preprocess the AE signals before sampling. By heterodyning, the AE signal frequency is down shifted from several hundred kHz to below 50 kHz. This reduced AE signal sampling rate is comparable to that of vibration signals. The presented approach is validated using seeded gear tooth crack fault tests on a notational split torque gearbox. The approach presented in this paper is physics based and the validation results have showed that it could effectively detect the gear faults.

Improved mesh based photon sampling techniques for neutron activation analysis

International Nuclear Information System (INIS)

Relson, E.; Wilson, P. P. H.; Biondo, E. D.

2013-01-01

The design of fusion power systems requires analysis of neutron activation of large, complex volumes, and the resulting particles emitted from these volumes. Structured mesh-based discretization of these problems allows for improved modeling in these activation analysis problems. Finer discretization of these problems results in large computational costs, which drives the investigation of more efficient methods. Within an ad hoc subroutine of the Monte Carlo transport code MCNP, we implement sampling of voxels and photon energies for volumetric sources using the alias method. The alias method enables efficient sampling of a discrete probability distribution, and operates in 0(1) time, whereas the simpler direct discrete method requires 0(log(n)) time. By using the alias method, voxel sampling becomes a viable alternative to sampling space with the 0(1) approach of uniformly sampling the problem volume. Additionally, with voxel sampling it is straightforward to introduce biasing of volumetric sources, and we implement this biasing of voxels as an additional variance reduction technique that can be applied. We verify our implementation and compare the alias method, with and without biasing, to direct discrete sampling of voxels, and to uniform sampling. We study the behavior of source biasing in a second set of tests and find trends between improvements and source shape, material, and material density. Overall, however, the magnitude of improvements from source biasing appears to be limited. Future work will benefit from the implementation of efficient voxel sampling - particularly with conformal unstructured meshes where the uniform sampling approach cannot be applied. (authors)

Correction of estimates of retention in care among a cohort of HIV-positive patients in Uganda in the period before starting ART: a sampling-based approach.

Science.gov (United States)

Nyakato, Patience; Kiragga, Agnes N; Kambugu, Andrew; Bradley, John; Baisley, Kathy

2018-04-20

The aim of this study was to use a sampling-based approach to obtain estimates of retention in HIV care before initiation of antiretroviral treatment (ART), corrected for outcomes in patients who were lost according to clinic registers. Retrospective cohort study of HIV-positive individuals not yet eligible for ART (CD4 >500). Three urban and three rural HIV care clinics in Uganda; information was extracted from the clinic registers for all patients who had registered for pre-ART care between January and August 2015. A random sample of patients who were lost according to the clinic registers (>3 months late to scheduled visit) was traced to ascertain their outcomes. The proportion of patients lost from care was estimated using a competing risks approach, first based on the information in the clinic records alone and then using inverse probability weights to incorporate the results from tracing. Cox regression was used to determine factors associated with loss from care. Of 1153 patients registered for pre-ART care (68% women, median age 29 years, median CD4 count 645 cells/µL), 307 (27%) were lost according to clinic records. Among these, 195 (63%) were selected for tracing; outcomes were ascertained in 118 (61%). Seven patients (6%) had died, 40 (34%) were in care elsewhere and 71 (60%) were out of care. Loss from care at 9 months was 30.2% (95% CI 27.3% to 33.5%). After incorporating outcomes from tracing, loss from care decreased to 18.5% (95% CI 13.8% to 23.6%). Estimates of loss from HIV care may be too high if based on routine clinic data alone. A sampling-based approach is a feasible way of obtaining more accurate estimates of retention, accounting for transfers to other clinics. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

An Iterative Load Disaggregation Approach Based on Appliance Consumption Pattern

Directory of Open Access Journals (Sweden)

Huijuan Wang

2018-04-01

Full Text Available Non-intrusive load monitoring (NILM, monitoring single-appliance consumption level by decomposing the aggregated energy consumption, is a novel and economic technology that is beneficial to energy utilities and energy demand management strategies development. Hardware costs of high-frequency sampling and algorithm’s computational complexity hampered NILM large-scale application. However, low sampling data shows poor performance in event detection when multiple appliances are simultaneously turned on. In this paper, we contribute an iterative disaggregation approach that is based on appliance consumption pattern (ILDACP. Our approach combined Fuzzy C-means clustering algorithm, which provide an initial appliance operating status, and sub-sequence searching Dynamic Time Warping, which retrieves single energy consumption based on the typical power consumption pattern. Results show that the proposed approach is effective to accurately disaggregate power consumption, and is suitable for the situation where different appliances are simultaneously operated. Also, the approach has lower computational complexity than Hidden Markov Model method and it is easy to implement in the household without installing special equipment.

Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

Directory of Open Access Journals (Sweden)

Parida Shreemanta K

2010-01-01

Full Text Available Abstract Background For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues. Results Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available. Conclusions The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in

Free Energy Calculations using a Swarm-Enhanced Sampling Molecular Dynamics Approach.

Science.gov (United States)

Burusco, Kepa K; Bruce, Neil J; Alibay, Irfan; Bryce, Richard A

2015-10-26

Free energy simulations are an established computational tool in modelling chemical change in the condensed phase. However, sampling of kinetically distinct substates remains a challenge to these approaches. As a route to addressing this, we link the methods of thermodynamic integration (TI) and swarm-enhanced sampling molecular dynamics (sesMD), where simulation replicas interact cooperatively to aid transitions over energy barriers. We illustrate the approach by using alchemical alkane transformations in solution, comparing them with the multiple independent trajectory TI (IT-TI) method. Free energy changes for transitions computed by using IT-TI grew increasingly inaccurate as the intramolecular barrier was heightened. By contrast, swarm-enhanced sampling TI (sesTI) calculations showed clear improvements in sampling efficiency, leading to more accurate computed free energy differences, even in the case of the highest barrier height. The sesTI approach, therefore, has potential in addressing chemical change in systems where conformations exist in slow exchange. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Silicon based ultrafast optical waveform sampling

DEFF Research Database (Denmark)

Ji, Hua; Galili, Michael; Pu, Minhao

2010-01-01

A 300 nmx450 nmx5 mm silicon nanowire is designed and fabricated for a four wave mixing based non-linear optical gate. Based on this silicon nanowire, an ultra-fast optical sampling system is successfully demonstrated using a free-running fiber laser with a carbon nanotube-based mode-locker as th......A 300 nmx450 nmx5 mm silicon nanowire is designed and fabricated for a four wave mixing based non-linear optical gate. Based on this silicon nanowire, an ultra-fast optical sampling system is successfully demonstrated using a free-running fiber laser with a carbon nanotube-based mode......-locker as the sampling source. A clear eye-diagram of a 320 Gbit/s data signal is obtained. The temporal resolution of the sampling system is estimated to 360 fs....

Fragment approaches in structure-based drug discovery

International Nuclear Information System (INIS)

Hubbard, Roderick E.

2008-01-01

Fragment-based methods are successfully generating novel and selective drug-like inhibitors of protein targets, with a number of groups reporting compounds entering clinical trials. This paper summarizes the key features of the approach as one of the tools in structure-guided drug discovery. There has been considerable interest recently in what is known as 'fragment-based lead discovery'. The novel feature of the approach is to begin with small low-affinity compounds. The main advantage is that a larger potential chemical diversity can be sampled with fewer compounds, which is particularly important for new target classes. The approach relies on careful design of the fragment library, a method that can detect binding of the fragment to the protein target, determination of the structure of the fragment bound to the target, and the conventional use of structural information to guide compound optimization. In this article the methods are reviewed, and experiences in fragment-based discovery of lead series of compounds against kinases such as PDK1 and ATPases such as Hsp90 are discussed. The examples illustrate some of the key benefits and issues of the approach and also provide anecdotal examples of the patterns seen in selectivity and the binding mode of fragments across different protein targets

Adaptive Sampling based 3D Profile Measuring Method for Free-Form Surface

Science.gov (United States)

Duan, Xianyin; Zou, Yu; Gao, Qiang; Peng, Fangyu; Zhou, Min; Jiang, Guozhang

2018-03-01

In order to solve the problem of adaptability and scanning efficiency of the current surface profile detection device, a high precision and high efficiency detection approach is proposed for surface contour of free-form surface parts based on self- adaptability. The contact mechanical probe and the non-contact laser probe are synthetically integrated according to the sampling approach of adaptive front-end path detection. First, the front-end path is measured by the non-contact laser probe, and the detection path is planned by the internal algorithm of the measuring instrument. Then a reasonable measurement sampling is completed according to the planned path by the contact mechanical probe. The detection approach can effectively improve the measurement efficiency of the free-form surface contours and can simultaneously detect the surface contours of unknown free-form surfaces with different curvatures and even different rate of curvature. The detection approach proposed in this paper also has important reference value for free-form surface contour detection.

Random sampling or geostatistical modelling? Choosing between design-based and model-based sampling strategies for soil (with discussion)

NARCIS (Netherlands)

Brus, D.J.; Gruijter, de J.J.

1997-01-01

Classical sampling theory has been repeatedly identified with classical statistics which assumes that data are identically and independently distributed. This explains the switch of many soil scientists from design-based sampling strategies, based on classical sampling theory, to the model-based

An integrate-over-temperature approach for enhanced sampling.

Science.gov (United States)

Gao, Yi Qin

2008-02-14

A simple method is introduced to achieve efficient random walking in the energy space in molecular dynamics simulations which thus enhances the sampling over a large energy range. The approach is closely related to multicanonical and replica exchange simulation methods in that it allows configurations of the system to be sampled in a wide energy range by making use of Boltzmann distribution functions at multiple temperatures. A biased potential is quickly generated using this method and is then used in accelerated molecular dynamics simulations.

Fourier-based approach to interpolation in single-slice helical computed tomography

International Nuclear Information System (INIS)

La Riviere, Patrick J.; Pan Xiaochuan

2001-01-01

It has recently been shown that longitudinal aliasing can be a significant and detrimental presence in reconstructed single-slice helical computed tomography (CT) volumes. This aliasing arises because the directly measured data in helical CT are generally undersampled by a factor of at least 2 in the longitudinal direction and because the exploitation of the redundancy of fanbeam data acquired over 360 degree sign to generate additional longitudinal samples does not automatically eliminate the aliasing. In this paper we demonstrate that for pitches near 1 or lower, the redundant fanbeam data, when used properly, can provide sufficient information to satisfy a generalized sampling theorem and thus to eliminate aliasing. We develop and evaluate a Fourier-based algorithm, called 180FT, that accomplishes this. As background we present a second Fourier-based approach, called 360FT, that makes use only of the directly measured data. Both Fourier-based approaches exploit the fast Fourier transform and the Fourier shift theorem to generate from the helical projection data a set of fanbeam sinograms corresponding to equispaced transverse slices. Slice-by-slice reconstruction is then performed by use of two-dimensional fanbeam algorithms. The proposed approaches are compared to their counterparts based on the use of linear interpolation - the 360LI and 180LI approaches. The aliasing suppression property of the 180FT approach is a clear advantage of the approach and represents a step toward the desirable goal of achieving uniform longitudinal resolution properties in reconstructed helical CT volumes

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

Science.gov (United States)

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

Science.gov (United States)

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

Science.gov (United States)

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Audit sampling: A qualitative study on the role of statistical and non-statistical sampling approaches on audit practices in Sweden

OpenAIRE

Ayam, Rufus Tekoh

2011-01-01

PURPOSE: The two approaches to audit sampling; statistical and nonstatistical have been examined in this study. The overall purpose of the study is to explore the current extent at which statistical and nonstatistical sampling approaches are utilized by independent auditors during auditing practices. Moreover, the study also seeks to achieve two additional purposes; the first is to find out whether auditors utilize different sampling techniques when auditing SME´s (Small and Medium-Sized Ente...

A combined approach of generalized additive model and bootstrap with small sample sets for fault diagnosis in fermentation process of glutamate.

Science.gov (United States)

Liu, Chunbo; Pan, Feng; Li, Yun

2016-07-29

Glutamate is of great importance in food and pharmaceutical industries. There is still lack of effective statistical approaches for fault diagnosis in the fermentation process of glutamate. To date, the statistical approach based on generalized additive model (GAM) and bootstrap has not been used for fault diagnosis in fermentation processes, much less the fermentation process of glutamate with small samples sets. A combined approach of GAM and bootstrap was developed for the online fault diagnosis in the fermentation process of glutamate with small sample sets. GAM was first used to model the relationship between glutamate production and different fermentation parameters using online data from four normal fermentation experiments of glutamate. The fitted GAM with fermentation time, dissolved oxygen, oxygen uptake rate and carbon dioxide evolution rate captured 99.6 % variance of glutamate production during fermentation process. Bootstrap was then used to quantify the uncertainty of the estimated production of glutamate from the fitted GAM using 95 % confidence interval. The proposed approach was then used for the online fault diagnosis in the abnormal fermentation processes of glutamate, and a fault was defined as the estimated production of glutamate fell outside the 95 % confidence interval. The online fault diagnosis based on the proposed approach identified not only the start of the fault in the fermentation process, but also the end of the fault when the fermentation conditions were back to normal. The proposed approach only used a small sample sets from normal fermentations excitements to establish the approach, and then only required online recorded data on fermentation parameters for fault diagnosis in the fermentation process of glutamate. The proposed approach based on GAM and bootstrap provides a new and effective way for the fault diagnosis in the fermentation process of glutamate with small sample sets.

Classification of cancerous cells based on the one-class problem approach

Science.gov (United States)

Murshed, Nabeel A.; Bortolozzi, Flavio; Sabourin, Robert

1996-03-01

One of the most important factors in reducing the effect of cancerous diseases is the early diagnosis, which requires a good and a robust method. With the advancement of computer technologies and digital image processing, the development of a computer-based system has become feasible. In this paper, we introduce a new approach for the detection of cancerous cells. This approach is based on the one-class problem approach, through which the classification system need only be trained with patterns of cancerous cells. This reduces the burden of the training task by about 50%. Based on this approach, a computer-based classification system is developed, based on the Fuzzy ARTMAP neural networks. Experimental results were performed using a set of 542 patterns taken from a sample of breast cancer. Results of the experiment show 98% correct identification of cancerous cells and 95% correct identification of non-cancerous cells.

An integrated approach for multi-level sample size determination

International Nuclear Information System (INIS)

Lu, M.S.; Teichmann, T.; Sanborn, J.B.

1997-01-01

Inspection procedures involving the sampling of items in a population often require steps of increasingly sensitive measurements, with correspondingly smaller sample sizes; these are referred to as multilevel sampling schemes. In the case of nuclear safeguards inspections verifying that there has been no diversion of Special Nuclear Material (SNM), these procedures have been examined often and increasingly complex algorithms have been developed to implement them. The aim in this paper is to provide an integrated approach, and, in so doing, to describe a systematic, consistent method that proceeds logically from level to level with increasing accuracy. The authors emphasize that the methods discussed are generally consistent with those presented in the references mentioned, and yield comparable results when the error models are the same. However, because of its systematic, integrated approach the proposed method elucidates the conceptual understanding of what goes on, and, in many cases, simplifies the calculations. In nuclear safeguards inspections, an important aspect of verifying nuclear items to detect any possible diversion of nuclear fissile materials is the sampling of such items at various levels of sensitivity. The first step usually is sampling by ''attributes'' involving measurements of relatively low accuracy, followed by further levels of sampling involving greater accuracy. This process is discussed in some detail in the references given; also, the nomenclature is described. Here, the authors outline a coordinated step-by-step procedure for achieving such multilevel sampling, and they develop the relationships between the accuracy of measurement and the sample size required at each stage, i.e., at the various levels. The logic of the underlying procedures is carefully elucidated; the calculations involved and their implications, are clearly described, and the process is put in a form that allows systematic generalization

A Proposal on the Advanced Sampling Based Sensitivity and Uncertainty Analysis Method for the Eigenvalue Uncertainty Analysis

International Nuclear Information System (INIS)

Kim, Song Hyun; Song, Myung Sub; Shin, Chang Ho; Noh, Jae Man

2014-01-01

In using the perturbation theory, the uncertainty of the response can be estimated by a single transport simulation, and therefore it requires small computational load. However, it has a disadvantage that the computation methodology must be modified whenever estimating different response type such as multiplication factor, flux, or power distribution. Hence, it is suitable for analyzing few responses with lots of perturbed parameters. Statistical approach is a sampling based method which uses randomly sampled cross sections from covariance data for analyzing the uncertainty of the response. XSUSA is a code based on the statistical approach. The cross sections are only modified with the sampling based method; thus, general transport codes can be directly utilized for the S/U analysis without any code modifications. However, to calculate the uncertainty distribution from the result, code simulation should be enough repeated with randomly sampled cross sections. Therefore, this inefficiency is known as a disadvantage of the stochastic method. In this study, an advanced sampling method of the cross sections is proposed and verified to increase the estimation efficiency of the sampling based method. In this study, to increase the estimation efficiency of the sampling based S/U method, an advanced sampling and estimation method was proposed. The main feature of the proposed method is that the cross section averaged from each single sampled cross section is used. For the use of the proposed method, the validation was performed using the perturbation theory

A copula-based sampling method for data-driven prognostics

International Nuclear Information System (INIS)

Xi, Zhimin; Jing, Rong; Wang, Pingfeng; Hu, Chao

2014-01-01

This paper develops a Copula-based sampling method for data-driven prognostics. The method essentially consists of an offline training process and an online prediction process: (i) the offline training process builds a statistical relationship between the failure time and the time realizations at specified degradation levels on the basis of off-line training data sets; and (ii) the online prediction process identifies probable failure times for online testing units based on the statistical model constructed in the offline process and the online testing data. Our contributions in this paper are three-fold, namely the definition of a generic health index system to quantify the health degradation of an engineering system, the construction of a Copula-based statistical model to learn the statistical relationship between the failure time and the time realizations at specified degradation levels, and the development of a simulation-based approach for the prediction of remaining useful life (RUL). Two engineering case studies, namely the electric cooling fan health prognostics and the 2008 IEEE PHM challenge problem, are employed to demonstrate the effectiveness of the proposed methodology. - Highlights: • We develop a novel mechanism for data-driven prognostics. • A generic health index system quantifies health degradation of engineering systems. • Off-line training model is constructed based on the Bayesian Copula model. • Remaining useful life is predicted from a simulation-based approach

THE SAMPLING PROCESS IN THE FINANCIAL AUDIT .TECHNICAL PRACTICE APPROACH

Directory of Open Access Journals (Sweden)

Cardos Vasile-Daniel

2014-12-01

“Audit sampling” (sampling assumes appliancing audit procedures for less than 100% of the elements within an account or a trasaction class balance, such that all the samples will be selected. This will allow the auditor to obtain and to evaluate the audit evidence on some features for the selected elements, in purpose to assist or to express a conclusion regardind the population within the sample was extracted. The sampling in audit can use both a statistical or a non-statistical approach. (THE AUDIT INTERNATIONAl STANDARD 530 –THE SAMPLING IN AUDIT AND OTHER SELECTIVE TESTING PROCEDURES

THE SAMPLING PROCESS IN THE FINANCIAL AUDIT .TECHNICAL PRACTICE APPROACH

Directory of Open Access Journals (Sweden)

GRIGORE MARIAN

2014-07-01

“Audit sampling” (sampling assumes appliancing audit procedures for less than 100% of the elements within an account or a trasaction class balance, such that all the samples will be selected. This will allow the auditor to obtain and to evaluate the audit evidence on some features for the selected elements, in purpose to assist or to express a conclusion regardind the population within the sample was extracted. The sampling in audit can use both a statistical or a non-statistical approach. (THE AUDIT INTERNATIONAl STANDARD 530 –THE SAMPLING IN AUDIT AND OTHER SELECTIVE TESTING PROCEDURES

Reachable Distance Space: Efficient Sampling-Based Planning for Spatially Constrained Systems

KAUST Repository

Xinyu Tang,

2010-01-25

Motion planning for spatially constrained robots is difficult due to additional constraints placed on the robot, such as closure constraints for closed chains or requirements on end-effector placement for articulated linkages. It is usually computationally too expensive to apply sampling-based planners to these problems since it is difficult to generate valid configurations. We overcome this challenge by redefining the robot\\'s degrees of freedom and constraints into a new set of parameters, called reachable distance space (RD-space), in which all configurations lie in the set of constraint-satisfying subspaces. This enables us to directly sample the constrained subspaces with complexity linear in the number of the robot\\'s degrees of freedom. In addition to supporting efficient sampling of configurations, we show that the RD-space formulation naturally supports planning and, in particular, we design a local planner suitable for use by sampling-based planners. We demonstrate the effectiveness and efficiency of our approach for several systems including closed chain planning with multiple loops, restricted end-effector sampling, and on-line planning for drawing/sculpting. We can sample single-loop closed chain systems with 1,000 links in time comparable to open chain sampling, and we can generate samples for 1,000-link multi-loop systems of varying topologies in less than a second. © 2010 The Author(s).

New approaches to nanoparticle sample fabrication for atom probe tomography

International Nuclear Information System (INIS)

Felfer, P.; Li, T.; Eder, K.; Galinski, H.; Magyar, A.P.; Bell, D.C.; Smith, G.D.W.; Kruse, N.; Ringer, S.P.; Cairney, J.M.

2015-01-01

Due to their unique properties, nano-sized materials such as nanoparticles and nanowires are receiving considerable attention. However, little data is available about their chemical makeup at the atomic scale, especially in three dimensions (3D). Atom probe tomography is able to answer many important questions about these materials if the challenge of producing a suitable sample can be overcome. In order to achieve this, the nanomaterial needs to be positioned within the end of a tip and fixed there so the sample possesses sufficient structural integrity for analysis. Here we provide a detailed description of various techniques that have been used to position nanoparticles on substrates for atom probe analysis. In some of the approaches, this is combined with deposition techniques to incorporate the particles into a solid matrix, and focused ion beam processing is then used to fabricate atom probe samples from this composite. Using these approaches, data has been achieved from 10–20 nm core–shell nanoparticles that were extracted directly from suspension (i.e. with no chemical modification) with a resolution of better than ±1 nm. - Highlights: • Samples for APT of nanoparticles were fabricated from particle powders and dispersions. • Electrophoresis was suitable for producing samples from dispersions. • Powder lift-out was successfully producing samples from particle agglomerates. • Dispersion application/coating delivered the highest quality results.

New approaches to nanoparticle sample fabrication for atom probe tomography

Energy Technology Data Exchange (ETDEWEB)

Felfer, P., E-mail: peter.felfer@sydney.edu.au [School for Aerospace, Mechanical and Mechatronic Engineering/Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); Li, T. [School for Aerospace, Mechanical and Mechatronic Engineering/Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); Materials Department, The University of Oxford, Oxford (United Kingdom); Eder, K. [School for Aerospace, Mechanical and Mechatronic Engineering/Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia); Galinski, H. [School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 (United States); Magyar, A.P.; Bell, D.C. [School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 (United States); Center for Nanoscale Systems, Harvard University, Cambridge, MA 02138 (United States); Smith, G.D.W. [Materials Department, The University of Oxford, Oxford (United Kingdom); Kruse, N. [Chemical Physics of Materials (Catalysis-Tribology), Université Libre de Bruxelles, Campus Plaine, CP 243, 1050 Brussels (Belgium); Ringer, S.P.; Cairney, J.M. [School for Aerospace, Mechanical and Mechatronic Engineering/Australian Centre for Microscopy and Microanalysis, The University of Sydney, NSW 2006 (Australia)

2015-12-15

Due to their unique properties, nano-sized materials such as nanoparticles and nanowires are receiving considerable attention. However, little data is available about their chemical makeup at the atomic scale, especially in three dimensions (3D). Atom probe tomography is able to answer many important questions about these materials if the challenge of producing a suitable sample can be overcome. In order to achieve this, the nanomaterial needs to be positioned within the end of a tip and fixed there so the sample possesses sufficient structural integrity for analysis. Here we provide a detailed description of various techniques that have been used to position nanoparticles on substrates for atom probe analysis. In some of the approaches, this is combined with deposition techniques to incorporate the particles into a solid matrix, and focused ion beam processing is then used to fabricate atom probe samples from this composite. Using these approaches, data has been achieved from 10–20 nm core–shell nanoparticles that were extracted directly from suspension (i.e. with no chemical modification) with a resolution of better than ±1 nm. - Highlights: • Samples for APT of nanoparticles were fabricated from particle powders and dispersions. • Electrophoresis was suitable for producing samples from dispersions. • Powder lift-out was successfully producing samples from particle agglomerates. • Dispersion application/coating delivered the highest quality results.

Sensitivity/uncertainty analysis of a borehole scenario comparing Latin Hypercube Sampling and deterministic sensitivity approaches

International Nuclear Information System (INIS)

Harper, W.V.; Gupta, S.K.

1983-10-01

A computer code was used to study steady-state flow for a hypothetical borehole scenario. The model consists of three coupled equations with only eight parameters and three dependent variables. This study focused on steady-state flow as the performance measure of interest. Two different approaches to sensitivity/uncertainty analysis were used on this code. One approach, based on Latin Hypercube Sampling (LHS), is a statistical sampling method, whereas, the second approach is based on the deterministic evaluation of sensitivities. The LHS technique is easy to apply and should work well for codes with a moderate number of parameters. Of deterministic techniques, the direct method is preferred when there are many performance measures of interest and a moderate number of parameters. The adjoint method is recommended when there are a limited number of performance measures and an unlimited number of parameters. This unlimited number of parameters capability can be extremely useful for finite element or finite difference codes with a large number of grid blocks. The Office of Nuclear Waste Isolation will use the technique most appropriate for an individual situation. For example, the adjoint method may be used to reduce the scope to a size that can be readily handled by a technique such as LHS. Other techniques for sensitivity/uncertainty analysis, e.g., kriging followed by conditional simulation, will be used also. 15 references, 4 figures, 9 tables

Data Set for the manuscript entitled, "Sample Processing Approach for Detection of Ricin in Surface Samples."

Data.gov (United States)

U.S. Environmental Protection Agency — Figure. This dataset is associated with the following publication: Shah, S., S. Kane, A.M. Erler, and T. Alfaro. Sample Processing Approach for Detection of Ricin in...

Sampled-Data Control of Spacecraft Rendezvous with Discontinuous Lyapunov Approach

Directory of Open Access Journals (Sweden)

Zhuoshi Li

2013-01-01

Full Text Available This paper investigates the sampled-data stabilization problem of spacecraft relative positional holding with improved Lyapunov function approach. The classical Clohessy-Wiltshire equation is adopted to describe the relative dynamic model. The relative position holding problem is converted into an output tracking control problem using sampling signals. A time-dependent discontinuous Lyapunov functionals approach is developed, which will lead to essentially less conservative results for the stability analysis and controller design of the corresponding closed-loop system. Sufficient conditions for the exponential stability analysis and the existence of the proposed controller are provided, respectively. Finally, a simulation result is established to illustrate the effectiveness of the proposed control scheme.

Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples

Science.gov (United States)

Khan, Faisal; Enzmann, Frieder; Kersten, Michael

2016-03-01

Image processing of X-ray-computed polychromatic cone-beam micro-tomography (μXCT) data of geological samples mainly involves artefact reduction and phase segmentation. For the former, the main beam-hardening (BH) artefact is removed by applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. A Matlab code for this approach is provided in the Appendix. The final BH-corrected image is extracted from the residual data or from the difference between the surface elevation values and the original grey-scale values. For the segmentation, we propose a novel least-squares support vector machine (LS-SVM, an algorithm for pixel-based multi-phase classification) approach. A receiver operating characteristic (ROC) analysis was performed on BH-corrected and uncorrected samples to show that BH correction is in fact an important prerequisite for accurate multi-phase classification. The combination of the two approaches was thus used to classify successfully three different more or less complex multi-phase rock core samples.

A cache-friendly sampling strategy for texture-based volume rendering on GPU

Directory of Open Access Journals (Sweden)

Junpeng Wang

2017-06-01

Full Text Available The texture-based volume rendering is a memory-intensive algorithm. Its performance relies heavily on the performance of the texture cache. However, most existing texture-based volume rendering methods blindly map computational resources to texture memory and result in incoherent memory access patterns, causing low cache hit rates in certain cases. The distance between samples taken by threads of an atomic scheduling unit (e.g. a warp of 32 threads in CUDA of the GPU is a crucial factor that affects the texture cache performance. Based on this fact, we present a new sampling strategy, called Warp Marching, for the ray-casting algorithm of texture-based volume rendering. The effects of different sample organizations and different thread-pixel mappings in the ray-casting algorithm are thoroughly analyzed. Also, a pipeline manner color blending approach is introduced and the power of warp-level GPU operations is leveraged to improve the efficiency of parallel executions on the GPU. In addition, the rendering performance of the Warp Marching is view-independent, and it outperforms existing empty space skipping techniques in scenarios that need to render large dynamic volumes in a low resolution image. Through a series of micro-benchmarking and real-life data experiments, we rigorously analyze our sampling strategies and demonstrate significant performance enhancements over existing sampling methods.

A genetic algorithm-based framework for wavelength selection on sample categorization.

Science.gov (United States)

Anzanello, Michel J; Yamashita, Gabrielli; Marcelo, Marcelo; Fogliatto, Flávio S; Ortiz, Rafael S; Mariotti, Kristiane; Ferrão, Marco F

2017-08-01

In forensic and pharmaceutical scenarios, the application of chemometrics and optimization techniques has unveiled common and peculiar features of seized medicine and drug samples, helping investigative forces to track illegal operations. This paper proposes a novel framework aimed at identifying relevant subsets of attenuated total reflectance Fourier transform infrared (ATR-FTIR) wavelengths for classifying samples into two classes, for example authentic or forged categories in case of medicines, or salt or base form in cocaine analysis. In the first step of the framework, the ATR-FTIR spectra were partitioned into equidistant intervals and the k-nearest neighbour (KNN) classification technique was applied to each interval to insert samples into proper classes. In the next step, selected intervals were refined through the genetic algorithm (GA) by identifying a limited number of wavelengths from the intervals previously selected aimed at maximizing classification accuracy. When applied to Cialis®, Viagra®, and cocaine ATR-FTIR datasets, the proposed method substantially decreased the number of wavelengths needed to categorize, and increased the classification accuracy. From a practical perspective, the proposed method provides investigative forces with valuable information towards monitoring illegal production of drugs and medicines. In addition, focusing on a reduced subset of wavelengths allows the development of portable devices capable of testing the authenticity of samples during police checking events, avoiding the need for later laboratorial analyses and reducing equipment expenses. Theoretically, the proposed GA-based approach yields more refined solutions than the current methods relying on interval approaches, which tend to insert irrelevant wavelengths in the retained intervals. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Rapid assessment of antimicrobial resistance prevalence using a Lot Quality Assurance sampling approach.

Science.gov (United States)

van Leth, Frank; den Heijer, Casper; Beerepoot, Mariëlle; Stobberingh, Ellen; Geerlings, Suzanne; Schultsz, Constance

2017-04-01

Increasing antimicrobial resistance (AMR) requires rapid surveillance tools, such as Lot Quality Assurance Sampling (LQAS). LQAS classifies AMR as high or low based on set parameters. We compared classifications with the underlying true AMR prevalence using data on 1335 Escherichia coli isolates from surveys of community-acquired urinary tract infection in women, by assessing operating curves, sensitivity and specificity. Sensitivity and specificity of any set of LQAS parameters was above 99% and between 79 and 90%, respectively. Operating curves showed high concordance of the LQAS classification with true AMR prevalence estimates. LQAS-based AMR surveillance is a feasible approach that provides timely and locally relevant estimates, and the necessary information to formulate and evaluate guidelines for empirical treatment.

A normative inference approach for optimal sample sizes in decisions from experience

Science.gov (United States)

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

“Decisions from experience” (DFE) refers to a body of work that emerged in research on behavioral decision making over the last decade. One of the major experimental paradigms employed to study experience-based choice is the “sampling paradigm,” which serves as a model of decision making under limited knowledge about the statistical structure of the world. In this paradigm respondents are presented with two payoff distributions, which, in contrast to standard approaches in behavioral economics, are specified not in terms of explicit outcome-probability information, but by the opportunity to sample outcomes from each distribution without economic consequences. Participants are encouraged to explore the distributions until they feel confident enough to decide from which they would prefer to draw from in a final trial involving real monetary payoffs. One commonly employed measure to characterize the behavior of participants in the sampling paradigm is the sample size, that is, the number of outcome draws which participants choose to obtain from each distribution prior to terminating sampling. A natural question that arises in this context concerns the “optimal” sample size, which could be used as a normative benchmark to evaluate human sampling behavior in DFE. In this theoretical study, we relate the DFE sampling paradigm to the classical statistical decision theoretic literature and, under a probabilistic inference assumption, evaluate optimal sample sizes for DFE. In our treatment we go beyond analytically established results by showing how the classical statistical decision theoretic framework can be used to derive optimal sample sizes under arbitrary, but numerically evaluable, constraints. Finally, we critically evaluate the value of deriving optimal sample sizes under this framework as testable predictions for the experimental study of sampling behavior in DFE. PMID:26441720

MULTI-LEVEL SAMPLING APPROACH FOR CONTINOUS LOSS DETECTION USING ITERATIVE WINDOW AND STATISTICAL MODEL

OpenAIRE

Mohd Fo'ad Rohani; Mohd Aizaini Maarof; Ali Selamat; Houssain Kettani

2010-01-01

This paper proposes a Multi-Level Sampling (MLS) approach for continuous Loss of Self-Similarity (LoSS) detection using iterative window. The method defines LoSS based on Second Order Self-Similarity (SOSS) statistical model. The Optimization Method (OM) is used to estimate self-similarity parameter since it is fast and more accurate in comparison with other estimation methods known in the literature. Probability of LoSS detection is introduced to measure continuous LoSS detection performance...

Immunophenotype Discovery, Hierarchical Organization, and Template-based Classification of Flow Cytometry Samples

Directory of Open Access Journals (Sweden)

Ariful Azad

2016-08-01

Full Text Available We describe algorithms for discovering immunophenotypes from large collections of flow cytometry (FC samples, and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters, a template consists of generic meta-populations (a group of homogeneous cell populations obtained from the samples in a class that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples, while ignoring noise and small sample-specific variations.We have applied the template-base scheme to analyze several data setsincluding one representing a healthy immune system, and one of Acute Myeloid Leukemia (AMLsamples. The last task is challenging due to the phenotypic heterogeneity of the severalsubtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML, and were able to distinguish Acute Promyelocytic Leukemia from other subtypes of AML.

Automatic Motion Generation for Robotic Milling Optimizing Stiffness with Sample-Based Planning

Directory of Open Access Journals (Sweden)

Julian Ricardo Diaz Posada

2017-01-01

Full Text Available Optimal and intuitive robotic machining is still a challenge. One of the main reasons for this is the lack of robot stiffness, which is also dependent on the robot positioning in the Cartesian space. To make up for this deficiency and with the aim of increasing robot machining accuracy, this contribution describes a solution approach for optimizing the stiffness over a desired milling path using the free degree of freedom of the machining process. The optimal motion is computed based on the semantic and mathematical interpretation of the manufacturing process modeled on its components: product, process and resource; and by configuring automatically a sample-based motion problem and the transition-based rapid-random tree algorithm for computing an optimal motion. The approach is simulated on a CAM software for a machining path revealing its functionality and outlining future potentials for the optimal motion generation for robotic machining processes.

Seasonal rationalization of river water quality sampling locations: a comparative study of the modified Sanders and multivariate statistical approaches.

Science.gov (United States)

Varekar, Vikas; Karmakar, Subhankar; Jha, Ramakar

2016-02-01

approach outperforms FA/PCA when limited water quality and extensive watershed information is available. The available water quality dataset is limited and FA/PCA-based approach fails to identify monitoring locations with higher variation, as these multivariate statistical approaches are data-driven. The priority/hierarchy and number of sampling sites designed by modified Sanders approach are well justified by the land use practices and observed river basin characteristics of the study area.

Dynamic flow-through approaches for metal fractionation in environmentally relevant solid samples

DEFF Research Database (Denmark)

Miró, Manuel; Hansen, Elo Harald; Chomchoei, Roongrat

2005-01-01

generations of flow-injection analysis. Special attention is also paid to a novel, robust, non-invasive approach for on-site continuous sampling of soil solutions, capitalizing on flow-through microdialysis, which presents itself as an appealing complementary approach to the conventional lysimeter experiments...

The redshift distribution of cosmological samples: a forward modeling approach

Energy Technology Data Exchange (ETDEWEB)

Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina, E-mail: joerg.herbel@phys.ethz.ch, E-mail: tomasz.kacprzak@phys.ethz.ch, E-mail: adam.amara@phys.ethz.ch, E-mail: alexandre.refregier@phys.ethz.ch, E-mail: claudio.bruderer@phys.ethz.ch, E-mail: andrina.nicola@phys.ethz.ch [Institute for Astronomy, Department of Physics, ETH Zürich, Wolfgang-Pauli-Strasse 27, 8093 Zürich (Switzerland)

2017-08-01

Determining the redshift distribution n ( z ) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n ( z ) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc(UFig) (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n ( z ) distributions for the acceptable models. We demonstrate the method by determining n ( z ) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n ( z ) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

The redshift distribution of cosmological samples: a forward modeling approach

Science.gov (United States)

Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina

2017-08-01

Determining the redshift distribution n(z) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n(z) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc{UFig} (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n(z) distributions for the acceptable models. We demonstrate the method by determining n(z) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n(z) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

The redshift distribution of cosmological samples: a forward modeling approach

International Nuclear Information System (INIS)

Herbel, Jörg; Kacprzak, Tomasz; Amara, Adam; Refregier, Alexandre; Bruderer, Claudio; Nicola, Andrina

2017-01-01

Determining the redshift distribution n ( z ) of galaxy samples is essential for several cosmological probes including weak lensing. For imaging surveys, this is usually done using photometric redshifts estimated on an object-by-object basis. We present a new approach for directly measuring the global n ( z ) of cosmological galaxy samples, including uncertainties, using forward modeling. Our method relies on image simulations produced using \\textsc(UFig) (Ultra Fast Image Generator) and on ABC (Approximate Bayesian Computation) within the MCCL (Monte-Carlo Control Loops) framework. The galaxy population is modeled using parametric forms for the luminosity functions, spectral energy distributions, sizes and radial profiles of both blue and red galaxies. We apply exactly the same analysis to the real data and to the simulated images, which also include instrumental and observational effects. By adjusting the parameters of the simulations, we derive a set of acceptable models that are statistically consistent with the data. We then apply the same cuts to the simulations that were used to construct the target galaxy sample in the real data. The redshifts of the galaxies in the resulting simulated samples yield a set of n ( z ) distributions for the acceptable models. We demonstrate the method by determining n ( z ) for a cosmic shear like galaxy sample from the 4-band Subaru Suprime-Cam data in the COSMOS field. We also complement this imaging data with a spectroscopic calibration sample from the VVDS survey. We compare our resulting posterior n ( z ) distributions to the one derived from photometric redshifts estimated using 36 photometric bands in COSMOS and find good agreement. This offers good prospects for applying our approach to current and future large imaging surveys.

A Model-free Approach to Fault Detection of Continuous-time Systems Based on Time Domain Data

Institute of Scientific and Technical Information of China (English)

Ping Zhang; Steven X. Ding

2007-01-01

In this paper, a model-free approach is presented to design an observer-based fault detection system of linear continuoustime systems based on input and output data in the time domain. The core of the approach is to directly identify parameters of the observer-based residual generator based on a numerically reliable data equation obtained by filtering and sampling the input and output signals.

