Barca, E; Castrignanò, A; Buttafuoco, G; De Benedetto, D; Passarella, G
2015-07-01
Soil survey is generally time-consuming, labor-intensive, and costly. Optimization of sampling scheme allows one to reduce the number of sampling points without decreasing or even increasing the accuracy of investigated attribute. Maps of bulk soil electrical conductivity (EC a ) recorded with electromagnetic induction (EMI) sensors could be effectively used to direct soil sampling design for assessing spatial variability of soil moisture. A protocol, using a field-scale bulk EC a survey, has been applied in an agricultural field in Apulia region (southeastern Italy). Spatial simulated annealing was used as a method to optimize spatial soil sampling scheme taking into account sampling constraints, field boundaries, and preliminary observations. Three optimization criteria were used. the first criterion (minimization of mean of the shortest distances, MMSD) optimizes the spreading of the point observations over the entire field by minimizing the expectation of the distance between an arbitrarily chosen point and its nearest observation; the second criterion (minimization of weighted mean of the shortest distances, MWMSD) is a weighted version of the MMSD, which uses the digital gradient of the grid EC a data as weighting function; and the third criterion (mean of average ordinary kriging variance, MAOKV) minimizes mean kriging estimation variance of the target variable. The last criterion utilizes the variogram model of soil water content estimated in a previous trial. The procedures, or a combination of them, were tested and compared in a real case. Simulated annealing was implemented by the software MSANOS able to define or redesign any sampling scheme by increasing or decreasing the original sampling locations. The output consists of the computed sampling scheme, the convergence time, and the cooling law, which can be an invaluable support to the process of sampling design. The proposed approach has found the optimal solution in a reasonable computation time. The
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. PMID:26211074
Yin, Jingjing; Samawi, Hani; Linder, Daniel
2016-07-01
A diagnostic cut-off point of a biomarker measurement is needed for classifying a random subject to be either diseased or healthy. However, the cut-off point is usually unknown and needs to be estimated by some optimization criteria. One important criterion is the Youden index, which has been widely adopted in practice. The Youden index, which is defined as the maximum of (sensitivity + specificity -1), directly measures the largest total diagnostic accuracy a biomarker can achieve. Therefore, it is desirable to estimate the optimal cut-off point associated with the Youden index. Sometimes, taking the actual measurements of a biomarker is very difficult and expensive, while ranking them without the actual measurement can be relatively easy. In such cases, ranked set sampling can give more precise estimation than simple random sampling, as ranked set samples are more likely to span the full range of the population. In this study, kernel density estimation is utilized to numerically solve for an estimate of the optimal cut-off point. The asymptotic distributions of the kernel estimators based on two sampling schemes are derived analytically and we prove that the estimators based on ranked set sampling are relatively more efficient than that of simple random sampling and both estimators are asymptotically unbiased. Furthermore, the asymptotic confidence intervals are derived. Intensive simulations are carried out to compare the proposed method using ranked set sampling with simple random sampling, with the proposed method outperforming simple random sampling in all cases. A real data set is analyzed for illustrating the proposed method.