Preview-based sampling for controlling gaseous simulations

KAUST Repository

Huang, Ruoguan

2011-01-01

In this work, we describe an automated method for directing the control of a high resolution gaseous fluid simulation based on the results of a lower resolution preview simulation. Small variations in accuracy between low and high resolution grids can lead to divergent simulations, which is problematic for those wanting to achieve a desired behavior. Our goal is to provide a simple method for ensuring that the high resolution simulation matches key properties from the lower resolution simulation. We first let a user specify a fast, coarse simulation that will be used for guidance. Our automated method samples the data to be matched at various positions and scales in the simulation, or allows the user to identify key portions of the simulation to maintain. During the high resolution simulation, a matching process ensures that the properties sampled from the low resolution simulation are maintained. This matching process keeps the different resolution simulations aligned even for complex systems, and can ensure consistency of not only the velocity field, but also advected scalar values. Because the final simulation is naturally similar to the preview simulation, only minor controlling adjustments are needed, allowing a simpler control method than that used in prior keyframing approaches. Copyright © 2011 by the Association for Computing Machinery, Inc.

Kaolin Quality Prediction from Samples: A Bayesian Network Approach

International Nuclear Information System (INIS)

Rivas, T.; Taboada, J.; Ordonez, C.; Matias, J. M.

2009-01-01

We describe the results of an expert system applied to the evaluation of samples of kaolin for industrial use in paper or ceramic manufacture. Different machine learning techniques - classification trees, support vector machines and Bayesian networks - were applied with the aim of evaluating and comparing their interpretability and prediction capacities. The predictive capacity of these models for the samples analyzed was highly satisfactory, both for ceramic quality and paper quality. However, Bayesian networks generally proved to be the most useful technique for our study, as this approach combines good predictive capacity with excellent interpretability of the kaolin quality structure, as it graphically represents relationships between variables and facilitates what-if analyses.

QNB: differential RNA methylation analysis for count-based small-sample sequencing data with a quad-negative binomial model.

Science.gov (United States)

Liu, Lian; Zhang, Shao-Wu; Huang, Yufei; Meng, Jia

2017-08-31

As a newly emerged research area, RNA epigenetics has drawn increasing attention recently for the participation of RNA methylation and other modifications in a number of crucial biological processes. Thanks to high throughput sequencing techniques, such as, MeRIP-Seq, transcriptome-wide RNA methylation profile is now available in the form of count-based data, with which it is often of interests to study the dynamics at epitranscriptomic layer. However, the sample size of RNA methylation experiment is usually very small due to its costs; and additionally, there usually exist a large number of genes whose methylation level cannot be accurately estimated due to their low expression level, making differential RNA methylation analysis a difficult task. We present QNB, a statistical approach for differential RNA methylation analysis with count-based small-sample sequencing data. Compared with previous approaches such as DRME model based on a statistical test covering the IP samples only with 2 negative binomial distributions, QNB is based on 4 independent negative binomial distributions with their variances and means linked by local regressions, and in the way, the input control samples are also properly taken care of. In addition, different from DRME approach, which relies only the input control sample only for estimating the background, QNB uses a more robust estimator for gene expression by combining information from both input and IP samples, which could largely improve the testing performance for very lowly expressed genes. QNB showed improved performance on both simulated and real MeRIP-Seq datasets when compared with competing algorithms. And the QNB model is also applicable to other datasets related RNA modifications, including but not limited to RNA bisulfite sequencing, m 1 A-Seq, Par-CLIP, RIP-Seq, etc.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

Science.gov (United States)

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

iTRAQ-Based and Label-Free Proteomics Approaches for Studies of Human Adenovirus Infections

OpenAIRE

Trinh, Hung V.; Grossmann, Jonas; Gehrig, Peter; Roschitzki, Bernd; Schlapbach, Ralph; Greber, Urs F.; Hemmi, Silvio

2013-01-01

Both isobaric tags for relative and absolute quantitation (iTRAQ) and label-free methods are widely used for quantitative proteomics. Here, we provide a detailed evaluation of these proteomics approaches based on large datasets from biological samples. iTRAQ-label-based and label-free quantitations were compared using protein lysate samples from noninfected human lung epithelial A549 cells and from cells infected for 24 h with human adenovirus type 3 or type 5. Either iTRAQ-label-based or lab...

Surrogate based approaches to parameter inference in ocean models

KAUST Repository

Knio, Omar

2016-01-06

This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.

Surrogate based approaches to parameter inference in ocean models

KAUST Repository

Knio, Omar

2016-01-01

This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.

A fuel-based approach to estimating motor vehicle exhaust emissions

Science.gov (United States)

Singer, Brett Craig

Motor vehicles contribute significantly to air pollution problems; accurate motor vehicle emission inventories are therefore essential to air quality planning. Current travel-based inventory models use emission factors measured from potentially biased vehicle samples and predict fleet-average emissions which are often inconsistent with on-road measurements. This thesis presents a fuel-based inventory approach which uses emission factors derived from remote sensing or tunnel-based measurements of on-road vehicles. Vehicle activity is quantified by statewide monthly fuel sales data resolved to the air basin level. Development of the fuel-based approach includes (1) a method for estimating cold start emission factors, (2) an analysis showing that fuel-normalized emission factors are consistent over a range of positive vehicle loads and that most fuel use occurs during loaded-mode driving, (3) scaling factors relating infrared hydrocarbon measurements to total exhaust volatile organic compound (VOC) concentrations, and (4) an analysis showing that economic factors should be considered when selecting on-road sampling sites. The fuel-based approach was applied to estimate carbon monoxide (CO) emissions from warmed-up vehicles in the Los Angeles area in 1991, and CO and VOC exhaust emissions for Los Angeles in 1997. The fuel-based CO estimate for 1991 was higher by a factor of 2.3 +/- 0.5 than emissions predicted by California's MVEI 7F model. Fuel-based inventory estimates for 1997 were higher than those of California's updated MVEI 7G model by factors of 2.4 +/- 0.2 for CO and 3.5 +/- 0.6 for VOC. Fuel-based estimates indicate a 20% decrease in the mass of CO emitted, despite an 8% increase in fuel use between 1991 and 1997; official inventory models predict a 50% decrease in CO mass emissions during the same period. Cold start CO and VOC emission factors derived from parking garage measurements were lower than those predicted by the MVEI 7G model. Current inventories

Mission Planning and Decision Support for Underwater Glider Networks: A Sampling on-Demand Approach.

Science.gov (United States)

Ferri, Gabriele; Cococcioni, Marco; Alvarez, Alberto

2015-12-26

This paper describes an optimal sampling approach to support glider fleet operators and marine scientists during the complex task of planning the missions of fleets of underwater gliders. Optimal sampling, which has gained considerable attention in the last decade, consists in planning the paths of gliders to minimize a specific criterion pertinent to the phenomenon under investigation. Different criteria (e.g., A, G, or E optimality), used in geosciences to obtain an optimum design, lead to different sampling strategies. In particular, the A criterion produces paths for the gliders that minimize the overall level of uncertainty over the area of interest. However, there are commonly operative situations in which the marine scientists may prefer not to minimize the overall uncertainty of a certain area, but instead they may be interested in achieving an acceptable uncertainty sufficient for the scientific or operational needs of the mission. We propose and discuss here an approach named sampling on-demand that explicitly addresses this need. In our approach the user provides an objective map, setting both the amount and the geographic distribution of the uncertainty to be achieved after assimilating the information gathered by the fleet. A novel optimality criterion, called A η , is proposed and the resulting minimization problem is solved by using a Simulated Annealing based optimizer that takes into account the constraints imposed by the glider navigation features, the desired geometry of the paths and the problems of reachability caused by ocean currents. This planning strategy has been implemented in a Matlab toolbox called SoDDS (Sampling on-Demand and Decision Support). The tool is able to automatically download the ocean fields data from MyOcean repository and also provides graphical user interfaces to ease the input process of mission parameters and targets. The results obtained by running SoDDS on three different scenarios are provided and show that So

Mission Planning and Decision Support for Underwater Glider Networks: A Sampling on-Demand Approach

Directory of Open Access Journals (Sweden)

Gabriele Ferri

2015-12-01

Full Text Available This paper describes an optimal sampling approach to support glider fleet operators and marine scientists during the complex task of planning the missions of fleets of underwater gliders. Optimal sampling, which has gained considerable attention in the last decade, consists in planning the paths of gliders to minimize a specific criterion pertinent to the phenomenon under investigation. Different criteria (e.g., A, G, or E optimality, used in geosciences to obtain an optimum design, lead to different sampling strategies. In particular, the A criterion produces paths for the gliders that minimize the overall level of uncertainty over the area of interest. However, there are commonly operative situations in which the marine scientists may prefer not to minimize the overall uncertainty of a certain area, but instead they may be interested in achieving an acceptable uncertainty sufficient for the scientific or operational needs of the mission. We propose and discuss here an approach named sampling on-demand that explicitly addresses this need. In our approach the user provides an objective map, setting both the amount and the geographic distribution of the uncertainty to be achieved after assimilating the information gathered by the fleet. A novel optimality criterion, called A η , is proposed and the resulting minimization problem is solved by using a Simulated Annealing based optimizer that takes into account the constraints imposed by the glider navigation features, the desired geometry of the paths and the problems of reachability caused by ocean currents. This planning strategy has been implemented in a Matlab toolbox called SoDDS (Sampling on-Demand and Decision Support. The tool is able to automatically download the ocean fields data from MyOcean repository and also provides graphical user interfaces to ease the input process of mission parameters and targets. The results obtained by running SoDDS on three different scenarios are provided

Mission Planning and Decision Support for Underwater Glider Networks: A Sampling on-Demand Approach

Science.gov (United States)

Ferri, Gabriele; Cococcioni, Marco; Alvarez, Alberto

2015-01-01

This paper describes an optimal sampling approach to support glider fleet operators and marine scientists during the complex task of planning the missions of fleets of underwater gliders. Optimal sampling, which has gained considerable attention in the last decade, consists in planning the paths of gliders to minimize a specific criterion pertinent to the phenomenon under investigation. Different criteria (e.g., A, G, or E optimality), used in geosciences to obtain an optimum design, lead to different sampling strategies. In particular, the A criterion produces paths for the gliders that minimize the overall level of uncertainty over the area of interest. However, there are commonly operative situations in which the marine scientists may prefer not to minimize the overall uncertainty of a certain area, but instead they may be interested in achieving an acceptable uncertainty sufficient for the scientific or operational needs of the mission. We propose and discuss here an approach named sampling on-demand that explicitly addresses this need. In our approach the user provides an objective map, setting both the amount and the geographic distribution of the uncertainty to be achieved after assimilating the information gathered by the fleet. A novel optimality criterion, called Aη, is proposed and the resulting minimization problem is solved by using a Simulated Annealing based optimizer that takes into account the constraints imposed by the glider navigation features, the desired geometry of the paths and the problems of reachability caused by ocean currents. This planning strategy has been implemented in a Matlab toolbox called SoDDS (Sampling on-Demand and Decision Support). The tool is able to automatically download the ocean fields data from MyOcean repository and also provides graphical user interfaces to ease the input process of mission parameters and targets. The results obtained by running SoDDS on three different scenarios are provided and show that So

Brain based learning with contextual approach to mathematics achievement

Directory of Open Access Journals (Sweden)

V Kartikaningtyas

2017-12-01

Full Text Available The aim of this study was to know the effect of Brain Based Learning (BBL with a contextual approach to mathematics achievement. BBL-contextual is the learning model that designed to develop and optimize the brain ability for getting a new concept and solving the real life problem. This study method was a quasi-experiment. The population was the junior high school students. The sample chosen by using stratified cluster random sampling. The sample was 109 students. The data collected through a mathematics achievement test that was given after the treatment. The data analyzed by using one way ANOVA. The results of the study showed that BBL-contextual is better than direct learning on mathematics achievement. It means BBL-contextual could be an effective and innovative model.

Practice and effectiveness of web-based problem-based learning approach in a large class-size system: A comparative study.

Science.gov (United States)

Ding, Yongxia; Zhang, Peili

2018-06-12

Problem-based learning (PBL) is an effective and highly efficient teaching approach that is extensively applied in education systems across a variety of countries. This study aimed to investigate the effectiveness of web-based PBL teaching pedagogies in large classes. The cluster sampling method was used to separate two college-level nursing student classes (graduating class of 2013) into two groups. The experimental group (n = 162) was taught using a web-based PBL teaching approach, while the control group (n = 166) was taught using conventional teaching methods. We subsequently assessed the satisfaction of the experimental group in relation to the web-based PBL teaching mode. This assessment was performed following comparison of teaching activity outcomes pertaining to exams and self-learning capacity between the two groups. When compared with the control group, the examination scores and self-learning capabilities were significantly higher in the experimental group (P web-based PBL teaching approach. In a large class-size teaching environment, the web-based PBL teaching approach appears to be more optimal than traditional teaching methods. These results demonstrate the effectiveness of web-based teaching technologies in problem-based learning. Copyright © 2018. Published by Elsevier Ltd.

[Application of simulated annealing method and neural network on optimizing soil sampling schemes based on road distribution].

Science.gov (United States)

Han, Zong-wei; Huang, Wei; Luo, Yun; Zhang, Chun-di; Qi, Da-cheng

2015-03-01

Taking the soil organic matter in eastern Zhongxiang County, Hubei Province, as a research object, thirteen sample sets from different regions were arranged surrounding the road network, the spatial configuration of which was optimized by the simulated annealing approach. The topographic factors of these thirteen sample sets, including slope, plane curvature, profile curvature, topographic wetness index, stream power index and sediment transport index, were extracted by the terrain analysis. Based on the results of optimization, a multiple linear regression model with topographic factors as independent variables was built. At the same time, a multilayer perception model on the basis of neural network approach was implemented. The comparison between these two models was carried out then. The results revealed that the proposed approach was practicable in optimizing soil sampling scheme. The optimal configuration was capable of gaining soil-landscape knowledge exactly, and the accuracy of optimal configuration was better than that of original samples. This study designed a sampling configuration to study the soil attribute distribution by referring to the spatial layout of road network, historical samples, and digital elevation data, which provided an effective means as well as a theoretical basis for determining the sampling configuration and displaying spatial distribution of soil organic matter with low cost and high efficiency.

Materiality in a Practice-Based Approach

Science.gov (United States)

Svabo, Connie

2009-01-01

Purpose: The paper aims to provide an overview of the vocabulary for materiality which is used by practice-based approaches to organizational knowing. Design/methodology/approach: The overview is theoretically generated and is based on the anthology Knowing in Organizations: A Practice-based Approach edited by Nicolini, Gherardi and Yanow. The…

A population-based approach to background discrimination in particle physics

International Nuclear Information System (INIS)

Colecchia, Federico

2012-01-01

Background properties in experimental particle physics are typically estimated from control samples corresponding to large numbers of events. This can provide precise knowledge of average background distributions, but typically does not take into account statistical fluctuations in a data set of interest. A novel approach based on mixture model decomposition is presented, as a way to extract additional information about statistical fluctuations from a given data set with a view to improving on knowledge of background distributions obtained from control samples. Events are treated as heterogeneous populations comprising particles originating from different processes, and individual particles are mapped to a process of interest on a probabilistic basis. The proposed approach makes it possible to estimate features of the background distributions from the data, and to extract information about statistical fluctuations that would otherwise be lost using traditional supervised classifiers trained on high-statistics control samples. A feasibility study on Monte Carlo is presented, together with a comparison with existing techniques. Finally, the prospects for the development of tools for intensive offline analysis of individual interesting events at the Large Hadron Collider are discussed.

Systematic sampling with errors in sample locations

DEFF Research Database (Denmark)

Ziegel, Johanna; Baddeley, Adrian; Dorph-Petersen, Karl-Anton

2010-01-01

analysis using point process methods. We then analyze three different models for the error process, calculate exact expressions for the variances, and derive asymptotic variances. Errors in the placement of sample points can lead to substantial inflation of the variance, dampening of zitterbewegung......Systematic sampling of points in continuous space is widely used in microscopy and spatial surveys. Classical theory provides asymptotic expressions for the variance of estimators based on systematic sampling as the grid spacing decreases. However, the classical theory assumes that the sample grid...... is exactly periodic; real physical sampling procedures may introduce errors in the placement of the sample points. This paper studies the effect of errors in sample positioning on the variance of estimators in the case of one-dimensional systematic sampling. First we sketch a general approach to variance...

Understanding reasons for and outcomes of patients lost to follow-up in antiretroviral therapy programs in Africa through a sampling-based approach.

Science.gov (United States)

Geng, Elvin H; Bangsberg, David R; Musinguzi, Nicolas; Emenyonu, Nneka; Bwana, Mwebesa Bosco; Yiannoutsos, Constantin T; Glidden, David V; Deeks, Steven G; Martin, Jeffrey N

2010-03-01

Losses to follow-up after initiation of antiretroviral therapy (ART) are common in Africa and are a considerable obstacle to understanding the effectiveness of nascent treatment programs. We sought to characterize, through a sampling-based approach, reasons for and outcomes of patients who become lost to follow-up. Cohort study. We searched for and interviewed a representative sample of lost patients or close informants in the community to determine reasons for and outcomes among lost patients. Three thousand six hundred twenty-eight HIV-infected adults initiated ART between January 1, 2004 and September 30, 2007 in Mbarara, Uganda. Eight hundred twenty-nine became lost to follow-up (cumulative incidence at 1, 2, and 3 years of 16%, 30%, and 39%). We sought a representative sample of 128 lost patients in the community and ascertained vital status in 111 (87%). Top reasons for loss included lack of transportation or money and work/child care responsibilities. Among the 111 lost patients who had their vital status ascertained through tracking, 32 deaths occurred (cumulative 1-year incidence 36%); mortality was highest shortly after the last clinic visit. Lower pre-ART CD4 T-cell count, older age, low blood pressure, and a central nervous system syndrome at the last clinic visit predicted deaths. Of patients directly interviewed, 83% were in care at another clinic and 71% were still using ART. Sociostructural factors are the primary reasons for loss to follow-up. Outcomes among the lost are heterogeneous: both deaths and transfers to other clinics were common. Tracking a sample of lost patients is an efficient means for programs to understand site-specific reasons for and outcomes among patients lost to follow-up.

An Efficient Approach for Mars Sample Return Using Emerging Commercial Capabilities.

Science.gov (United States)

Gonzales, Andrew A; Stoker, Carol R

2016-06-01

Mars Sample Return is the highest priority science mission for the next decade as recommended by the 2011 Decadal Survey of Planetary Science [1]. This article presents the results of a feasibility study for a Mars Sample Return mission that efficiently uses emerging commercial capabilities expected to be available in the near future. The motivation of our study was the recognition that emerging commercial capabilities might be used to perform Mars Sample Return with an Earth-direct architecture, and that this may offer a desirable simpler and lower cost approach. The objective of the study was to determine whether these capabilities can be used to optimize the number of mission systems and launches required to return the samples, with the goal of achieving the desired simplicity. All of the major element required for the Mars Sample Return mission are described. Mission system elements were analyzed with either direct techniques or by using parametric mass estimating relationships. The analysis shows the feasibility of a complete and closed Mars Sample Return mission design based on the following scenario: A SpaceX Falcon Heavy launch vehicle places a modified version of a SpaceX Dragon capsule, referred to as "Red Dragon", onto a Trans Mars Injection trajectory. The capsule carries all the hardware needed to return to Earth Orbit samples collected by a prior mission, such as the planned NASA Mars 2020 sample collection rover. The payload includes a fully fueled Mars Ascent Vehicle; a fueled Earth Return Vehicle, support equipment, and a mechanism to transfer samples from the sample cache system onboard the rover to the Earth Return Vehicle. The Red Dragon descends to land on the surface of Mars using Supersonic Retropropulsion. After collected samples are transferred to the Earth Return Vehicle, the single-stage Mars Ascent Vehicle launches the Earth Return Vehicle from the surface of Mars to a Mars phasing orbit. After a brief phasing period, the Earth Return

Recruiting Pregnant Patients for Survey Research: A Head to Head Comparison of Social Media-Based Versus Clinic-Based Approaches.

Science.gov (United States)

Admon, Lindsay; Haefner, Jessica K; Kolenic, Giselle E; Chang, Tammy; Davis, Matthew M; Moniz, Michelle H

2016-12-21

Recruiting a diverse sample of pregnant women for clinical research is a challenging but crucial task for improving obstetric services and maternal and child health outcomes. To compare the feasibility and cost of recruiting pregnant women for survey research using social media-based and clinic-based approaches. Advertisements were used to recruit pregnant women from the social media website Facebook. In-person methods were used to recruit pregnant women from the outpatient clinic of a large, tertiary care center. In both approaches, potential respondents were invited to participate in a 15-minute Web-based survey. Each recruitment method was monitored for 1 month. Using bivariate statistics, we compared the number, demographic characteristics, and health characteristics of women recruited and the cost per completed survey for each recruitment method. The social media-based approach recruited 1178 women and the clinic-based approach recruited 219 women. A higher proportion of subjects recruited through social media identified as African American (29.4%, 207/705 vs 11.2%, 20/179), reported household incomes social media had earned a college degree (21.3%, 153/717 vs 62.3%, 114/183) and were married or in a domestic partnership (45.7%, 330/722 vs 72.1%, 132/183; all PSocial media-based recruitment costs were US $14.63 per completed survey, compared with US $23.51 for clinic-based recruitment. Web-based recruitment through a social networking platform is a feasible, inexpensive, and rapid means of recruiting a large, diverse sample of pregnant women for survey research. ©Lindsay Admon, Jessica K Haefner, Giselle E Kolenic, Tammy Chang, Matthew M Davis, Michelle H Moniz. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.12.2016.

A comparison of temporal and location-based sampling strategies for global positioning system-triggered electronic diaries.

Science.gov (United States)

Törnros, Tobias; Dorn, Helen; Reichert, Markus; Ebner-Priemer, Ulrich; Salize, Hans-Joachim; Tost, Heike; Meyer-Lindenberg, Andreas; Zipf, Alexander

2016-11-21

Self-reporting is a well-established approach within the medical and psychological sciences. In order to avoid recall bias, i.e. past events being remembered inaccurately, the reports can be filled out on a smartphone in real-time and in the natural environment. This is often referred to as ambulatory assessment and the reports are usually triggered at regular time intervals. With this sampling scheme, however, rare events (e.g. a visit to a park or recreation area) are likely to be missed. When addressing the correlation between mood and the environment, it may therefore be beneficial to include participant locations within the ambulatory assessment sampling scheme. Based on the geographical coordinates, the database query system then decides if a self-report should be triggered or not. We simulated four different ambulatory assessment sampling schemes based on movement data (coordinates by minute) from 143 voluntary participants tracked for seven consecutive days. Two location-based sampling schemes incorporating the environmental characteristics (land use and population density) at each participant's location were introduced and compared to a time-based sampling scheme triggering a report on the hour as well as to a sampling scheme incorporating physical activity. We show that location-based sampling schemes trigger a report less often, but we obtain more unique trigger positions and a greater spatial spread in comparison to sampling strategies based on time and distance. Additionally, the location-based methods trigger significantly more often at rarely visited types of land use and less often outside the study region where no underlying environmental data are available.

Research on test of product based on spatial sampling criteria and variable step sampling mechanism

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Li, Ruihong; Han, Yueping

2014-09-01

This paper presents an effective approach for online testing the assembly structures inside products using multiple views technique and X-ray digital radiography system based on spatial sampling criteria and variable step sampling mechanism. Although there are some objects inside one product to be tested, there must be a maximal rotary step for an object within which the least structural size to be tested is predictable. In offline learning process, Rotating the object by the step and imaging it and so on until a complete cycle is completed, an image sequence is obtained that includes the full structural information for recognition. The maximal rotary step is restricted by the least structural size and the inherent resolution of the imaging system. During online inspection process, the program firstly finds the optimum solutions to all different target parts in the standard sequence, i.e., finds their exact angles in one cycle. Aiming at the issue of most sizes of other targets in product are larger than that of the least structure, the paper adopts variable step-size sampling mechanism to rotate the product specific angles with different steps according to different objects inside the product and match. Experimental results show that the variable step-size method can greatly save time compared with the traditional fixed-step inspection method while the recognition accuracy is guaranteed.

Bio-sample detection on paper-based devices with inkjet printer-sprayed reagents.

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Liang, Wun-Hong; Chu, Chien-Hung; Yang, Ruey-Jen

2015-12-01

The reagent required for bio-sample detection on paper-based analytical devices is generally introduced manually using a pipette. Such an approach is time-consuming; particularly if a large number of devices are required. Automated methods provide a far more convenient solution for large-scale production, but incur a substantial cost. Accordingly, the present study proposes a low-cost method for the paper-based analytical devices in which the biochemical reagents are sprayed onto the device directly using a modified commercial inkjet printer. The feasibility of the proposed method is demonstrated by performing aspartate aminotransferase (AST) and alanine aminotransferase (ALT) tests using simple two-dimensional (2D) paper-based devices. In both cases, the reaction process is analyzed using an image-processing-based colorimetric method. The experimental results show that for AST detection within the 0-105 U/l concentration range, the optimal observation time is around four minutes, while for ALT detection in the 0-125 U/l concentration range, the optimal observation time is approximately one minute. Finally, for both samples, the detection performance of the sprayed-reagent analytical devices is insensitive to the glucose concentration. Copyright © 2015 Elsevier B.V. All rights reserved.

Sample Based Unit Liter Dose Estimates

International Nuclear Information System (INIS)

JENSEN, L.

2000-01-01

The Tank Waste Characterization Program has taken many core samples, grab samples, and auger samples from the single-shell and double-shell tanks during the past 10 years. Consequently, the amount of sample data available has increased, both in terms of quantity of sample results and the number of tanks characterized. More and better data is available than when the current radiological and toxicological source terms used in the Basis for Interim Operation (BIO) (FDH 1999a) and the Final Safety Analysis Report (FSAR) (FDH 1999b) were developed. The Nuclear Safety and Licensing (NS and L) organization wants to use the new data to upgrade the radiological and toxicological source terms used in the BIO and FSAR. The NS and L organization requested assistance in producing a statistically based process for developing the source terms. This report describes the statistical techniques used and the assumptions made to support the development of a new radiological source term for liquid and solid wastes stored in single-shell and double-shell tanks. The results given in this report are a revision to similar results given in an earlier version of the document (Jensen and Wilmarth 1999). The main difference between the results in this document and the earlier version is that the dose conversion factors (DCF) for converting μCi/g or μCi/L to Sv/L (sieverts per liter) have changed. There are now two DCFs, one based on ICRP-68 and one based on ICW-71 (Brevick 2000)

A critical review of microextraction by packed sorbent as a sample preparation approach in drug bioanalysis.

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Alves, Gilberto; Rodrigues, Márcio; Fortuna, Ana; Falcão, Amílcar; Queiroz, João

2013-06-01

Sample preparation is widely accepted as the most labor-intensive and error-prone part of the bioanalytical process. The recent advances in this field have been focused on the miniaturization and integration of sample preparation online with analytical instrumentation, in order to reduce laboratory workload and increase analytical performance. From this perspective, microextraction by packed sorbent (MEPS) has emerged in the last few years as a powerful sample preparation approach suitable to be easily automated with liquid and gas chromatographic systems applied in a variety of bioanalytical areas (pharmaceutical, clinical, toxicological, environmental and food research). This paper aims to provide an overview and a critical discussion of recent bioanalytical methods reported in literature based on MEPS, with special emphasis on those developed for the quantification of therapeutic drugs and/or metabolites in biological samples. The advantages and some limitations of MEPS, as well as its comparison with other extraction techniques, are also addressed herein.

Optimal cross-sectional sampling for river modelling with bridges: An information theory-based method

Energy Technology Data Exchange (ETDEWEB)

Ridolfi, E.; Napolitano, F., E-mail: francesco.napolitano@uniroma1.it [Sapienza Università di Roma, Dipartimento di Ingegneria Civile, Edile e Ambientale (Italy); Alfonso, L. [Hydroinformatics Chair Group, UNESCO-IHE, Delft (Netherlands); Di Baldassarre, G. [Department of Earth Sciences, Program for Air, Water and Landscape Sciences, Uppsala University (Sweden)

2016-06-08

The description of river topography has a crucial role in accurate one-dimensional (1D) hydraulic modelling. Specifically, cross-sectional data define the riverbed elevation, the flood-prone area, and thus, the hydraulic behavior of the river. Here, the problem of the optimal cross-sectional spacing is solved through an information theory-based concept. The optimal subset of locations is the one with the maximum information content and the minimum amount of redundancy. The original contribution is the introduction of a methodology to sample river cross sections in the presence of bridges. The approach is tested on the Grosseto River (IT) and is compared to existing guidelines. The results show that the information theory-based approach can support traditional methods to estimate rivers’ cross-sectional spacing.

Optimal cross-sectional sampling for river modelling with bridges: An information theory-based method

International Nuclear Information System (INIS)

Ridolfi, E.; Napolitano, F.; Alfonso, L.; Di Baldassarre, G.

2016-01-01

The description of river topography has a crucial role in accurate one-dimensional (1D) hydraulic modelling. Specifically, cross-sectional data define the riverbed elevation, the flood-prone area, and thus, the hydraulic behavior of the river. Here, the problem of the optimal cross-sectional spacing is solved through an information theory-based concept. The optimal subset of locations is the one with the maximum information content and the minimum amount of redundancy. The original contribution is the introduction of a methodology to sample river cross sections in the presence of bridges. The approach is tested on the Grosseto River (IT) and is compared to existing guidelines. The results show that the information theory-based approach can support traditional methods to estimate rivers’ cross-sectional spacing.

A novel four-dimensional analytical approach for analysis of complex samples.

Science.gov (United States)

Stephan, Susanne; Jakob, Cornelia; Hippler, Jörg; Schmitz, Oliver J

2016-05-01

A two-dimensional LC (2D-LC) method, based on the work of Erni and Frei in 1978, was developed and coupled to an ion mobility-high-resolution mass spectrometer (IM-MS), which enabled the separation of complex samples in four dimensions (2D-LC, ion mobility spectrometry (IMS), and mass spectrometry (MS)). This approach works as a continuous multiheart-cutting LC system, using a long modulation time of 4 min, which allows the complete transfer of most of the first - dimension peaks to the second - dimension column without fractionation, in comparison to comprehensive two-dimensional liquid chromatography. Hence, each compound delivers only one peak in the second dimension, which simplifies the data handling even when ion mobility spectrometry as a third and mass spectrometry as a fourth dimension are introduced. The analysis of a plant extract from Ginkgo biloba shows the separation power of this four-dimensional separation method with a calculated total peak capacity of more than 8700. Furthermore, the advantage of ion mobility for characterizing unknown compounds by their collision cross section (CCS) and accurate mass in a non-target approach is shown for different matrices like plant extracts and coffee. Graphical abstract Principle of the four-dimensional separation.

A Novel Method of Adrenal Venous Sampling via an Antecubital Approach

Energy Technology Data Exchange (ETDEWEB)

Jiang, Xiongjing, E-mail: jxj103@hotmail.com; Dong, Hui; Peng, Meng; Che, Wuqiang; Zou, Yubao; Song, Lei; Zhang, Huimin; Wu, Haiying [Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease (China)

2017-03-15

PurposeCurrently, almost all adrenal venous sampling (AVS) procedures are performed by femoral vein access. The purpose of this study was to establish the technique of AVS via an antecubital approach and evaluate its safety and feasibility.Materials and MethodsFrom January 2012 to June 2015, 194 consecutive patients diagnosed as primary aldosteronism underwent AVS via an antecubital approach without ACTH simulation. Catheters used for bilateral adrenal cannulations were recorded. The success rate of bilateral adrenal sampling, operation time, fluoroscopy time, dosage of contrast, and incidence of complications were calculated.ResultsA 5F MPA1 catheter was first used to attempt right adrenal cannulation in all patients. Cannulation of the right adrenal vein was successfully performed in 164 (84.5%) patients. The 5F JR5, Cobra2, and TIG catheters were the ultimate catheters for right adrenal cannulation in 16 (8.2%), 5 (2.6%), and 9 (4.6%) patients, respectively. For left adrenal cannulation, JR5 and Cobra2 catheters were used in 19 (9.8%) and 10 (5.2%) patients, respectively, while only TIG catheters were used in the remaining 165 (85.1%) patients. The rate of successful adrenal sampling on the right, left, and bilateral sides was 91.8%, 93.3%, and 87.6%, respectively. The mean time of operation was (16.3 ± 4.3) minutes, mean fluoroscopy time was (4.7 ± 1.3) minutes, and the mean use of contrast was (14.3 ± 4.7) ml. The incidence of adrenal hematoma was 1.0%.ConclusionsThis study showed that AVS via an antecubital approach was safe and feasible, with a high rate of successful sampling.

Structure-based sampling and self-correcting machine learning for accurate calculations of potential energy surfaces and vibrational levels

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Dral, Pavlo O.; Owens, Alec; Yurchenko, Sergei N.; Thiel, Walter

2017-06-01

We present an efficient approach for generating highly accurate molecular potential energy surfaces (PESs) using self-correcting, kernel ridge regression (KRR) based machine learning (ML). We introduce structure-based sampling to automatically assign nuclear configurations from a pre-defined grid to the training and prediction sets, respectively. Accurate high-level ab initio energies are required only for the points in the training set, while the energies for the remaining points are provided by the ML model with negligible computational cost. The proposed sampling procedure is shown to be superior to random sampling and also eliminates the need for training several ML models. Self-correcting machine learning has been implemented such that each additional layer corrects errors from the previous layer. The performance of our approach is demonstrated in a case study on a published high-level ab initio PES of methyl chloride with 44 819 points. The ML model is trained on sets of different sizes and then used to predict the energies for tens of thousands of nuclear configurations within seconds. The resulting datasets are utilized in variational calculations of the vibrational energy levels of CH3Cl. By using both structure-based sampling and self-correction, the size of the training set can be kept small (e.g., 10% of the points) without any significant loss of accuracy. In ab initio rovibrational spectroscopy, it is thus possible to reduce the number of computationally costly electronic structure calculations through structure-based sampling and self-correcting KRR-based machine learning by up to 90%.

Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes

Directory of Open Access Journals (Sweden)

Heinz Gallaun

2015-09-01

Full Text Available Land cover change processes are accelerating at the regional to global level. The remote sensing community has developed reliable and robust methods for wall-to-wall mapping of land cover changes; however, land cover changes often occur at rates below the mapping errors. In the current publication, we propose a cost-effective approach to complement wall-to-wall land cover change maps with a sampling approach, which is used for accuracy assessment and accurate estimation of areas undergoing land cover changes, including provision of confidence intervals. We propose a two-stage sampling approach in order to keep accuracy, efficiency, and effort of the estimations in balance. Stratification is applied in both stages in order to gain control over the sample size allocated to rare land cover change classes on the one hand and the cost constraints for very high resolution reference imagery on the other. Bootstrapping is used to complement the accuracy measures and the area estimates with confidence intervals. The area estimates and verification estimations rely on a high quality visual interpretation of the sampling units based on time series of satellite imagery. To demonstrate the cost-effective operational applicability of the approach we applied it for assessment of deforestation in an area characterized by frequent cloud cover and very low change rate in the Republic of Congo, which makes accurate deforestation monitoring particularly challenging.

A Table-Based Random Sampling Simulation for Bioluminescence Tomography

Directory of Open Access Journals (Sweden)

Xiaomeng Zhang

2006-01-01

Full Text Available As a popular simulation of photon propagation in turbid media, the main problem of Monte Carlo (MC method is its cumbersome computation. In this work a table-based random sampling simulation (TBRS is proposed. The key idea of TBRS is to simplify multisteps of scattering to a single-step process, through randomly table querying, thus greatly reducing the computing complexity of the conventional MC algorithm and expediting the computation. The TBRS simulation is a fast algorithm of the conventional MC simulation of photon propagation. It retained the merits of flexibility and accuracy of conventional MC method and adapted well to complex geometric media and various source shapes. Both MC simulations were conducted in a homogeneous medium in our work. Also, we present a reconstructing approach to estimate the position of the fluorescent source based on the trial-and-error theory as a validation of the TBRS algorithm. Good agreement is found between the conventional MC simulation and the TBRS simulation.

Human Rights-Based Approaches to Mental Health: A Review of Programs.

Science.gov (United States)

Porsdam Mann, Sebastian; Bradley, Valerie J; Sahakian, Barbara J

2016-06-01

The incidence of human rights violations in mental health care across nations has been described as a "global emergency" and an "unresolved global crisis." The relationship between mental health and human rights is complex and bidirectional. Human rights violations can negatively impact mental health. Conversely, respecting human rights can improve mental health. This article reviews cases where an explicitly human rights-based approach was used in mental health care settings. Although the included studies did not exhibit a high level of methodological rigor, the qualitative information obtained was considered useful and informative for future studies. All studies reviewed suggest that human-rights based approaches can lead to clinical improvements at relatively low costs. Human rights-based approaches should be utilized for legal and moral reasons, since human rights are fundamental pillars of justice and civilization. The fact that such approaches can contribute to positive therapeutic outcomes and, potentially, cost savings, is additional reason for their implementation. However, the small sample size and lack of controlled, quantitative measures limit the strength of conclusions drawn from included studies. More objective, high quality research is needed to ascertain the true extent of benefits to service users and providers.

MITIE: Simultaneous RNA-Seq-based transcript identification and quantification in multiple samples.

Science.gov (United States)

Behr, Jonas; Kahles, André; Zhong, Yi; Sreedharan, Vipin T; Drewe, Philipp; Rätsch, Gunnar

2013-10-15

High-throughput sequencing of mRNA (RNA-Seq) has led to tremendous improvements in the detection of expressed genes and reconstruction of RNA transcripts. However, the extensive dynamic range of gene expression, technical limitations and biases, as well as the observed complexity of the transcriptional landscape, pose profound computational challenges for transcriptome reconstruction. We present the novel framework MITIE (Mixed Integer Transcript IdEntification) for simultaneous transcript reconstruction and quantification. We define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data and show how to find the optimal solution using Mixed Integer Programming. MITIE can (i) take advantage of known transcripts, (ii) reconstruct and quantify transcripts simultaneously in multiple samples, and (iii) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction. We present an extensive study based on realistic simulated RNA-Seq data. When compared with state-of-the-art approaches, MITIE proves to be significantly more sensitive and overall more accurate. Moreover, MITIE yields substantial performance gains when used with multiple samples. We applied our system to 38 Drosophila melanogaster modENCODE RNA-Seq libraries and estimated the sensitivity of reconstructing omitted transcript annotations and the specificity with respect to annotated transcripts. Our results corroborate that a well-motivated objective paired with appropriate optimization techniques lead to significant improvements over the state-of-the-art in transcriptome reconstruction. MITIE is implemented in C++ and is available from http://bioweb.me/mitie under the GPL license.

Acrylamide exposure among Turkish toddlers from selected cereal-based baby food samples.

Science.gov (United States)

Cengiz, Mehmet Fatih; Gündüz, Cennet Pelin Boyacı

2013-10-01

In this study, acrylamide exposure from selected cereal-based baby food samples was investigated among toddlers aged 1-3 years in Turkey. The study contained three steps. The first step was collecting food consumption data and toddlers' physical properties, such as gender, age and body weight, using a questionnaire given to parents by a trained interviewer between January and March 2012. The second step was determining the acrylamide levels in food samples that were reported on by the parents in the questionnaire, using a gas chromatography-mass spectrometry (GC-MS) method. The last step was combining the determined acrylamide levels in selected food samples with individual food consumption and body weight data using a deterministic approach to estimate the acrylamide exposure levels. The mean acrylamide levels of baby biscuits, breads, baby bread-rusks, crackers, biscuits, breakfast cereals and powdered cereal-based baby foods were 153, 225, 121, 604, 495, 290 and 36 μg/kg, respectively. The minimum, mean and maximum acrylamide exposures were estimated to be 0.06, 1.43 and 6.41 μg/kg BW per day, respectively. The foods that contributed to acrylamide exposure were aligned from high to low as bread, crackers, biscuits, baby biscuits, powdered cereal-based baby foods, baby bread-rusks and breakfast cereals. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Nonparametric Operational Risk Modeling Approach Based on Cornish-Fisher Expansion

Directory of Open Access Journals (Sweden)

Xiaoqian Zhu

2014-01-01

Full Text Available It is generally accepted that the choice of severity distribution in loss distribution approach has a significant effect on the operational risk capital estimation. However, the usually used parametric approaches with predefined distribution assumption might be not able to fit the severity distribution accurately. The objective of this paper is to propose a nonparametric operational risk modeling approach based on Cornish-Fisher expansion. In this approach, the samples of severity are generated by Cornish-Fisher expansion and then used in the Monte Carlo simulation to sketch the annual operational loss distribution. In the experiment, the proposed approach is employed to calculate the operational risk capital charge for the overall Chinese banking. The experiment dataset is the most comprehensive operational risk dataset in China as far as we know. The results show that the proposed approach is able to use the information of high order moments and might be more effective and stable than the usually used parametric approach.

Statistical conditional sampling for variable-resolution video compression.

Directory of Open Access Journals (Sweden)

Alexander Wong

Full Text Available In this study, we investigate a variable-resolution approach to video compression based on Conditional Random Field and statistical conditional sampling in order to further improve compression rate while maintaining high-quality video. In the proposed approach, representative key-frames within a video shot are identified and stored at full resolution. The remaining frames within the video shot are stored and compressed at a reduced resolution. At the decompression stage, a region-based dictionary is constructed from the key-frames and used to restore the reduced resolution frames to the original resolution via statistical conditional sampling. The sampling approach is based on the conditional probability of the CRF modeling by use of the constructed dictionary. Experimental results show that the proposed variable-resolution approach via statistical conditional sampling has potential for improving compression rates when compared to compressing the video at full resolution, while achieving higher video quality when compared to compressing the video at reduced resolution.

Adaptive sampling based on the cumulative distribution function of order statistics to delineate heavy-metal contaminated soils using kriging

International Nuclear Information System (INIS)

Juang, K.-W.; Lee, D.-Y.; Teng, Y.-L.

2005-01-01

Correctly classifying 'contaminated' areas in soils, based on the threshold for a contaminated site, is important for determining effective clean-up actions. Pollutant mapping by means of kriging is increasingly being used for the delineation of contaminated soils. However, those areas where the kriged pollutant concentrations are close to the threshold have a high possibility for being misclassified. In order to reduce the misclassification due to the over- or under-estimation from kriging, an adaptive sampling using the cumulative distribution function of order statistics (CDFOS) was developed to draw additional samples for delineating contaminated soils, while kriging. A heavy-metal contaminated site in Hsinchu, Taiwan was used to illustrate this approach. The results showed that compared with random sampling, adaptive sampling using CDFOS reduced the kriging estimation errors and misclassification rates, and thus would appear to be a better choice than random sampling, as additional sampling is required for delineating the 'contaminated' areas. - A sampling approach was derived for drawing additional samples while kriging

Constraining Unsaturated Hydraulic Parameters Using the Latin Hypercube Sampling Method and Coupled Hydrogeophysical Approach

Science.gov (United States)

Farzamian, Mohammad; Monteiro Santos, Fernando A.; Khalil, Mohamed A.

2017-12-01

The coupled hydrogeophysical approach has proved to be a valuable tool for improving the use of geoelectrical data for hydrological model parameterization. In the coupled approach, hydrological parameters are directly inferred from geoelectrical measurements in a forward manner to eliminate the uncertainty connected to the independent inversion of electrical resistivity data. Several numerical studies have been conducted to demonstrate the advantages of a coupled approach; however, only a few attempts have been made to apply the coupled approach to actual field data. In this study, we developed a 1D coupled hydrogeophysical code to estimate the van Genuchten-Mualem model parameters, K s, n, θ r and α, from time-lapse vertical electrical sounding data collected during a constant inflow infiltration experiment. van Genuchten-Mualem parameters were sampled using the Latin hypercube sampling method to provide a full coverage of the range of each parameter from their distributions. By applying the coupled approach, vertical electrical sounding data were coupled to hydrological models inferred from van Genuchten-Mualem parameter samples to investigate the feasibility of constraining the hydrological model. The key approaches taken in the study are to (1) integrate electrical resistivity and hydrological data and avoiding data inversion, (2) estimate the total water mass recovery of electrical resistivity data and consider it in van Genuchten-Mualem parameters evaluation and (3) correct the influence of subsurface temperature fluctuations during the infiltration experiment on electrical resistivity data. The results of the study revealed that the coupled hydrogeophysical approach can improve the value of geophysical measurements in hydrological model parameterization. However, the approach cannot overcome the technical limitations of the geoelectrical method associated with resolution and of water mass recovery.

Approaches to sampling and case selection in qualitative research: examples in the geography of health.

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Curtis, S; Gesler, W; Smith, G; Washburn, S

2000-04-01

This paper focuses on the question of sampling (or selection of cases) in qualitative research. Although the literature includes some very useful discussions of qualitative sampling strategies, the question of sampling often seems to receive less attention in methodological discussion than questions of how data is collected or is analysed. Decisions about sampling are likely to be important in many qualitative studies (although it may not be an issue in some research). There are varying accounts of the principles applicable to sampling or case selection. Those who espouse 'theoretical sampling', based on a 'grounded theory' approach, are in some ways opposed to those who promote forms of 'purposive sampling' suitable for research informed by an existing body of social theory. Diversity also results from the many different methods for drawing purposive samples which are applicable to qualitative research. We explore the value of a framework suggested by Miles and Huberman [Miles, M., Huberman,, A., 1994. Qualitative Data Analysis, Sage, London.], to evaluate the sampling strategies employed in three examples of research by the authors. Our examples comprise three studies which respectively involve selection of: 'healing places'; rural places which incorporated national anti-malarial policies; young male interviewees, identified as either chronically ill or disabled. The examples are used to show how in these three studies the (sometimes conflicting) requirements of the different criteria were resolved, as well as the potential and constraints placed on the research by the selection decisions which were made. We also consider how far the criteria Miles and Huberman suggest seem helpful for planning 'sample' selection in qualitative research.

A dimensional approach to personality disorders in a sample of juvenile offenders

Directory of Open Access Journals (Sweden)

Daniela Cantone

2012-03-01

Full Text Available In a sample of 60 male Italian subjects imprisoned at a juvenile detention institute (JDI, psychopathological aspects of the AXIS II were described and the validity of a psychopathological dimensional approach for describing criminological issues was examined. The data show that the sample has psychopathological characteristics which revolve around ego weakness and poor management of relations and aggression. Statistically these psychopathological characteristics explain 85% of criminal behavior.

Flexible automated approach for quantitative liquid handling of complex biological samples.

Science.gov (United States)

Palandra, Joe; Weller, David; Hudson, Gary; Li, Jeff; Osgood, Sarah; Hudson, Emily; Zhong, Min; Buchholz, Lisa; Cohen, Lucinda H

2007-11-01

A fully automated protein precipitation technique for biological sample preparation has been developed for the quantitation of drugs in various biological matrixes. All liquid handling during sample preparation was automated using a Hamilton MicroLab Star Robotic workstation, which included the preparation of standards and controls from a Watson laboratory information management system generated work list, shaking of 96-well plates, and vacuum application. Processing time is less than 30 s per sample or approximately 45 min per 96-well plate, which is then immediately ready for injection onto an LC-MS/MS system. An overview of the process workflow is discussed, including the software development. Validation data are also provided, including specific liquid class data as well as comparative data of automated vs manual preparation using both quality controls and actual sample data. The efficiencies gained from this automated approach are described.

Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

Science.gov (United States)

Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

2017-09-01

The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.

Target and suspect screening of psychoactive substances in sewage-based samples by UHPLC-QTOF

Energy Technology Data Exchange (ETDEWEB)

Baz-Lomba, J.A., E-mail: jba@niva.no [Norwegian Institute for Water Research, Gaustadalléen 21, NO-0349, Oslo (Norway); Faculty of Medicine, University of Oslo, PO box 1078 Blindern, 0316, Oslo (Norway); Reid, Malcolm J.; Thomas, Kevin V. [Norwegian Institute for Water Research, Gaustadalléen 21, NO-0349, Oslo (Norway)

2016-03-31

The quantification of illicit drug and pharmaceutical residues in sewage has been shown to be a valuable tool that complements existing approaches in monitoring the patterns and trends of drug use. The present work delineates the development of a novel analytical tool and dynamic workflow for the analysis of a wide range of substances in sewage-based samples. The validated method can simultaneously quantify 51 target psychoactive substances and pharmaceuticals in sewage-based samples using an off-line automated solid phase extraction (SPE-DEX) method, using Oasis HLB disks, followed by ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) in MS{sup e}. Quantification and matrix effect corrections were overcome with the use of 25 isotopic labeled internal standards (ILIS). Recoveries were generally greater than 60% and the limits of quantification were in the low nanogram-per-liter range (0.4–187 ng L{sup −1}). The emergence of new psychoactive substances (NPS) on the drug scene poses a specific analytical challenge since their market is highly dynamic with new compounds continuously entering the market. Suspect screening using high-resolution mass spectrometry (HRMS) simultaneously allowed the unequivocal identification of NPS based on a mass accuracy criteria of 5 ppm (of the molecular ion and at least two fragments) and retention time (2.5% tolerance) using the UNIFI screening platform. Applying MS{sup e} data against a suspect screening database of over 1000 drugs and metabolites, this method becomes a broad and reliable tool to detect and confirm NPS occurrence. This was demonstrated through the HRMS analysis of three different sewage-based sample types; influent wastewater, passive sampler extracts and pooled urine samples resulting in the concurrent quantification of known psychoactive substances and the identification of NPS and pharmaceuticals. - Highlights: • A novel reiterative workflow

Target and suspect screening of psychoactive substances in sewage-based samples by UHPLC-QTOF

International Nuclear Information System (INIS)

Baz-Lomba, J.A.; Reid, Malcolm J.; Thomas, Kevin V.

2016-01-01

The quantification of illicit drug and pharmaceutical residues in sewage has been shown to be a valuable tool that complements existing approaches in monitoring the patterns and trends of drug use. The present work delineates the development of a novel analytical tool and dynamic workflow for the analysis of a wide range of substances in sewage-based samples. The validated method can simultaneously quantify 51 target psychoactive substances and pharmaceuticals in sewage-based samples using an off-line automated solid phase extraction (SPE-DEX) method, using Oasis HLB disks, followed by ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) in MS"e. Quantification and matrix effect corrections were overcome with the use of 25 isotopic labeled internal standards (ILIS). Recoveries were generally greater than 60% and the limits of quantification were in the low nanogram-per-liter range (0.4–187 ng L"−"1). The emergence of new psychoactive substances (NPS) on the drug scene poses a specific analytical challenge since their market is highly dynamic with new compounds continuously entering the market. Suspect screening using high-resolution mass spectrometry (HRMS) simultaneously allowed the unequivocal identification of NPS based on a mass accuracy criteria of 5 ppm (of the molecular ion and at least two fragments) and retention time (2.5% tolerance) using the UNIFI screening platform. Applying MS"e data against a suspect screening database of over 1000 drugs and metabolites, this method becomes a broad and reliable tool to detect and confirm NPS occurrence. This was demonstrated through the HRMS analysis of three different sewage-based sample types; influent wastewater, passive sampler extracts and pooled urine samples resulting in the concurrent quantification of known psychoactive substances and the identification of NPS and pharmaceuticals. - Highlights: • A novel reiterative workflow based on three

Preparing Digital Stories through the Inquiry-Based Learning Approach: Its Effect on Prospective Teachers' Resistive Behaviors toward Research and Technology-Based Instruction

Science.gov (United States)

Yavuz Konokman, Gamze; Yanpar Yelken, Tugba

2016-01-01

The purpose of the study was to determine the effect of preparing digital stories through an inquiry based learning approach on prospective teachers' resistive behaviors toward technology based instruction and conducting research. The research model was convergent parallel design. The sample consisted of 50 prospective teachers who had completed…

Form-based Approaches vs. Task-Based Approaches

Directory of Open Access Journals (Sweden)

Zahra Talebi

2015-07-01

Full Text Available This study aimed at investigating whether task-based approaches bear any superiority to that of more traditional ones evident in presentation-practice- and production phase .to fulfill the purpose of the study, the participants within the age range of 11-19, took part in the study. Following a pretest, treatment, and a posttest, the obtained data was analyzed using analysis of covariance (ANCOVA to examine the effects of the variables. The results of the analysis showed that participants in the PPP group did significantly better in the grammar recognition of the posttest than that of the task group. However, their counterparts in the task group gained better scores in the writing section of the test .this research study provided evidence in support of task proponents' claim in the merit of task-based activity in raising learners' implicit knowledge claiming to play the primary role in spontaneous speech.

Consensus of heterogeneous multi-agent systems based on sampled data with a small sampling delay

International Nuclear Information System (INIS)

Wang Na; Wu Zhi-Hai; Peng Li

2014-01-01

In this paper, consensus problems of heterogeneous multi-agent systems based on sampled data with a small sampling delay are considered. First, a consensus protocol based on sampled data with a small sampling delay for heterogeneous multi-agent systems is proposed. Then, the algebra graph theory, the matrix method, the stability theory of linear systems, and some other techniques are employed to derive the necessary and sufficient conditions guaranteeing heterogeneous multi-agent systems to asymptotically achieve the stationary consensus. Finally, simulations are performed to demonstrate the correctness of the theoretical results. (interdisciplinary physics and related areas of science and technology)

A sampling and metagenomic sequencing-based methodology for monitoring antimicrobial resistance in swine herds

DEFF Research Database (Denmark)

Munk, Patrick; Dalhoff Andersen, Vibe; de Knegt, Leonardo

2016-01-01

Objectives Reliable methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs are essential to understand the trends, transmission and importance of agricultural resistance. Quantification of AMR is mostly done using culture-based techniques, but metagenomic read...... mapping shows promise for quantitative resistance monitoring. Methods We evaluated the ability of: (i) MIC determination for Escherichia coli; (ii) cfu counting of E. coli; (iii) cfu counting of aerobic bacteria; and (iv) metagenomic shotgun sequencing to predict expected tetracycline resistance based...... cultivation-based techniques in terms of predicting expected tetracycline resistance based on antimicrobial consumption. Our metagenomic approach had sufficient resolution to detect antimicrobial-induced changes to individual resistance gene abundances. Pen floor manure samples were found to represent rectal...

Efficient sampling algorithms for Monte Carlo based treatment planning

International Nuclear Information System (INIS)

DeMarco, J.J.; Solberg, T.D.; Chetty, I.; Smathers, J.B.

1998-01-01

Efficient sampling algorithms are necessary for producing a fast Monte Carlo based treatment planning code. This study evaluates several aspects of a photon-based tracking scheme and the effect of optimal sampling algorithms on the efficiency of the code. Four areas were tested: pseudo-random number generation, generalized sampling of a discrete distribution, sampling from the exponential distribution, and delta scattering as applied to photon transport through a heterogeneous simulation geometry. Generalized sampling of a discrete distribution using the cutpoint method can produce speedup gains of one order of magnitude versus conventional sequential sampling. Photon transport modifications based upon the delta scattering method were implemented and compared with a conventional boundary and collision checking algorithm. The delta scattering algorithm is faster by a factor of six versus the conventional algorithm for a boundary size of 5 mm within a heterogeneous geometry. A comparison of portable pseudo-random number algorithms and exponential sampling techniques is also discussed

Sampling-based approaches to improve estimation of mortality among patient dropouts: experience from a large PEPFAR-funded program in Western Kenya.

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Constantin T Yiannoutsos

Full Text Available Monitoring and evaluation (M&E of HIV care and treatment programs is impacted by losses to follow-up (LTFU in the patient population. The severity of this effect is undeniable but its extent unknown. Tracing all lost patients addresses this but census methods are not feasible in programs involving rapid scale-up of HIV treatment in the developing world. Sampling-based approaches and statistical adjustment are the only scaleable methods permitting accurate estimation of M&E indices.In a large antiretroviral therapy (ART program in western Kenya, we assessed the impact of LTFU on estimating patient mortality among 8,977 adult clients of whom, 3,624 were LTFU. Overall, dropouts were more likely male (36.8% versus 33.7%; p = 0.003, and younger than non-dropouts (35.3 versus 35.7 years old; p = 0.020, with lower median CD4 count at enrollment (160 versus 189 cells/ml; p<0.001 and WHO stage 3-4 disease (47.5% versus 41.1%; p<0.001. Urban clinic clients were 75.0% of non-dropouts but 70.3% of dropouts (p<0.001. Of the 3,624 dropouts, 1,143 were sought and 621 had their vital status ascertained. Statistical techniques were used to adjust mortality estimates based on information obtained from located LTFU patients. Observed mortality estimates one year after enrollment were 1.7% (95% CI 1.3%-2.0%, revised to 2.8% (2.3%-3.1% when deaths discovered through outreach were added and adjusted to 9.2% (7.8%-10.6% and 9.9% (8.4%-11.5% through statistical modeling depending on the method used. The estimates 12 months after ART initiation were 1.7% (1.3%-2.2%, 3.4% (2.9%-4.0%, 10.5% (8.7%-12.3% and 10.7% (8.9%-12.6% respectively. CONCLUSIONS/SIGNIFICANCE ABSTRACT: Assessment of the impact of LTFU is critical in program M&E as estimated mortality based on passive monitoring may underestimate true mortality by up to 80%. This bias can be ameliorated by tracing a sample of dropouts and statistically adjust the mortality estimates to properly evaluate and guide large

APPROACH ON INTELLIGENT OPTIMIZATION DESIGN BASED ON COMPOUND KNOWLEDGE

Institute of Scientific and Technical Information of China (English)

Yao Jianchu; Zhou Ji; Yu Jun

2003-01-01

A concept of an intelligent optimal design approach is proposed, which is organized by a kind of compound knowledge model. The compound knowledge consists of modularized quantitative knowledge, inclusive experience knowledge and case-based sample knowledge. By using this compound knowledge model, the abundant quantity information of mathematical programming and the symbolic knowledge of artificial intelligence can be united together in this model. The intelligent optimal design model based on such a compound knowledge and the automatically generated decomposition principles based on it are also presented. Practically, it is applied to the production planning, process schedule and optimization of production process of a refining & chemical work and a great profit is achieved. Specially, the methods and principles are adaptable not only to continuous process industry, but also to discrete manufacturing one.

Cassette-based in-situ TEM sample inspection in the dual-beam FIB

International Nuclear Information System (INIS)

Kendrick, A B; Moore, T M; Zaykova-Feldman, L; Amador, G; Hammer, M

2008-01-01

A novel method is presented, combining site-specific TEM sample preparation and in-situ STEM analysis in a dual-beam microscope (FIB/SEM) fitted with a chamber mounted nano-manipulator. TEM samples are prepared using a modified in-situ, lift-out method, whereby the samples are thinned and oriented for immediate in-situ STEM analysis using the tilt, translation, and rotation capabilities of a FIB/SEM sample stage, a nano-manipulator, and a novel cassette. This cassette can provide a second tilt axis, orthogonal to the stage tilt axis, so that the STEM image contrast can be optimized to reveal the structural features of the sample (true STEM imaging in the FIB/SEM). The angles necessary for stage rotation and probe shaft rotation are calculated based on the position of the nano-manipulator relative to the stage and door and the stage tilt angle. A FIB/SEM instrument, equipped with a high resolution scanning electron column, can provide sufficiently high image resolution to enable many failure analysis and process control applications to be successfully carried out without requiring the use of a separate dedicated TEM/STEM instrument. The benefits of this novel approach are increased throughput and reduced cost per sample. Comparative analysis of different sample preparation methods is provided, and the STEM images obtained are shown.

MStern Blotting-High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates.

Science.gov (United States)

Berger, Sebastian T; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

2015-10-01

We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge

Science.gov (United States)

Kumar, Ashutosh; Zhang, Kam Y. J.

2012-05-01

SAMPL3 fragment based virtual screening challenge provides a valuable opportunity for researchers to test their programs, methods and screening protocols in a blind testing environment. We participated in SAMPL3 challenge and evaluated our virtual fragment screening protocol, which involves RosettaLigand as the core component by screening a 500 fragments Maybridge library against bovine pancreatic trypsin. Our study reaffirmed that the real test for any virtual screening approach would be in a blind testing environment. The analyses presented in this paper also showed that virtual screening performance can be improved, if a set of known active compounds is available and parameters and methods that yield better enrichment are selected. Our study also highlighted that to achieve accurate orientation and conformation of ligands within a binding site, selecting an appropriate method to calculate partial charges is important. Another finding is that using multiple receptor ensembles in docking does not always yield better enrichment than individual receptors. On the basis of our results and retrospective analyses from SAMPL3 fragment screening challenge we anticipate that chances of success in a fragment screening process could be increased significantly with careful selection of receptor structures, protein flexibility, sufficient conformational sampling within binding pocket and accurate assignment of ligand and protein partial charges.

Teaching Probability to Pre-Service Teachers with Argumentation Based Science Learning Approach

Science.gov (United States)

Can, Ömer Sinan; Isleyen, Tevfik

2016-01-01

The aim of this study is to explore the effects of the argumentation based science learning (ABSL) approach on the teaching probability to pre-service teachers. The sample of the study included 41 students studying at the Department of Elementary School Mathematics Education in a public university during the 2014-2015 academic years. The study is…

Predicting Drug-Target Interactions Based on Small Positive Samples.

Science.gov (United States)

Hu, Pengwei; Chan, Keith C C; Hu, Yanxing

2018-01-01

A basic task in drug discovery is to find new medication in the form of candidate compounds that act on a target protein. In other words, a drug has to interact with a target and such drug-target interaction (DTI) is not expected to be random. Significant and interesting patterns are expected to be hidden in them. If these patterns can be discovered, new drugs are expected to be more easily discoverable. Currently, a number of computational methods have been proposed to predict DTIs based on their similarity. However, such as approach does not allow biochemical features to be directly considered. As a result, some methods have been proposed to try to discover patterns in physicochemical interactions. Since the number of potential negative DTIs are very high both in absolute terms and in comparison to that of the known ones, these methods are rather computationally expensive and they can only rely on subsets, rather than the full set, of negative DTIs for training and validation. As there is always a relatively high chance for negative DTIs to be falsely identified and as only partial subset of such DTIs is considered, existing approaches can be further improved to better predict DTIs. In this paper, we present a novel approach, called ODT (one class drug target interaction prediction), for such purpose. One main task of ODT is to discover association patterns between interacting drugs and proteins from the chemical structure of the former and the protein sequence network of the latter. ODT does so in two phases. First, the DTI-network is transformed to a representation by structural properties. Second, it applies a oneclass classification algorithm to build a prediction model based only on known positive interactions. We compared the best AUROC scores of the ODT with several state-of-art approaches on Gold standard data. The prediction accuracy of the ODT is superior in comparison with all the other methods at GPCRs dataset and Ion channels dataset. Performance

PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE

Directory of Open Access Journals (Sweden)

Wei Leong Khong

2014-02-01

Full Text Available Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to the high probability of changing vehicle appearance and illumination, besides the occlusion and overlapping incidents. Particle filter has been proven as an approach which can overcome nonlinear and non-Gaussian situations caused by cluttered background and occlusion incidents. Unfortunately, conventional particle filter approach encounters particle degeneracy especially during and after the occlusion. Particle filter with sampling important resampling (SIR is an important step to overcome the drawback of particle filter, but SIR faced the problem of sample impoverishment when heavy particles are statistically selected many times. In this work, genetic algorithm has been proposed to be implemented in the particle filter resampling stage, where the estimated position can converge faster to hit the real position of target vehicle under various occlusion incidents. The experimental results show that the improved particle filter with genetic algorithm resampling method manages to increase the tracking accuracy and meanwhile reduce the particle sample size in the resampling stage.

Sample size calculations based on a difference in medians for positively skewed outcomes in health care studies

Directory of Open Access Journals (Sweden)

Aidan G. O’Keeffe

2017-12-01

Full Text Available Abstract Background In healthcare research, outcomes with skewed probability distributions are common. Sample size calculations for such outcomes are typically based on estimates on a transformed scale (e.g. log which may sometimes be difficult to obtain. In contrast, estimates of median and variance on the untransformed scale are generally easier to pre-specify. The aim of this paper is to describe how to calculate a sample size for a two group comparison of interest based on median and untransformed variance estimates for log-normal outcome data. Methods A log-normal distribution for outcome data is assumed and a sample size calculation approach for a two-sample t-test that compares log-transformed outcome data is demonstrated where the change of interest is specified as difference in median values on the untransformed scale. A simulation study is used to compare the method with a non-parametric alternative (Mann-Whitney U test in a variety of scenarios and the method is applied to a real example in neurosurgery. Results The method attained a nominal power value in simulation studies and was favourable in comparison to a Mann-Whitney U test and a two-sample t-test of untransformed outcomes. In addition, the method can be adjusted and used in some situations where the outcome distribution is not strictly log-normal. Conclusions We recommend the use of this sample size calculation approach for outcome data that are expected to be positively skewed and where a two group comparison on a log-transformed scale is planned. An advantage of this method over usual calculations based on estimates on the log-transformed scale is that it allows clinical efficacy to be specified as a difference in medians and requires a variance estimate on the untransformed scale. Such estimates are often easier to obtain and more interpretable than those for log-transformed outcomes.

Exploitation of FTA cartridges for the sampling, long-term storage, and DNA-based analyses of plant-parasitic nematodes.

Science.gov (United States)

Marek, Martin; Zouhar, Miloslav; Douda, Ondřej; Maňasová, Marie; Ryšánek, Pavel

2014-03-01

The use of DNA-based analyses in molecular plant nematology research has dramatically increased over recent decades. Therefore, the development and adaptation of simple, robust, and cost-effective DNA purification procedures are required to address these contemporary challenges. The solid-phase-based approach developed by Flinders Technology Associates (FTA) has been shown to be a powerful technology for the preparation of DNA from different biological materials, including blood, saliva, plant tissues, and various human and plant microbial pathogens. In this work, we demonstrate, for the first time, that this FTA-based technology is a valuable, low-cost, and time-saving approach for the sampling, long-term archiving, and molecular analysis of plant-parasitic nematodes. Despite the complex structure and anatomical organization of the multicellular bodies of nematodes, we report the successful and reliable DNA-based analysis of nematode high-copy and low-copy genes using the FTA technology. This was achieved by applying nematodes to the FTA cards either in the form of a suspension of individuals, as intact or pestle-crushed nematodes, or by the direct mechanical printing of nematode-infested plant tissues. We further demonstrate that the FTA method is also suitable for the so-called "one-nematode-assay", in which the target DNA is typically analyzed from a single individual nematode. More surprisingly, a time-course experiment showed that nematode DNA can be detected specifically in the FTA-captured samples many years after initial sampling occurs. Collectively, our data clearly demonstrate the applicability and the robustness of this FTA-based approach for molecular research and diagnostics concerning phytonematodes; this research includes economically important species such as the stem nematode (Ditylenchus dipsaci), the sugar beet nematode (Heterodera schachtii), and the Northern root-knot nematode (Meloidogyne hapla).

Downsampling Non-Uniformly Sampled Data

Directory of Open Access Journals (Sweden)

Fredrik Gustafsson

2007-10-01

Full Text Available Decimating a uniformly sampled signal a factor D involves low-pass antialias filtering with normalized cutoff frequency 1/D followed by picking out every Dth sample. Alternatively, decimation can be done in the frequency domain using the fast Fourier transform (FFT algorithm, after zero-padding the signal and truncating the FFT. We outline three approaches to decimate non-uniformly sampled signals, which are all based on interpolation. The interpolation is done in different domains, and the inter-sample behavior does not need to be known. The first one interpolates the signal to a uniformly sampling, after which standard decimation can be applied. The second one interpolates a continuous-time convolution integral, that implements the antialias filter, after which every Dth sample can be picked out. The third frequency domain approach computes an approximate Fourier transform, after which truncation and IFFT give the desired result. Simulations indicate that the second approach is particularly useful. A thorough analysis is therefore performed for this case, using the assumption that the non-uniformly distributed sampling instants are generated by a stochastic process.

A Story-Based Simulation for Teaching Sampling Distributions

Science.gov (United States)

Turner, Stephen; Dabney, Alan R.

2015-01-01

Statistical inference relies heavily on the concept of sampling distributions. However, sampling distributions are difficult to teach. We present a series of short animations that are story-based, with associated assessments. We hope that our contribution can be useful as a tool to teach sampling distributions in the introductory statistics…

Investigating role stress in frontline bank employees: A cluster based approach

Directory of Open Access Journals (Sweden)

Arti Devi

2013-09-01

Full Text Available An effective role stress management programme would benefit from a segmentation of employees based on their experience of role stressors. This study explores role stressor based segments of frontline bank employees towards providing a framework for designing such a programme. Cluster analysis on a random sample of 501 frontline employees of commercial banks in Jammu and Kashmir (India revealed three distinct segments – “overloaded employees”, “unclear employees”, and “underutilised employees”, based on their experience of role stressors. The findings suggest a customised approach to role stress management, with the role stress management programme designed to address cluster specific needs.

The generalization ability of online SVM classification based on Markov sampling.

Science.gov (United States)

Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

2015-03-01

In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

Task-based Language Teaching and Text Types in Teaching Writing Using Communicative Approach

Directory of Open Access Journals (Sweden)

Riyana Sari Ni Nyoman

2018-01-01

Full Text Available One of the most important language competencies in teaching learning process is writing. The present study focused on investigating the effect of communicative approach with task-based language teaching and communicative approach on the students’ writing competency at SMP N 2 Kediri viewed from text types(i.e. descriptive, recount, and narrative. To analyze the data, the design of the experimental study was posttest-only comparison groups by involving 60 students that were selected as the sample of the study through cluster random design. The sample’s post tests were assessed by using analytical scoring rubric. The data were then analyzed by using One-way ANOVA and the post hoc test was done by computing Multiple Comparison using Tukey HSD Test. The result showed that there was significant difference of the effect of communicative approach with task-based language teaching and communicative approach on the students’ writing competency. These findings are expected to give contribution in teaching English, particularly writing.

Use of amplicon sequencing to improve sensitivity in PCR-based detection of microbial pathogen in environmental samples.

Science.gov (United States)

Saingam, Prakit; Li, Bo; Yan, Tao

2018-06-01

DNA-based molecular detection of microbial pathogens in complex environments is still plagued by sensitivity, specificity and robustness issues. We propose to address these issues by viewing them as inadvertent consequences of requiring specific and adequate amplification (SAA) of target DNA molecules by current PCR methods. Using the invA gene of Salmonella as the model system, we investigated if next generation sequencing (NGS) can be used to directly detect target sequences in false-negative PCR reaction (PCR-NGS) in order to remove the SAA requirement from PCR. False-negative PCR and qPCR reactions were first created using serial dilutions of laboratory-prepared Salmonella genomic DNA and then analyzed directly by NGS. Target invA sequences were detected in all false-negative PCR and qPCR reactions, which lowered the method detection limits near the theoretical minimum of single gene copy detection. The capability of the PCR-NGS approach in correcting false negativity was further tested and confirmed under more environmentally relevant conditions using Salmonella-spiked stream water and sediment samples. Finally, the PCR-NGS approach was applied to ten urban stream water samples and detected invA sequences in eight samples that would be otherwise deemed Salmonella negative. Analysis of the non-target sequences in the false-negative reactions helped to identify primer dime-like short sequences as the main cause of the false negativity. Together, the results demonstrated that the PCR-NGS approach can significantly improve method sensitivity, correct false-negative detections, and enable sequence-based analysis for failure diagnostics in complex environmental samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Sample Based Unit Liter Dose Estimates

International Nuclear Information System (INIS)

JENSEN, L.

1999-01-01

The Tank Waste Characterization Program has taken many core samples, grab samples, and auger samples from the single-shell and double-shell tanks during the past 10 years. Consequently, the amount of sample data available has increased, both in terms of quantity of sample results and the number of tanks characterized. More and better data is available than when the current radiological and toxicological source terms used in the Basis for Interim Operation (BIO) (FDH 1999) and the Final Safety Analysis Report (FSAR) (FDH 1999) were developed. The Nuclear Safety and Licensing (NS and L) organization wants to use the new data to upgrade the radiological and toxicological source terms used in the BIO and FSAR. The NS and L organization requested assistance in developing a statistically based process for developing the source terms. This report describes the statistical techniques used and the assumptions made to support the development of a new radiological source term for liquid and solid wastes stored in single-shell and double-shell tanks

Understanding images using knowledge based approach

International Nuclear Information System (INIS)

Tascini, G.

1985-01-01

This paper presents an approach to image understanding focusing on low level image processing and proposes a rule-based approach as part of larger knowledge-based system. The general system has a yerarchical structure that comprises several knowledge-based layers. The main idea is to confine at the lower level the domain independent knowledge and to reserve the higher levels for the domain dependent knowledge, that is for the interpretation

DEVELOPING AN EXCELLENT SEDIMENT RATING CURVE FROM ONE HYDROLOGICAL YEAR SAMPLING PROGRAMME DATA: APPROACH

Directory of Open Access Journals (Sweden)

Preksedis M. Ndomba

2008-01-01

Full Text Available This paper presents preliminary findings on the adequacy of one hydrological year sampling programme data in developing an excellent sediment rating curve. The study case is a 1DD1 subcatchment in the upstream of Pangani River Basin (PRB, located in the North Eastern part of Tanzania. 1DD1 is the major runoff-sediment contributing tributary to the downstream hydropower reservoir, the Nyumba Ya Mungu (NYM. In literature sediment rating curve method is known to underestimate the actual sediment load. In the case of developing countries long-term sediment sampling monitoring or conservation campaigns have been reported as unworkable options. Besides, to the best knowledge of the authors, to date there is no consensus on how to develop an excellent rating curve. Daily-midway and intermittent-cross section sediment samples from Depth Integrating sampler (D-74 were used to calibrate the subdaily automatic sediment pumping sampler (ISCO 6712 near bank point samples for developing the rating curve. Sediment load correction factors were derived from both statistical bias estimators and actual sediment load approaches. It should be noted that the ongoing study is guided by findings of other studies in the same catchment. For instance, long term sediment yield rate estimated based on reservoir survey validated the performance of the developed rating curve. The result suggests that excellent rating curve could be developed from one hydrological year sediment sampling programme data. This study has also found that uncorrected rating curve underestimates sediment load. The degreeof underestimation depends on the type of rating curve developed and data used.

Alternative approaches to risk-based technical specifications

International Nuclear Information System (INIS)

Atefi, B.; Gallagher, D.W.; Liner, R.T.; Lofgren, E.V.

1987-01-01

Four alternative risk-based approaches to Technical Specifications are identified. These are: a Probabilistic Risk Assessment (PRA) oriented approach; a reliability goal-oriented approach; an approach based on configuration control; a data-oriented approach. Based on preliminary results, the PRA-oriented approach, which has been developed further than the other approaches, seems to offer a logical, quantitative basis for setting Allowed Outage Times (AOTs) and Surveillance Test Intervals (STIs) for some plant components and systems. The most attractive feature of this approach is that it directly links the AOTs and STIs with the risk associated with the operation of the plant. This would focus the plant operator's and the regulatory agency's attention on the most risk-significant components of the plant. A series of practical issues related to the level of detail and content of the plant PRAs, requirements for the review of these PRAs, and monitoring cf the plant's performance by the regulatory agency must be resolved before the approach could be implemented. Future efforts will examine the other three approaches and their practicality before firm conclusions are drawn regarding the viability of any of these approaches

Transfer function design based on user selected samples for intuitive multivariate volume exploration

KAUST Repository

Zhou, Liang

2013-02-01

Multivariate volumetric datasets are important to both science and medicine. We propose a transfer function (TF) design approach based on user selected samples in the spatial domain to make multivariate volumetric data visualization more accessible for domain users. Specifically, the user starts the visualization by probing features of interest on slices and the data values are instantly queried by user selection. The queried sample values are then used to automatically and robustly generate high dimensional transfer functions (HDTFs) via kernel density estimation (KDE). Alternatively, 2D Gaussian TFs can be automatically generated in the dimensionality reduced space using these samples. With the extracted features rendered in the volume rendering view, the user can further refine these features using segmentation brushes. Interactivity is achieved in our system and different views are tightly linked. Use cases show that our system has been successfully applied for simulation and complicated seismic data sets. © 2013 IEEE.

Transfer function design based on user selected samples for intuitive multivariate volume exploration

KAUST Repository

Zhou, Liang; Hansen, Charles

2013-01-01

Multivariate volumetric datasets are important to both science and medicine. We propose a transfer function (TF) design approach based on user selected samples in the spatial domain to make multivariate volumetric data visualization more accessible for domain users. Specifically, the user starts the visualization by probing features of interest on slices and the data values are instantly queried by user selection. The queried sample values are then used to automatically and robustly generate high dimensional transfer functions (HDTFs) via kernel density estimation (KDE). Alternatively, 2D Gaussian TFs can be automatically generated in the dimensionality reduced space using these samples. With the extracted features rendered in the volume rendering view, the user can further refine these features using segmentation brushes. Interactivity is achieved in our system and different views are tightly linked. Use cases show that our system has been successfully applied for simulation and complicated seismic data sets. © 2013 IEEE.

A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

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Daniel Vasiliu

Full Text Available Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED. Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

Newly developed liquid-based cytology. TACAS™: cytological appearance and HPV testing using liquid-based sample.

Science.gov (United States)

Kubushiro, Kaneyuki; Taoka, Hideki; Sakurai, Nobuyuki; Yamamoto, Yasuhiro; Kurasaki, Akiko; Asakawa, Yasuyuki; Iwahara, Minoru; Takahashi, Kei

2011-09-01

Cell profiles determined by the thin-layer advanced cytology assay system (TACAS™), a liquid-based cytology technique newly developed in Japan, were analyzed in this study. Hybrid capture 2 (HC-2) was also performed using the liquid-based samples prepared by TACAS to ascertain its ability to detect human papillomavirus (HPV). Cell collection samples from uterine cervix were obtained from 359 patients and examined cytologically. A HC-2 assay for HPV was carried out in the cell specimens. All specimens were found to show background factors such as leukocytes. After excluding the 5 unsatisfactory cases from the total 354 cases, 82 cases (23.2%) were positive and 272 cases (76.8%) were negative for HPV. Cell specimens from 30 HPV-positive cases and 166 HPV-negative cases were subjected to 4 weeks of preservation at room temperature. Then, when subsequently re-assayed, 28 cases (93.3%) in the former group were found to be HPV positive and 164 cases (98.8%) in the latter group were found to be HPV negative. These results supported the excellent reproducibility of TACAS for HPV testing. A reasonable inference from the foregoing analysis is that TACAS may be distinguished from other liquid-based cytological approaches, such as ThinPrep and SurePath, in that it can retain the cell backgrounds. Furthermore, this study raises the possibility that cell specimens prepared using TACAS could be preserved for at least 4 weeks prior to carrying out a HC-2 assay for HPV.

Experimental and Sampling Design for the INL-2 Sample Collection Operational Test

Energy Technology Data Exchange (ETDEWEB)

Piepel, Gregory F.; Amidan, Brett G.; Matzke, Brett D.