Yin, Jingjing; Samawi, Hani; Linder, Daniel
2016-07-01
A diagnostic cut-off point of a biomarker measurement is needed for classifying a random subject to be either diseased or healthy. However, the cut-off point is usually unknown and needs to be estimated by some optimization criteria. One important criterion is the Youden index, which has been widely adopted in practice. The Youden index, which is defined as the maximum of (sensitivity + specificity -1), directly measures the largest total diagnostic accuracy a biomarker can achieve. Therefore, it is desirable to estimate the optimal cut-off point associated with the Youden index. Sometimes, taking the actual measurements of a biomarker is very difficult and expensive, while ranking them without the actual measurement can be relatively easy. In such cases, ranked set sampling can give more precise estimation than simple random sampling, as ranked set samples are more likely to span the full range of the population. In this study, kernel density estimation is utilized to numerically solve for an estimate of the optimal cut-off point. The asymptotic distributions of the kernel estimators based on two sampling schemes are derived analytically and we prove that the estimators based on ranked set sampling are relatively more efficient than that of simple random sampling and both estimators are asymptotically unbiased. Furthermore, the asymptotic confidence intervals are derived. Intensive simulations are carried out to compare the proposed method using ranked set sampling with simple random sampling, with the proposed method outperforming simple random sampling in all cases. A real data set is analyzed for illustrating the proposed method. PMID:26756282
da Costa, Nuno Maçarico; Hepp, Klaus; Martin, Kevan A C
2009-05-30
Synapses can only be morphologically identified by electron microscopy and this is often a very labor-intensive and time-consuming task. When quantitative estimates are required for pathways that contribute a small proportion of synapses to the neuropil, the problems of accurate sampling are particularly severe and the total time required may become prohibitive. Here we present a sampling method devised to count the percentage of rarely occurring synapses in the neuropil using a large sample (approximately 1000 sampling sites), with the strong constraint of doing it in reasonable time. The strategy, which uses the unbiased physical disector technique, resembles that used in particle physics to detect rare events. We validated our method in the primary visual cortex of the cat, where we used biotinylated dextran amine to label thalamic afferents and measured the density of their synapses using the physical disector method. Our results show that we could obtain accurate counts of the labeled synapses, even when they represented only 0.2% of all the synapses in the neuropil.
NASA Technical Reports Server (NTRS)
Khayat, Michael A.; Wilton, Donald R.; Fink, Patrick W.
2007-01-01
Simple and efficient numerical procedures using singularity cancellation methods are presented for evaluating singular and near-singular potential integrals. Four different transformations are compared and the advantages of the Radial-angular transform are demonstrated. A method is then described for optimizing this integration scheme.
Evolutionary Algorithm for Optimal Vaccination Scheme
NASA Astrophysics Data System (ADS)
Parousis-Orthodoxou, K. J.; Vlachos, D. S.
2014-03-01
The following work uses the dynamic capabilities of an evolutionary algorithm in order to obtain an optimal immunization strategy in a user specified network. The produced algorithm uses a basic genetic algorithm with crossover and mutation techniques, in order to locate certain nodes in the inputted network. These nodes will be immunized in an SIR epidemic spreading process, and the performance of each immunization scheme, will be evaluated by the level of containment that provides for the spreading of the disease.
Comparative study of numerical schemes of TVD3, UNO3-ACM and optimized compact scheme
NASA Technical Reports Server (NTRS)
Lee, Duck-Joo; Hwang, Chang-Jeon; Ko, Duck-Kon; Kim, Jae-Wook
1995-01-01
Three different schemes are employed to solve the benchmark problem. The first one is a conventional TVD-MUSCL (Monotone Upwind Schemes for Conservation Laws) scheme. The second scheme is a UNO3-ACM (Uniformly Non-Oscillatory Artificial Compression Method) scheme. The third scheme is an optimized compact finite difference scheme modified by us: the 4th order Runge Kutta time stepping, the 4th order pentadiagonal compact spatial discretization with the maximum resolution characteristics. The problems of category 1 are solved by using the second (UNO3-ACM) and third (Optimized Compact) schemes. The problems of category 2 are solved by using the first (TVD3) and second (UNO3-ACM) schemes. The problem of category 5 is solved by using the first (TVD3) scheme. It can be concluded from the present calculations that the Optimized Compact scheme and the UN03-ACM show good resolutions for category 1 and category 2 respectively.
Optimal coding schemes for conflict-free channel access
NASA Astrophysics Data System (ADS)
Browning, Douglas W.; Thomas, John B.
1989-10-01
A method is proposed for conflict-free access of a broadcast channel. The method uses a variable-length coding scheme to determine which user gains access to the channel. For an idle channel, an equation for optimal expected overhead is derived and a coding scheme that produces optimal codes is presented. Algorithms for generating optimal codes for access on a busy channel are discussed. Suboptimal schemes are found that perform in a nearly optimal fashion. The method is shown to be superior in performance to previously developed conflict-free channel access schemes.