2009-02-16

, sample extraction, and analytical methods to be used in the INL-2 study. For each of the five test events, the specified floor of the INL building will be contaminated with BG using a point-release device located in the room specified in the experimental design. Then quality control (QC), reference material coupon (RMC), judgmental, and probabilistic samples will be collected according to the sampling plan for each test event. Judgmental samples will be selected based on professional judgment and prior information. Probabilistic samples were selected with a random aspect and in sufficient numbers to provide desired confidence for detecting contamination or clearing uncontaminated (or decontaminated) areas. Following sample collection for a given test event, the INL building will be decontaminated. For possibly contaminated areas, the numbers of probabilistic samples were chosen to provide 95% confidence of detecting contaminated areas of specified sizes. For rooms that may be uncontaminated following a contamination event, or for whole floors after decontamination, the numbers of judgmental and probabilistic samples were chosen using the CJR approach. The numbers of samples were chosen to support making X%/Y% clearance statements with X = 95% or 99% and Y = 96% or 97%. The experimental and sampling design also provides for making X%/Y% clearance statements using only probabilistic samples. For each test event, the numbers of characterization and clearance samples were selected within limits based on operational considerations while still maintaining high confidence for detection and clearance aspects. The sampling design for all five test events contains 2085 samples, with 1142 after contamination and 943 after decontamination. These numbers include QC, RMC, judgmental, and probabilistic samples. The experimental and sampling design specified in this report provides a good statistical foundation for achieving the objectives of the INL-2 study.

Hybrid Feature Selection Approach Based on GRASP for Cancer Microarray Data

Directory of Open Access Journals (Sweden)

Arpita Nagpal

2017-01-01

Full Text Available Microarray data usually contain a large number of genes, but a small number of samples. Feature subset selection for microarray data aims at reducing the number of genes so that useful information can be extracted from the samples. Reducing the dimension of data sets further helps in improving the computational efficiency of the learning model. In this paper, we propose a modified algorithm based on the tabu search as local search procedures to a Greedy Randomized Adaptive Search Procedure (GRASP for high dimensional microarray data sets. The proposed Tabu based Greedy Randomized Adaptive Search Procedure algorithm is named as TGRASP. In TGRASP, a new parameter has been introduced named as Tabu Tenure and the existing parameters, NumIter and size have been modified. We observed that different parameter settings affect the quality of the optimum. The second proposed algorithm known as FFGRASP (Firefly Greedy Randomized Adaptive Search Procedure uses a firefly optimization algorithm in the local search optimzation phase of the greedy randomized adaptive search procedure (GRASP. Firefly algorithm is one of the powerful algorithms for optimization of multimodal applications. Experimental results show that the proposed TGRASP and FFGRASP algorithms are much better than existing algorithm with respect to three performance parameters viz. accuracy, run time, number of a selected subset of features. We have also compared both the approaches with a unified metric (Extended Adjusted Ratio of Ratios which has shown that TGRASP approach outperforms existing approach for six out of nine cancer microarray datasets and FFGRASP performs better on seven out of nine datasets.

Microcomputer-based systems for automatic control of sample irradiation and chemical analysis of short-lived isotopes

International Nuclear Information System (INIS)

Bourret, S.C.

1974-01-01

Two systems resulted from the need for the study of the nuclear decay of short-lived radionuclides. Automation was required for better repeatability, speed of chemical separation after irradiation and for protection from the high radiation fields of the samples. A MCS-8 computer was used as the nucleus of the automatic sample irradiation system because the control system required an extensive multiple-sequential circuit. This approach reduced the sequential problem to a computer program. The automatic chemistry control system is a mixture of a fixed and a computer-based programmable control system. The fixed control receives the irradiated liquid sample from the reactor, extracts the liquid and disposes of the used sample container. The programmable control executes the chemistry program that the user has entered through the teletype. (U.S.)

Efficient sample preparation method based on solvent-assisted dispersive solid-phase extraction for the trace detection of butachlor in urine and waste water samples.

Science.gov (United States)

Aladaghlo, Zolfaghar; Fakhari, Alireza; Behbahani, Mohammad

2016-10-01

In this work, an efficient sample preparation method termed solvent-assisted dispersive solid-phase extraction was applied. The used sample preparation method was based on the dispersion of the sorbent (benzophenone) into the aqueous sample to maximize the interaction surface. In this approach, the dispersion of the sorbent at a very low milligram level was achieved by inserting a solution of the sorbent and disperser solvent into the aqueous sample. The cloudy solution created from the dispersion of the sorbent in the bulk aqueous sample. After pre-concentration of the butachlor, the cloudy solution was centrifuged and butachlor in the sediment phase dissolved in ethanol and determined by gas chromatography with flame ionization detection. Under the optimized conditions (solution pH = 7.0, sorbent: benzophenone, 2%, disperser solvent: ethanol, 500 μL, centrifuged at 4000 rpm for 3 min), the method detection limit for butachlor was 2, 3 and 3 μg/L for distilled water, waste water, and urine sample, respectively. Furthermore, the preconcentration factor was 198.8, 175.0, and 174.2 in distilled water, waste water, and urine sample, respectively. Solvent-assisted dispersive solid-phase extraction was successfully used for the trace monitoring of butachlor in urine and waste water samples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Network-based Approaches in Pharmacology.

Science.gov (United States)

Boezio, Baptiste; Audouze, Karine; Ducrot, Pierre; Taboureau, Olivier

2017-10-01

In drug discovery, network-based approaches are expected to spotlight our understanding of drug action across multiple layers of information. On one hand, network pharmacology considers the drug response in the context of a cellular or phenotypic network. On the other hand, a chemical-based network is a promising alternative for characterizing the chemical space. Both can provide complementary support for the development of rational drug design and better knowledge of the mechanisms underlying the multiple actions of drugs. Recent progress in both concepts is discussed here. In addition, a network-based approach using drug-target-therapy data is introduced as an example. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic failure of dry and fully saturated limestone samples based on incubation time concept

Directory of Open Access Journals (Sweden)

Yuri V. Petrov

2017-02-01

Full Text Available This paper outlines the results of experimental study of the dynamic rock failure based on the comparison of dry and saturated limestone samples obtained during the dynamic compression and split tests. The tests were performed using the Kolsky method and its modifications for dynamic splitting. The mechanical data (e.g. strength, time and energy characteristics of this material at high strain rates are obtained. It is shown that these characteristics are sensitive to the strain rate. A unified interpretation of these rate effects, based on the structural–temporal approach, is hereby presented. It is demonstrated that the temporal dependence of the dynamic compressive and split tensile strengths of dry and saturated limestone samples can be predicted by the incubation time criterion. Previously discovered possibilities to optimize (minimize the energy input for the failure process is discussed in connection with industrial rock failure processes. It is shown that the optimal energy input value associated with critical load, which is required to initialize failure in the rock media, strongly depends on the incubation time and the impact duration. The optimal load shapes, which minimize the momentum for a single failure impact, are demonstrated. Through this investigation, a possible approach to reduce the specific energy required for rock cutting by means of high-frequency vibrations is also discussed.

Application of the Sampling Selection Technique in Approaching Financial Audit

Directory of Open Access Journals (Sweden)

Victor Munteanu

2018-03-01

Full Text Available In his professional approach, the financial auditor has a wide range of working techniques, including selection techniques. They are applied depending on the nature of the information available to the financial auditor, the manner in which they are presented - paper or electronic format, and, last but not least, the time available. Several techniques are applied, successively or in parallel, to increase the safety of the expressed opinion and to provide the audit report with a solid basis of information. Sampling is used in the phase of control or clarification of the identified error. The main purpose is to corroborate or measure the degree of risk detected following a pertinent analysis. Since the auditor does not have time or means to thoroughly rebuild the information, the sampling technique can provide an effective response to the need for valorization.

A CD45-based barcoding approach to multiplex mass-cytometry (CyTOF).

Science.gov (United States)

Lai, Liyun; Ong, Raymond; Li, Juntao; Albani, Salvatore

2015-04-01

CyTOF enables the study of the immune system with a complexity, depth, and multidimensionality never achieved before. However, the full potential of using CyTOF can be limited by scarce cell samples. Barcoding strategies developed based on direct labeling of cells using maleimido-monoamide-DOTA (m-DOTA) provide a very useful tool. However, using m-DOTA has some inherent problems, mainly associated with signal intensity. This may be a source of uncertainty when samples are multiplexed. As an alternative or complementary approach to m-DOTA, conjugating an antibody, specific for a membrane protein present on most immune cells, with different isotopes could address the issues of stability and signal intensity needed for effective barcoding. We chose for this purpose CD45, and designed experiments to address different types of cultures and the ability to detect extra- and intra-cellular targets. We show here that our approach provides an useful alternative to m-DOTA in terms of sensitivity, specificity, flexibility, and user-friendliness. Our manuscript provides details to effectively barcode immune cells, overcoming limitations in current technology and enabling the use of CyTOF with scarce samples (for instance precious clinical samples). © 2015 The Authors. Published by Wiley Periodicals, Inc.

Chemometric classification of casework arson samples based on gasoline content.

Science.gov (United States)

Sinkov, Nikolai A; Sandercock, P Mark L; Harynuk, James J

2014-02-01

Detection and identification of ignitable liquids (ILs) in arson debris is a critical part of arson investigations. The challenge of this task is due to the complex and unpredictable chemical nature of arson debris, which also contains pyrolysis products from the fire. ILs, most commonly gasoline, are complex chemical mixtures containing hundreds of compounds that will be consumed or otherwise weathered by the fire to varying extents depending on factors such as temperature, air flow, the surface on which IL was placed, etc. While methods such as ASTM E-1618 are effective, data interpretation can be a costly bottleneck in the analytical process for some laboratories. In this study, we address this issue through the application of chemometric tools. Prior to the application of chemometric tools such as PLS-DA and SIMCA, issues of chromatographic alignment and variable selection need to be addressed. Here we use an alignment strategy based on a ladder consisting of perdeuterated n-alkanes. Variable selection and model optimization was automated using a hybrid backward elimination (BE) and forward selection (FS) approach guided by the cluster resolution (CR) metric. In this work, we demonstrate the automated construction, optimization, and application of chemometric tools to casework arson data. The resulting PLS-DA and SIMCA classification models, trained with 165 training set samples, have provided classification of 55 validation set samples based on gasoline content with 100% specificity and sensitivity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Assessing Acid-Base Status: Physiologic Versus Physicochemical Approach.

Science.gov (United States)

Adrogué, Horacio J; Madias, Nicolaos E

2016-11-01

The physiologic approach has long been used in assessing acid-base status. This approach considers acids as hydrogen ion donors and bases as hydrogen ion acceptors and the acid-base status of the organism as reflecting the interaction of net hydrogen ion balance with body buffers. In the physiologic approach, the carbonic acid/bicarbonate buffer pair is used for assessing acid-base status and blood pH is determined by carbonic acid (ie, Paco 2 ) and serum bicarbonate levels. More recently, the physicochemical approach was introduced, which has gained popularity, particularly among intensivists and anesthesiologists. This approach posits that the acid-base status of body fluids is determined by changes in the dissociation of water that are driven by the interplay of 3 independent variables: the sum of strong (fully dissociated) cation concentrations minus the sum of strong anion concentrations (strong ion difference); the total concentration of weak acids; and Paco 2 . These 3 independent variables mechanistically determine both hydrogen ion concentration and bicarbonate concentration of body fluids, which are considered as dependent variables. Our experience indicates that the average practitioner is familiar with only one of these approaches and knows very little, if any, about the other approach. In the present Acid-Base and Electrolyte Teaching Case, we attempt to bridge this knowledge gap by contrasting the physiologic and physicochemical approaches to assessing acid-base status. We first outline the essential features, advantages, and limitations of each of the 2 approaches and then apply each approach to the same patient presentation. We conclude with our view about the optimal approach. Copyright © 2016 National Kidney Foundation, Inc. All rights reserved.

Support vector machine based fault detection approach for RFT-30 cyclotron

Energy Technology Data Exchange (ETDEWEB)

Kong, Young Bae, E-mail: ybkong@kaeri.re.kr; Lee, Eun Je; Hur, Min Goo; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

2016-10-21

An RFT-30 is a 30 MeV cyclotron used for radioisotope applications and radiopharmaceutical researches. The RFT-30 cyclotron is highly complex and includes many signals for control and monitoring of the system. It is quite difficult to detect and monitor the system failure in real time. Moreover, continuous monitoring of the system is hard and time-consuming work for human operators. In this paper, we propose a support vector machine (SVM) based fault detection approach for the RFT-30 cyclotron. The proposed approach performs SVM learning with training samples to construct the classification model. To compensate the system complexity due to the large-scale accelerator, we utilize the principal component analysis (PCA) for transformation of the original data. After training procedure, the proposed approach detects the system faults in real time. We analyzed the performance of the proposed approach utilizing the experimental data of the RFT-30 cyclotron. The performance results show that the proposed SVM approach can provide an efficient way to control the cyclotron system.

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Energy Technology Data Exchange (ETDEWEB)

Boardman, Beth Leigh [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-10-12

The common theme of this dissertation is sampling-based motion planning with the two key contributions being in the area of replanning and spatial load balancing for robotic systems. Here, we begin by recalling two sampling-based motion planners: the asymptotically optimal rapidly-exploring random tree (RRT*), and the asymptotically optimal probabilistic roadmap (PRM*). We also provide a brief background on collision cones and the Distributed Reactive Collision Avoidance (DRCA) algorithm. The next four chapters detail novel contributions for motion replanning in environments with unexpected static obstacles, for multi-agent collision avoidance, and spatial load balancing. First, we show improved performance of the RRT* when using the proposed Grandparent-Connection (GP) or Focused-Refinement (FR) algorithms. Next, the Goal Tree algorithm for replanning with unexpected static obstacles is detailed and proven to be asymptotically optimal. A multi-agent collision avoidance problem in obstacle environments is approached via the RRT*, leading to the novel Sampling-Based Collision Avoidance (SBCA) algorithm. The SBCA algorithm is proven to guarantee collision free trajectories for all of the agents, even when subject to uncertainties in the knowledge of the other agents’ positions and velocities. Given that a solution exists, we prove that livelocks and deadlock will lead to the cost to the goal being decreased. We introduce a new deconfliction maneuver that decreases the cost-to-come at each step. This new maneuver removes the possibility of livelocks and allows a result to be formed that proves convergence to the goal configurations. Finally, we present a limited range Graph-based Spatial Load Balancing (GSLB) algorithm which fairly divides a non-convex space among multiple agents that are subject to differential constraints and have a limited travel distance. The GSLB is proven to converge to a solution when maximizing the area covered by the agents. The analysis

Wastewater treatment plants as a pathway for microplastics: Development of a new approach to sample wastewater-based microplastics.

Science.gov (United States)

Ziajahromi, Shima; Neale, Peta A; Rintoul, Llew; Leusch, Frederic D L

2017-04-01

Wastewater effluent is expected to be a pathway for microplastics to enter the aquatic environment, with microbeads from cosmetic products and polymer fibres from clothes likely to enter wastewater treatment plants (WWTP). To date, few studies have quantified microplastics in wastewater. Moreover, the lack of a standardized and applicable method to identify microplastics in complex samples, such as wastewater, has limited the accurate assessment of microplastics and may lead to an incorrect estimation. This study aimed to develop a validated method to sample and process microplastics from wastewater effluent and to apply the developed method to quantify and characterise wastewater-based microplastics in effluent from three WWTPs that use primary, secondary and tertiary treatment processes. We applied a high-volume sampling device that fractionated microplastics in situ and an efficient sample processing procedure to improve the sampling of microplastics in wastewater and to minimize the false detection of non-plastic particles. The sampling device captured between 92% and 99% of polystyrene microplastics using 25 μm-500 μm mesh screens in laboratory tests. Microplastic type, size and suspected origin in all studied WWTPs, along with the removal efficiency during the secondary and tertiary treatment stages, was investigated. Suspected microplastics were characterised using Fourier Transform Infrared spectroscopy, with between 22 and 90% of the suspected microplastics found to be non-plastic particles. An average of 0.28, 0.48 and 1.54 microplastics per litre of final effluent was found in tertiary, secondary and primary treated effluent, respectively. This study suggests that although low concentrations of microplastics are detected in wastewater effluent, WWTPs still have the potential to act as a pathway to release microplastics given the large volumes of effluent discharged to the aquatic environment. This study focused on a single sampling campaign, with

An algorithm to improve sampling efficiency for uncertainty propagation using sampling based method

International Nuclear Information System (INIS)

Campolina, Daniel; Lima, Paulo Rubens I.; Pereira, Claubia; Veloso, Maria Auxiliadora F.

2015-01-01

Sample size and computational uncertainty were varied in order to investigate sample efficiency and convergence of the sampling based method for uncertainty propagation. Transport code MCNPX was used to simulate a LWR model and allow the mapping, from uncertain inputs of the benchmark experiment, to uncertain outputs. Random sampling efficiency was improved through the use of an algorithm for selecting distributions. Mean range, standard deviation range and skewness were verified in order to obtain a better representation of uncertainty figures. Standard deviation of 5 pcm in the propagated uncertainties for 10 n-samples replicates was adopted as convergence criterion to the method. Estimation of 75 pcm uncertainty on reactor k eff was accomplished by using sample of size 93 and computational uncertainty of 28 pcm to propagate 1σ uncertainty of burnable poison radius. For a fixed computational time, in order to reduce the variance of the uncertainty propagated, it was found, for the example under investigation, it is preferable double the sample size than double the amount of particles followed by Monte Carlo process in MCNPX code. (author)

An assessment of uncertainty on a LOFT L2-5 LBLOCA PCT based on the ACE-RSM approach: complementary work for the OECD BEMUSE PHASE-III program

International Nuclear Information System (INIS)

Ahn, Kwang Il; Chung, Bub Dong; Lee, John C.

2010-01-01

As pointed out in the OECD BEMUSE Program, when a high computation time is taken to obtain the relevant output values of a complex physical model (or code), the number of statistical samples that must be evaluated through it is a critical factor for the sampling-based uncertainty analysis. Two alternative methods have been utilized to avoid the problem associated with the size of these statistical samples: one is based on Wilks' formula, which is based on simple random sampling, and the other is based on the conventional nonlinear regression approach. While both approaches provide a useful means for drawing conclusions on the resultant uncertainty with a limited number of code runs, there are also some unique corresponding limitations. For example, a conclusion based on the Wilks' formula can be highly affected by the sampled values themselves, while the conventional regression approach requires an a priori estimate on the functional forms of a regression model. The main objective of this paper is to assess the feasibility of the ACE-RSM approach as a complementary method to the Wilks' formula and the conventional regression-based uncertainty analysis. This feasibility was assessed through a practical application of the ACE-RSM approach to the LOFT L2-5 LBLOCA PCT uncertainty analysis, which was implemented as a part of the OECD BEMUSE Phase III program

A Global Sampling Based Image Matting Using Non-Negative Matrix Factorization

Directory of Open Access Journals (Sweden)

NAVEED ALAM

2017-10-01

Full Text Available Image matting is a technique in which a foreground is separated from the background of a given image along with the pixel wise opacity. This foreground can then be seamlessly composited in a different background to obtain a novel scene. This paper presents a global non-parametric sampling algorithm over image patches and utilizes a dimension reduction technique known as NMF (Non-Negative Matrix Factorization. Although some existing non-parametric approaches use large nearby foreground and background regions to sample patches but these approaches fail to take the whole image to sample patches. It is because of the high memory and computational requirements. The use of NMF in the proposed algorithm allows the dimension reduction which reduces the computational cost and memory requirement. The use of NMF also allow the proposed approach to use the whole foreground and background region in the image and reduces the patch complexity and help in efficient patch sampling. The use of patches not only allows the incorporation of the pixel colour but also the local image structure. The use of local structures in the image is important to estimate a high-quality alpha matte especially in the images which have regions containing high texture. The proposed algorithm is evaluated on the standard data set and obtained results are comparable to the state-of-the-art matting techniques

A global sampling based image matting using non-negative matrix factorization

International Nuclear Information System (INIS)

Alam, N.; Sarim, M.; Shaikh, A.B.

2017-01-01

Image matting is a technique in which a foreground is separated from the background of a given image along with the pixel wise opacity. This foreground can then be seamlessly composited in a different background to obtain a novel scene. This paper presents a global non-parametric sampling algorithm over image patches and utilizes a dimension reduction technique known as NMF (Non-Negative Matrix Factorization). Although some existing non-parametric approaches use large nearby foreground and background regions to sample patches but these approaches fail to take the whole image to sample patches. It is because of the high memory and computational requirements. The use of NMF in the proposed algorithm allows the dimension reduction which reduces the computational cost and memory requirement. The use of NMF also allow the proposed approach to use the whole foreground and background region in the image and reduces the patch complexity and help in efficient patch sampling. The use of patches not only allows the incorporation of the pixel colour but also the local image structure. The use of local structures in the image is important to estimate a high-quality alpha matte especially in the images which have regions containing high texture. The proposed algorithm is evaluated on the standard data set and obtained results are comparable to the state-of-the-art matting techniques. (author)

Reliable Quantification of the Potential for Equations Based on Spot Urine Samples to Estimate Population Salt Intake

DEFF Research Database (Denmark)

Huang, Liping; Crino, Michelle; Wu, Jason Hy

2016-01-01

to a standard format. Individual participant records will be compiled and a series of analyses will be completed to: (1) compare existing equations for estimating 24-hour salt intake from spot urine samples with 24-hour urine samples, and assess the degree of bias according to key demographic and clinical......BACKGROUND: Methods based on spot urine samples (a single sample at one time-point) have been identified as a possible alternative approach to 24-hour urine samples for determining mean population salt intake. OBJECTIVE: The aim of this study is to identify a reliable method for estimating mean...... population salt intake from spot urine samples. This will be done by comparing the performance of existing equations against one other and against estimates derived from 24-hour urine samples. The effects of factors such as ethnicity, sex, age, body mass index, antihypertensive drug use, health status...

An integrated sampling and analysis approach for improved biodiversity monitoring

Science.gov (United States)

DeWan, Amielle A.; Zipkin, Elise F.

2010-01-01

Successful biodiversity conservation requires high quality monitoring data and analyses to ensure scientifically defensible policy, legislation, and management. Although monitoring is a critical component in assessing population status and trends, many governmental and non-governmental organizations struggle to develop and implement effective sampling protocols and statistical analyses because of the magnitude and diversity of species in conservation concern. In this article we describe a practical and sophisticated data collection and analysis framework for developing a comprehensive wildlife monitoring program that includes multi-species inventory techniques and community-level hierarchical modeling. Compared to monitoring many species individually, the multi-species approach allows for improved estimates of individual species occurrences, including rare species, and an increased understanding of the aggregated response of a community to landscape and habitat heterogeneity. We demonstrate the benefits and practicality of this approach to address challenges associated with monitoring in the context of US state agencies that are legislatively required to monitor and protect species in greatest conservation need. We believe this approach will be useful to regional, national, and international organizations interested in assessing the status of both common and rare species.

Compressed sensing of roller bearing fault based on multiple down-sampling strategy

Science.gov (United States)

Wang, Huaqing; Ke, Yanliang; Luo, Ganggang; Tang, Gang

2016-02-01

Roller bearings are essential components of rotating machinery and are often exposed to complex operating conditions, which can easily lead to their failures. Thus, to ensure normal production and the safety of machine operators, it is essential to detect the failures as soon as possible. However, it is a major challenge to maintain a balance between detection efficiency and big data acquisition given the limitations of sampling theory. To overcome these limitations, we try to preserve the information pertaining to roller bearing failures using a sampling rate far below the Nyquist sampling rate, which can ease the pressure generated by the large-scale data. The big data of a faulty roller bearing’s vibration signals is firstly reduced by a down-sample strategy while preserving the fault features by selecting peaks to represent the data segments in time domain. However, a problem arises in that the fault features may be weaker than before, since the noise may be mistaken for the peaks when the noise is stronger than the vibration signals, which makes the fault features unable to be extracted by commonly-used envelope analysis. Here we employ compressive sensing theory to overcome this problem, which can make a signal enhancement and reduce the sample sizes further. Moreover, it is capable of detecting fault features from a small number of samples based on orthogonal matching pursuit approach, which can overcome the shortcomings of the multiple down-sample algorithm. Experimental results validate the effectiveness of the proposed technique in detecting roller bearing faults.

Compressed sensing of roller bearing fault based on multiple down-sampling strategy

International Nuclear Information System (INIS)

Wang, Huaqing; Ke, Yanliang; Luo, Ganggang; Tang, Gang

2016-01-01

Roller bearings are essential components of rotating machinery and are often exposed to complex operating conditions, which can easily lead to their failures. Thus, to ensure normal production and the safety of machine operators, it is essential to detect the failures as soon as possible. However, it is a major challenge to maintain a balance between detection efficiency and big data acquisition given the limitations of sampling theory. To overcome these limitations, we try to preserve the information pertaining to roller bearing failures using a sampling rate far below the Nyquist sampling rate, which can ease the pressure generated by the large-scale data. The big data of a faulty roller bearing’s vibration signals is firstly reduced by a down-sample strategy while preserving the fault features by selecting peaks to represent the data segments in time domain. However, a problem arises in that the fault features may be weaker than before, since the noise may be mistaken for the peaks when the noise is stronger than the vibration signals, which makes the fault features unable to be extracted by commonly-used envelope analysis. Here we employ compressive sensing theory to overcome this problem, which can make a signal enhancement and reduce the sample sizes further. Moreover, it is capable of detecting fault features from a small number of samples based on orthogonal matching pursuit approach, which can overcome the shortcomings of the multiple down-sample algorithm. Experimental results validate the effectiveness of the proposed technique in detecting roller bearing faults. (paper)

A new approach to hand-based authentication

Science.gov (United States)

Amayeh, G.; Bebis, G.; Erol, A.; Nicolescu, M.

2007-04-01

Hand-based authentication is a key biometric technology with a wide range of potential applications both in industry and government. Traditionally, hand-based authentication is performed by extracting information from the whole hand. To account for hand and finger motion, guidance pegs are employed to fix the position and orientation of the hand. In this paper, we consider a component-based approach to hand-based verification. Our objective is to investigate the discrimination power of different parts of the hand in order to develop a simpler, faster, and possibly more accurate and robust verification system. Specifically, we propose a new approach which decomposes the hand in different regions, corresponding to the fingers and the back of the palm, and performs verification using information from certain parts of the hand only. Our approach operates on 2D images acquired by placing the hand on a flat lighting table. Using a part-based representation of the hand allows the system to compensate for hand and finger motion without using any guidance pegs. To decompose the hand in different regions, we use a robust methodology based on morphological operators which does not require detecting any landmark points on the hand. To capture the geometry of the back of the palm and the fingers in suffcient detail, we employ high-order Zernike moments which are computed using an effcient methodology. The proposed approach has been evaluated on a database of 100 subjects with 10 images per subject, illustrating promising performance. Comparisons with related approaches using the whole hand for verification illustrate the superiority of the proposed approach. Moreover, qualitative comparisons with state-of-the-art approaches indicate that the proposed approach has comparable or better performance.

A novel PMT test system based on waveform sampling

Science.gov (United States)

Yin, S.; Ma, L.; Ning, Z.; Qian, S.; Wang, Y.; Jiang, X.; Wang, Z.; Yu, B.; Gao, F.; Zhu, Y.; Wang, Z.

2018-01-01

Comparing with the traditional test system based on a QDC and TDC and scaler, a test system based on waveform sampling is constructed for signal sampling of the 8"R5912 and the 20"R12860 Hamamatsu PMT in different energy states from single to multiple photoelectrons. In order to achieve high throughput and to reduce the dead time in data processing, the data acquisition software based on LabVIEW is developed and runs with a parallel mechanism. The analysis algorithm is realized in LabVIEW and the spectra of charge, amplitude, signal width and rising time are analyzed offline. The results from Charge-to-Digital Converter, Time-to-Digital Converter and waveform sampling are discussed in detailed comparison.

Coupling pervaporation to AAS for inorganic and organic mercury determination. A new approach to speciation of Hg in environmental samples.

Science.gov (United States)

Fernandez-Rivas, C; Muñoz-Olivas, R; Camara, C

2001-12-01

The design and development of a new approach for Hg speciation in environmental samples is described in detail. This method, consisting of the coupling of pervaporation and atomic absorption spectrometry, is based on a membrane phenomenon that combines the evaporation of volatile analytes and their diffusion through a polymeric membrane. It is proposed here as an alternative to gas chromatography for speciation of inorganic and organic Hg compounds, as the latter compounds are volatile and can be separated by applying the principles mentioned above. The interest of this method lies in its easy handling, low cost, and rapidity for the analysis of liquid and solid samples. This method has been applied to Hg speciation in a compost sample provided by a waste water treatment plant.

Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain

KAUST Repository

Beck, Joakim

2018-02-19

In calculating expected information gain in optimal Bayesian experimental design, the computation of the inner loop in the classical double-loop Monte Carlo requires a large number of samples and suffers from underflow if the number of samples is small. These drawbacks can be avoided by using an importance sampling approach. We present a computationally efficient method for optimal Bayesian experimental design that introduces importance sampling based on the Laplace method to the inner loop. We derive the optimal values for the method parameters in which the average computational cost is minimized for a specified error tolerance. We use three numerical examples to demonstrate the computational efficiency of our method compared with the classical double-loop Monte Carlo, and a single-loop Monte Carlo method that uses the Laplace approximation of the return value of the inner loop. The first demonstration example is a scalar problem that is linear in the uncertain parameter. The second example is a nonlinear scalar problem. The third example deals with the optimal sensor placement for an electrical impedance tomography experiment to recover the fiber orientation in laminate composites.

Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain

Science.gov (United States)

Beck, Joakim; Dia, Ben Mansour; Espath, Luis F. R.; Long, Quan; Tempone, Raúl

2018-06-01

In calculating expected information gain in optimal Bayesian experimental design, the computation of the inner loop in the classical double-loop Monte Carlo requires a large number of samples and suffers from underflow if the number of samples is small. These drawbacks can be avoided by using an importance sampling approach. We present a computationally efficient method for optimal Bayesian experimental design that introduces importance sampling based on the Laplace method to the inner loop. We derive the optimal values for the method parameters in which the average computational cost is minimized according to the desired error tolerance. We use three numerical examples to demonstrate the computational efficiency of our method compared with the classical double-loop Monte Carlo, and a more recent single-loop Monte Carlo method that uses the Laplace method as an approximation of the return value of the inner loop. The first example is a scalar problem that is linear in the uncertain parameter. The second example is a nonlinear scalar problem. The third example deals with the optimal sensor placement for an electrical impedance tomography experiment to recover the fiber orientation in laminate composites.

Control charts for location based on different sampling schemes

NARCIS (Netherlands)

Mehmood, R.; Riaz, M.; Does, R.J.M.M.

2013-01-01

Control charts are the most important statistical process control tool for monitoring variations in a process. A number of articles are available in the literature for the X̄ control chart based on simple random sampling, ranked set sampling, median-ranked set sampling (MRSS), extreme-ranked set

Individual and pen-based oral fluid sampling: A welfare-friendly sampling method for group-housed gestating sows.

Science.gov (United States)

Pol, Françoise; Dorenlor, Virginie; Eono, Florent; Eudier, Solveig; Eveno, Eric; Liégard-Vanhecke, Dorine; Rose, Nicolas; Fablet, Christelle

2017-11-01

The aims of this study were to assess the feasibility of individual and pen-based oral fluid sampling (OFS) in 35 pig herds with group-housed sows, compare these methods to blood sampling, and assess the factors influencing the success of sampling. Individual samples were collected from at least 30 sows per herd. Pen-based OFS was performed using devices placed in at least three pens for 45min. Information related to the farm, the sows, and their living conditions were collected. Factors significantly associated with the duration of sampling and the chewing behaviour of sows were identified by logistic regression. Individual OFS took 2min 42s on average; the type of floor, swab size, and operator were associated with a sampling time >2min. Pen-based OFS was obtained from 112 devices (62.2%). The type of floor, parity, pen-level activity, and type of feeding were associated with chewing behaviour. Pen activity was associated with the latency to interact with the device. The type of floor, gestation stage, parity, group size, and latency to interact with the device were associated with a chewing time >10min. After 15, 30 and 45min of pen-based OFS, 48%, 60% and 65% of the sows were lying down, respectively. The time spent after the beginning of sampling, genetic type, and time elapsed since the last meal were associated with 50% of the sows lying down at one time point. The mean time to blood sample the sows was 1min 16s and 2min 52s if the number of operators required was considered in the sampling time estimation. The genetic type, parity, and type of floor were significantly associated with a sampling time higher than 1min 30s. This study shows that individual OFS is easy to perform in group-housed sows by a single operator, even though straw-bedded animals take longer to sample than animals housed on slatted floors, and suggests some guidelines to optimise pen-based OFS success. Copyright © 2017 Elsevier B.V. All rights reserved.

Large-volume injection of sample diluents not miscible with the mobile phase as an alternative approach in sample preparation for bioanalysis: an application for fenspiride bioequivalence.

Science.gov (United States)

Medvedovici, Andrei; Udrescu, Stefan; Albu, Florin; Tache, Florentin; David, Victor

2011-09-01

Liquid-liquid extraction of target compounds from biological matrices followed by the injection of a large volume from the organic layer into the chromatographic column operated under reversed-phase (RP) conditions would successfully combine the selectivity and the straightforward character of the procedure in order to enhance sensitivity, compared with the usual approach of involving solvent evaporation and residue re-dissolution. Large-volume injection of samples in diluents that are not miscible with the mobile phase was recently introduced in chromatographic practice. The risk of random errors produced during the manipulation of samples is also substantially reduced. A bioanalytical method designed for the bioequivalence of fenspiride containing pharmaceutical formulations was based on a sample preparation procedure involving extraction of the target analyte and the internal standard (trimetazidine) from alkalinized plasma samples in 1-octanol. A volume of 75 µl from the octanol layer was directly injected on a Zorbax SB C18 Rapid Resolution, 50 mm length × 4.6 mm internal diameter × 1.8 µm particle size column, with the RP separation being carried out under gradient elution conditions. Detection was made through positive ESI and MS/MS. Aspects related to method development and validation are discussed. The bioanalytical method was successfully applied to assess bioequivalence of a modified release pharmaceutical formulation containing 80 mg fenspiride hydrochloride during two different studies carried out as single-dose administration under fasting and fed conditions (four arms), and multiple doses administration, respectively. The quality attributes assigned to the bioanalytical method, as resulting from its application to the bioequivalence studies, are highlighted and fully demonstrate that sample preparation based on large-volume injection of immiscible diluents has an increased potential for application in bioanalysis.

A novel local learning based approach with application to breast cancer diagnosis

Science.gov (United States)

Xu, Songhua; Tourassi, Georgia

2012-03-01

In this paper, we introduce a new local learning based approach and apply it for the well-studied problem of breast cancer diagnosis using BIRADS-based mammographic features. To learn from our clinical dataset the latent relationship between these features and the breast biopsy result, our method first dynamically partitions the whole sample population into multiple sub-population groups through stochastically searching the sample population clustering space. Each encountered clustering scheme in our online searching process is then used to create a certain sample population partition plan. For every resultant sub-population group identified according to a partition plan, our method then trains a dedicated local learner to capture the underlying data relationship. In our study, we adopt the linear logistic regression model as our local learning method's base learner. Such a choice is made both due to the well-understood linear nature of the problem, which is compellingly revealed by a rich body of prior studies, and the computational efficiency of linear logistic regression--the latter feature allows our local learning method to more effectively perform its search in the sample population clustering space. Using a database of 850 biopsy-proven cases, we compared the performance of our method with a large collection of publicly available state-of-the-art machine learning methods and successfully demonstrated its performance advantage with statistical significance.

Study on a pattern classification method of soil quality based on simplified learning sample dataset

Science.gov (United States)

Zhang, Jiahua; Liu, S.; Hu, Y.; Tian, Y.

2011-01-01

Based on the massive soil information in current soil quality grade evaluation, this paper constructed an intelligent classification approach of soil quality grade depending on classical sampling techniques and disordered multiclassification Logistic regression model. As a case study to determine the learning sample capacity under certain confidence level and estimation accuracy, and use c-means algorithm to automatically extract the simplified learning sample dataset from the cultivated soil quality grade evaluation database for the study area, Long chuan county in Guangdong province, a disordered Logistic classifier model was then built and the calculation analysis steps of soil quality grade intelligent classification were given. The result indicated that the soil quality grade can be effectively learned and predicted by the extracted simplified dataset through this method, which changed the traditional method for soil quality grade evaluation. ?? 2011 IEEE.

Finding metastabilities in reversible Markov chains based on incomplete sampling

Directory of Open Access Journals (Sweden)

Fackeldey Konstantin

2017-01-01

Full Text Available In order to fully characterize the state-transition behaviour of finite Markov chains one needs to provide the corresponding transition matrix P. In many applications such as molecular simulation and drug design, the entries of the transition matrix P are estimated by generating realizations of the Markov chain and determining the one-step conditional probability Pij for a transition from one state i to state j. This sampling can be computational very demanding. Therefore, it is a good idea to reduce the sampling effort. The main purpose of this paper is to design a sampling strategy, which provides a partial sampling of only a subset of the rows of such a matrix P. Our proposed approach fits very well to stochastic processes stemming from simulation of molecular systems or random walks on graphs and it is different from the matrix completion approaches which try to approximate the transition matrix by using a low-rank-assumption. It will be shown how Markov chains can be analyzed on the basis of a partial sampling. More precisely. First, we will estimate the stationary distribution from a partially given matrix P. Second, we will estimate the infinitesimal generator Q of P on the basis of this stationary distribution. Third, from the generator we will compute the leading invariant subspace, which should be identical to the leading invariant subspace of P. Forth, we will apply Robust Perron Cluster Analysis (PCCA+ in order to identify metastabilities using this subspace.

IPTV inter-destination synchronization: A network-based approach

NARCIS (Netherlands)

Stokking, H.M.; Deventer, M.O. van; Niamut, O.A.; Walraven, F.A.; Mekuria, R.N.

2010-01-01

This paper introduces a novel network-based approach to inter-destination media synchronization. The approach meets the need for synchronization in advanced TV concepts like social TV and offers high scalability, unlike conventional end-point based approaches. The solution for interdestination media

Frame-based safety analysis approach for decision-based errors

International Nuclear Information System (INIS)

Fan, Chin-Feng; Yihb, Swu

1997-01-01

A frame-based approach is proposed to analyze decision-based errors made by automatic controllers or human operators due to erroneous reference frames. An integrated framework, Two Frame Model (TFM), is first proposed to model the dynamic interaction between the physical process and the decision-making process. Two important issues, consistency and competing processes, are raised. Consistency between the physical and logic frames makes a TFM-based system work properly. Loss of consistency refers to the failure mode that the logic frame does not accurately reflect the state of the controlled processes. Once such failure occurs, hazards may arise. Among potential hazards, the competing effect between the controller and the controlled process is the most severe one, which may jeopardize a defense-in-depth design. When the logic and physical frames are inconsistent, conventional safety analysis techniques are inadequate. We propose Frame-based Fault Tree; Analysis (FFTA) and Frame-based Event Tree Analysis (FETA) under TFM to deduce the context for decision errors and to separately generate the evolution of the logical frame as opposed to that of the physical frame. This multi-dimensional analysis approach, different from the conventional correctness-centred approach, provides a panoramic view in scenario generation. Case studies using the proposed techniques are also given to demonstrate their usage and feasibility

Tetrahedral meshing via maximal Poisson-disk sampling

KAUST Repository

Guo, Jianwei

2016-02-15

In this paper, we propose a simple yet effective method to generate 3D-conforming tetrahedral meshes from closed 2-manifold surfaces. Our approach is inspired by recent work on maximal Poisson-disk sampling (MPS), which can generate well-distributed point sets in arbitrary domains. We first perform MPS on the boundary of the input domain, we then sample the interior of the domain, and we finally extract the tetrahedral mesh from the samples by using 3D Delaunay or regular triangulation for uniform or adaptive sampling, respectively. We also propose an efficient optimization strategy to protect the domain boundaries and to remove slivers to improve the meshing quality. We present various experimental results to illustrate the efficiency and the robustness of our proposed approach. We demonstrate that the performance and quality (e.g., minimal dihedral angle) of our approach are superior to current state-of-the-art optimization-based approaches.

Aleatoric and epistemic uncertainties in sampling based nuclear data uncertainty and sensitivity analyses

International Nuclear Information System (INIS)

Zwermann, W.; Krzykacz-Hausmann, B.; Gallner, L.; Klein, M.; Pautz, A.; Velkov, K.

2012-01-01

Sampling based uncertainty and sensitivity analyses due to epistemic input uncertainties, i.e. to an incomplete knowledge of uncertain input parameters, can be performed with arbitrary application programs to solve the physical problem under consideration. For the description of steady-state particle transport, direct simulations of the microscopic processes with Monte Carlo codes are often used. This introduces an additional source of uncertainty, the aleatoric sampling uncertainty, which is due to the randomness of the simulation process performed by sampling, and which adds to the total combined output sampling uncertainty. So far, this aleatoric part of uncertainty is minimized by running a sufficiently large number of Monte Carlo histories for each sample calculation, thus making its impact negligible as compared to the impact from sampling the epistemic uncertainties. Obviously, this process may cause high computational costs. The present paper shows that in many applications reliable epistemic uncertainty results can also be obtained with substantially lower computational effort by performing and analyzing two appropriately generated series of samples with much smaller number of Monte Carlo histories each. The method is applied along with the nuclear data uncertainty and sensitivity code package XSUSA in combination with the Monte Carlo transport code KENO-Va to various critical assemblies and a full scale reactor calculation. It is shown that the proposed method yields output uncertainties and sensitivities equivalent to the traditional approach, with a high reduction of computing time by factors of the magnitude of 100. (authors)

Sampling-based nuclear data uncertainty quantification for continuous energy Monte-Carlo codes

International Nuclear Information System (INIS)

Zhu, T.

2015-01-01

Research on the uncertainty of nuclear data is motivated by practical necessity. Nuclear data uncertainties can propagate through nuclear system simulations into operation and safety related parameters. The tolerance for uncertainties in nuclear reactor design and operation can affect the economic efficiency of nuclear power, and essentially its sustainability. The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of MCNPX makes it the choice of routine criticality safety calculations at PSI/LRS, but also raises challenges for NDUQ by conventional sensitivity/uncertainty (S/U) methods. For example, only recently in 2011, the capability of calculating continuous energy κ_e_f_f sensitivity to nuclear data was demonstrated in certain M-C codes by using the method of iterated fission probability. The methodology developed during this PhD research is fundamentally different from the conventional S/U approach: nuclear data are treated as random variables and sampled in accordance to presumed probability distributions. When sampled nuclear data are used in repeated model calculations, the output variance is attributed to the collective uncertainties of nuclear data. The NUSS (Nuclear data Uncertainty Stochastic Sampling) tool is based on this sampling approach and implemented to work with MCNPX’s ACE format of nuclear data, which also gives NUSS compatibility with MCNP and SERPENT M-C codes. In contrast, multigroup uncertainties are used for the sampling of ACE-formatted pointwise-energy nuclear data in a groupwise manner due to the more limited quantity and quality of nuclear data uncertainties. Conveniently, the usage of multigroup nuclear data uncertainties allows consistent comparison between NUSS and other methods (both S/U and sampling-based) that employ the same

Sampling-based nuclear data uncertainty quantification for continuous energy Monte-Carlo codes

Energy Technology Data Exchange (ETDEWEB)

Zhu, T.

2015-07-01

Research on the uncertainty of nuclear data is motivated by practical necessity. Nuclear data uncertainties can propagate through nuclear system simulations into operation and safety related parameters. The tolerance for uncertainties in nuclear reactor design and operation can affect the economic efficiency of nuclear power, and essentially its sustainability. The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of MCNPX makes it the choice of routine criticality safety calculations at PSI/LRS, but also raises challenges for NDUQ by conventional sensitivity/uncertainty (S/U) methods. For example, only recently in 2011, the capability of calculating continuous energy κ{sub eff} sensitivity to nuclear data was demonstrated in certain M-C codes by using the method of iterated fission probability. The methodology developed during this PhD research is fundamentally different from the conventional S/U approach: nuclear data are treated as random variables and sampled in accordance to presumed probability distributions. When sampled nuclear data are used in repeated model calculations, the output variance is attributed to the collective uncertainties of nuclear data. The NUSS (Nuclear data Uncertainty Stochastic Sampling) tool is based on this sampling approach and implemented to work with MCNPX’s ACE format of nuclear data, which also gives NUSS compatibility with MCNP and SERPENT M-C codes. In contrast, multigroup uncertainties are used for the sampling of ACE-formatted pointwise-energy nuclear data in a groupwise manner due to the more limited quantity and quality of nuclear data uncertainties. Conveniently, the usage of multigroup nuclear data uncertainties allows consistent comparison between NUSS and other methods (both S/U and sampling-based) that employ the same

A simple Bayesian approach to quantifying confidence level of adverse event incidence proportion in small samples.

Science.gov (United States)

Liu, Fang

2016-01-01

In both clinical development and post-marketing of a new therapy or a new treatment, incidence of an adverse event (AE) is always a concern. When sample sizes are small, large sample-based inferential approaches on an AE incidence proportion in a certain time period no longer apply. In this brief discussion, we introduce a simple Bayesian framework to quantify, in small sample studies and the rare AE case, (1) the confidence level that the incidence proportion of a particular AE p is over or below a threshold, (2) the lower or upper bounds on p with a certain level of confidence, and (3) the minimum required number of patients with an AE before we can be certain that p surpasses a specific threshold, or the maximum allowable number of patients with an AE after which we can no longer be certain that p is below a certain threshold, given a certain confidence level. The method is easy to understand and implement; the interpretation of the results is intuitive. This article also demonstrates the usefulness of simple Bayesian concepts when it comes to answering practical questions.

Introducing a rainfall compound distribution model based on weather patterns sub-sampling

Directory of Open Access Journals (Sweden)

F. Garavaglia

2010-06-01

Full Text Available This paper presents a probabilistic model for daily rainfall, using sub-sampling based on meteorological circulation. We classified eight typical but contrasted synoptic situations (weather patterns for France and surrounding areas, using a "bottom-up" approach, i.e. from the shape of the rain field to the synoptic situations described by geopotential fields. These weather patterns (WP provide a discriminating variable that is consistent with French climatology, and allows seasonal rainfall records to be split into more homogeneous sub-samples, in term of meteorological genesis.

First results show how the combination of seasonal and WP sub-sampling strongly influences the identification of the asymptotic behaviour of rainfall probabilistic models. Furthermore, with this level of stratification, an asymptotic exponential behaviour of each sub-sample appears as a reasonable hypothesis. This first part is illustrated with two daily rainfall records from SE of France.

The distribution of the multi-exponential weather patterns (MEWP is then defined as the composition, for a given season, of all WP sub-sample marginal distributions, weighted by the relative frequency of occurrence of each WP. This model is finally compared to Exponential and Generalized Pareto distributions, showing good features in terms of robustness and accuracy. These final statistical results are computed from a wide dataset of 478 rainfall chronicles spread on the southern half of France. All these data cover the 1953–2005 period.

A network-based biomarker approach for molecular investigation and diagnosis of lung cancer

Directory of Open Access Journals (Sweden)

Chen Bor-Sen

2011-01-01

Full Text Available Abstract Background Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, based on the research dedicated to this field, there is no highly sensitive network-based method for carcinogenesis characterization and diagnosis from the systems perspective. Methods In this study, a systems biology approach integrating microarray gene expression profiles and protein-protein interaction information was proposed to develop a network-based biomarker for molecular investigation into the network mechanism of lung carcinogenesis and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and non-cancer samples. Results Based on the network-based biomarker, a total of 40 significant proteins in lung carcinogenesis were identified with carcinogenesis relevance values (CRVs. In addition, the network-based biomarker, acting as the screening test, proved to be effective in diagnosing smokers with signs of lung cancer. Conclusions A network-based biomarker using constructed protein association networks is a useful tool to highlight the pathways and mechanisms of the lung carcinogenic process and, more importantly, provides potential therapeutic targets to combat cancer.

Novel Sample-handling Approach for XRD Analysis with Minimal Sample Preparation

Science.gov (United States)

Sarrazin, P.; Chipera, S.; Bish, D.; Blake, D.; Feldman, S.; Vaniman, D.; Bryson, C.

2004-01-01

Sample preparation and sample handling are among the most critical operations associated with X-ray diffraction (XRD) analysis. These operations require attention in a laboratory environment, but they become a major constraint in the deployment of XRD instruments for robotic planetary exploration. We are developing a novel sample handling system that dramatically relaxes the constraints on sample preparation by allowing characterization of coarse-grained material that would normally be impossible to analyze with conventional powder-XRD techniques.

Target and suspect screening of psychoactive substances in sewage-based samples by UHPLC-QTOF.

Science.gov (United States)

Baz-Lomba, J A; Reid, Malcolm J; Thomas, Kevin V

2016-03-31

The quantification of illicit drug and pharmaceutical residues in sewage has been shown to be a valuable tool that complements existing approaches in monitoring the patterns and trends of drug use. The present work delineates the development of a novel analytical tool and dynamic workflow for the analysis of a wide range of substances in sewage-based samples. The validated method can simultaneously quantify 51 target psychoactive substances and pharmaceuticals in sewage-based samples using an off-line automated solid phase extraction (SPE-DEX) method, using Oasis HLB disks, followed by ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) in MS(e). Quantification and matrix effect corrections were overcome with the use of 25 isotopic labeled internal standards (ILIS). Recoveries were generally greater than 60% and the limits of quantification were in the low nanogram-per-liter range (0.4-187 ng L(-1)). The emergence of new psychoactive substances (NPS) on the drug scene poses a specific analytical challenge since their market is highly dynamic with new compounds continuously entering the market. Suspect screening using high-resolution mass spectrometry (HRMS) simultaneously allowed the unequivocal identification of NPS based on a mass accuracy criteria of 5 ppm (of the molecular ion and at least two fragments) and retention time (2.5% tolerance) using the UNIFI screening platform. Applying MS(e) data against a suspect screening database of over 1000 drugs and metabolites, this method becomes a broad and reliable tool to detect and confirm NPS occurrence. This was demonstrated through the HRMS analysis of three different sewage-based sample types; influent wastewater, passive sampler extracts and pooled urine samples resulting in the concurrent quantification of known psychoactive substances and the identification of NPS and pharmaceuticals. Copyright © 2016 Elsevier B.V. All rights reserved.

Genotyping-by-sequencing for Populus population genomics: an assessment of genome sampling patterns and filtering approaches.

Directory of Open Access Journals (Sweden)

Martin P Schilling

Full Text Available Continuing advances in nucleotide sequencing technology are inspiring a suite of genomic approaches in studies of natural populations. Researchers are faced with data management and analytical scales that are increasing by orders of magnitude. With such dramatic advances comes a need to understand biases and error rates, which can be propagated and magnified in large-scale data acquisition and processing. Here we assess genomic sampling biases and the effects of various population-level data filtering strategies in a genotyping-by-sequencing (GBS protocol. We focus on data from two species of Populus, because this genus has a relatively small genome and is emerging as a target for population genomic studies. We estimate the proportions and patterns of genomic sampling by examining the Populus trichocarpa genome (Nisqually-1, and demonstrate a pronounced bias towards coding regions when using the methylation-sensitive ApeKI restriction enzyme in this species. Using population-level data from a closely related species (P. tremuloides, we also investigate various approaches for filtering GBS data to retain high-depth, informative SNPs that can be used for population genetic analyses. We find a data filter that includes the designation of ambiguous alleles resulted in metrics of population structure and Hardy-Weinberg equilibrium that were most consistent with previous studies of the same populations based on other genetic markers. Analyses of the filtered data (27,910 SNPs also resulted in patterns of heterozygosity and population structure similar to a previous study using microsatellites. Our application demonstrates that technically and analytically simple approaches can readily be developed for population genomics of natural populations.

A retrospective cross-sectional quantitative molecular approach in biological samples from patients with syphilis.

Science.gov (United States)

Pinto, Miguel; Antelo, Minia; Ferreira, Rita; Azevedo, Jacinta; Santo, Irene; Borrego, Maria José; Gomes, João Paulo

2017-03-01

Syphilis is the sexually transmitted disease caused by Treponema pallidum, a pathogen highly adapted to the human host. As a multistage disease, syphilis presents distinct clinical manifestations that pose different implications for diagnosis. Nevertheless, the inherent factors leading to diverse disease progressions are still unknown. We aimed to assess the association between treponemal loads and dissimilar disease outcomes, to better understand syphilis. We retrospectively analyzed 309 DNA samples distinct anatomic sites associated with particular syphilis manifestations. All samples had previously tested positive by a PCR-based diagnostic kit. An absolute quantitative real-time PCR procedure was used to precisely quantify the number of treponemal and human cells to determine T. pallidum loads in each sample. In general, lesion exudates presented the highest T. pallidum loads in contrast with blood-derived samples. Within the latter, a higher dispersion of T. pallidum quantities was observed for secondary syphilis. T. pallidum was detected in substantial amounts in 37 samples of seronegative individuals and in 13 cases considered as syphilis-treated. No association was found between treponemal loads and serological results or HIV status. This study suggests a scenario where syphilis may be characterized by: i) heterogeneous and high treponemal loads in primary syphilis, regardless of the anatomic site, reflecting dissimilar duration of chancres development and resolution; ii) high dispersion of bacterial concentrations in secondary syphilis, potentially suggesting replication capability of T. pallidum while in the bloodstream; and iii) bacterial evasiveness, either to the host immune system or antibiotic treatment, while remaining hidden in privileged niches. This work highlights the importance of using molecular approaches to study uncultivable human pathogens, such as T. pallidum, in the infection process. Copyright © 2017 Elsevier Ltd. All rights

A Task-Based Approach to Materials Development

Science.gov (United States)

Nunan, David

2010-01-01

The purpose of this chapter is to present a task-based approach to materials development. In the first part of the chapter, I sketch out the evolution of task based language teaching, drawing on a distinction between synthetic and analytical approaches to syllabus design first articulated by Wilkins (1976).

Effective sampling range of a synthetic protein-based attractant for Ceratitis capitata (Diptera: Tephritidae).

Science.gov (United States)

Epsky, Nancy D; Espinoza, Hernán R; Kendra, Paul E; Abernathy, Robert; Midgarden, David; Heath, Robert R

2010-10-01

Studies were conducted in Honduras to determine effective sampling range of a female-targeted protein-based synthetic attractant for the Mediterranean fruit fly, Ceratitis capitata (Wiedemann) (Diptera: Tephritidae). Multilure traps were baited with ammonium acetate, putrescine, and trimethylamine lures (three-component attractant) and sampled over eight consecutive weeks. Field design consisted of 38 traps (over 0.5 ha) placed in a combination of standard and high-density grids to facilitate geostatistical analysis, and tests were conducted in coffee (Coffea arabica L.),mango (Mangifera indica L.),and orthanique (Citrus sinensis X Citrus reticulata). Effective sampling range, as determined from the range parameter obtained from experimental variograms that fit a spherical model, was approximately 30 m for flies captured in tests in coffee or mango and approximately 40 m for flies captured in orthanique. For comparison, a release-recapture study was conducted in mango using wild (field-collected) mixed sex C. capitata and an array of 20 baited traps spaced 10-50 m from the release point. Contour analysis was used to document spatial distribution of fly recaptures and to estimate effective sampling range, defined by the area that encompassed 90% of the recaptures. With this approach, effective range of the three-component attractant was estimated to be approximately 28 m, similar to results obtained from variogram analysis. Contour maps indicated that wind direction had a strong influence on sampling range, which was approximately 15 m greater upwind compared with downwind from the release point. Geostatistical analysis of field-captured insects in appropriately designed trapping grids may provide a supplement or alternative to release-recapture studies to estimate sampling ranges for semiochemical-based trapping systems.

Frame-Based and Subpicture-Based Parallelization Approaches of the HEVC Video Encoder

Directory of Open Access Journals (Sweden)

Héctor Migallón

2018-05-01

Full Text Available The most recent video coding standard, High Efficiency Video Coding (HEVC, is able to significantly improve the compression performance at the expense of a huge computational complexity increase with respect to its predecessor, H.264/AVC. Parallel versions of the HEVC encoder may help to reduce the overall encoding time in order to make it more suitable for practical applications. In this work, we study two parallelization strategies. One of them follows a coarse-grain approach, where parallelization is based on frames, and the other one follows a fine-grain approach, where parallelization is performed at subpicture level. Two different frame-based approaches have been developed. The first one only uses MPI and the second one is a hybrid MPI/OpenMP algorithm. An exhaustive experimental test was carried out to study the performance of both approaches in order to find out the best setup in terms of parallel efficiency and coding performance. Both frame-based and subpicture-based approaches are compared under the same hardware platform. Although subpicture-based schemes provide an excellent performance with high-resolution video sequences, scalability is limited by resolution, and the coding performance worsens by increasing the number of processes. Conversely, the proposed frame-based approaches provide the best results with respect to both parallel performance (increasing scalability and coding performance (not degrading the rate/distortion behavior.

A new insert sample approach to paper spray mass spectrometry: a paper substrate with paraffin barriers.

Science.gov (United States)

Colletes, T C; Garcia, P T; Campanha, R B; Abdelnur, P V; Romão, W; Coltro, W K T; Vaz, B G

2016-03-07

The analytical performance for paper spray (PS) using a new insert sample approach based on paper with paraffin barriers (PS-PB) is presented. The paraffin barrier is made using a simple, fast and cheap method based on the stamping of paraffin onto a paper surface. Typical operation conditions of paper spray such as the solvent volume applied on the paper surface, and the paper substrate type are evaluated. A paper substrate with paraffin barriers shows better performance on analysis of a range of typical analytes when compared to the conventional PS-MS using normal paper (PS-NP) and PS-MS using paper with two rounded corners (PS-RC). PS-PB was applied to detect sugars and their inhibitors in sugarcane bagasse liquors from a second generation ethanol process. Moreover, the PS-PB proved to be excellent, showing results for the quantification of glucose in hydrolysis liquors with excellent linearity (R(2) = 0.99), limits of detection (2.77 mmol L(-1)) and quantification (9.27 mmol L(-1)). The results are better than for PS-NP and PS-RC. The PS-PB was also excellent in performance when compared with the HPLC-UV method for glucose quantification on hydrolysis of liquor samples.

Cognition-Based Approaches for High-Precision Text Mining

Science.gov (United States)

Shannon, George John

2017-01-01

This research improves the precision of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant improvements in both…

RF Sub-sampling Receiver Architecture based on Milieu Adapting Techniques

DEFF Research Database (Denmark)

Behjou, Nastaran; Larsen, Torben; Jensen, Ole Kiel

2012-01-01

A novel sub-sampling based architecture is proposed which has the ability of reducing the problem of image distortion and improving the signal to noise ratio significantly. The technique is based on sensing the environment and adapting the sampling rate of the receiver to the best possible...

Subsurface Noble Gas Sampling Manual

Energy Technology Data Exchange (ETDEWEB)

Carrigan, C. R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sun, Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-09-18

The intent of this document is to provide information about best available approaches for performing subsurface soil gas sampling during an On Site Inspection or OSI. This information is based on field sampling experiments, computer simulations and data from the NA-22 Noble Gas Signature Experiment Test Bed at the Nevada Nuclear Security Site (NNSS). The approaches should optimize the gas concentration from the subsurface cavity or chimney regime while simultaneously minimizing the potential for atmospheric radioxenon and near-surface Argon-37 contamination. Where possible, we quantitatively assess differences in sampling practices for the same sets of environmental conditions. We recognize that all sampling scenarios cannot be addressed. However, if this document helps to inform the intuition of the reader about addressing the challenges resulting from the inevitable deviations from the scenario assumed here, it will have achieved its goal.

Service creation: a model-based approach

NARCIS (Netherlands)

Quartel, Dick; van Sinderen, Marten J.; Ferreira Pires, Luis

1999-01-01

This paper presents a model-based approach to support service creation. In this approach, services are assumed to be created from (available) software components. The creation process may involve multiple design steps in which the requested service is repeatedly decomposed into more detailed

Advances in paper-based sample pretreatment for point-of-care testing.

Science.gov (United States)

Tang, Rui Hua; Yang, Hui; Choi, Jane Ru; Gong, Yan; Feng, Shang Sheng; Pingguan-Murphy, Belinda; Huang, Qing Sheng; Shi, Jun Ling; Mei, Qi Bing; Xu, Feng

2017-06-01

In recent years, paper-based point-of-care testing (POCT) has been widely used in medical diagnostics, food safety and environmental monitoring. However, a high-cost, time-consuming and equipment-dependent sample pretreatment technique is generally required for raw sample processing, which are impractical for low-resource and disease-endemic areas. Therefore, there is an escalating demand for a cost-effective, simple and portable pretreatment technique, to be coupled with the commonly used paper-based assay (e.g. lateral flow assay) in POCT. In this review, we focus on the importance of using paper as a platform for sample pretreatment. We firstly discuss the beneficial use of paper for sample pretreatment, including sample collection and storage, separation, extraction, and concentration. We highlight the working principle and fabrication of each sample pretreatment device, the existing challenges and the future perspectives for developing paper-based sample pretreatment technique.

Solid-Phase Extraction Strategies to Surmount Body Fluid Sample Complexity in High-Throughput Mass Spectrometry-Based Proteomics

Science.gov (United States)

Bladergroen, Marco R.; van der Burgt, Yuri E. M.

2015-01-01

For large-scale and standardized applications in mass spectrometry- (MS-) based proteomics automation of each step is essential. Here we present high-throughput sample preparation solutions for balancing the speed of current MS-acquisitions and the time needed for analytical workup of body fluids. The discussed workflows reduce body fluid sample complexity and apply for both bottom-up proteomics experiments and top-down protein characterization approaches. Various sample preparation methods that involve solid-phase extraction (SPE) including affinity enrichment strategies have been automated. Obtained peptide and protein fractions can be mass analyzed by direct infusion into an electrospray ionization (ESI) source or by means of matrix-assisted laser desorption ionization (MALDI) without further need of time-consuming liquid chromatography (LC) separations. PMID:25692071

Fungi identify the geographic origin of dust samples.

Directory of Open Access Journals (Sweden)

Neal S Grantham

Full Text Available There is a long history of archaeologists and forensic scientists using pollen found in a dust sample to identify its geographic origin or history. Such palynological approaches have important limitations as they require time-consuming identification of pollen grains, a priori knowledge of plant species distributions, and a sufficient diversity of pollen types to permit spatial or temporal identification. We demonstrate an alternative approach based on DNA sequencing analyses of the fungal diversity found in dust samples. Using nearly 1,000 dust samples collected from across the continental U.S., our analyses identify up to 40,000 fungal taxa from these samples, many of which exhibit a high degree of geographic endemism. We develop a statistical learning algorithm via discriminant analysis that exploits this geographic endemicity in the fungal diversity to correctly identify samples to within a few hundred kilometers of their geographic origin with high probability. In addition, our statistical approach provides a measure of certainty for each prediction, in contrast with current palynology methods that are almost always based on expert opinion and devoid of statistical inference. Fungal taxa found in dust samples can therefore be used to identify the origin of that dust and, more importantly, we can quantify our degree of certainty that a sample originated in a particular place. This work opens up a new approach to forensic biology that could be used by scientists to identify the origin of dust or soil samples found on objects, clothing, or archaeological artifacts.

Automated CBED processing: Sample thickness estimation based on analysis of zone-axis CBED pattern

Energy Technology Data Exchange (ETDEWEB)

Klinger, M., E-mail: klinger@post.cz; Němec, M.; Polívka, L.; Gärtnerová, V.; Jäger, A.

2015-03-15

An automated processing of convergent beam electron diffraction (CBED) patterns is presented. The proposed methods are used in an automated tool for estimating the thickness of transmission electron microscopy (TEM) samples by matching an experimental zone-axis CBED pattern with a series of patterns simulated for known thicknesses. The proposed tool detects CBED disks, localizes a pattern in detected disks and unifies the coordinate system of the experimental pattern with the simulated one. The experimental pattern is then compared disk-by-disk with a series of simulated patterns each corresponding to different known thicknesses. The thickness of the most similar simulated pattern is then taken as the thickness estimate. The tool was tested on [0 1 1] Si, [0 1 0] α-Ti and [0 1 1] α-Ti samples prepared using different techniques. Results of the presented approach were compared with thickness estimates based on analysis of CBED patterns in two beam conditions. The mean difference between these two methods was 4.1% for the FIB-prepared silicon samples, 5.2% for the electro-chemically polished titanium and 7.9% for Ar{sup +} ion-polished titanium. The proposed techniques can also be employed in other established CBED analyses. Apart from the thickness estimation, it can potentially be used to quantify lattice deformation, structure factors, symmetry, defects or extinction distance. - Highlights: • Automated TEM sample thickness estimation using zone-axis CBED is presented. • Computer vision and artificial intelligence are employed in CBED processing. • This approach reduces operator effort, analysis time and increases repeatability. • Individual parts can be employed in other analyses of CBED/diffraction pattern.

Determination of total concentration of chemically labeled metabolites as a means of metabolome sample normalization and sample loading optimization in mass spectrometry-based metabolomics.

Science.gov (United States)

Wu, Yiman; Li, Liang

2012-12-18

For mass spectrometry (MS)-based metabolomics, it is important to use the same amount of starting materials from each sample to compare the metabolome changes in two or more comparative samples. Unfortunately, for biological samples, the total amount or concentration of metabolites is difficult to determine. In this work, we report a general approach of determining the total concentration of metabolites based on the use of chemical labeling to attach a UV absorbent to the metabolites to be analyzed, followed by rapid step-gradient liquid chromatography (LC) UV detection of the labeled metabolites. It is shown that quantification of the total labeled analytes in a biological sample facilitates the preparation of an appropriate amount of starting materials for MS analysis as well as the optimization of the sample loading amount to a mass spectrometer for achieving optimal detectability. As an example, dansylation chemistry was used to label the amine- and phenol-containing metabolites in human urine samples. LC-UV quantification of the labeled metabolites could be optimally performed at the detection wavelength of 338 nm. A calibration curve established from the analysis of a mixture of 17 labeled amino acid standards was found to have the same slope as that from the analysis of the labeled urinary metabolites, suggesting that the labeled amino acid standard calibration curve could be used to determine the total concentration of the labeled urinary metabolites. A workflow incorporating this LC-UV metabolite quantification strategy was then developed in which all individual urine samples were first labeled with (12)C-dansylation and the concentration of each sample was determined by LC-UV. The volumes of urine samples taken for producing the pooled urine standard were adjusted to ensure an equal amount of labeled urine metabolites from each sample was used for the pooling. The pooled urine standard was then labeled with (13)C-dansylation. Equal amounts of the (12)C

Soil sampling strategies: Evaluation of different approaches

Energy Technology Data Exchange (ETDEWEB)

De Zorzi, Paolo [Agenzia per la Protezione dell' Ambiente e per i Servizi Tecnici (APAT), Servizio Metrologia Ambientale, Via di Castel Romano, 100-00128 Roma (Italy)], E-mail: paolo.dezorzi@apat.it; Barbizzi, Sabrina; Belli, Maria [Agenzia per la Protezione dell' Ambiente e per i Servizi Tecnici (APAT), Servizio Metrologia Ambientale, Via di Castel Romano, 100-00128 Roma (Italy); Mufato, Renzo; Sartori, Giuseppe; Stocchero, Giulia [Agenzia Regionale per la Prevenzione e Protezione dell' Ambiente del Veneto, ARPA Veneto, U.O. Centro Qualita Dati, Via Spalato, 14-36045 Vicenza (Italy)

2008-11-15

The National Environmental Protection Agency of Italy (APAT) performed a soil sampling intercomparison, inviting 14 regional agencies to test their own soil sampling strategies. The intercomparison was carried out at a reference site, previously characterised for metal mass fraction distribution. A wide range of sampling strategies, in terms of sampling patterns, type and number of samples collected, were used to assess the mean mass fraction values of some selected elements. The different strategies led in general to acceptable bias values (D) less than 2{sigma}, calculated according to ISO 13258. Sampling on arable land was relatively easy, with comparable results between different sampling strategies.

Soil sampling strategies: Evaluation of different approaches

International Nuclear Information System (INIS)

De Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Mufato, Renzo; Sartori, Giuseppe; Stocchero, Giulia

2008-01-01

The National Environmental Protection Agency of Italy (APAT) performed a soil sampling intercomparison, inviting 14 regional agencies to test their own soil sampling strategies. The intercomparison was carried out at a reference site, previously characterised for metal mass fraction distribution. A wide range of sampling strategies, in terms of sampling patterns, type and number of samples collected, were used to assess the mean mass fraction values of some selected elements. The different strategies led in general to acceptable bias values (D) less than 2σ, calculated according to ISO 13258. Sampling on arable land was relatively easy, with comparable results between different sampling strategies

Soil sampling strategies: evaluation of different approaches.

Science.gov (United States)

de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Mufato, Renzo; Sartori, Giuseppe; Stocchero, Giulia

2008-11-01

The National Environmental Protection Agency of Italy (APAT) performed a soil sampling intercomparison, inviting 14 regional agencies to test their own soil sampling strategies. The intercomparison was carried out at a reference site, previously characterised for metal mass fraction distribution. A wide range of sampling strategies, in terms of sampling patterns, type and number of samples collected, were used to assess the mean mass fraction values of some selected elements. The different strategies led in general to acceptable bias values (D) less than 2sigma, calculated according to ISO 13258. Sampling on arable land was relatively easy, with comparable results between different sampling strategies.

Survey of sampling-based methods for uncertainty and sensitivity analysis

International Nuclear Information System (INIS)

Helton, J.C.; Johnson, J.D.; Sallaberry, C.J.; Storlie, C.B.

2006-01-01

Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (i) definition of probability distributions to characterize epistemic uncertainty in analysis inputs (ii) generation of samples from uncertain analysis inputs (iii) propagation of sampled inputs through an analysis (iv) presentation of uncertainty analysis results, and (v) determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two-dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition

Survey of sampling-based methods for uncertainty and sensitivity analysis.

Energy Technology Data Exchange (ETDEWEB)

Johnson, Jay Dean; Helton, Jon Craig; Sallaberry, Cedric J. PhD. (.; .); Storlie, Curt B. (Colorado State University, Fort Collins, CO)

2006-06-01

Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (1) Definition of probability distributions to characterize epistemic uncertainty in analysis inputs, (2) Generation of samples from uncertain analysis inputs, (3) Propagation of sampled inputs through an analysis, (4) Presentation of uncertainty analysis results, and (5) Determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition.

Network Sampling with Memory: A proposal for more efficient sampling from social networks

Science.gov (United States)

Mouw, Ted; Verdery, Ashton M.

2013-01-01

Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)—the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a “List” mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a “Search” mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS. PMID:24159246

Metrological approach to quantitative analysis of clinical samples by LA-ICP-MS: A critical review of recent studies.

Science.gov (United States)

Sajnóg, Adam; Hanć, Anetta; Barałkiewicz, Danuta

2018-05-15

Analysis of clinical specimens by imaging techniques allows to determine the content and distribution of trace elements on the surface of the examined sample. In order to obtain reliable results, the developed procedure should be based not only on the properly prepared sample and performed calibration. It is also necessary to carry out all phases of the procedure in accordance with the principles of chemical metrology whose main pillars are the use of validated analytical methods, establishing the traceability of the measurement results and the estimation of the uncertainty. This review paper discusses aspects related to sampling, preparation and analysis of clinical samples by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) with emphasis on metrological aspects, i.e. selected validation parameters of the analytical method, the traceability of the measurement result and the uncertainty of the result. This work promotes the introduction of metrology principles for chemical measurement with emphasis to the LA-ICP-MS which is the comparative method that requires studious approach to the development of the analytical procedure in order to acquire reliable quantitative results. Copyright © 2018 Elsevier B.V. All rights reserved.

Adaptive Angular Sampling for SPECT Imaging

OpenAIRE

Li, Nan; Meng, Ling-Jian

2011-01-01

This paper presents an analytical approach for performing adaptive angular sampling in single photon emission computed tomography (SPECT) imaging. It allows for a rapid determination of the optimum sampling strategy that minimizes image variance in regions-of-interest (ROIs). The proposed method consists of three key components: (a) a set of close-form equations for evaluating image variance and resolution attainable with a given sampling strategy, (b) a gradient-based algor...

The Recent Developments in Sample Preparation for Mass Spectrometry-Based Metabolomics.

Science.gov (United States)

Gong, Zhi-Gang; Hu, Jing; Wu, Xi; Xu, Yong-Jiang

2017-07-04

Metabolomics is a critical member in systems biology. Although great progress has been achieved in metabolomics, there are still some problems in sample preparation, data processing and data interpretation. In this review, we intend to explore the roles, challenges and trends in sample preparation for mass spectrometry- (MS-) based metabolomics. The newly emerged sample preparation methods were also critically examined, including laser microdissection, in vivo sampling, dried blood spot, microwave, ultrasound and enzyme-assisted extraction, as well as microextraction techniques. Finally, we provide some conclusions and perspectives for sample preparation in MS-based metabolomics.

Diversification Strategies and Firm Performance: A Sample Selection Approach

OpenAIRE

Santarelli, Enrico; Tran, Hien Thu

2013-01-01

This paper is based upon the assumption that firm profitability is determined by its degree of diversification which in turn is strongly related to the antecedent decision to carry out diversification activities. This calls for an empirical approach that permits the joint analysis of the three interrelated and consecutive stages of the overall diversification process: diversification decision, degree of diversification, and outcome of diversification. We apply parametric and semiparametric ap...

Textual, Genre and Social Features of Spoken Grammar: A Corpus-Based Approach

Directory of Open Access Journals (Sweden)

Carmen Pérez-Llantada

2009-02-01

Full Text Available This paper describes a corpus-based approach to teaching and learning spoken grammar for English for Academic Purposes with reference to Bhatia’s (2002 multi-perspective model for discourse analysis: a textual perspective, a genre perspective and a social perspective. From a textual perspective, corpus-informed instruction helps students identify grammar items through statistical frequencies, collocational patterns, context-sensitive meanings and discoursal uses of words. From a genre perspective, corpus observation provides students with exposure to recurrent lexico-grammatical patterns across different academic text types (genres. From a social perspective, corpus models can be used to raise learners’ awareness of how speakers’ different discourse roles, discourse privileges and power statuses are enacted in their grammar choices. The paper describes corpus-based instructional procedures, gives samples of learners’ linguistic output, and provides comments on the students’ response to this method of instruction. Data resulting from the assessment process and student production suggest that corpus-informed instruction grounded in Bhatia’s multi-perspective model can constitute a pedagogical approach in order to i obtain positive student responses from input and authentic samples of grammar use, ii help students identify and understand the textual, genre and social aspects of grammar in real contexts of use, and therefore iii help develop students’ ability to use grammar accurately and appropriately.

Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

Science.gov (United States)

Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

2016-01-01

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

Networked Estimation for Event-Based Sampling Systems with Packet Dropouts

Directory of Open Access Journals (Sweden)

Young Soo Suh

2009-04-01

Full Text Available This paper is concerned with a networked estimation problem in which sensor data are transmitted over the network. In the event-based sampling scheme known as level-crossing or send-on-delta (SOD, sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. Event-based sampling has been shown to be more efficient than the time-triggered one in some situations, especially in network bandwidth improvement. However, it cannot detect packet dropout situations because data transmission and reception do not use a periodical time-stamp mechanism as found in time-triggered sampling systems. Motivated by this issue, we propose a modified event-based sampling scheme called modified SOD in which sensor data are sent when either the change of sensor output exceeds a given threshold or the time elapses more than a given interval. Through simulation results, we show that the proposed modified SOD sampling significantly improves estimation performance when packet dropouts happen.

Knowledge-Based Approaches: Two cases of applicability

DEFF Research Database (Denmark)

Andersen, Tom

1997-01-01

Basic issues of the term: A knowledge-based approach (KBA) are discussed. Two cases of applicable to KBA are presented, and its concluded that KBA is more than just IT.......Basic issues of the term: A knowledge-based approach (KBA) are discussed. Two cases of applicable to KBA are presented, and its concluded that KBA is more than just IT....

Wavelength dispersive X-ray fluorescence analysis using fundamental parameter approach of Catha edulis and other related plant samples

Energy Technology Data Exchange (ETDEWEB)

Shaltout, Abdallah A., E-mail: shaltout_a@hotmail.com [Spectroscopy Department, Physics Division, National Research Center, El Behooth Str., 12622 Dokki, Cairo (Egypt); Faculty of science, Taif University, 21974 Taif, P.O. Box 888 (Saudi Arabia); Moharram, Mohammed A. [Spectroscopy Department, Physics Division, National Research Center, El Behooth Str., 12622 Dokki, Cairo (Egypt); Mostafa, Nasser Y. [Faculty of science, Taif University, 21974 Taif, P.O. Box 888 (Saudi Arabia); Chemistry Department, Faculty of Science, Suez Canal University, Ismailia (Egypt)

2012-01-15

This work is the first attempt to quantify trace elements in the Catha edulis plant (Khat) with a fundamental parameter approach. C. edulis is a famous drug plant in east Africa and Arabian Peninsula. We have previously confirmed that hydroxyapatite represents one of the main inorganic compounds in the leaves and stalks of C. edulis. Comparable plant leaves from basil, mint and green tea were included in the present investigation as well as trifolium leaves were included as a non-related plant. The elemental analyses of the plants were done by Wavelength Dispersive X-Ray Fluorescence (WDXRF) spectroscopy. Standard-less quantitative WDXRF analysis was carried out based on the fundamental parameter approaches. According to the standard-less analysis algorithms, there is an essential need for an accurate determination of the amount of organic material in the sample. A new approach, based on the differential thermal analysis, was successfully used for the organic material determination. The obtained results based on this approach were in a good agreement with the commonly used methods. Depending on the developed method, quantitative analysis results of eighteen elements including; Al, Br, Ca, Cl, Cu, Fe, K, Na, Ni, Mg, Mn, P, Rb, S, Si, Sr, Ti and Zn were obtained for each plant. The results of the certified reference materials of green tea (NCSZC73014, China National Analysis Center for Iron and Steel, Beijing, China) confirmed the validity of the proposed method. - Highlights: Black-Right-Pointing-Pointer Quantitative analysis of Catha edulis was carried out using standardless WDXRF. Black-Right-Pointing-Pointer Differential thermal analysis was used for determination of the loss of ignition. Black-Right-Pointing-Pointer The existence of hydroxyapatite in Catha edulis plant has been confirmed. Black-Right-Pointing-Pointer The CRM results confirmed the validity of the developed method.

Wavelength dispersive X-ray fluorescence analysis using fundamental parameter approach of Catha edulis and other related plant samples

International Nuclear Information System (INIS)

Shaltout, Abdallah A.; Moharram, Mohammed A.; Mostafa, Nasser Y.