Optimal Symmetric Ternary Quantum Encryption Schemes
NASA Astrophysics Data System (ADS)
Wang, Yu-qi; She, Kun; Huang, Ru-fen; Ouyang, Zhong
2016-07-01
In this paper, we present two definitions of the orthogonality and orthogonal rate of an encryption operator, and we provide a verification process for the former. Then, four improved ternary quantum encryption schemes are constructed. Compared with Scheme 1 (see Section 2.3), these four schemes demonstrate significant improvements in term of calculation and execution efficiency. Especially, under the premise of the orthogonal rate ɛ as secure parameter, Scheme 3 (see Section 4.1) shows the highest level of security among them. Through custom interpolation functions, the ternary secret key source, which is composed of the digits 0, 1 and 2, is constructed. Finally, we discuss the security of both the ternary encryption operator and the secret key source, and both of them show a high level of security and high performance in execution efficiency.
GENERAL: Linear Optical Scheme for Implementing Optimal Real State Cloning
NASA Astrophysics Data System (ADS)
Wan, Hong-Bo; Ye, Liu
2010-06-01
We propose an experimental scheme for implementing the optimal 1 → 3 real state cloning via linear optical elements. This method relies on one polarized qubit and two location qubits and is feasible with current experimental technology.
XFEM schemes for level set based structural optimization
NASA Astrophysics Data System (ADS)
Li, Li; Wang, Michael Yu; Wei, Peng
2012-12-01
In this paper, some elegant extended finite element method (XFEM) schemes for level set method structural optimization are proposed. Firstly, two-dimension (2D) and three-dimension (3D) XFEM schemes with partition integral method are developed and numerical examples are employed to evaluate their accuracy, which indicate that an accurate analysis result can be obtained on the structural boundary. Furthermore, the methods for improving the computational accuracy and efficiency of XFEM are studied, which include the XFEM integral scheme without quadrature sub-cells and higher order element XFEM scheme. Numerical examples show that the XFEM scheme without quadrature sub-cells can yield similar accuracy of structural analysis while prominently reducing the time cost and that higher order XFEM elements can improve the computational accuracy of structural analysis in the boundary elements, but the time cost is increasing. Therefore, the balance of time cost between FE system scale and the order of element needs to be discussed. Finally, the reliability and advantages of the proposed XFEM schemes are illustrated with several 2D and 3D mean compliance minimization examples that are widely used in the recent literature of structural topology optimization. All numerical results demonstrate that the proposed XFEM is a promising structural analysis approach for structural optimization with the level set method.
Multiobjective hyper heuristic scheme for system design and optimization
NASA Astrophysics Data System (ADS)
Rafique, Amer Farhan
2012-11-01
As system design is becoming more and more multifaceted, integrated, and complex, the traditional single objective optimization trends of optimal design are becoming less and less efficient and effective. Single objective optimization methods present a unique optimal solution whereas multiobjective methods present pareto front. The foremost intent is to predict a reasonable distributed pareto-optimal solution set independent of the problem instance through multiobjective scheme. Other objective of application of intended approach is to improve the worthiness of outputs of the complex engineering system design process at the conceptual design phase. The process is automated in order to provide the system designer with the leverage of the possibility of studying and analyzing a large multiple of possible solutions in a short time. This article presents Multiobjective Hyper Heuristic Optimization Scheme based on low level meta-heuristics developed for the application in engineering system design. Herein, we present a stochastic function to manage meta-heuristics (low-level) to augment surety of global optimum solution. Generic Algorithm, Simulated Annealing and Swarm Intelligence are used as low-level meta-heuristics in this study. Performance of the proposed scheme is investigated through a comprehensive empirical analysis yielding acceptable results. One of the primary motives for performing multiobjective optimization is that the current engineering systems require simultaneous optimization of conflicting and multiple. Random decision making makes the implementation of this scheme attractive and easy. Injecting feasible solutions significantly alters the search direction and also adds diversity of population resulting in accomplishment of pre-defined goals set in the proposed scheme.
Effects of sparse sampling schemes on image quality in low-dose CT
Abbas, Sajid; Lee, Taewon; Cho, Seungryong; Shin, Sukyoung; Lee, Rena
2013-11-15
Purpose: Various scanning methods and image reconstruction algorithms are actively investigated for low-dose computed tomography (CT) that can potentially reduce a health-risk related to radiation dose. Particularly, compressive-sensing (CS) based algorithms have been successfully developed for reconstructing images from sparsely sampled data. Although these algorithms have shown promises in low-dose CT, it has not been studied how sparse sampling schemes affect image quality in CS-based image reconstruction. In this work, the authors present several sparse-sampling schemes for low-dose CT, quantitatively analyze their data property, and compare effects of the sampling schemes on the image quality.Methods: Data properties of several sampling schemes are analyzed with respect to the CS-based image reconstruction using two measures: sampling density and data incoherence. The authors present five different sparse sampling schemes, and simulated those schemes to achieve a targeted dose reduction. Dose reduction factors of about 75% and 87.5%, compared to a conventional scan, were tested. A fully sampled circular cone-beam CT data set was used as a reference, and sparse sampling has been realized numerically based on the CBCT data.Results: It is found that both sampling density and data incoherence affect the image quality in the CS-based reconstruction. Among the sampling schemes the authors investigated, the sparse-view, many-view undersampling (MVUS)-fine, and MVUS-moving cases have shown promising results. These sampling schemes produced images with similar image quality compared to the reference image and their structure similarity index values were higher than 0.92 in the mouse head scan with 75% dose reduction.Conclusions: The authors found that in CS-based image reconstructions both sampling density and data incoherence affect the image quality, and suggest that a sampling scheme should be devised and optimized by use of these indicators. With this strategic
Global search acceleration in the nested optimization scheme
NASA Astrophysics Data System (ADS)
Grishagin, Vladimir A.; Israfilov, Ruslan A.
2016-06-01
Multidimensional unconstrained global optimization problem with objective function under Lipschitz condition is considered. For solving this problem the dimensionality reduction approach on the base of the nested optimization scheme is used. This scheme reduces initial multidimensional problem to a family of one-dimensional subproblems being Lipschitzian as well and thus allows applying univariate methods for the execution of multidimensional optimization. For two well-known one-dimensional methods of Lipschitz optimization the modifications providing the acceleration of the search process in the situation when the objective function is continuously differentiable in a vicinity of the global minimum are considered and compared. Results of computational experiments on conventional test class of multiextremal functions confirm efficiency of the modified methods.
Attributes mode sampling schemes for international material accountancy verification
Sanborn, J.B.
1982-12-01
This paper addresses the question of detecting falsifications in material balance accountancy reporting by comparing independently measured values to the declared values of a randomly selected sample of items in the material balance. A two-level strategy is considered, consisting of a relatively large number of measurements made at low accuracy, and a smaller number of measurements made at high accuracy. Sampling schemes for both types of measurements are derived, and rigorous proofs supplied that guarantee desired detection probabilities. Sample sizes derived using these methods are sometimes considerably smaller than those calculated previously.
Optimization algorithm based characterization scheme for tunable semiconductor lasers.
Chen, Quanan; Liu, Gonghai; Lu, Qiaoyin; Guo, Weihua
2016-09-01
In this paper, an optimization algorithm based characterization scheme for tunable semiconductor lasers is proposed and demonstrated. In the process of optimization, the ratio between the power of the desired frequency and the power except of the desired frequency is used as the figure of merit, which approximately represents the side-mode suppression ratio. In practice, we use tunable optical band-pass and band-stop filters to obtain the power of the desired frequency and the power except of the desired frequency separately. With the assistance of optimization algorithms, such as the particle swarm optimization (PSO) algorithm, we can get stable operation conditions for tunable lasers at designated frequencies directly and efficiently. PMID:27607701
A geometric representation scheme suitable for shape optimization
NASA Technical Reports Server (NTRS)
Tortorelli, Daniel A.