2012-01-01

This work is the first attempt to quantify trace elements in the Catha edulis plant (Khat) with a fundamental parameter approach. C. edulis is a famous drug plant in east Africa and Arabian Peninsula. We have previously confirmed that hydroxyapatite represents one of the main inorganic compounds in the leaves and stalks of C. edulis. Comparable plant leaves from basil, mint and green tea were included in the present investigation as well as trifolium leaves were included as a non-related plant. The elemental analyses of the plants were done by Wavelength Dispersive X-Ray Fluorescence (WDXRF) spectroscopy. Standard-less quantitative WDXRF analysis was carried out based on the fundamental parameter approaches. According to the standard-less analysis algorithms, there is an essential need for an accurate determination of the amount of organic material in the sample. A new approach, based on the differential thermal analysis, was successfully used for the organic material determination. The obtained results based on this approach were in a good agreement with the commonly used methods. Depending on the developed method, quantitative analysis results of eighteen elements including; Al, Br, Ca, Cl, Cu, Fe, K, Na, Ni, Mg, Mn, P, Rb, S, Si, Sr, Ti and Zn were obtained for each plant. The results of the certified reference materials of green tea (NCSZC73014, China National Analysis Center for Iron and Steel, Beijing, China) confirmed the validity of the proposed method. - Highlights: ► Quantitative analysis of Catha edulis was carried out using standardless WDXRF. ► Differential thermal analysis was used for determination of the loss of ignition. ► The existence of hydroxyapatite in Catha edulis plant has been confirmed. ► The CRM results confirmed the validity of the developed method.

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

Science.gov (United States)

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

High Throughput Sample Preparation and Analysis for DNA Sequencing, PCR and Combinatorial Screening of Catalysis Based on Capillary Array Technique

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yonghua [Iowa State Univ., Ames, IA (United States)

2000-01-01

Sample preparation has been one of the major bottlenecks for many high throughput analyses. The purpose of this research was to develop new sample preparation and integration approach for DNA sequencing, PCR based DNA analysis and combinatorial screening of homogeneous catalysis based on multiplexed capillary electrophoresis with laser induced fluorescence or imaging UV absorption detection. The author first introduced a method to integrate the front-end tasks to DNA capillary-array sequencers. protocols for directly sequencing the plasmids from a single bacterial colony in fused-silica capillaries were developed. After the colony was picked, lysis was accomplished in situ in the plastic sample tube using either a thermocycler or heating block. Upon heating, the plasmids were released while chromsomal DNA and membrane proteins were denatured and precipitated to the bottom of the tube. After adding enzyme and Sanger reagents, the resulting solution was aspirated into the reaction capillaries by a syringe pump, and cycle sequencing was initiated. No deleterious effect upon the reaction efficiency, the on-line purification system, or the capillary electrophoresis separation was observed, even though the crude lysate was used as the template. Multiplexed on-line DNA sequencing data from 8 parallel channels allowed base calling up to 620 bp with an accuracy of 98%. The entire system can be automatically regenerated for repeated operation. For PCR based DNA analysis, they demonstrated that capillary electrophoresis with UV detection can be used for DNA analysis starting from clinical sample without purification. After PCR reaction using cheek cell, blood or HIV-1 gag DNA, the reaction mixtures was injected into the capillary either on-line or off-line by base stacking. The protocol was also applied to capillary array electrophoresis. The use of cheaper detection, and the elimination of purification of DNA sample before or after PCR reaction, will make this approach an

Accelerated Enveloping Distribution Sampling: Enabling Sampling of Multiple End States while Preserving Local Energy Minima.

Science.gov (United States)

Perthold, Jan Walther; Oostenbrink, Chris

2018-05-17

Enveloping distribution sampling (EDS) is an efficient approach to calculate multiple free-energy differences from a single molecular dynamics (MD) simulation. However, the construction of an appropriate reference-state Hamiltonian that samples all states efficiently is not straightforward. We propose a novel approach for the construction of the EDS reference-state Hamiltonian, related to a previously described procedure to smoothen energy landscapes. In contrast to previously suggested EDS approaches, our reference-state Hamiltonian preserves local energy minima of the combined end-states. Moreover, we propose an intuitive, robust and efficient parameter optimization scheme to tune EDS Hamiltonian parameters. We demonstrate the proposed method with established and novel test systems and conclude that our approach allows for the automated calculation of multiple free-energy differences from a single simulation. Accelerated EDS promises to be a robust and user-friendly method to compute free-energy differences based on solid statistical mechanics.

Evaluation of Approaches to Analyzing Continuous Correlated Eye Data When Sample Size Is Small.

Science.gov (United States)

Huang, Jing; Huang, Jiayan; Chen, Yong; Ying, Gui-Shuang

2018-02-01

To evaluate the performance of commonly used statistical methods for analyzing continuous correlated eye data when sample size is small. We simulated correlated continuous data from two designs: (1) two eyes of a subject in two comparison groups; (2) two eyes of a subject in the same comparison group, under various sample size (5-50), inter-eye correlation (0-0.75) and effect size (0-0.8). Simulated data were analyzed using paired t-test, two sample t-test, Wald test and score test using the generalized estimating equations (GEE) and F-test using linear mixed effects model (LMM). We compared type I error rates and statistical powers, and demonstrated analysis approaches through analyzing two real datasets. In design 1, paired t-test and LMM perform better than GEE, with nominal type 1 error rate and higher statistical power. In design 2, no test performs uniformly well: two sample t-test (average of two eyes or a random eye) achieves better control of type I error but yields lower statistical power. In both designs, the GEE Wald test inflates type I error rate and GEE score test has lower power. When sample size is small, some commonly used statistical methods do not perform well. Paired t-test and LMM perform best when two eyes of a subject are in two different comparison groups, and t-test using the average of two eyes performs best when the two eyes are in the same comparison group. When selecting the appropriate analysis approach the study design should be considered.

Performance and separation occurrence of binary probit regression estimator using maximum likelihood method and Firths approach under different sample size

Science.gov (United States)

Lusiana, Evellin Dewi

2017-12-01

The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.

Pedestrian detection from thermal images: A sparse representation based approach

Science.gov (United States)

Qi, Bin; John, Vijay; Liu, Zheng; Mita, Seiichi

2016-05-01

Pedestrian detection, a key technology in computer vision, plays a paramount role in the applications of advanced driver assistant systems (ADASs) and autonomous vehicles. The objective of pedestrian detection is to identify and locate people in a dynamic environment so that accidents can be avoided. With significant variations introduced by illumination, occlusion, articulated pose, and complex background, pedestrian detection is a challenging task for visual perception. Different from visible images, thermal images are captured and presented with intensity maps based objects' emissivity, and thus have an enhanced spectral range to make human beings perceptible from the cool background. In this study, a sparse representation based approach is proposed for pedestrian detection from thermal images. We first adopted the histogram of sparse code to represent image features and then detect pedestrian with the extracted features in an unimodal and a multimodal framework respectively. In the unimodal framework, two types of dictionaries, i.e. joint dictionary and individual dictionary, are built by learning from prepared training samples. In the multimodal framework, a weighted fusion scheme is proposed to further highlight the contributions from features with higher separability. To validate the proposed approach, experiments were conducted to compare with three widely used features: Haar wavelets (HWs), histogram of oriented gradients (HOG), and histogram of phase congruency (HPC) as well as two classification methods, i.e. AdaBoost and support vector machine (SVM). Experimental results on a publicly available data set demonstrate the superiority of the proposed approach.

Use of GIS-Based Sampling to Inform Food Security Assessments and Decision Making in Kenya

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Wahome, A.; Ndubi, A. O.; Ndungu, L. W.; Mugo, R. M.; Flores Cordova, A. I.

2017-12-01

Kenya relies on agricultural production for supporting local consumption and other processing value chains. With changing climate in a rain-fed dependent agricultural production system, cropping zones are shifting and proper decision making will require updated data. Where up-to-date data is not available it is important that it is generated and passed over to relevant stakeholders to inform their decision making. The process of generating this data should be cost effective and less time consuming. The Kenyan State Department of Agriculture (SDA) runs an insurance programme for maize farmers in a number of counties in Kenya. Previously, SDA was using a list of farmers to identify the crop fields for this insurance programme. However, the process of listing of all farmers in each Unit Area of Insurance (UAI) proved to be tedious and very costly, hence need for an alternative approach, but acceptable sampling methodology. Building on the existing cropland maps, SERVIR, a joint NASA-USAID initiative that brings Earth observations (EO) for improved environmental decision making in developing countries, specifically its hub in Eastern and Soutehrn Africa developed a High Resolution Map based on 10m Sentinel satellite images from which a GIS based sampling frame for identifying maize fields was developed. Sampling points were randomly generated in each UAI and navigated to using hand-held GPS units for identification of maize farmers. In the GIS-based identification of farmers SDA uses 1 day to cover an area covered in 1 week by list identification of farmers. Similarly, SDA spends approximately 3,000 USD per sub-county to locate maize fields using GIS-based sampling as compared 10,000 USD they used to spend before. This has resulted in 70% cost reduction.

Basic distribution free identification tests for small size samples of environmental data

International Nuclear Information System (INIS)

Federico, A.G.; Musmeci, F.

1998-01-01

Testing two or more data sets for the hypothesis that they are sampled form the same population is often required in environmental data analysis. Typically the available samples have a small number of data and often then assumption of normal distributions is not realistic. On the other hand the diffusion of the days powerful Personal Computers opens new possible opportunities based on a massive use of the CPU resources. The paper reviews the problem introducing the feasibility of two non parametric approaches based on intrinsic equi probability properties of the data samples. The first one is based on a full re sampling while the second is based on a bootstrap approach. A easy to use program is presented. A case study is given based on the Chernobyl children contamination data [it

Transaction based approach

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Hunka, Frantisek; Matula, Jiri

2017-07-01

Transaction based approach is utilized in some methodologies in business process modeling. Essential parts of these transactions are human beings. The notion of agent or actor role is usually used for them. The paper on a particular example describes possibilities of Design Engineering Methodology for Organizations (DEMO) and Resource-Event-Agent (REA) methodology. Whereas the DEMO methodology can be regarded as a generic methodology having its foundation in the theory of Enterprise Ontology the REA methodology is regarded as the domain specific methodology and has its origin in accountancy systems. The results of these approaches is that the DEMO methodology captures everything that happens in the reality with a good empirical evidence whereas the REA methodology captures only changes connected with economic events. Economic events represent either change of the property rights to economic resource or consumption or production of economic resources. This results from the essence of economic events and their connection to economic resources.

Risk-Based Sampling: I Don't Want to Weight in Vain.

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Powell, Mark R

2015-12-01

Recently, there has been considerable interest in developing risk-based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk-based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz (1952) laid the foundation for modern portfolio theory based on mean-variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false "optimal" portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out-of-sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk-based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers. © 2015 Society for Risk Analysis.

Sampling plans in attribute mode with multiple levels of precision

International Nuclear Information System (INIS)

Franklin, M.

1986-01-01

This paper describes a method for deriving sampling plans for nuclear material inventory verification. The method presented is different from the classical approach which envisages two levels of measurement precision corresponding to NDA and DA. In the classical approach the precisions of the two measurement methods are taken as fixed parameters. The new approach is based on multiple levels of measurement precision. The design of the sampling plan consists of choosing the number of measurement levels, the measurement precision to be used at each level and the sample size to be used at each level

Quality based approach for adaptive face recognition

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Abboud, Ali J.; Sellahewa, Harin; Jassim, Sabah A.

2009-05-01

Recent advances in biometric technology have pushed towards more robust and reliable systems. We aim to build systems that have low recognition errors and are less affected by variation in recording conditions. Recognition errors are often attributed to the usage of low quality biometric samples. Hence, there is a need to develop new intelligent techniques and strategies to automatically measure/quantify the quality of biometric image samples and if necessary restore image quality according to the need of the intended application. In this paper, we present no-reference image quality measures in the spatial domain that have impact on face recognition. The first is called symmetrical adaptive local quality index (SALQI) and the second is called middle halve (MH). Also, an adaptive strategy has been developed to select the best way to restore the image quality, called symmetrical adaptive histogram equalization (SAHE). The main benefits of using quality measures for adaptive strategy are: (1) avoidance of excessive unnecessary enhancement procedures that may cause undesired artifacts, and (2) reduced computational complexity which is essential for real time applications. We test the success of the proposed measures and adaptive approach for a wavelet-based face recognition system that uses the nearest neighborhood classifier. We shall demonstrate noticeable improvements in the performance of adaptive face recognition system over the corresponding non-adaptive scheme.

A Market-Based Approach to Multi-factory Scheduling

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Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

Paper-based microfluidic approach for surface-enhanced raman spectroscopy and highly reproducible detection of proteins beyond picomolar concentration.

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Saha, Arindam; Jana, Nikhil R

2015-01-14

Although microfluidic approach is widely used in various point of care diagnostics, its implementation in surface enhanced Raman spectroscopy (SERS)-based detection is challenging. This is because SERS signal depends on plasmonic nanoparticle aggregation induced generation of stable electromagnetic hot spots and in currently available microfluidic platform this condition is difficult to adapt. Here we show that SERS can be adapted using simple paper based microfluidic system where both the plasmonic nanomaterials and analyte are used in mobile phase. This approach allows analyte induced controlled particle aggregation and electromagnetic hot spot generation inside the microfluidic channel with the resultant SERS signal, which is highly reproducible and sensitive. This approach has been used for reproducible detection of protein in the pico to femtomolar concentration. Presented approach is simple, rapid, and cost-effective, and requires low sample volume. Method can be extended for SERS-based detection of other biomolecules.

Direct RNA-based detection of CTX-M β-lactamases in human blood samples.

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Stein, Claudia; Makarewicz, Oliwia; Pfeifer, Yvonne; Brandt, Christian; Pletz, Mathias W

2015-05-01

Bloodstream infections with ESBL-producers are associated with increased mortality, which is due to delayed appropriate treatment resulting in clinical failure. Current routine diagnostics for detection of bloodstream infections consists of blood culture followed by species identification and susceptibility testing. In attempts to improve and accelerate diagnostic procedures, PCR-based methods have been developed. These methods focus on species identification covering only a limited number of ESBL coding genes. Therefore, they fail to cover the steadily further evolving genetic diversity of clinically relevant β-lactamases. We have recently designed a fast and novel RNA targeting method to detect and specify CTX-M alleles from bacterial cultures, based on an amplification-pyrosequencing approach. We further developed this assay towards a diagnostic tool for clinical use and evaluated its sensitivity and specificity when applied directly to human blood samples. An optimized protocol for mRNA isolation allows detection of specific CTX-M groups from as little as 100 CFU/mL blood via reverse transcription, amplification, and pyrosequencing directly from human EDTA blood samples as well as from pre-incubated human blood cultures with a turnaround time for test results of <7 h. Copyright © 2015 Elsevier GmbH. All rights reserved.

Selecting Sample Preparation Workflows for Mass Spectrometry-Based Proteomic and Phosphoproteomic Analysis of Patient Samples with Acute Myeloid Leukemia.

Science.gov (United States)

Hernandez-Valladares, Maria; Aasebø, Elise; Selheim, Frode; Berven, Frode S; Bruserud, Øystein

2016-08-22

Global mass spectrometry (MS)-based proteomic and phosphoproteomic studies of acute myeloid leukemia (AML) biomarkers represent a powerful strategy to identify and confirm proteins and their phosphorylated modifications that could be applied in diagnosis and prognosis, as a support for individual treatment regimens and selection of patients for bone marrow transplant. MS-based studies require optimal and reproducible workflows that allow a satisfactory coverage of the proteome and its modifications. Preparation of samples for global MS analysis is a crucial step and it usually requires method testing, tuning and optimization. Different proteomic workflows that have been used to prepare AML patient samples for global MS analysis usually include a standard protein in-solution digestion procedure with a urea-based lysis buffer. The enrichment of phosphopeptides from AML patient samples has previously been carried out either with immobilized metal affinity chromatography (IMAC) or metal oxide affinity chromatography (MOAC). We have recently tested several methods of sample preparation for MS analysis of the AML proteome and phosphoproteome and introduced filter-aided sample preparation (FASP) as a superior methodology for the sensitive and reproducible generation of peptides from patient samples. FASP-prepared peptides can be further fractionated or IMAC-enriched for proteome or phosphoproteome analyses. Herein, we will review both in-solution and FASP-based sample preparation workflows and encourage the use of the latter for the highest protein and phosphorylation coverage and reproducibility.

Approaching near real-time biosensing: microfluidic microsphere based biosensor for real-time analyte detection.

Science.gov (United States)

Cohen, Noa; Sabhachandani, Pooja; Golberg, Alexander; Konry, Tania

2015-04-15

In this study we describe a simple lab-on-a-chip (LOC) biosensor approach utilizing well mixed microfluidic device and a microsphere-based assay capable of performing near real-time diagnostics of clinically relevant analytes such cytokines and antibodies. We were able to overcome the adsorption kinetics reaction rate-limiting mechanism, which is diffusion-controlled in standard immunoassays, by introducing the microsphere-based assay into well-mixed yet simple microfluidic device with turbulent flow profiles in the reaction regions. The integrated microsphere-based LOC device performs dynamic detection of the analyte in minimal amount of biological specimen by continuously sampling micro-liter volumes of sample per minute to detect dynamic changes in target analyte concentration. Furthermore we developed a mathematical model for the well-mixed reaction to describe the near real time detection mechanism observed in the developed LOC method. To demonstrate the specificity and sensitivity of the developed real time monitoring LOC approach, we applied the device for clinically relevant analytes: Tumor Necrosis Factor (TNF)-α cytokine and its clinically used inhibitor, anti-TNF-α antibody. Based on the reported results herein, the developed LOC device provides continuous sensitive and specific near real-time monitoring method for analytes such as cytokines and antibodies, reduces reagent volumes by nearly three orders of magnitude as well as eliminates the washing steps required by standard immunoassays. Copyright © 2014 Elsevier B.V. All rights reserved.

Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

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Lieven P C Verbeke

Full Text Available The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad

Sampling Approaches for Multi-Domain Internet Performance Measurement Infrastructures

Energy Technology Data Exchange (ETDEWEB)

Calyam, Prasad

2014-09-15

The next-generation of high-performance networks being developed in DOE communities are critical for supporting current and emerging data-intensive science applications. The goal of this project is to investigate multi-domain network status sampling techniques and tools to measure/analyze performance, and thereby provide “network awareness” to end-users and network operators in DOE communities. We leverage the infrastructure and datasets available through perfSONAR, which is a multi-domain measurement framework that has been widely deployed in high-performance computing and networking communities; the DOE community is a core developer and the largest adopter of perfSONAR. Our investigations include development of semantic scheduling algorithms, measurement federation policies, and tools to sample multi-domain and multi-layer network status within perfSONAR deployments. We validate our algorithms and policies with end-to-end measurement analysis tools for various monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. In addition, we develop a multi-domain architecture for an enterprise-specific perfSONAR deployment that can implement monitoring-objective based sampling and that adheres to any domain-specific measurement policies.

The anterior interhemispheric approach: a safe and effective approach to anterior skull base lesions.

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Mielke, Dorothee; Mayfrank, Lothar; Psychogios, Marios Nikos; Rohde, Veit

2014-04-01

Many approaches to the anterior skull base have been reported. Frequently used are the pterional, the unilateral or bilateral frontobasal, the supraorbital and the frontolateral approach. Recently, endoscopic transnasal approaches have become more popular. The benefits of each approach has to be weighted against its complications and limitations. The aim of this study was to investigate if the anterior interhemispheric approach (AIA) could be a safe and effective alternative approach to tumorous and non-tumorous lesions of the anterior skull base. We screened the operative records of all patients with an anterior skull base lesion undergoing transcranial surgery. We have used the AIA in 61 patients. These were exclusively patients with either olfactory groove meningioma (OGM) (n = 43), ethmoidal dural arteriovenous fistula (dAVF) ( n = 6) or frontobasal fractures of the anterior midline with cerebrospinal fluid (CSF) leakage ( n = 12). Patient records were evaluated concerning accessibility of the lesion, realization of surgical aims (complete tumor removal, dAVF obliteration, closure of the dural tear), and approach related complications. The use of the AIA exclusively in OGMs, ethmoidal dAVFs and midline frontobasal fractures indicated that we considered lateralized frontobasal lesions not suitable to be treated successfully. If restricted to these three pathologies, the AIA is highly effective and safe. The surgical aim (complete tumor removal, complete dAVF occlusion, no rhinorrhea) was achieved in all patients. The complication rate was 11.5 % (wound infection (n = 2; 3.2 %), contusion of the genu of the corpus callosum, subdural hygroma, epileptic seizure, anosmia and asymptomatic bleed into the tumor cavity (n = 1 each). Only the contusion of the corpus callosum was directly related to the approach (1.6 %). Olfaction, if present before surgery, was preserved in all patients, except one (1.6 %). The AIA is an effective and a safe approach

A Ligand-observed Mass Spectrometry Approach Integrated into the Fragment Based Lead Discovery Pipeline

Science.gov (United States)

Chen, Xin; Qin, Shanshan; Chen, Shuai; Li, Jinlong; Li, Lixin; Wang, Zhongling; Wang, Quan; Lin, Jianping; Yang, Cheng; Shui, Wenqing

2015-01-01

In fragment-based lead discovery (FBLD), a cascade combining multiple orthogonal technologies is required for reliable detection and characterization of fragment binding to the target. Given the limitations of the mainstream screening techniques, we presented a ligand-observed mass spectrometry approach to expand the toolkits and increase the flexibility of building a FBLD pipeline especially for tough targets. In this study, this approach was integrated into a FBLD program targeting the HCV RNA polymerase NS5B. Our ligand-observed mass spectrometry analysis resulted in the discovery of 10 hits from a 384-member fragment library through two independent screens of complex cocktails and a follow-up validation assay. Moreover, this MS-based approach enabled quantitative measurement of weak binding affinities of fragments which was in general consistent with SPR analysis. Five out of the ten hits were then successfully translated to X-ray structures of fragment-bound complexes to lay a foundation for structure-based inhibitor design. With distinctive strengths in terms of high capacity and speed, minimal method development, easy sample preparation, low material consumption and quantitative capability, this MS-based assay is anticipated to be a valuable addition to the repertoire of current fragment screening techniques. PMID:25666181

On incomplete sampling under birth-death models and connections to the sampling-based coalescent.

Science.gov (United States)

Stadler, Tanja

2009-11-07

The constant rate birth-death process is used as a stochastic model for many biological systems, for example phylogenies or disease transmission. As the biological data are usually not fully available, it is crucial to understand the effect of incomplete sampling. In this paper, we analyze the constant rate birth-death process with incomplete sampling. We derive the density of the bifurcation events for trees on n leaves which evolved under this birth-death-sampling process. This density is used for calculating prior distributions in Bayesian inference programs and for efficiently simulating trees. We show that the birth-death-sampling process can be interpreted as a birth-death process with reduced rates and complete sampling. This shows that joint inference of birth rate, death rate and sampling probability is not possible. The birth-death-sampling process is compared to the sampling-based population genetics model, the coalescent. It is shown that despite many similarities between these two models, the distribution of bifurcation times remains different even in the case of very large population sizes. We illustrate these findings on an Hepatitis C virus dataset from Egypt. We show that the transmission times estimates are significantly different-the widely used Gamma statistic even changes its sign from negative to positive when switching from the coalescent to the birth-death process.

Methodologies for the Extraction of Phenolic Compounds from Environmental Samples: New Approaches

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Cristina Mahugo Santana

2009-01-01

Full Text Available Phenolic derivatives are among the most important contaminants present in the environment. These compounds are used in several industrial processes to manufacture chemicals such as pesticides, explosives, drugs and dyes. They also are used in the bleaching process of paper manufacturing. Apart from these sources, phenolic compounds have substantial applications in agriculture as herbicides, insecticides and fungicides. However, phenolic compounds are not only generated by human activity, but they are also formed naturally, e.g., during the decomposition of leaves or wood. As a result of these applications, they are found in soils and sediments and this often leads to wastewater and ground water contamination. Owing to their high toxicity and persistence in the environment, both, the US Environmental Protection Agency (EPA and the European Union have included some of them in their lists of priority pollutants. Current standard methods of phenolic compounds analysis in water samples are based on liquid–liquid extraction (LLE while Soxhlet extraction is the most used technique for isolating phenols from solid matrices. However, these techniques require extensive cleanup procedures that are time-intensive and involve expensive and hazardous organic solvents, which are undesirable for health and disposal reasons. In the last years, the use of news methodologies such as solid-phase extraction (SPE and solid-phase microextraction (SPME have increased for the extraction of phenolic compounds from liquid samples. In the case of solid samples, microwave assisted extraction (MAE is demonstrated to be an efficient technique for the extraction of these compounds. In this work we review the developed methods in the extraction and determination of phenolic derivatives in different types of environmental matrices such as water, sediments and soils. Moreover, we present the new approach in the use of micellar media coupled with SPME process for the

Teaching Electronic Literacy A Concepts-Based Approach for School Library Media Specialists

CERN Document Server

Craver, Kathleen W

1997-01-01

School library media specialists will find this concepts-based approach to teaching electronic literacy an indispensable basic tool for instructing students and teachers. It provides step-by-step instruction on how to find and evaluate needed information from electronic databases and the Internet, how to formulate successful electronic search strategies and retrieve relevant results, and how to interpret and critically analyze search results. The chapters contain a suggested lesson plan and sample assignments for the school library media specialist to use in teaching electronic literacy skills

Quantifying Tip-Sample Interactions in Vacuum Using Cantilever-Based Sensors: An Analysis

Science.gov (United States)

Dagdeviren, Omur E.; Zhou, Chao; Altman, Eric I.; Schwarz, Udo D.

2018-04-01

Atomic force microscopy is an analytical characterization method that is able to image a sample's surface topography at high resolution while simultaneously probing a variety of different sample properties. Such properties include tip-sample interactions, the local measurement of which has gained much popularity in recent years. To this end, either the oscillation frequency or the oscillation amplitude and phase of the vibrating force-sensing cantilever are recorded as a function of tip-sample distance and subsequently converted into quantitative values for the force or interaction potential. Here, we theoretically and experimentally show that the force law obtained from such data acquired under vacuum conditions using the most commonly applied methods may deviate more than previously assumed from the actual interaction when the oscillation amplitude of the probe is of the order of the decay length of the force near the surface, which may result in a non-negligible error if correct absolute values are of importance. Caused by approximations made in the development of the mathematical reconstruction procedures, the related inaccuracies can be effectively suppressed by using oscillation amplitudes sufficiently larger than the decay length. To facilitate efficient data acquisition, we propose a technique that includes modulating the drive amplitude at a constant height from the surface while monitoring the oscillation amplitude and phase. Ultimately, such an amplitude-sweep-based force spectroscopy enables shorter data acquisition times and increased accuracy for quantitative chemical characterization compared to standard approaches that vary the tip-sample distance. An additional advantage is that since no feedback loop is active while executing the amplitude sweep, the force can be consistently recovered deep into the repulsive regime.

Poverty reduction Approaches in Kenya: Assessing the Usefulness of the Right Based Approach in Kenya

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Wambua Leonard Munyao, Ph.D

2013-06-01

Full Text Available While billions of dollars have been spent in development projects in least developed countries, poverty continues to increase. This study proposes human-rights based approach to poverty eradication. To this end, the study seeks to assess the key determinants of use of rights- based approaches to poverty reduction and it’s usefulness in Kenya with special reference to NGOs in Kibera. The study further high lights some of the basic skills of implementing the rights based approach to poverty reduction. The attempts to establish the proportion of NGOs applying rights based approach to poverty reduction in Kibera Division as well. The review of relevant literature has been undertaken and a field study done. The study is informed by a qualitative human rights framework.

Practice-Based Interdisciplinary Approach and Environmental Research

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Ranjan Kumar Datta

2017-03-01

Full Text Available Interdisciplinary researchers and educators, as community members, creators of knowledge, and environmental activists and practitioners, have a responsibility to build a bridge between community practice, academic scholarship, and professional contributions aimed at establishing environmental sustainability. In this paper, I focus on an undervalued area of environmental politics, practices, and often unarticulated assumptions which underlie human–environmental relations. This article challenges interdisciplinary studies that are not connected with practice by reconfiguring the meaning of a community-based, interdisciplinary approach. Drawing from works by Foucault, Latour, and Haraway, this paper first shows how to reconfigure the meaning of an interdisciplinary approach. Second, using Bourdieu and Brightman’s ethnographic studies as a framework, the paper situates practice as central to our efforts to deconstruct and replace current interdisciplinary initiatives with a practice-based approach. Through a practice-based interdisciplinary approach (PIA, environmental educators and researchers gain an awareness of and learn to make an investment in sustainable communities. As teams of environmental researchers practising in the local community, they are meaningfully involved with the community, with each other, and with the environment.

A spin column-free approach to sodium hydroxide-based glycan permethylation.

Science.gov (United States)

Hu, Yueming; Borges, Chad R

2017-07-24

Glycan permethylation was introduced as a tool to facilitate the study of glycans in 1903. Since that time, permethylation procedures have been continually modified to improve permethylation efficiency and qualitative applicability. Typically, however, either laborious preparation steps or cumbersome and uneconomical spin columns have been needed to obtain decent permethylation yields on small glycan samples. Here we describe a spin column-free (SCF) glycan permethylation procedure that is applicable to both O- and N-linked glycans and can be employed upstream to intact glycan analysis by MALDI-MS, ESI-MS, or glycan linkage analysis by GC-MS. The SCF procedure involves neutralization of NaOH beads by acidified phosphate buffer, which eliminates the risk of glycan oxidative degradation and avoids the use of spin columns. Optimization of the new permethylation procedure provided high permethylation efficiency for both hexose (>98%) and HexNAc (>99%) residues-yields which were comparable to (or better than) those of some widely-used spin column-based procedures. A light vs. heavy labelling approach was employed to compare intact glycan yields from a popular spin-column based approach to the SCF approach. Recovery of intact N-glycans was significantly better with the SCF procedure (p 0.75; p < 0.01). In summary, the SCF permethylation procedure expedites and economizes both intact glycan analysis and linkage analysis of glycans from whole biospecimens.

A spin column-free approach to sodium hydroxide-based glycan permethylation†

Science.gov (United States)

Hu, Yueming; Borges, Chad R.

2018-01-01

Glycan permethylation was introduced as a tool to facilitate the study of glycans in 1903. Since that time, permethylation procedures have been continually modified to improve permethylation efficiency and qualitative applicability. Typically, however, either laborious preparation steps or cumbersome and uneconomical spin columns have been needed to obtain decent permethylation yields on small glycan samples. Here we describe a spin column-free (SCF) glycan permethylation procedure that is applicable to both O- and N-linked glycans and can be employed upstream to intact glycan analysis by MALDI-MS, ESI-MS, or glycan linkage analysis by GC-MS. The SCF procedure involves neutralization of NaOH beads by acidified phosphate buffer, which eliminates the risk of glycan oxidative degradation and avoids the use of spin columns. Optimization of the new permethylation procedure provided high permethylation efficiency for both hexose (>98%) and HexNAc (>99%) residues—yields which were comparable to (or better than) those of some widely-used spin column-based procedures. A light vs. heavy labelling approach was employed to compare intact glycan yields from a popular spin-column based approach to the SCF approach. Recovery of intact N-glycans was significantly better with the SCF procedure (p 0.75; p < 0.01). In summary, the SCF permethylation procedure expedites and economizes both intact glycan analysis and linkage analysis of glycans from whole biospecimens. PMID:28635997

Sample-Based Extreme Learning Machine with Missing Data

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Hang Gao

2015-01-01

Full Text Available Extreme learning machine (ELM has been extensively studied in machine learning community during the last few decades due to its high efficiency and the unification of classification, regression, and so forth. Though bearing such merits, existing ELM algorithms cannot efficiently handle the issue of missing data, which is relatively common in practical applications. The problem of missing data is commonly handled by imputation (i.e., replacing missing values with substituted values according to available information. However, imputation methods are not always effective. In this paper, we propose a sample-based learning framework to address this issue. Based on this framework, we develop two sample-based ELM algorithms for classification and regression, respectively. Comprehensive experiments have been conducted in synthetic data sets, UCI benchmark data sets, and a real world fingerprint image data set. As indicated, without introducing extra computational complexity, the proposed algorithms do more accurate and stable learning than other state-of-the-art ones, especially in the case of higher missing ratio.

A non-iterative sampling approach using noise subspace projection for EIT

International Nuclear Information System (INIS)

Bellis, Cédric; Constantinescu, Andrei; Coquet, Thomas; Jaravel, Thomas; Lechleiter, Armin

2012-01-01

This study concerns the problem of the reconstruction of inclusions embedded in a conductive medium in the context of electrical impedance tomography (EIT), which is investigated within the framework of a non-iterative sampling approach. This type of identification strategy relies on the construction of a special indicator function that takes, roughly speaking, small values outside the inclusion and large values inside. Such a function is constructed in this paper from the projection of a fundamental singular solution onto the space spanned by the singular vectors associated with some of the smallest singular values of the data-to-measurement operator. The behavior of the novel indicator function is analyzed. For a subsequent implementation in a discrete setting, the quality of classical finite-dimensional approximations of the measurement operator is discussed. The robustness of this approach is also analyzed when only noisy spectral information is available. Finally, this identification method is implemented numerically and experimentally, and its efficiency is discussed on a set of, partly experimental, examples. (paper)

An improved approach for flow-based cloud point extraction.

Science.gov (United States)

Frizzarin, Rejane M; Rocha, Fábio R P

2014-04-11

Novel strategies are proposed to circumvent the main drawbacks of flow-based cloud point extraction (CPE). The surfactant-rich phase (SRP) was directly retained into the optical path of the spectrophotometric cell, thus avoiding its dilution previously to the measurement and yielding higher sensitivity. Solenoid micro-pumps were exploited to improve mixing by the pulsed flow and also to modulate the flow-rate for retention and removal of the SRP, thus avoiding the elution step, often carried out with organic solvents. The heat released and the increase of the salt concentration provided by an on-line neutralization reaction were exploited to induce the cloud point without an external heating device. These innovations were demonstrated by the spectrophotometric determination of iron, yielding a linear response from 10 to 200 μg L(-1) with a coefficient of variation of 2.3% (n=7). Detection limit and sampling rate were estimated at 5 μg L(-1) (95% confidence level) and 26 samples per hour, respectively. The enrichment factor was 8.9 and the procedure consumed only 6 μg of TAN and 390 μg of Triton X-114 per determination. At the 95% confidence level, the results obtained for freshwater samples agreed with the reference procedure and those obtained for digests of bovine muscle, rice flour, brown bread and tort lobster agreed with the certified reference values. The proposed procedure thus shows advantages in relation to previously proposed approaches for flow-based CPE, being a fast and environmental friendly alternative for on-line separation and pre-concentration. Copyright © 2014 Elsevier B.V. All rights reserved.

A hybrid agent-based approach for modeling microbiological systems.

Science.gov (United States)

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Sampling free energy surfaces as slices by combining umbrella sampling and metadynamics.

Science.gov (United States)

Awasthi, Shalini; Kapil, Venkat; Nair, Nisanth N

2016-06-15

Metadynamics (MTD) is a very powerful technique to sample high-dimensional free energy landscapes, and due to its self-guiding property, the method has been successful in studying complex reactions and conformational changes. MTD sampling is based on filling the free energy basins by biasing potentials and thus for cases with flat, broad, and unbound free energy wells, the computational time to sample them becomes very large. To alleviate this problem, we combine the standard Umbrella Sampling (US) technique with MTD to sample orthogonal collective variables (CVs) in a simultaneous way. Within this scheme, we construct the equilibrium distribution of CVs from biased distributions obtained from independent MTD simulations with umbrella potentials. Reweighting is carried out by a procedure that combines US reweighting and Tiwary-Parrinello MTD reweighting within the Weighted Histogram Analysis Method (WHAM). The approach is ideal for a controlled sampling of a CV in a MTD simulation, making it computationally efficient in sampling flat, broad, and unbound free energy surfaces. This technique also allows for a distributed sampling of a high-dimensional free energy surface, further increasing the computational efficiency in sampling. We demonstrate the application of this technique in sampling high-dimensional surface for various chemical reactions using ab initio and QM/MM hybrid molecular dynamics simulations. Further, to carry out MTD bias reweighting for computing forward reaction barriers in ab initio or QM/MM simulations, we propose a computationally affordable approach that does not require recrossing trajectories. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Joint importance sampling of low-order volumetric scattering

DEFF Research Database (Denmark)

Georgiev, Iliyan; Křivánek, Jaroslav; Hachisuka, Toshiya

2013-01-01

Central to all Monte Carlo-based rendering algorithms is the construction of light transport paths from the light sources to the eye. Existing rendering approaches sample path vertices incrementally when constructing these light transport paths. The resulting probability density is thus a product...... of the conditional densities of each local sampling step, constructed without explicit control over the form of the final joint distribution of the complete path. We analyze why current incremental construction schemes often lead to high variance in the presence of participating media, and reveal...... that such approaches are an unnecessary legacy inherited from traditional surface-based rendering algorithms. We devise joint importance sampling of path vertices in participating media to construct paths that explicitly account for the product of all scattering and geometry terms along a sequence of vertices instead...

PWR steam generator tubing sample library

International Nuclear Information System (INIS)

Anon.

1987-01-01

In order to compile the tubing sample library, two approaches were employed: (a) tubing sample replication by either chemical or mechanical means, based on field tube data and metallography reports for tubes already destructively examined; and (b) acquisition of field tubes removed from operating or retired steam generators. In addition, a unique mercury modeling concept is in use to guide the selection of replica samples. A compendium was compiled that summarizes field observations and morphologies of steam generator tube degradation types based on available NDE, destructive examinations, and field reports. This compendium was used in selecting candidate degradation types that were manufactured for inclusion in the tube library

A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples

Directory of Open Access Journals (Sweden)

Rígel Licier

2016-10-01

Full Text Available The proper handling of samples to be analyzed by mass spectrometry (MS can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine.

A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples.

Science.gov (United States)

Licier, Rígel; Miranda, Eric; Serrano, Horacio

2016-10-17

The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine.

A holistic passive integrative sampling approach for assessing the presence and potential impacts of waterborne environmental contaminants

Science.gov (United States)

Petty, J.D.; Huckins, J.N.; Alvarez, D.A.; Brumbaugh, W. G.; Cranor, W.L.; Gale, R.W.; Rastall, A.C.; Jones-Lepp, T. L.; Leiker, T.J.; Rostad, C. E.; Furlong, E.T.

2004-01-01

As an integral part of our continuing research in environmental quality assessment approaches, we have developed a variety of passive integrative sampling devices widely applicable for use in defining the presence and potential impacts of a broad array of contaminants. The semipermeable membrane device has gained widespread use for sampling hydrophobic chemicals from water and air, the polar organic chemical integrative sampler is applicable for sequestering waterborne hydrophilic organic chemicals, the stabilized liquid membrane device is used to integratively sample waterborne ionic metals, and the passive integrative mercury sampler is applicable for sampling vapor phase or dissolved neutral mercury species. This suite of integrative samplers forms the basis for a new passive sampling approach for assessing the presence and potential toxicological significance of a broad spectrum of environmental contaminants. In a proof-of-concept study, three of our four passive integrative samplers were used to assess the presence of a wide variety of contaminants in the waters of a constructed wetland, and to determine the effectiveness of the constructed wetland in removing contaminants. The wetland is used for final polishing of secondary-treatment municipal wastewater and the effluent is used as a source of water for a state wildlife area. Numerous contaminants, including organochlorine pesticides, polycyclic aromatic hydrocarbons, organophosphate pesticides, and pharmaceutical chemicals (e.g., ibuprofen, oxindole, etc.) were detected in the wastewater. Herein we summarize the results of the analysis of the field-deployed samplers and demonstrate the utility of this holistic approach.

Selecting Sample Preparation Workflows for Mass Spectrometry-Based Proteomic and Phosphoproteomic Analysis of Patient Samples with Acute Myeloid Leukemia

Directory of Open Access Journals (Sweden)

Maria Hernandez-Valladares

2016-08-01

Full Text Available Global mass spectrometry (MS-based proteomic and phosphoproteomic studies of acute myeloid leukemia (AML biomarkers represent a powerful strategy to identify and confirm proteins and their phosphorylated modifications that could be applied in diagnosis and prognosis, as a support for individual treatment regimens and selection of patients for bone marrow transplant. MS-based studies require optimal and reproducible workflows that allow a satisfactory coverage of the proteome and its modifications. Preparation of samples for global MS analysis is a crucial step and it usually requires method testing, tuning and optimization. Different proteomic workflows that have been used to prepare AML patient samples for global MS analysis usually include a standard protein in-solution digestion procedure with a urea-based lysis buffer. The enrichment of phosphopeptides from AML patient samples has previously been carried out either with immobilized metal affinity chromatography (IMAC or metal oxide affinity chromatography (MOAC. We have recently tested several methods of sample preparation for MS analysis of the AML proteome and phosphoproteome and introduced filter-aided sample preparation (FASP as a superior methodology for the sensitive and reproducible generation of peptides from patient samples. FASP-prepared peptides can be further fractionated or IMAC-enriched for proteome or phosphoproteome analyses. Herein, we will review both in-solution and FASP-based sample preparation workflows and encourage the use of the latter for the highest protein and phosphorylation coverage and reproducibility.

Methodological approaches based on business rules

Directory of Open Access Journals (Sweden)

Anca Ioana ANDREESCU

2008-01-01

Full Text Available Business rules and business processes are essential artifacts in defining the requirements of a software system. Business processes capture business behavior, while rules connect processes and thus control processes and business behavior. Traditionally, rules are scattered inside application code. This approach makes it very difficult to change rules and shorten the life cycle of the software system. Because rules change more quickly than the application itself, it is desirable to externalize the rules and move them outside the application. This paper analyzes and evaluates three well-known business rules approaches. It also outlines some critical factors that have to be taken into account in the decision to introduce business rules facilities in a software system. Based on the concept of explicit manipulation of business rules in a software system, the need for a general approach based on business rules is discussed.

SLS Navigation Model-Based Design Approach

Science.gov (United States)

Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

2018-01-01

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

Green approaches in sample preparation of bioanalytical samples prior to chromatographic analysis.

Science.gov (United States)

Filippou, Olga; Bitas, Dimitrios; Samanidou, Victoria

2017-02-01

Sample preparation is considered to be the most challenging step of the analytical procedure, since it has an effect on the whole analytical methodology, therefore it contributes significantly to the greenness or lack of it of the entire process. The elimination of the sample treatment steps, pursuing at the same time the reduction of the amount of the sample, strong reductions in consumption of hazardous reagents and energy also maximizing safety for operators and environment, the avoidance of the use of big amount of organic solvents, form the basis for greening sample preparation and analytical methods. In the last decade, the development and utilization of greener and sustainable microextraction techniques is an alternative to classical sample preparation procedures. In this review, the main green microextraction techniques (solid phase microextraction, stir bar sorptive extraction, hollow-fiber liquid phase microextraction, dispersive liquid - liquid microextraction, etc.) will be presented, with special attention to bioanalytical applications of these environment-friendly sample preparation techniques which comply with the green analytical chemistry principles. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimizing sampling approaches along ecological gradients

DEFF Research Database (Denmark)

Schweiger, Andreas; Irl, Severin D. H.; Steinbauer, Manuel

2016-01-01

1. Natural scientists and especially ecologists use manipulative experiments or field observations along gradients to differentiate patterns driven by processes from those caused by random noise. A well-conceived sampling design is essential for identifying, analysing and reporting underlying...... patterns in a statistically solid and reproducible manner, given the normal restrictions in labour, time and money. However, a technical guideline about an adequate sampling design to maximize prediction success under restricted resources is lacking. This study aims at developing such a solid...... and reproducible guideline for sampling along gradients in all fields of ecology and science in general. 2. We conducted simulations with artificial data for five common response types known in ecology, each represented by a simple function (no response, linear, exponential, symmetric unimodal and asymmetric...

Investigative Primary Science: A Problem-Based Learning Approach

Science.gov (United States)

Etherington, Matthew B.

2011-01-01

This study reports on the success of using a problem-based learning approach (PBL) as a pedagogical mode of learning open inquiry science within a traditional four-year undergraduate elementary teacher education program. In 2010, a problem-based learning approach to teaching primary science replaced the traditional content driven syllabus. During…

A Brief Introduction of Task-based Approach

Institute of Scientific and Technical Information of China (English)

王丹

2012-01-01

The task-based language teaching approach is one of the syllabus models that have been proposed in the last twenty years or so. Task-based syllabus represent a particular realization of communicative language teaching. Task-based teaching/learning helps develop students’ communicative competence, enabling them to communicate effectively in real communicating world and engage in interaction. The most active element in the process of the task-based teaching is the learner’ creativity. By exploiting this kind of creativity, learning can be made significantly more efficient and more interesting. It is well-known that the task-based teaching/learning have a rich potential for promoting successful second language learning than the traditional teaching/learning. Task-based approach is reflected not only in China but also in some other countries, such as America, Canada, Singapore, Hong Kong and son on.

Bayesian Sampling using Condition Indicators

DEFF Research Database (Denmark)

Faber, Michael H.; Sørensen, John Dalsgaard

2002-01-01

of condition indicators introduced by Benjamin and Cornell (1970) a Bayesian approach to quality control is formulated. The formulation is then extended to the case where the quality control is based on sampling of indirect information about the condition of the components, i.e. condition indicators...

Asymptotic Effectiveness of the Event-Based Sampling According to the Integral Criterion

Directory of Open Access Journals (Sweden)

Marek Miskowicz

2007-01-01

Full Text Available A rapid progress in intelligent sensing technology creates new interest in a development of analysis and design of non-conventional sampling schemes. The investigation of the event-based sampling according to the integral criterion is presented in this paper. The investigated sampling scheme is an extension of the pure linear send-on- delta/level-crossing algorithm utilized for reporting the state of objects monitored by intelligent sensors. The motivation of using the event-based integral sampling is outlined. The related works in adaptive sampling are summarized. The analytical closed-form formulas for the evaluation of the mean rate of event-based traffic, and the asymptotic integral sampling effectiveness, are derived. The simulation results verifying the analytical formulas are reported. The effectiveness of the integral sampling is compared with the related linear send-on-delta/level-crossing scheme. The calculation of the asymptotic effectiveness for common signals, which model the state evolution of dynamic systems in time, is exemplified.

New approach for risk based inspection of H2S based Process Plants

International Nuclear Information System (INIS)

Vinod, Gopika; Sharma, Pavan K.; Santosh, T.V.; Hari Prasad, M.; Vaze, K.K.

2014-01-01

Highlights: • Study looks into improving the consequence evaluation in risk based inspection. • Ways to revise the quantity factors used in qualitative approach. • New approach based on computational fluid dynamics along with probit mathematics. • Demonstrated this methodology along with a suitable case study for the said issue. - Abstract: Recent trend in risk informed and risk based approaches in life management issues have certainly put the focus on developing estimation methods for real risk. Idea of employing risk as an optimising measure for in-service inspection, termed as risk based inspection, was accepted in principle from late 80s. While applying risk based inspection, consequence of failure from each component needs to be assessed. Consequence evaluation in a Process Plant is a crucial task. It may be noted that, in general, the number of components to be considered for life management is very large and hence the consequence evaluation resulting from their failures (individually) is a laborious task. Screening of critical components is usually carried out using simplified qualitative approach, which primarily uses influence factors for categorisation. This necessitates logical formulation of influence factors and their ranges with a suitable technical basis for acceptance from regulators. This paper describes application of risk based inspection for H 2 S based Process Plant along with the approach devised for handling the influence factor related to the quantity of H 2 S released

Cross-Platform Mobile Application Development: A Pattern-Based Approach

Science.gov (United States)

2012-03-01

TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Cross-Platform Mobile Application Development: A Pattern-Based Approach 5. FUNDING...for public release; distribution is unlimited CROSS-PLATFORM MOBILE APPLICATION DEVELOPMENT: A PATTERN-BASED APPROACH Christian G. Acord...occurring design problems. We then discuss common approaches to mobile development, including common aspects of mobile application development, including

Isotope Enrichment Detection by Laser Ablation - Laser Absorption Spectrometry: Automated Environmental Sampling and Laser-Based Analysis for HEU Detection

International Nuclear Information System (INIS)

Anheier, Norman C.; Bushaw, Bruce A.

2010-01-01

The global expansion of nuclear power, and consequently the uranium enrichment industry, requires the development of new safeguards technology to mitigate proliferation risks. Current enrichment monitoring instruments exist that provide only yes/no detection of highly enriched uranium (HEU) production. More accurate accountancy measurements are typically restricted to gamma-ray and weight measurements taken in cylinder storage yards. Analysis of environmental and cylinder content samples have much higher effectiveness, but this approach requires onsite sampling, shipping, and time-consuming laboratory analysis and reporting. Given that large modern gaseous centrifuge enrichment plants (GCEPs) can quickly produce a significant quantity (SQ ) of HEU, these limitations in verification suggest the need for more timely detection of potential facility misuse. The Pacific Northwest National Laboratory (PNNL) is developing an unattended safeguards instrument concept, combining continuous aerosol particulate collection with uranium isotope assay, to provide timely analysis of enrichment levels within low enriched uranium facilities. This approach is based on laser vaporization of aerosol particulate samples, followed by wavelength tuned laser diode spectroscopy to characterize the uranium isotopic ratio through subtle differences in atomic absorption wavelengths. Environmental sampling (ES) media from an integrated aerosol collector is introduced into a small, reduced pressure chamber, where a focused pulsed laser vaporizes material from a 10 to 20-(micro)m diameter spot of the surface of the sampling media. The plume of ejected material begins as high-temperature plasma that yields ions and atoms, as well as molecules and molecular ions. We concentrate on the plume of atomic vapor that remains after the plasma has expanded and then cooled by the surrounding cover gas. Tunable diode lasers are directed through this plume and each isotope is detected by monitoring absorbance

Contingency inferences driven by base rates: Valid by sampling

Directory of Open Access Journals (Sweden)

Florian Kutzner

2011-04-01

Full Text Available Fiedler et al. (2009, reviewed evidence for the utilization of a contingency inference strategy termed pseudocontingencies (PCs. In PCs, the more frequent levels (and, by implication, the less frequent levels are assumed to be associated. PCs have been obtained using a wide range of task settings and dependent measures. Yet, the readiness with which decision makers rely on PCs is poorly understood. A computer simulation explored two potential sources of subjective validity of PCs. First, PCs are shown to perform above chance level when the task is to infer the sign of moderate to strong population contingencies from a sample of observations. Second, contingency inferences based on PCs and inferences based on cell frequencies are shown to partially agree across samples. Intriguingly, this criterion and convergent validity are by-products of random sampling error, highlighting the inductive nature of contingency inferences.

Knowledge-based biomedical word sense disambiguation: comparison of approaches

Directory of Open Access Journals (Sweden)

Aronson Alan R

2010-11-01

Full Text Available Abstract Background Word sense disambiguation (WSD algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be used to annotate the biomedical literature. Statistical learning approaches have produced good results, but the size of the UMLS makes the production of training data infeasible to cover all the domain. Methods We present research on existing WSD approaches based on knowledge bases, which complement the studies performed on statistical learning. We compare four approaches which rely on the UMLS Metathesaurus as the source of knowledge. The first approach compares the overlap of the context of the ambiguous word to the candidate senses based on a representation built out of the definitions, synonyms and related terms. The second approach collects training data for each of the candidate senses to perform WSD based on queries built using monosemous synonyms and related terms. These queries are used to retrieve MEDLINE citations. Then, a machine learning approach is trained on this corpus. The third approach is a graph-based method which exploits the structure of the Metathesaurus network of relations to perform unsupervised WSD. This approach ranks nodes in the graph according to their relative structural importance. The last approach uses the semantic types assigned to the concepts in the Metathesaurus to perform WSD. The context of the ambiguous word and semantic types of the candidate concepts are mapped to Journal Descriptors. These mappings are compared to decide among the candidate concepts. Results are provided estimating accuracy of the different methods on the WSD test collection available from the NLM. Conclusions We have found that the last approach achieves better results compared to the other methods. The graph-based approach, using the structure of the Metathesaurus network to estimate the relevance of the Metathesaurus concepts, does not perform well

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.

Directory of Open Access Journals (Sweden)

Simon Boitard

2016-03-01

Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

Biomarker- and similarity coefficient-based approaches to bacterial mixture characterization using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS).

Science.gov (United States)

Zhang, Lin; Smart, Sonja; Sandrin, Todd R

2015-11-05

MALDI-TOF MS profiling has been shown to be a rapid and reliable method to characterize pure cultures of bacteria. Currently, there is keen interest in using this technique to identify bacteria in mixtures. Promising results have been reported with two- or three-isolate model systems using biomarker-based approaches. In this work, we applied MALDI-TOF MS-based methods to a more complex model mixture containing six bacteria. We employed: 1) a biomarker-based approach that has previously been shown to be useful in identification of individual bacteria in pure cultures and simple mixtures and 2) a similarity coefficient-based approach that is routinely and nearly exclusively applied to identification of individual bacteria in pure cultures. Both strategies were developed and evaluated using blind-coded mixtures. With regard to the biomarker-based approach, results showed that most peaks in mixture spectra could be assigned to those found in spectra of each component bacterium; however, peaks shared by two isolates as well as peaks that could not be assigned to any individual component isolate were observed. For two-isolate blind-coded samples, bacteria were correctly identified using both similarity coefficient- and biomarker-based strategies, while for blind-coded samples containing more than two isolates, bacteria were more effectively identified using a biomarker-based strategy.

Constructing a justice model based on Sen's capability approach

OpenAIRE

Yüksel, Sevgi; Yuksel, Sevgi

2008-01-01

The thesis provides a possible justice model based on Sen's capability approach. For this goal, we first analyze the general structure of a theory of justice, identifying the main variables and issues. Furthermore, based on Sen (2006) and Kolm (1998), we look at 'transcendental' and 'comparative' approaches to justice and concentrate on the sufficiency condition for the comparative approach. Then, taking Rawls' theory of justice as a starting point, we present how Sen's capability approach em...

Descriptions of Sampling Practices Within Five Approaches to Qualitative Research in Education and the Health Sciences

Directory of Open Access Journals (Sweden)

Timothy C. Guetterman

2015-05-01

Full Text Available Although recommendations exist for determining qualitative sample sizes, the literature appears to contain few instances of research on the topic. Practical guidance is needed for determining sample sizes to conduct rigorous qualitative research, to develop proposals, and to budget resources. The purpose of this article is to describe qualitative sample size and sampling practices within published studies in education and the health sciences by research design: case study, ethnography, grounded theory methodology, narrative inquiry, and phenomenology. I analyzed the 51 most highly cited studies using predetermined content categories and noteworthy sampling characteristics that emerged. In brief, the findings revealed a mean sample size of 87. Less than half of the studies identified a sampling strategy. I include a description of findings by approach and recommendations for sampling to assist methodologists, reviewers, program officers, graduate students, and other qualitative researchers in understanding qualitative sampling practices in recent studies. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1502256

Feasibility assessment of a risk-based approach to technical specifications

International Nuclear Information System (INIS)

Atefi, B.; Gallagher, D.W.

1991-05-01

To assess the potential use of risk and reliability techniques for improving the effectiveness of the technical specifications to control plant operational risk, the Technical Specifications Branch of the Nuclear Regulatory Commission initiated an effort to identify and evaluate alternative risk-based approaches that could bring greater risk perspective to these requirements. In the first phase four alternative approaches were identified and their characteristics were analyzed. Among these, the risk-based approach to technical specifications is the most promising approach for controlling plant operational risk using technical specifications. The second phase of the study concentrated on detailed characteristics of the real time risk-based approach. It is concluded that a real time risk-based approach to technical specifications has the potential to improve both plant safety and availability. 33 figs., 5 figs., 6 tabs

Distance matrix-based approach to protein structure prediction.

Science.gov (United States)

Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

2009-03-01

Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

Soft magnetic properties of bulk amorphous Co-based samples

International Nuclear Information System (INIS)

Fuezer, J.; Bednarcik, J.; Kollar, P.

2006-01-01

Ball milling of melt-spun ribbons and subsequent compaction of the resulting powders in the supercooled liquid region were used to prepare disc shaped bulk amorphous Co-based samples. The several bulk samples have been prepared by hot compaction with subsequent heat treatment (500 deg C - 575 deg C). The influence of the consolidation temperature and follow-up heat treatment on the magnetic properties of bulk samples was investigated. The final heat treatment leads to decrease of the coercivity to the value between the 7.5 to 9 A/m (Authors)

Bayesian approach to MSD-based analysis of particle motion in live cells.

Science.gov (United States)

Monnier, Nilah; Guo, Syuan-Ming; Mori, Masashi; He, Jun; Lénárt, Péter; Bathe, Mark

2012-08-08

Quantitative tracking of particle motion using live-cell imaging is a powerful approach to understanding the mechanism of transport of biological molecules, organelles, and cells. However, inferring complex stochastic motion models from single-particle trajectories in an objective manner is nontrivial due to noise from sampling limitations and biological heterogeneity. Here, we present a systematic Bayesian approach to multiple-hypothesis testing of a general set of competing motion models based on particle mean-square displacements that automatically classifies particle motion, properly accounting for sampling limitations and correlated noise while appropriately penalizing model complexity according to Occam's Razor to avoid over-fitting. We test the procedure rigorously using simulated trajectories for which the underlying physical process is known, demonstrating that it chooses the simplest physical model that explains the observed data. Further, we show that computed model probabilities provide a reliability test for the downstream biological interpretation of associated parameter values. We subsequently illustrate the broad utility of the approach by applying it to disparate biological systems including experimental particle trajectories from chromosomes, kinetochores, and membrane receptors undergoing a variety of complex motions. This automated and objective Bayesian framework easily scales to large numbers of particle trajectories, making it ideal for classifying the complex motion of large numbers of single molecules and cells from high-throughput screens, as well as single-cell-, tissue-, and organism-level studies. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A mixture model-based approach to the clustering of microarray expression data.

Science.gov (United States)

McLachlan, G J; Bean, R W; Peel, D

2002-03-01

This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets. EMMIX-GENE is available at http://www.maths.uq.edu.au/~gjm/emmix-gene/

The Effectiveness of Problem-Based Learning Approach Based on Multiple Intelligences in Terms of Student’s Achievement, Mathematical Connection Ability, and Self-Esteem

Science.gov (United States)

Kartikasari, A.; Widjajanti, D. B.

2017-02-01

The aim of this study is to explore the effectiveness of learning approach using problem-based learning based on multiple intelligences in developing student’s achievement, mathematical connection ability, and self-esteem. This study is experimental research with research sample was 30 of Grade X students of MIA III MAN Yogyakarta III. Learning materials that were implemented consisting of trigonometry and geometry. For the purpose of this study, researchers designed an achievement test made up of 44 multiple choice questions with respectively 24 questions on the concept of trigonometry and 20 questions for geometry. The researcher also designed a connection mathematical test and self-esteem questionnaire that consisted of 7 essay questions on mathematical connection test and 30 items of self-esteem questionnaire. The learning approach said that to be effective if the proportion of students who achieved KKM on achievement test, the proportion of students who achieved a minimum score of high category on the results of both mathematical connection test and self-esteem questionnaire were greater than or equal to 70%. Based on the hypothesis testing at the significance level of 5%, it can be concluded that the learning approach using problem-based learning based on multiple intelligences was effective in terms of student’s achievement, mathematical connection ability, and self-esteem.

Interteaching: An Evidence-Based Approach to Instruction

Science.gov (United States)

Brown, Thomas Wade; Killingsworth, Kenneth; Alavosius, Mark P.

2014-01-01

This paper describes "interteaching" as an evidence-based method of instruction. Instructors often rely on more traditional approaches, such as lectures, as means to deliver instruction. Despite high usage, these methods are ineffective at achieving desirable academic outcomes. We discuss an innovative approach to delivering instruction…

Sample preparation combined with electroanalysis to improve simultaneous determination of antibiotics in animal derived food samples.

Science.gov (United States)

da Silva, Wesley Pereira; de Oliveira, Luiz Henrique; Santos, André Luiz Dos; Ferreira, Valdir Souza; Trindade, Magno Aparecido Gonçalves

2018-06-01

A procedure based on liquid-liquid extraction (LLE) and phase separation using magnetically stirred salt-induced high-temperature liquid-liquid extraction (PS-MSSI-HT-LLE) was developed to extract and pre-concentrate ciprofloxacin (CIPRO) and enrofloxacin (ENRO) from animal food samples before electroanalysis. Firstly, simple LLE was used to extract the fluoroquinolones (FQs) from animal food samples, in which dilution was performed to reduce interference effects to below a tolerable threshold. Then, adapted PS-MSSI-HT-LLE protocols allowed re-extraction and further pre-concentration of target analytes in the diluted acid samples for simultaneous electrochemical quantification at low concentration levels. To improve the peak separation, in simultaneous detection, a baseline-corrected second-order derivative approach was processed. These approaches allowed quantification of target FQs from animal food samples spiked at levels of 0.80 to 2.00 µmol L -1 in chicken meat, with recovery values always higher than 80.5%, as well as in milk samples spiked at 4.00 µmol L -1 , with recovery values close to 70.0%. Copyright © 2018 Elsevier Ltd. All rights reserved.

Considerations for potency equivalent calculations in the Ah receptor-based CALUX bioassay: normalization of superinduction results for improved sample potency estimation.

Science.gov (United States)

Baston, David S; Denison, Michael S

2011-02-15

The chemically activated luciferase expression (CALUX) system is a mechanistically based recombinant luciferase reporter gene cell bioassay used in combination with chemical extraction and clean-up methods for the detection and relative quantitation of 2,3,7,8-tetrachlorodibenzo-p-dioxin and related dioxin-like halogenated aromatic hydrocarbons in a wide variety of sample matrices. While sample extracts containing complex mixtures of chemicals can produce a variety of distinct concentration-dependent luciferase induction responses in CALUX cells, these effects are produced through a common mechanism of action (i.e. the Ah receptor (AhR)) allowing normalization of results and sample potency determination. Here we describe the diversity in CALUX response to PCDD/Fs from sediment and soil extracts and not only report the occurrence of superinduction of the CALUX bioassay, but we describe a mechanistically based approach for normalization of superinduction data that results in a more accurate estimation of the relative potency of such sample extracts. Copyright © 2010 Elsevier B.V. All rights reserved.

A Survey of Blue-Noise Sampling and Its Applications

KAUST Repository

Yan, Dongming; Guo, Jian-Wei; Wang, Bin; Zhang, Xiao-Peng; Wonka, Peter

2015-01-01

In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.

A Survey of Blue-Noise Sampling and Its Applications

KAUST Repository

Yan, Dongming

2015-05-05

In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.

Toward a risk-based approach to the assessment of the surety of information systems

Energy Technology Data Exchange (ETDEWEB)

Wyss, G.D.; Fletcher, S.K.; Halbgewachs, R.D.; Jansma, R.M.; Lim, J.J.; Murphy, M.; Sands, P.D.

1995-03-01

Traditional approaches to the assessment of information systems have treated system security, system reliability, data integrity, and application functionality as separate disciplines. However, each areas requirements and solutions have a profound impact on the successful implementation of the other areas. A better approach is to assess the ``surety`` of an information system, which is defined as ensuring the ``correct`` operation of an information system by incorporating appropriate levels of safety, functionality, confidentiality, availability, and integrity. Information surety examines the combined impact of design alternatives on all of these areas. We propose a modelling approach that combines aspects of fault trees and influence diagrams for assessing information surety requirements under a risk assessment framework. This approach allows tradeoffs to be based on quantitative importance measures such as risk reduction while maintaining the modelling flexibility of the influence diagram paradigm. This paper presents an overview of the modelling method and a sample application problem.

Cost-of-illness studies based on massive data: a prevalence-based, top-down regression approach.

Science.gov (United States)

Stollenwerk, Björn; Welchowski, Thomas; Vogl, Matthias; Stock, Stephanie

2016-04-01

Despite the increasing availability of routine data, no analysis method has yet been presented for cost-of-illness (COI) studies based on massive data. We aim, first, to present such a method and, second, to assess the relevance of the associated gain in numerical efficiency. We propose a prevalence-based, top-down regression approach consisting of five steps: aggregating the data; fitting a generalized additive model (GAM); predicting costs via the fitted GAM; comparing predicted costs between prevalent and non-prevalent subjects; and quantifying the stochastic uncertainty via error propagation. To demonstrate the method, it was applied to aggregated data in the context of chronic lung disease to German sickness funds data (from 1999), covering over 7.3 million insured. To assess the gain in numerical efficiency, the computational time of the innovative approach has been compared with corresponding GAMs applied to simulated individual-level data. Furthermore, the probability of model failure was modeled via logistic regression. Applying the innovative method was reasonably fast (19 min). In contrast, regarding patient-level data, computational time increased disproportionately by sample size. Furthermore, using patient-level data was accompanied by a substantial risk of model failure (about 80 % for 6 million subjects). The gain in computational efficiency of the innovative COI method seems to be of practical relevance. Furthermore, it may yield more precise cost estimates.

On the generalization of the hazard rate twisting-based simulation approach

KAUST Repository

Rached, Nadhir B.

2016-11-17

Estimating the probability that a sum of random variables (RVs) exceeds a given threshold is a well-known challenging problem. A naive Monte Carlo simulation is the standard technique for the estimation of this type of probability. However, this approach is computationally expensive, especially when dealing with rare events. An alternative approach is represented by the use of variance reduction techniques, known for their efficiency in requiring less computations for achieving the same accuracy requirement. Most of these methods have thus far been proposed to deal with specific settings under which the RVs belong to particular classes of distributions. In this paper, we propose a generalization of the well-known hazard rate twisting Importance Sampling-based approach that presents the advantage of being logarithmic efficient for arbitrary sums of RVs. The wide scope of applicability of the proposed method is mainly due to our particular way of selecting the twisting parameter. It is worth observing that this interesting feature is rarely satisfied by variance reduction algorithms whose performances were only proven under some restrictive assumptions. It comes along with a good efficiency, illustrated by some selected simulation results comparing the performance of the proposed method with some existing techniques.

Sampling guidelines for oral fluid-based surveys of group-housed animals.

Science.gov (United States)

Rotolo, Marisa L; Sun, Yaxuan; Wang, Chong; Giménez-Lirola, Luis; Baum, David H; Gauger, Phillip C; Harmon, Karen M; Hoogland, Marlin; Main, Rodger; Zimmerman, Jeffrey J

2017-09-01

Formulas and software for calculating sample size for surveys based on individual animal samples are readily available. However, sample size formulas are not available for oral fluids and other aggregate samples that are increasingly used in production settings. Therefore, the objective of this study was to develop sampling guidelines for oral fluid-based porcine reproductive and respiratory syndrome virus (PRRSV) surveys in commercial swine farms. Oral fluid samples were collected in 9 weekly samplings from all pens in 3 barns on one production site beginning shortly after placement of weaned pigs. Samples (n=972) were tested by real-time reverse-transcription PCR (RT-rtPCR) and the binary results analyzed using a piecewise exponential survival model for interval-censored, time-to-event data with misclassification. Thereafter, simulation studies were used to study the barn-level probability of PRRSV detection as a function of sample size, sample allocation (simple random sampling vs fixed spatial sampling), assay diagnostic sensitivity and specificity, and pen-level prevalence. These studies provided estimates of the probability of detection by sample size and within-barn prevalence. Detection using fixed spatial sampling was as good as, or better than, simple random sampling. Sampling multiple barns on a site increased the probability of detection with the number of barns sampled. These results are relevant to PRRSV control or elimination projects at the herd, regional, or national levels, but the results are also broadly applicable to contagious pathogens of swine for which oral fluid tests of equivalent performance are available. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Failure Probability Calculation Method Using Kriging Metamodel-based Importance Sampling Method

Energy Technology Data Exchange (ETDEWEB)

Lee, Seunggyu [Korea Aerospace Research Institue, Daejeon (Korea, Republic of); Kim, Jae Hoon [Chungnam Nat’l Univ., Daejeon (Korea, Republic of)

2017-05-15

The kernel density was determined based on sampling points obtained in a Markov chain simulation and was assumed to be an important sampling function. A Kriging metamodel was constructed in more detail in the vicinity of a limit state. The failure probability was calculated based on importance sampling, which was performed for the Kriging metamodel. A pre-existing method was modified to obtain more sampling points for a kernel density in the vicinity of a limit state. A stable numerical method was proposed to find a parameter of the kernel density. To assess the completeness of the Kriging metamodel, the possibility of changes in the calculated failure probability due to the uncertainty of the Kriging metamodel was calculated.

Adaptive list sequential sampling method for population-based observational studies

NARCIS (Netherlands)

Hof, Michel H.; Ravelli, Anita C. J.; Zwinderman, Aeilko H.

2014-01-01

In population-based observational studies, non-participation and delayed response to the invitation to participate are complications that often arise during the recruitment of a sample. When both are not properly dealt with, the composition of the sample can be different from the desired

An Event-driven, Value-based, Pull Systems Engineering Scheduling Approach

Science.gov (United States)

2012-03-01

combining a services approach to systems engineering with a kanban -based scheduling system. It provides the basis for validating the approach with...agent-based simulations. Keywords-systems engineering; systems engineering process; lean; kanban ; process simulation I. INTRODUCTION AND BACKGROUND...approaches [8], [9], we are investigating the use of flow-based pull scheduling techniques ( kanban systems) in a rapid response development

User-based and Cognitive Approaches to Knowledge Organization

DEFF Research Database (Denmark)

Hjørland, Birger

2013-01-01

’s PageRank are not based on the empirical studies of users. In knowledge organization, the Book House System is one example of a system based on user studies. In cognitive science the important WordNet database is claimed to be based on psychological research. This article considers such examples......In the 1970s and 1980s, forms of user-based and cognitive approaches to knowledge organization came to the forefront as part of the overall development in library and information science and in the broader society. The specific nature of userbased approaches is their basis in the empirical studies...

Stochastic bounded consensus tracking of leader-follower multi-agent systems with measurement noises based on sampled data with general sampling delay

International Nuclear Information System (INIS)

Wu Zhi-Hai; Peng Li; Xie Lin-Bo; Wen Ji-Wei

2013-01-01

In this paper we provide a unified framework for consensus tracking of leader-follower multi-agent systems with measurement noises based on sampled data with a general sampling delay. First, a stochastic bounded consensus tracking protocol based on sampled data with a general sampling delay is presented by employing the delay decomposition technique. Then, necessary and sufficient conditions are derived for guaranteeing leader-follower multi-agent systems with measurement noises and a time-varying reference state to achieve mean square bounded consensus tracking. The obtained results cover no sampling delay, a small sampling delay and a large sampling delay as three special cases. Last, simulations are provided to demonstrate the effectiveness of the theoretical results. (interdisciplinary physics and related areas of science and technology)

A new approach to the analysis of alpha spectra based on neural network techniques

Energy Technology Data Exchange (ETDEWEB)

Baeza, A.; Miranda, J. [LARUEX, Environmental Radioactivity Laboratory, Dept. Applied Physics, Faculty of Veterinary Science, University of Extremadura, Avda. Universidad s/n, 10003 Caceres (Spain); Guillen, J., E-mail: fguillen@unex.es [LARUEX, Environmental Radioactivity Laboratory, Dept. Applied Physics, Faculty of Veterinary Science, University of Extremadura, Avda. Universidad s/n, 10003 Caceres (Spain); Corbacho, J.A. [LARUEX, Environmental Radioactivity Laboratory, Dept. Applied Physics, Faculty of Veterinary Science, University of Extremadura, Avda. Universidad s/n, 10003 Caceres (Spain); Perez, R. [Dept. Technology of Computers and Communications, Polytechnics School, University of Extremadura, Avda. Universidad s/n, 10003 Caceres (Spain)

2011-10-01

The analysis of alpha spectra requires good radiochemical procedures in order to obtain well differentiated alpha peaks in the spectrum, and the easiest way to analyze them is by directly summing the counts obtained in the Regions of Interest (ROIs). However, the low-energy tails of the alpha peaks frequently make this simple approach unworkable because some peaks partially overlap. Many fitting procedures have been proposed to solve this problem, most of them based on semi-empirical mathematical functions that emulate the shape of a theoretical alpha peak. The main drawback of these methods is that the great number of fitting parameters used means that their physical meaning is obscure or completely lacking. We propose another approach-the application of an artificial neural network. Instead of fitting the experimental data to a mathematical function, the fit is carried out by an artificial neural network (ANN) that has previously been trained to model the shape of an alpha peak using as training patterns several polonium spectra obtained from actual samples analyzed in our laboratory. In this sense, the ANN is able to learn the shape of an actual alpha peak. We have designed such an ANN as a feed-forward multi-layer perceptron with supervised training based on a back-propagation algorithm. The fitting procedure is based on the experimental observables that are characteristic of alpha peaks-the number of counts of the maximum and several peak widths at different heights. Polonium isotope spectra were selected because the alpha peaks corresponding to {sup 208}Po, {sup 209}Po, and {sup 210}Po are monoenergetic and well separated. The uncertainties introduced by this fitting procedure were less than the counting uncertainties. This new approach was applied to the problem of resolving overlapping peaks. Firstly, a theoretical study was carried out by artificially overlapping alpha peaks from actual samples in order to test the ability of the ANN to resolve each peak

A new approach to the analysis of alpha spectra based on neural network techniques

International Nuclear Information System (INIS)

Baeza, A.; Miranda, J.; Guillen, J.; Corbacho, J.A.; Perez, R.

2011-01-01

The analysis of alpha spectra requires good radiochemical procedures in order to obtain well differentiated alpha peaks in the spectrum, and the easiest way to analyze them is by directly summing the counts obtained in the Regions of Interest (ROIs). However, the low-energy tails of the alpha peaks frequently make this simple approach unworkable because some peaks partially overlap. Many fitting procedures have been proposed to solve this problem, most of them based on semi-empirical mathematical functions that emulate the shape of a theoretical alpha peak. The main drawback of these methods is that the great number of fitting parameters used means that their physical meaning is obscure or completely lacking. We propose another approach-the application of an artificial neural network. Instead of fitting the experimental data to a mathematical function, the fit is carried out by an artificial neural network (ANN) that has previously been trained to model the shape of an alpha peak using as training patterns several polonium spectra obtained from actual samples analyzed in our laboratory. In this sense, the ANN is able to learn the shape of an actual alpha peak. We have designed such an ANN as a feed-forward multi-layer perceptron with supervised training based on a back-propagation algorithm. The fitting procedure is based on the experimental observables that are characteristic of alpha peaks-the number of counts of the maximum and several peak widths at different heights. Polonium isotope spectra were selected because the alpha peaks corresponding to 208 Po, 209 Po, and 210 Po are monoenergetic and well separated. The uncertainties introduced by this fitting procedure were less than the counting uncertainties. This new approach was applied to the problem of resolving overlapping peaks. Firstly, a theoretical study was carried out by artificially overlapping alpha peaks from actual samples in order to test the ability of the ANN to resolve each peak. Then, the ANN

Improving advanced cardiovascular life support skills in medical students: simulation-based education approach

Directory of Open Access Journals (Sweden)

Hamidreza Reihani

2015-01-01

Full Text Available Objective: In this trial, we intend to assess the effect of simulation-based education approach on advanced cardiovascular life support skills among medical students. Methods: Through convenient sampling method, 40 interns of Mashhad University of Medical Sciences in their emergency medicine rotation (from September to December 2012 participated in this study. Advanced Cardiovascular Life Support (ACLS workshops with pretest and post-test exams were performed. Workshops and checklists for pretest and post-test exams were designed according to the latest American Heart Association (AHA guidelines. Results: The total score of the students increased significantly after workshops (24.6 out of 100 to 78.6 out of 100. This demonstrates 53.9% improvement in the skills after the simulation-based education (P< 0.001. Also the mean score of each station had a significant improvement (P< 0.001. Conclusion: Pretests showed that interns had poor performance in practical clinical matters while their scientific knowledge, such as ECG interpretation was acceptable. The overall results of the study highlights that Simulation based-education approach is highly effective in Improving ACLS skills among medical students.

Hyperspectral Data for Mangrove Species Mapping: A Comparison of Pixel-Based and Object-Based Approach

Directory of Open Access Journals (Sweden)

Muhammad Kamal

2011-10-01

Full Text Available Visual image interpretation and digital image classification have been used to map and monitor mangrove extent and composition for decades. The presence of a high-spatial resolution hyperspectral sensor can potentially improve our ability to differentiate mangrove species. However, little research has explored the use of pixel-based and object-based approaches on high-spatial hyperspectral datasets for this purpose. This study assessed the ability of CASI-2 data for mangrove species mapping using pixel-based and object-based approaches at the mouth of the Brisbane River area, southeast Queensland, Australia. Three mapping techniques used in this study: spectral angle mapper (SAM and linear spectral unmixing (LSU for the pixel-based approaches, and multi-scale segmentation for the object-based image analysis (OBIA. The endmembers for the pixel-based approach were collected based on existing vegetation community map. Nine targeted classes were mapped in the study area from each approach, including three mangrove species: Avicennia marina, Rhizophora stylosa, and Ceriops australis. The mapping results showed that SAM produced accurate class polygons with only few unclassified pixels (overall accuracy 69%, Kappa 0.57, the LSU resulted in a patchy polygon pattern with many unclassified pixels (overall accuracy 56%, Kappa 0.41, and the object-based mapping produced the most accurate results (overall accuracy 76%, Kappa 0.67. Our results demonstrated that the object-based approach, which combined a rule-based and nearest-neighbor classification method, was the best classifier to map mangrove species and its adjacent environments.

Managing projects a team-based approach

CERN Document Server

Brown, Karen A

2010-01-01

Students today are likely to be assigned to project teams or to be project managers almost immediately in their first job. Managing Projects: A Team-Based Approach was written for a wide range of stakeholders, including project managers, project team members, support personnel, functional mangers who provide resources for projects, project customers (and customer representatives), project sponsors, project subcontractors, and anyone who plays a role in the project delivery process. The need for project management is on the rise as product life cycles compress, demand for IT systems increases, and business takes on an increasingly global character. This book adds to the project management knowledge base in a way that fills an unmet need—it shows how teams can apply many of the standard project management tools, as well as several tools that are relatively new to the field. Managing Projects: A Team-Based Approach offers the academic rigor found in most textbooks along with the practical attributes often foun...

Modern survey sampling

CERN Document Server

Chaudhuri, Arijit

2014-01-01

Exposure to SamplingAbstract Introduction Concepts of Population, Sample, and SamplingInitial RamificationsAbstract Introduction Sampling Design, Sampling SchemeRandom Numbers and Their Uses in Simple RandomSampling (SRS)Drawing Simple Random Samples with and withoutReplacementEstimation of Mean, Total, Ratio of Totals/Means:Variance and Variance EstimationDetermination of Sample SizesA.2 Appendix to Chapter 2 A.More on Equal Probability Sampling A.Horvitz-Thompson EstimatorA.SufficiencyA.LikelihoodA.Non-Existence Theorem More Intricacies Abstract Introduction Unequal Probability Sampling StrategiesPPS Sampling Exploring Improved WaysAbstract Introduction Stratified Sampling Cluster SamplingMulti-Stage SamplingMulti-Phase Sampling: Ratio and RegressionEstimationviiviii ContentsControlled SamplingModeling Introduction Super-Population ModelingPrediction Approach Model-Assisted Approach Bayesian Methods Spatial SmoothingSampling on Successive Occasions: Panel Rotation Non-Response and Not-at-Homes Weighting Adj...