1990-01-01
A geometric representation scheme is outlined which utilizes the natural design variable concept. A base configuration with distinct topological features is created. This configuration is then deformed to define components with similar topology but different geometry. The values of the deforming loads are the geometric entities used in the shape representation. The representation can be used for all geometric design studies; it is demonstrated here for structural optimization. This technique can be used in parametric design studies, where the system response is defined as functions of geometric entities. It can also be used in shape optimization, where the geometric entities of an original design are modified to maximize performance and satisfy constraints. Two example problems are provided. A cantilever beam is elongated to meet new design specifications and then optimized to reduce volume and satisfy stress constraints. A similar optimization problem is presented for an automobile crankshaft section. The finite element method is used to perform the analyses.
Optimizing passive acoustic sampling of bats in forests.
Froidevaux, Jérémy S P; Zellweger, Florian; Bollmann, Kurt; Obrist, Martin K
2014-12-01
Passive acoustic methods are increasingly used in biodiversity research and monitoring programs because they are cost-effective and permit the collection of large datasets. However, the accuracy of the results depends on the bioacoustic characteristics of the focal taxa and their habitat use. In particular, this applies to bats which exhibit distinct activity patterns in three-dimensionally structured habitats such as forests. We assessed the performance of 21 acoustic sampling schemes with three temporal sampling patterns and seven sampling designs. Acoustic sampling was performed in 32 forest plots, each containing three microhabitats: forest ground, canopy, and forest gap. We compared bat activity, species richness, and sampling effort using species accumulation curves fitted with the clench equation. In addition, we estimated the sampling costs to undertake the best sampling schemes. We recorded a total of 145,433 echolocation call sequences of 16 bat species. Our results indicated that to generate the best outcome, it was necessary to sample all three microhabitats of a given forest location simultaneously throughout the entire night. Sampling only the forest gaps and the forest ground simultaneously was the second best choice and proved to be a viable alternative when the number of available detectors is limited. When assessing bat species richness at the 1-km(2) scale, the implementation of these sampling schemes at three to four forest locations yielded highest labor cost-benefit ratios but increasing equipment costs. Our study illustrates that multiple passive acoustic sampling schemes require testing based on the target taxa and habitat complexity and should be performed with reference to cost-benefit ratios. Choosing a standardized and replicated sampling scheme is particularly important to optimize the level of precision in inventories, especially when rare or elusive species are expected. PMID:25558363
Towards optimal sampling schedules for integral pumping tests
NASA Astrophysics Data System (ADS)
Leschik, Sebastian; Bayer-Raich, Marti; Musolff, Andreas; Schirmer, Mario
2011-06-01
Conventional point sampling may miss plumes in groundwater due to an insufficient density of sampling locations. The integral pumping test (IPT) method overcomes this problem by increasing the sampled volume. One or more wells are pumped for a long duration (several days) and samples are taken during pumping. The obtained concentration-time series are used for the estimation of average aquifer concentrations Cav and mass flow rates MCP. Although the IPT method is a well accepted approach for the characterization of contaminated sites, no substantiated guideline for the design of IPT sampling schedules (optimal number of samples and optimal sampling times) is available. This study provides a first step towards optimal IPT sampling schedules by a detailed investigation of 30 high-frequency concentration-time series. Different sampling schedules were tested by modifying the original concentration-time series. The results reveal that the relative error in the Cav estimation increases with a reduced number of samples and higher variability of the investigated concentration-time series. Maximum errors of up to 22% were observed for sampling schedules with the lowest number of samples of three. The sampling scheme that relies on constant time intervals ∆t between different samples yielded the lowest errors.
A new configurational bias scheme for sampling supramolecular structures.
De Gernier, Robin; Curk, Tine; Dubacheva, Galina V; Richter, Ralf P; Mognetti, Bortolo M
2014-12-28
We present a new simulation scheme which allows an efficient sampling of reconfigurable supramolecular structures made of polymeric constructs functionalized by reactive binding sites. The algorithm is based on the configurational bias scheme of Siepmann and Frenkel and is powered by the possibility of changing the topology of the supramolecular network by a non-local Monte Carlo algorithm. Such a plan is accomplished by a multi-scale modelling that merges coarse-grained simulations, describing the typical polymer conformations, with experimental results accounting for free energy terms involved in the reactions of the active sites. We test the new algorithm for a system of DNA coated colloids for which we compute the hybridisation free energy cost associated to the binding of tethered single stranded DNAs terminated by short sequences of complementary nucleotides. In order to demonstrate the versatility of our method, we also consider polymers functionalized by receptors that bind a surface decorated by ligands. In particular, we compute the density of states of adsorbed polymers as a function of the number of ligand-receptor complexes formed. Such a quantity can be used to study the conformational properties of adsorbed polymers useful when engineering adsorption with tailored properties. We successfully compare the results with the predictions of a mean field theory. We believe that the proposed method will be a useful tool to investigate supramolecular structures resulting from direct interactions between functionalized polymers for which efficient numerical methodologies of investigation are still lacking. PMID:25554182
A new configurational bias scheme for sampling supramolecular structures
De Gernier, Robin; Mognetti, Bortolo M.; Curk, Tine; Dubacheva, Galina V.; Richter, Ralf P.
2014-12-28
We present a new simulation scheme which allows an efficient sampling of reconfigurable supramolecular structures made of polymeric constructs functionalized by reactive binding sites. The algorithm is based on the configurational bias scheme of Siepmann and Frenkel and is powered by the possibility of changing the topology of the supramolecular network by a non-local Monte Carlo algorithm. Such a plan is accomplished by a multi-scale modelling that merges coarse-grained simulations, describing the typical polymer conformations, with experimental results accounting for free energy terms involved in the reactions of the active sites. We test the new algorithm for a system of DNA coated colloids for which we compute the hybridisation free energy cost associated to the binding of tethered single stranded DNAs terminated by short sequences of complementary nucleotides. In order to demonstrate the versatility of our method, we also consider polymers functionalized by receptors that bind a surface decorated by ligands. In particular, we compute the density of states of adsorbed polymers as a function of the number of ligand–receptor complexes formed. Such a quantity can be used to study the conformational properties of adsorbed polymers useful when engineering adsorption with tailored properties. We successfully compare the results with the predictions of a mean field theory. We believe that the proposed method will be a useful tool to investigate supramolecular structures resulting from direct interactions between functionalized polymers for which efficient numerical methodologies of investigation are still lacking.
Variational scheme towards an optimal lifting drive in fluid adhesion.
Dias, Eduardo O; Miranda, José A
2012-10-01
One way of determining the adhesive strength of liquids is provided by a probe-tack test, which measures the force or energy required to pull apart two parallel flat plates separated by a thin fluid film. The vast majority of the existing theoretical and experimental works in fluid adhesion use very viscous fluids, and consider a linear drive L(t)∼Vt with constant lifting plate velocity V. This implies a given energy cost and large lifting force magnitude. One challenging question in this field pertains to what would be the optimal time-dependent drive Lopt(t) for which the adhesion energy would be minimized. We use a variational scheme to systematically search for such Lopt(t). By employing an optimal lifting drive, in addition to saving energy, we verify a significant decrease in the adhesion force peak. The effectiveness of the proposed lifting procedure is checked for both Newtonian and power-law fluids.