An Image-Based Finite Element Approach for Simulating Viscoelastic Response of Asphalt Mixture

Directory of Open Access Journals (Sweden)

Wenke Huang

2016-01-01

Full Text Available This paper presents an image-based micromechanical modeling approach to predict the viscoelastic behavior of asphalt mixture. An improved image analysis technique based on the OTSU thresholding operation was employed to reduce the beam hardening effect in X-ray CT images. We developed a voxel-based 3D digital reconstruction model of asphalt mixture with the CT images after being processed. In this 3D model, the aggregate phase and air void were considered as elastic materials while the asphalt mastic phase was considered as linear viscoelastic material. The viscoelastic constitutive model of asphalt mastic was implemented in a finite element code using the ABAQUS user material subroutine (UMAT. An experimental procedure for determining the parameters of the viscoelastic constitutive model at a given temperature was proposed. To examine the capability of the model and the accuracy of the parameter, comparisons between the numerical predictions and the observed laboratory results of bending and compression tests were conducted. Finally, the verified digital sample of asphalt mixture was used to predict the asphalt mixture viscoelastic behavior under dynamic loading and creep-recovery loading. Simulation results showed that the presented image-based digital sample may be appropriate for predicting the mechanical behavior of asphalt mixture when all the mechanical properties for different phases became available.

An introduction to statistical computing a simulation-based approach

CERN Document Server

Voss, Jochen

2014-01-01

A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems.  Sampling-based simulation techniques are now an invaluable tool for exploring statistical models.  This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods.  It also includes some advanced met

Trait-based approaches in the analysis of stream fish communities

Science.gov (United States)

Frimpong, Emmanuel; Angermeier, Paul

2010-01-01

Species traits are used to study the functional organization of fish communities for a range of reasons, from simply reducing data dimensionality to providing mechanistic explanations for observed variation in communities. Ecological and life history traits have been used to understand the basic ecology of fishes and predict (1) species and community responses to habitat and climate alteration, and (2) species extinction, species invasion, and community homogenization. Many approaches in this arena have been developed during the past three decades, but they often have not been integrated with related ecological concepts or subdisciplines, which has led to confusion in terminology. We review 102 studies of species traits and then summarize patterns in traits being used and questions being addressed with trait-based approaches. Overall, studies of fish–habitat relationships that apply habitat templates and hierarchical filters dominate our sample; the most frequently used traits are related to feeding. We define and show the relationships among key terms such as fundamental and realized niches; functional traits, performance, and fitness; tactic, trait-state, syndromes, and strategies; and guilds and functional groups. We propose accelerating research to (1) quantify trait plasticity, (2) identify traits useful for testing ecological hypotheses, (3) model habitat and biotic interactions in communities while explicitly accounting for phylogenetic relationships, (4) explore how traits control community assembly, and (5) document the importance of traits in fish– community responses to anthropogenic change and in delivering ecosystem services. Further synthesis of these topics is still needed to develop concepts, models, and principles that can unify the disparate approaches taken in trait-based analysis of fish communities, link fish community ecology to general community ecology, and inform sustainable management of ecosystems.

Adaptive sampling strategies with high-throughput molecular dynamics

Science.gov (United States)

Clementi, Cecilia

Despite recent significant hardware and software developments, the complete thermodynamic and kinetic characterization of large macromolecular complexes by molecular simulations still presents significant challenges. The high dimensionality of these systems and the complexity of the associated potential energy surfaces (creating multiple metastable regions connected by high free energy barriers) does not usually allow to adequately sample the relevant regions of their configurational space by means of a single, long Molecular Dynamics (MD) trajectory. Several different approaches have been proposed to tackle this sampling problem. We focus on the development of ensemble simulation strategies, where data from a large number of weakly coupled simulations are integrated to explore the configurational landscape of a complex system more efficiently. Ensemble methods are of increasing interest as the hardware roadmap is now mostly based on increasing core counts, rather than clock speeds. The main challenge in the development of an ensemble approach for efficient sampling is in the design of strategies to adaptively distribute the trajectories over the relevant regions of the systems' configurational space, without using any a priori information on the system global properties. We will discuss the definition of smart adaptive sampling approaches that can redirect computational resources towards unexplored yet relevant regions. Our approaches are based on new developments in dimensionality reduction for high dimensional dynamical systems, and optimal redistribution of resources. NSF CHE-1152344, NSF CHE-1265929, Welch Foundation C-1570.

Automated sampling and control of gaseous simulations

KAUST Repository

Huang, Ruoguan; Keyser, John

2013-01-01

In this work, we describe a method that automates the sampling and control of gaseous fluid simulations. Several recent approaches have provided techniques for artists to generate high-resolution simulations based on a low-resolution simulation

Automated Prediction of Catalytic Mechanism and Rate Law Using Graph-Based Reaction Path Sampling.

Science.gov (United States)

Habershon, Scott

2016-04-12

In a recent article [ J. Chem. Phys. 2015 , 143 , 094106 ], we introduced a novel graph-based sampling scheme which can be used to generate chemical reaction paths in many-atom systems in an efficient and highly automated manner. The main goal of this work is to demonstrate how this approach, when combined with direct kinetic modeling, can be used to determine the mechanism and phenomenological rate law of a complex catalytic cycle, namely cobalt-catalyzed hydroformylation of ethene. Our graph-based sampling scheme generates 31 unique chemical products and 32 unique chemical reaction pathways; these sampled structures and reaction paths enable automated construction of a kinetic network model of the catalytic system when combined with density functional theory (DFT) calculations of free energies and resultant transition-state theory rate constants. Direct simulations of this kinetic network across a range of initial reactant concentrations enables determination of both the reaction mechanism and the associated rate law in an automated fashion, without the need for either presupposing a mechanism or making steady-state approximations in kinetic analysis. Most importantly, we find that the reaction mechanism which emerges from these simulations is exactly that originally proposed by Heck and Breslow; furthermore, the simulated rate law is also consistent with previous experimental and computational studies, exhibiting a complex dependence on carbon monoxide pressure. While the inherent errors of using DFT simulations to model chemical reactivity limit the quantitative accuracy of our calculated rates, this work confirms that our automated simulation strategy enables direct analysis of catalytic mechanisms from first principles.

Knowledge-based approach to video content classification

Science.gov (United States)

Chen, Yu; Wong, Edward K.

2001-01-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

Observer-Based Stabilization of Spacecraft Rendezvous with Variable Sampling and Sensor Nonlinearity

Directory of Open Access Journals (Sweden)

Zhuoshi Li

2013-01-01

Full Text Available This paper addresses the observer-based control problem of spacecraft rendezvous with nonuniform sampling period. The relative dynamic model is based on the classical Clohessy-Wiltshire equation, and sensor nonlinearity and sampling are considered together in a unified framework. The purpose of this paper is to perform an observer-based controller synthesis by using sampled and saturated output measurements, such that the resulting closed-loop system is exponentially stable. A time-dependent Lyapunov functional is developed which depends on time and the upper bound of the sampling period and also does not grow along the input update times. The controller design problem is solved in terms of the linear matrix inequality method, and the obtained results are less conservative than using the traditional Lyapunov functionals. Finally, a numerical simulation example is built to show the validity of the developed sampled-data control strategy.

A quantitative approach to measure road network information based on edge diversity

Science.gov (United States)

Wu, Xun; Zhang, Hong; Lan, Tian; Cao, Weiwei; He, Jing

2015-12-01

The measure of map information has been one of the key issues in assessing cartographic quality and map generalization algorithms. It is also important for developing efficient approaches to transfer geospatial information. Road network is the most common linear object in real world. Approximately describe road network information will benefit road map generalization, navigation map production and urban planning. Most of current approaches focused on node diversities and supposed that all the edges are the same, which is inconsistent to real-life condition, and thus show limitations in measuring network information. As real-life traffic flow are directed and of different quantities, the original undirected vector road map was first converted to a directed topographic connectivity map. Then in consideration of preferential attachment in complex network study and rich-club phenomenon in social network, the from and to weights of each edge are assigned. The from weight of a given edge is defined as the connectivity of its end node to the sum of the connectivities of all the neighbors of the from nodes of the edge. After getting the from and to weights of each edge, edge information, node information and the whole network structure information entropies could be obtained based on information theory. The approach has been applied to several 1 square mile road network samples. Results show that information entropies based on edge diversities could successfully describe the structural differences of road networks. This approach is a complementarity to current map information measurements, and can be extended to measure other kinds of geographical objects.

Sample preparation prior to the LC-MS-based metabolomics/metabonomics of blood-derived samples.

Science.gov (United States)

Gika, Helen; Theodoridis, Georgios

2011-07-01

Blood represents a very important biological fluid and has been the target of continuous and extensive research for diagnostic, or health and drug monitoring reasons. Recently, metabonomics/metabolomics have emerged as a new and promising 'omics' platform that shows potential in biomarker discovery, especially in areas such as disease diagnosis, assessment of drug efficacy or toxicity. Blood is collected in various establishments in conditions that are not standardized. Next, the samples are prepared and analyzed using different methodologies or tools. When targeted analysis of key molecules (e.g., a drug or its metabolite[s]) is the aim, enforcement of certain measures or additional analyses may correct and harmonize these discrepancies. In omics fields such as those performed by holistic analytical approaches, no such rules or tools are available. As a result, comparison or correlation of results or data fusion becomes impractical. However, it becomes evident that such obstacles should be overcome in the near future to allow for large-scale studies that involve the assaying of samples from hundreds of individuals. In this case the effect of sample handling and preparation becomes very serious, in order to avoid wasting months of work from experts and expensive instrument time. The present review aims to cover the different methodologies applied to the pretreatment of blood prior to LC-MS metabolomic/metabonomic studies. The article tries to critically compare the methods and highlight issues that need to be addressed.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications.

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Elias Chaibub Neto

Full Text Available In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson's sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling.

Structural design principles of complex bird songs: a network-based approach.

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Kazutoshi Sasahara

Full Text Available Bird songs are acoustic communication signals primarily used in male-male aggression and in male-female attraction. These are often monotonous patterns composed of a few phrases, yet some birds have extremely complex songs with a large phrase repertoire, organized in non-random fashion with discernible patterns. Since structure is typically associated with function, the structures of complex bird songs provide important clues to the evolution of animal communication systems. Here we propose an efficient network-based approach to explore structural design principles of complex bird songs, in which the song networks--transition relationships among different phrases and the related structural measures--are employed. We demonstrate how this approach works with an example using California Thrasher songs, which are sequences of highly varied phrases delivered in succession over several minutes. These songs display two distinct features: a large phrase repertoire with a 'small-world' architecture, in which subsets of phrases are highly grouped and linked with a short average path length; and a balanced transition diversity amongst phrases, in which deterministic and non-deterministic transition patterns are moderately mixed. We explore the robustness of this approach with variations in sample size and the amount of noise. Our approach enables a more quantitative study of global and local structural properties of complex bird songs than has been possible to date.

Representativeness of two sampling procedures for an internet intervention targeting cancer-related distress: a comparison of convenience and registry samples.

Science.gov (United States)

Owen, Jason E; Bantum, Erin O'Carroll; Criswell, Kevin; Bazzo, Julie; Gorlick, Amanda; Stanton, Annette L

2014-08-01

Internet interventions often rely on convenience sampling, yet convenience samples may differ in important ways from systematic recruitment approaches. The purpose of this study was to evaluate potential demographic, medical, and psychosocial differences between Internet-recruited and registry-recruited cancer survivors in an Internet-based intervention. Participants were recruited from a cancer registry (n = 80) and via broad Internet outreach efforts (n = 160). Participants completed a set of self-report questionnaires, and both samples were compared to a population-based sample of cancer survivors (n = 5,150). The Internet sample was younger, better educated, more likely to be female, had longer time since diagnosis, and had more advanced stage of disease (p's sample was over-represented by men and those with prostate or other cancer types (p's sample also exhibited lower quality of life and social support and greater mood disturbance (p's convenience and systematic samples differ has important implications for external validity and potential for dissemination of Internet-based interventions.

Use of Complementary Approaches to Imaging Biomolecules and Endogenous and Exogenous Trace Elements and Nanoparticles in Biological Samples

Science.gov (United States)

Brown, Koshonna Dinettia

X-ray Fluorescence Microscopy (XFM) is a useful technique for study of biological samples. XFM was used to map and quantify endogenous biological elements as well as exogenous materials in biological samples, such as the distribution of titanium dioxide (TiO2) nanoparticles. TiO 2 nanoparticles are produced for many different purposes, including development of therapeutic and diagnostic particles for cancer detection and treatment, drug delivery, and induction of DNA breaks. Delivery of such nanoparticles can be targeted to specific cells and subcellular structures. In this work, we develop two novel approaches to stain TiO2 nanoparticles for optical microscopy and to confirm that staining by XFM. The first approach utilizes fluorescent biotin and fluorescent streptavidin to label the nanoparticles before and after cellular uptake; the second approach is based on the copper-catalyzed azide-alkyne cycloaddition, the so-called CLICK chemistry, for labeling of azide conjugated TiO2 nanoparticles with "clickable" dyes such as alkyne Alexa Fluor dyes with a high fluorescent yield. To confirm that the optical fluorescence signals of nanoparticles stained in situ match the distribution of the Ti element, we used high resolution synchrotron X-Ray Fluorescence Microscopy (XFM) using the Bionanoprobe instrument at the Advanced Photon Source at Argonne National Laboratory. Titanium-specific X-ray fluorescence showed excellent overlap with the location of Alexa Fluor optical fluorescence detected by confocal microscopy. In this work XFM was also used to investigate native elemental differences between two different types of head and neck cancer, one associated with human papilloma virus infection, the other virus free. Future work may see a cross between these themes, for example, exploration of TiO2 nanoparticles as anticancer treatment for these two different types of head and neck cancer.

Interactive Fuzzy Goal Programming approach in multi-response stratified sample surveys

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Gupta Neha

2016-01-01

Full Text Available In this paper, we applied an Interactive Fuzzy Goal Programming (IFGP approach with linear, exponential and hyperbolic membership functions, which focuses on maximizing the minimum membership values to determine the preferred compromise solution for the multi-response stratified surveys problem, formulated as a Multi- Objective Non Linear Programming Problem (MONLPP, and by linearizing the nonlinear objective functions at their individual optimum solution, the problem is approximated to an Integer Linear Programming Problem (ILPP. A numerical example based on real data is given, and comparison with some existing allocations viz. Cochran’s compromise allocation, Chatterjee’s compromise allocation and Khowaja’s compromise allocation is made to demonstrate the utility of the approach.

Development of Scientific Approach Based on Discovery Learning Module

Science.gov (United States)

Ellizar, E.; Hardeli, H.; Beltris, S.; Suharni, R.

2018-04-01

Scientific Approach is a learning process, designed to make the students actively construct their own knowledge through stages of scientific method. The scientific approach in learning process can be done by using learning modules. One of the learning model is discovery based learning. Discovery learning is a learning model for the valuable things in learning through various activities, such as observation, experience, and reasoning. In fact, the students’ activity to construct their own knowledge were not optimal. It’s because the available learning modules were not in line with the scientific approach. The purpose of this study was to develop a scientific approach discovery based learning module on Acid Based, also on electrolyte and non-electrolyte solution. The developing process of this chemistry modules use the Plomp Model with three main stages. The stages are preliminary research, prototyping stage, and the assessment stage. The subject of this research was the 10th and 11th Grade of Senior High School students (SMAN 2 Padang). Validation were tested by the experts of Chemistry lecturers and teachers. Practicality of these modules had been tested through questionnaire. The effectiveness had been tested through experimental procedure by comparing student achievement between experiment and control groups. Based on the findings, it can be concluded that the developed scientific approach discovery based learning module significantly improve the students’ learning in Acid-based and Electrolyte solution. The result of the data analysis indicated that the chemistry module was valid in content, construct, and presentation. Chemistry module also has a good practicality level and also accordance with the available time. This chemistry module was also effective, because it can help the students to understand the content of the learning material. That’s proved by the result of learning student. Based on the result can conclude that chemistry module based on

Perfluoroalkyl substances in aquatic environment-comparison of fish and passive sampling approaches.

Science.gov (United States)

Cerveny, Daniel; Grabic, Roman; Fedorova, Ganna; Grabicova, Katerina; Turek, Jan; Kodes, Vit; Golovko, Oksana; Zlabek, Vladimir; Randak, Tomas

2016-01-01

The concentrations of seven perfluoroalkyl substances (PFASs) were investigated in 36 European chub (Squalius cephalus) individuals from six localities in the Czech Republic. Chub muscle and liver tissue were analysed at all sampling sites. In addition, analyses of 16 target PFASs were performed in Polar Organic Chemical Integrative Samplers (POCISs) deployed in the water at the same sampling sites. We evaluated the possibility of using passive samplers as a standardized method for monitoring PFAS contamination in aquatic environments and the mutual relationships between determined concentrations. Only perfluorooctane sulphonate was above the LOQ in fish muscle samples and 52% of the analysed fish individuals exceeded the Environmental Quality Standard for water biota. Fish muscle concentration is also particularly important for risk assessment of fish consumers. The comparison of fish tissue results with published data showed the similarity of the Czech results with those found in Germany and France. However, fish liver analysis and the passive sampling approach resulted in different fish exposure scenarios. The total concentration of PFASs in fish liver tissue was strongly correlated with POCIS data, but pollutant patterns differed between these two matrices. The differences could be attributed to the metabolic activity of the living organism. In addition to providing a different view regarding the real PFAS cocktail to which the fish are exposed, POCISs fulfil the Three Rs strategy (replacement, reduction, and refinement) in animal testing. Copyright © 2015 Elsevier Inc. All rights reserved.

The Utility of Synthetic-based Approach of Writing among Iranian EFL Learners

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Nasrin Derakhshandeh

2014-05-01

Full Text Available The present study intends to examine the utility of synthetic-based approach versus traditional approaches of writing among Iranian EFL learners. To achieve this end, ninety students at Upper-Intermediate level were randomly chosen from the English population of Kish and Gooyesh English Institutes. The students were divided into three groups. Group1 was asked to do a writing task based on product-based approach. A writing task based on process-oriented approach was administered to Group2; later on, Group 3 was invited to write a composition to assess their performance based on synthetic-based approach. The result of the t test and two-way ANOVA revealed that the students performed better in writing using synthetic approach rather than traditional approaches to writing.

Accounting for detectability in fish distribution models: an approach based on time-to-first-detection

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Mário Ferreira

2015-12-01

Full Text Available Imperfect detection (i.e., failure to detect a species when the species is present is increasingly recognized as an important source of uncertainty and bias in species distribution modeling. Although methods have been developed to solve this problem by explicitly incorporating variation in detectability in the modeling procedure, their use in freshwater systems remains limited. This is probably because most methods imply repeated sampling (≥ 2 of each location within a short time frame, which may be impractical or too expensive in most studies. Here we explore a novel approach to control for detectability based on the time-to-first-detection, which requires only a single sampling occasion and so may find more general applicability in freshwaters. The approach uses a Bayesian framework to combine conventional occupancy modeling with techniques borrowed from parametric survival analysis, jointly modeling factors affecting the probability of occupancy and the time required to detect a species. To illustrate the method, we modeled large scale factors (elevation, stream order and precipitation affecting the distribution of six fish species in a catchment located in north-eastern Portugal, while accounting for factors potentially affecting detectability at sampling points (stream depth and width. Species detectability was most influenced by depth and to lesser extent by stream width and tended to increase over time for most species. Occupancy was consistently affected by stream order, elevation and annual precipitation. These species presented a widespread distribution with higher uncertainty in tributaries and upper stream reaches. This approach can be used to estimate sampling efficiency and provide a practical framework to incorporate variations in the detection rate in fish distribution models.

A support vector density-based importance sampling for reliability assessment

International Nuclear Information System (INIS)

Dai, Hongzhe; Zhang, Hao; Wang, Wei

2012-01-01

An importance sampling method based on the adaptive Markov chain simulation and support vector density estimation is developed in this paper for efficient structural reliability assessment. The methodology involves the generation of samples that can adaptively populate the important region by the adaptive Metropolis algorithm, and the construction of importance sampling density by support vector density. The use of the adaptive Metropolis algorithm may effectively improve the convergence and stability of the classical Markov chain simulation. The support vector density can approximate the sampling density with fewer samples in comparison to the conventional kernel density estimation. The proposed importance sampling method can effectively reduce the number of structural analysis required for achieving a given accuracy. Examples involving both numerical and practical structural problems are given to illustrate the application and efficiency of the proposed methodology.

Ethics education for health professionals: a values based approach.

Science.gov (United States)

Godbold, Rosemary; Lees, Amanda

2013-11-01

It is now widely accepted that ethics is an essential part of educating health professionals. Despite a clear mandate to educators, there are differing approaches, in particular, how and where ethics is positioned in training programmes, underpinning philosophies and optimal modes of assessment. This paper explores varying practices and argues for a values based approach to ethics education. It then explores the possibility of using a web-based technology, the Values Exchange, to facilitate a values based approach. It uses the findings of a small scale study to signal the potential of the Values Exchange for engaging, meaningful and applied ethics education. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of area-wide management of insect pests based on sampling

Science.gov (United States)

David W. Onstad; Mark S. Sisterson

2011-01-01

The control of invasive species greatly depends on area-wide pest management (AWPM) in heterogeneous landscapes. Decisions about when and where to treat a population with pesticide are based on sampling pest abundance. One of the challenges of AWPM is sampling large areas with limited funds to cover the cost of sampling. Additionally, AWPM programs are often confronted...

Community-based survey versus sentinel site sampling in ...

African Journals Online (AJOL)

rural children. Implications for nutritional surveillance and the development of nutritional programmes. G. c. Solarsh, D. M. Sanders, C. A. Gibson, E. Gouws. A study of the anthropometric status of under-5-year-olds was conducted in the Nqutu district of Kwazulu by means of a representative community-based sample and.

Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

Science.gov (United States)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological

Approximation of the exponential integral (well function) using sampling methods

Science.gov (United States)

Baalousha, Husam Musa

2015-04-01

Exponential integral (also known as well function) is often used in hydrogeology to solve Theis and Hantush equations. Many methods have been developed to approximate the exponential integral. Most of these methods are based on numerical approximations and are valid for a certain range of the argument value. This paper presents a new approach to approximate the exponential integral. The new approach is based on sampling methods. Three different sampling methods; Latin Hypercube Sampling (LHS), Orthogonal Array (OA), and Orthogonal Array-based Latin Hypercube (OA-LH) have been used to approximate the function. Different argument values, covering a wide range, have been used. The results of sampling methods were compared with results obtained by Mathematica software, which was used as a benchmark. All three sampling methods converge to the result obtained by Mathematica, at different rates. It was found that the orthogonal array (OA) method has the fastest convergence rate compared with LHS and OA-LH. The root mean square error RMSE of OA was in the order of 1E-08. This method can be used with any argument value, and can be used to solve other integrals in hydrogeology such as the leaky aquifer integral.

Model-based estimation of finite population total in stratified sampling

African Journals Online (AJOL)

The work presented in this paper concerns the estimation of finite population total under model – based framework. Nonparametric regression approach as a method of estimating finite population total is explored. The asymptotic properties of the estimators based on nonparametric regression are also developed under ...

Combining Electrochemical Sensors with Miniaturized Sample Preparation for Rapid Detection in Clinical Samples

Science.gov (United States)

Bunyakul, Natinan; Baeumner, Antje J.

2015-01-01

Clinical analyses benefit world-wide from rapid and reliable diagnostics tests. New tests are sought with greatest demand not only for new analytes, but also to reduce costs, complexity and lengthy analysis times of current techniques. Among the myriad of possibilities available today to develop new test systems, amperometric biosensors are prominent players—best represented by the ubiquitous amperometric-based glucose sensors. Electrochemical approaches in general require little and often enough only simple hardware components, are rugged and yet provide low limits of detection. They thus offer many of the desirable attributes for point-of-care/point-of-need tests. This review focuses on investigating the important integration of sample preparation with (primarily electrochemical) biosensors. Sample clean up requirements, miniaturized sample preparation strategies, and their potential integration with sensors will be discussed, focusing on clinical sample analyses. PMID:25558994

Metagenomic analysis of medicinal Cannabis samples; pathogenic bacteria, toxigenic fungi, and beneficial microbes grow in culture-based yeast and mold tests.

Science.gov (United States)

McKernan, Kevin; Spangler, Jessica; Helbert, Yvonne; Lynch, Ryan C; Devitt-Lee, Adrian; Zhang, Lei; Orphe, Wendell; Warner, Jason; Foss, Theodore; Hudalla, Christopher J; Silva, Matthew; Smith, Douglas R

2016-01-01

Background : The presence of bacteria and fungi in medicinal or recreational Cannabis poses a potential threat to consumers if those microbes include pathogenic or toxigenic species. This study evaluated two widely used culture-based platforms for total yeast and mold (TYM) testing marketed by 3M Corporation and Biomérieux, in comparison with a quantitative PCR (qPCR) approach marketed by Medicinal Genomics Corporation. Methods : A set of 15 medicinal Cannabis samples were analyzed using 3M and Biomérieux culture-based platforms and by qPCR to quantify microbial DNA. All samples were then subjected to next-generation sequencing and metagenomics analysis to enumerate the bacteria and fungi present before and after growth on culture-based media. Results : Several pathogenic or toxigenic bacterial and fungal species were identified in proportions of >5% of classified reads on the samples, including Acinetobacter baumannii, Escherichia coli, Pseudomonas aeruginosa, Ralstonia pickettii, Salmonella enterica, Stenotrophomonas maltophilia, Aspergillus ostianus, Aspergillus sydowii, Penicillium citrinum and Penicillium steckii. Samples subjected to culture showed substantial shifts in the number and diversity of species present, including the failure of Aspergillus species to grow well on either platform. Substantial growth of Clostridium botulinum and other bacteria were frequently observed on one or both of the culture-based TYM platforms. The presence of plant growth promoting (beneficial) fungal species further influenced the differential growth of species in the microbiome of each sample. Conclusions : These findings have important implications for the Cannabis and food safety testing industries.

Application of In-Segment Multiple Sampling in Object-Based Classification

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Nataša Đurić

2014-12-01

Full Text Available When object-based analysis is applied to very high-resolution imagery, pixels within the segments reveal large spectral inhomogeneity; their distribution can be considered complex rather than normal. When normality is violated, the classification methods that rely on the assumption of normally distributed data are not as successful or accurate. It is hard to detect normality violations in small samples. The segmentation process produces segments that vary highly in size; samples can be very big or very small. This paper investigates whether the complexity within the segment can be addressed using multiple random sampling of segment pixels and multiple calculations of similarity measures. In order to analyze the effect sampling has on classification results, statistics and probability value equations of non-parametric two-sample Kolmogorov-Smirnov test and parametric Student’s t-test are selected as similarity measures in the classification process. The performance of both classifiers was assessed on a WorldView-2 image for four land cover classes (roads, buildings, grass and trees and compared to two commonly used object-based classifiers—k-Nearest Neighbor (k-NN and Support Vector Machine (SVM. Both proposed classifiers showed a slight improvement in the overall classification accuracies and produced more accurate classification maps when compared to the ground truth image.

A two-stage cluster sampling method using gridded population data, a GIS, and Google EarthTM imagery in a population-based mortality survey in Iraq

Directory of Open Access Journals (Sweden)

Galway LP

2012-04-01

Full Text Available Abstract Background Mortality estimates can measure and monitor the impacts of conflict on a population, guide humanitarian efforts, and help to better understand the public health impacts of conflict. Vital statistics registration and surveillance systems are rarely functional in conflict settings, posing a challenge of estimating mortality using retrospective population-based surveys. Results We present a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method utilizes gridded population data and a geographic information system (GIS to select clusters in the first sampling stage and Google Earth TM imagery and sampling grids to select households in the second sampling stage. The sampling method is implemented in a household mortality study in Iraq in 2011. Factors affecting feasibility and methodological quality are described. Conclusion Sampling is a challenge in retrospective population-based mortality studies and alternatives that improve on the conventional approaches are needed. The sampling strategy presented here was designed to generate a representative sample of the Iraqi population while reducing the potential for bias and considering the context specific challenges of the study setting. This sampling strategy, or variations on it, are adaptable and should be considered and tested in other conflict settings.

A New Spin on Teaching Vocabulary: A Source-Based Approach.

Science.gov (United States)

Nilsen, Alleen Pace; Nilsen, Don L. F.

2003-01-01

Suggests that teachers should try to use a source-based approach to teaching vocabulary. Explains that a source-based approach starts with basic concepts of human languages and then works with lexical and metaphorical extensions of these basic words. Notes that the purpose of this approach is to find groups of words that can be taught as webs and…

A novel approach to Lagrangian sampling of marine boundary layer cloud and aerosol in the northeast Pacific: case studies from CSET

Science.gov (United States)

Mohrmann, J.; Albrecht, B. A.; Bretherton, C. S.; Ghate, V. P.; Zuidema, P.; Wood, R.

2015-12-01

The Cloud System Evolution in the Trades (CSET) field campaign took place during July/August 2015 with the purpose of characterizing the cloud, aerosol and thermodynamic properties of the northeast Pacific marine boundary layer. One major science goal of the campaign was to observe a Lagrangian transition from thin stratocumulus (Sc) upwind near California to trade cumulus (Cu) nearer to Hawaii. Cloud properties were observed from the NSF/NCAR Gulfstream V research plane (GV) using the HIAPER Cloud Radar (HCR) and the HIAPER Spectral Resolution Lidar (HSRL), among other instrumentation. Aircraft observations were complemented by a suite of satellite-derived products. To observe a the evolution of airmasses over the course of two days, upwind regions were sampled on an outbound flight to from Sacramento, CA, to Kona, HI. The sampled airmasses were then tracked using HYSPLIT trajectories based on GFS model forecasts, and the return flight to California was planned to intercept those airmasses, using satellite observation to track cloud evolution in the interim. This approach required that trajectories were reasonably stable up to 3 days prior to final sampling, and also that forecast trajectories were in agreement with post-flight analysis and visual cloud feature tracking. The extent to which this was realised, and hence the validity of this new approach to Lagrangian airmass observation, is assessed here. We also present results showing that a Sc-Cu airmass transition was consistently observed during the CSET study using measurements from research flights and satellite.

A model-data based systems approach to process intensification

DEFF Research Database (Denmark)

Gani, Rafiqul

. Their developments, however, are largely due to experiment based trial and error approaches and while they do not require validation, they can be time consuming and resource intensive. Also, one may ask, can a truly new intensified unit operation be obtained in this way? An alternative two-stage approach is to apply...... a model-based synthesis method to systematically generate and evaluate alternatives in the first stage and an experiment-model based validation in the second stage. In this way, the search for alternatives is done very quickly, reliably and systematically over a wide range, while resources are preserved...... for focused validation of only the promising candidates in the second-stage. This approach, however, would be limited to intensification based on “known” unit operations, unless the PI process synthesis/design is considered at a lower level of aggregation, namely the phenomena level. That is, the model-based...

Assessment of Sampling Approaches for Remote Sensing Image Classification in the Iranian Playa Margins

Science.gov (United States)

Kazem Alavipanah, Seyed

There are some problems in soil salinity studies based upon remotely sensed data: 1-spectral world is full of ambiguity and therefore soil reflectance can not be attributed to a single soil property such as salinity, 2) soil surface conditions as a function of time and space is a complex phenomena, 3) vegetation with a dynamic biological nature may create some problems in the study of soil salinity. Due to these problems the first question which may arise is how to overcome or minimise these problems. In this study we hypothesised that different sources of data, well established sampling plan and optimum approach could be useful. In order to choose representative training sites in the Iranian playa margins, to define the spectral and informational classes and to overcome some problems encountered in the variation within the field, the following attempts were made: 1) Principal Component Analysis (PCA) in order: a) to determine the most important variables, b) to understand the Landsat satellite images and the most informative components, 2) the photomorphic unit (PMU) consideration and interpretation; 3) study of salt accumulation and salt distribution in the soil profile, 4) use of several forms of field data, such as geologic, geomorphologic and soil information; 6) confirmation of field data and land cover types with farmers and the members of the team. The results led us to find at suitable approaches with a high and acceptable image classification accuracy and image interpretation. KEY WORDS; Photo Morphic Unit, Pprincipal Ccomponent Analysis, Soil Salinity, Field Work, Remote Sensing

A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red

Science.gov (United States)

Maes, Thomas; Jessop, Rebecca; Wellner, Nikolaus; Haupt, Karsten; Mayes, Andrew G.

2017-03-01

A new approach is presented for analysis of microplastics in environmental samples, based on selective fluorescent staining using Nile Red (NR), followed by density-based extraction and filtration. The dye adsorbs onto plastic surfaces and renders them fluorescent when irradiated with blue light. Fluorescence emission is detected using simple photography through an orange filter. Image-analysis allows fluorescent particles to be identified and counted. Magnified images can be recorded and tiled to cover the whole filter area, allowing particles down to a few micrometres to be detected. The solvatochromic nature of Nile Red also offers the possibility of plastic categorisation based on surface polarity characteristics of identified particles. This article details the development of this staining method and its initial cross-validation by comparison with infrared (IR) microscopy. Microplastics of different sizes could be detected and counted in marine sediment samples. The fluorescence staining identified the same particles as those found by scanning a filter area with IR-microscopy.

Mindfulness-Based Group Approach for Undergraduate Students with Disordered Eating or Body Image Issues: A Case Study

Directory of Open Access Journals (Sweden)

Olivia Stumpf

2017-11-01

Conclusions: A mindfulness-based group approach to treatment of disordered eating or body image issues shows promise for improving the quality of life for college-aged students. Undergraduate institutions have the advantage of using social interaction to facilitate healthy behavioral change. Future research with larger and more diverse samples is suggested, and implications regarding practice and education are also discussed.

The k0-based neutron activation analysis: a mono standard to standardless approach of NAA

International Nuclear Information System (INIS)

Acharya, R.; Nair, A.G.C.; Sudarshan, K.; Goswami, A.; Reddy, A.V.R.

2006-01-01

The k 0 -based neutron activation analysis (k 0 -NAA) uses neutron flux parameters, detection efficiency and nuclear constants namely k 0 and Q 0 for the determination of concentration of elements. Gold ( 197 Au) or any other element having suitable nuclear properties is used as external or internal single comparator. This article describes the principle of k 0 -NAA and standardization of method by characterization of reactor irradiation sites and calibration of efficiency of the detector and applications. The method was validated using CRMs obtained from USGS, IAEA and NIST. The applications of method includes samples like gemstones (ruby, beryl and emerald), sediments, manganese nodules and encrustations, cereals, and medicinal and edible leaves. Recently, a k-o-based internal mono standard INAA (IM-NAA) method using in-situ relative efficiency has been standardized by us for the analysis of small and large samples of different shapes and sizes. The method was applied to a new meteorite sample and large size wheat samples. Non-standard size and shape samples of nuclear cladding materials namely zircaloy 2 and 4, stainless steels (SS 316M and D9) and 1S aluminium were analysed. Standard-less analysis of these cladding materials was possible by mass balance approach since all the major and minor elements were amenable to NAA. (author)

Randomization-Based Inference about Latent Variables from Complex Samples: The Case of Two-Stage Sampling

Science.gov (United States)

Li, Tiandong

2012-01-01

In large-scale assessments, such as the National Assessment of Educational Progress (NAEP), plausible values based on Multiple Imputations (MI) have been used to estimate population characteristics for latent constructs under complex sample designs. Mislevy (1991) derived a closed-form analytic solution for a fixed-effect model in creating…

Evaluation of Sampling Methods for Bacillus Spore ...

Science.gov (United States)

Journal Article Following a wide area release of biological materials, mapping the extent of contamination is essential for orderly response and decontamination operations. HVAC filters process large volumes of air and therefore collect highly representative particulate samples in buildings. HVAC filter extraction may have great utility in rapidly estimating the extent of building contamination following a large-scale incident. However, until now, no studies have been conducted comparing the two most appropriate sampling approaches for HVAC filter materials: direct extraction and vacuum-based sampling.

Graph sampling

OpenAIRE

Zhang, L.-C.; Patone, M.

2017-01-01

We synthesise the existing theory of graph sampling. We propose a formal definition of sampling in finite graphs, and provide a classification of potential graph parameters. We develop a general approach of Horvitz–Thompson estimation to T-stage snowball sampling, and present various reformulations of some common network sampling methods in the literature in terms of the outlined graph sampling theory.

Econutrition and utilization of food-based approaches for nutritional health.

Science.gov (United States)

Blasbalg, Tanya L; Wispelwey, Bram; Deckelbaum, Richard J

2011-03-01

Macronutrient and micronutrient deficiencies continue to have a detrimental impact in lower-income countries, with significant costs in morbidity, mortality, and productivity. Food is the primary source of the nutrients needed to sustain life, and it is the essential component that links nutrition, agriculture, and ecology in the econutrition framework. To present evidence and analysis of food-based approaches for improving nutritional and health outcomes in lower-income countries. Review of existing literature. The benefits of food-based approaches may include nutritional improvement, food security, cost-effectiveness, sustainability, and human productivity. Food-based approaches require additional inputs, including nutrition education, gender considerations, and agricultural planning. Although some forms of malnutrition can be addressed via supplements, food-based approaches are optimal to achieve sustainable solutions to multiple nutrient deficiencies.

A modified approach to estimating sample size for simple logistic regression with one continuous covariate.

Science.gov (United States)

Novikov, I; Fund, N; Freedman, L S

2010-01-15

Different methods for the calculation of sample size for simple logistic regression (LR) with one normally distributed continuous covariate give different results. Sometimes the difference can be large. Furthermore, some methods require the user to specify the prevalence of cases when the covariate equals its population mean, rather than the more natural population prevalence. We focus on two commonly used methods and show through simulations that the power for a given sample size may differ substantially from the nominal value for one method, especially when the covariate effect is large, while the other method performs poorly if the user provides the population prevalence instead of the required parameter. We propose a modification of the method of Hsieh et al. that requires specification of the population prevalence and that employs Schouten's sample size formula for a t-test with unequal variances and group sizes. This approach appears to increase the accuracy of the sample size estimates for LR with one continuous covariate.

Adaptive Sampling for Nonlinear Dimensionality Reduction Based on Manifold Learning

DEFF Research Database (Denmark)

Franz, Thomas; Zimmermann, Ralf; Goertz, Stefan

2017-01-01

We make use of the non-intrusive dimensionality reduction method Isomap in order to emulate nonlinear parametric flow problems that are governed by the Reynolds-averaged Navier-Stokes equations. Isomap is a manifold learning approach that provides a low-dimensional embedding space that is approxi...... to detect and fill up gaps in the sampling in the embedding space. The performance of the proposed manifold filling method will be illustrated by numerical experiments, where we consider nonlinear parameter-dependent steady-state Navier-Stokes flows in the transonic regime.......We make use of the non-intrusive dimensionality reduction method Isomap in order to emulate nonlinear parametric flow problems that are governed by the Reynolds-averaged Navier-Stokes equations. Isomap is a manifold learning approach that provides a low-dimensional embedding space...

A Study of Assimilation Bias in Name-Based Sampling of Migrants

Directory of Open Access Journals (Sweden)

Schnell Rainer

2014-06-01

Full Text Available The use of personal names for screening is an increasingly popular sampling technique for migrant populations. Although this is often an effective sampling procedure, very little is known about the properties of this method. Based on a large German survey, this article compares characteristics of respondents whose names have been correctly classified as belonging to a migrant population with respondentswho aremigrants and whose names have not been classified as belonging to a migrant population. Although significant differences were found for some variables even with some large effect sizes, the overall bias introduced by name-based sampling (NBS is small as long as procedures with small false-negative rates are employed.

A novel approach to non-biased systematic random sampling: a stereologic estimate of Purkinje cells in the human cerebellum.