Duy, Pham K; Chang, Kyeol; Sriphong, Lawan; Chung, Hoeil
2015-03-17
An axially perpendicular offset (APO) scheme that is able to directly acquire reproducible Raman spectra of samples contained in an oval container under variation of container orientation has been demonstrated. This scheme utilized an axially perpendicular geometry between the laser illumination and the Raman photon detection, namely, irradiation through a sidewall of the container and gathering of the Raman photon just beneath the container. In the case of either backscattering or transmission measurements, Raman sampling volumes for an internal sample vary when the orientation of an oval container changes; therefore, the Raman intensities of acquired spectra are inconsistent. The generated Raman photons traverse the same bottom of the container in the APO scheme; the Raman sampling volumes can be relatively more consistent under the same situation. For evaluation, the backscattering, transmission, and APO schemes were simultaneously employed to measure alcohol gel samples contained in an oval polypropylene container at five different orientations and then the accuracies of the determination of the alcohol concentrations were compared. The APO scheme provided the most reproducible spectra, yielding the best accuracy when the axial offset distance was 10 mm. Monte Carlo simulations were performed to study the characteristics of photon propagation in the APO scheme and to explain the origin of the optimal offset distance that was observed. In addition, the utility of the APO scheme was further demonstrated by analyzing samples in a circular glass container.
Accurate scoring of non-uniform sampling schemes for quantitative NMR
Aoto, Phillip C.; Fenwick, R. Bryn; Kroon, Gerard J. A.; Wright, Peter E.
2014-01-01
Non-uniform sampling (NUS) in NMR spectroscopy is a recognized and powerful tool to minimize acquisition time. Recent advances in reconstruction methodologies are paving the way for the use of NUS in quantitative applications, where accurate measurement of peak intensities is crucial. The presence or absence of NUS artifacts in reconstructed spectra ultimately determines the success of NUS in quantitative NMR. The quality of reconstructed spectra from NUS acquired data is dependent upon the quality of the sampling scheme. Here we demonstrate that the best performing sampling schemes make up a very small percentage of the total randomly generated schemes. A scoring method is found to accurately predict the quantitative similarity between reconstructed NUS spectra and those of fully sampled spectra. We present an easy-to-use protocol to batch generate and rank optimal Poisson-gap NUS schedules for use with 2D NMR with minimized noise and accurate signal reproduction, without the need for the creation of synthetic spectra. PMID:25063954
Regulatory schemes to achieve optimal flux partitioning in bacterial metabolism
NASA Astrophysics Data System (ADS)
Tang, Lei-Han; Yang, Zhu; Hui, Sheng; Kim, Pan-Jun; Li, Xue-Fei; Hwa, Terence
2012-02-01
The flux balance analysis (FBA) offers a way to compute the optimal performance of a given metabolic network when the maximum incoming flux of nutrient molecules and other essential ingredients for biosynthesis are specified. Here we report a theoretical and computational analysis of the network structure and regulatory interactions in an E. coli cell. An automated scheme is devised to simplify the network topology and to enumerate the independent flux degrees of freedom. The network organization revealed by the scheme enables a detailed interpretation of the three layers of metabolic regulation known in the literature: i) independent transcriptional regulation of biosynthesis and salvage pathways to render the network tree-like under a given nutrient condition; ii) allosteric end-product inhibition of enzyme activity at entry points of synthesis pathways for metabolic flux partitioning according to consumption; iii) homeostasis of currency and carrier compounds to maintain sufficient supply of global commodities. Using the amino-acid synthesis pathways as an example, we show that the FBA result can be reproduced with suitable implementation of the three classes of regulatory interactions with literature evidence.
An optimal performance control scheme for a 3D crane
NASA Astrophysics Data System (ADS)
Maghsoudi, Mohammad Javad; Mohamed, Z.; Husain, A. R.; Tokhi, M. O.
2016-01-01
This paper presents an optimal performance control scheme for control of a three dimensional (3D) crane system including a Zero Vibration shaper which considers two control objectives concurrently. The control objectives are fast and accurate positioning of a trolley and minimum sway of a payload. A complete mathematical model of a lab-scaled 3D crane is simulated in Simulink. With a specific cost function the proposed controller is designed to cater both control objectives similar to a skilled operator. Simulation and experimental studies on a 3D crane show that the proposed controller has better performance as compared to a sequentially tuned PID-PID anti swing controller. The controller provides better position response with satisfactory payload sway in both rail and trolley responses. Experiments with different payloads and cable lengths show that the proposed controller is robust to changes in payload with satisfactory responses.
Optimal sampling ratios in comparative diagnostic trials
Dong, Ting; Tang, Liansheng Larry; Rosenberger, William F.
2014-01-01
Summary A subjective sampling ratio between the case and the control groups is not always an efficient choice to maximize the power or to minimize the total required sample size in comparative diagnostic trials.We derive explicit expressions for an optimal sampling ratio based on a common variance structure shared by several existing summary statistics of the receiver operating characteristic curve. We propose a two-stage procedure to estimate adaptively the optimal ratio without pilot data. We investigate the properties of the proposed method through theoretical proofs, extensive simulation studies and a real example in cancer diagnostic studies. PMID:24948841
SEARCH, blackbox optimization, and sample complexity
Kargupta, H.; Goldberg, D.E.
1996-05-01
The SEARCH (Search Envisioned As Relation and Class Hierarchizing) framework developed elsewhere (Kargupta, 1995; Kargupta and Goldberg, 1995) offered an alternate perspective toward blackbox optimization -- optimization in presence of little domain knowledge. The SEARCH framework investigates the conditions essential for transcending the limits of random enumerative search using a framework developed in terms of relations, classes and partial ordering. This paper presents a summary of some of the main results of that work. A closed form bound on the sample complexity in terms of the cardinality of the relation space, class space, desired quality of the solution and the reliability is presented. This also leads to the identification of the class of order-k delineable problems that can be solved in polynomial sample complexity. These results are applicable to any blackbox search algorithms, including evolutionary optimization techniques.
Optimization of filtering schemes for broadband astro-combs.
Chang, Guoqing; Li, Chih-Hao; Phillips, David F; Szentgyorgyi, Andrew; Walsworth, Ronald L; Kärtner, Franz X
2012-10-22
To realize a broadband, large-line-spacing astro-comb, suitable for wavelength calibration of astrophysical spectrographs, from a narrowband, femtosecond laser frequency comb ("source-comb"), one must integrate the source-comb with three additional components: (1) one or more filter cavities to multiply the source-comb's repetition rate and thus line spacing; (2) power amplifiers to boost the power of pulses from the filtered comb; and (3) highly nonlinear optical fiber to spectrally broaden the filtered and amplified narrowband frequency comb. In this paper we analyze the interplay of Fabry-Perot (FP) filter cavities with power amplifiers and nonlinear broadening fiber in the design of astro-combs optimized for radial-velocity (RV) calibration accuracy. We present analytic and numeric models and use them to evaluate a variety of FP filtering schemes (labeled as identical, co-prime, fraction-prime, and conjugate cavities), coupled to chirped-pulse amplification (CPA). We find that even a small nonlinear phase can reduce suppression of filtered comb lines, and increase RV error for spectrograph calibration. In general, filtering with two cavities prior to the CPA fiber amplifier outperforms an amplifier placed between the two cavities. In particular, filtering with conjugate cavities is able to provide <1 cm/s RV calibration error with >300 nm wavelength coverage. Such superior performance will facilitate the search for and characterization of Earth-like exoplanets, which requires <10 cm/s RV calibration error.
Sampling design optimization for spatial functions
Olea, R.A.
1984-01-01
A new procedure is presented for minimizing the sampling requirements necessary to estimate a mappable spatial function at a specified level of accuracy. The technique is based on universal kriging, an estimation method within the theory of regionalized variables. Neither actual implementation of the sampling nor universal kriging estimations are necessary to make an optimal design. The average standard error and maximum standard error of estimation over the sampling domain are used as global indices of sampling efficiency. The procedure optimally selects those parameters controlling the magnitude of the indices, including the density and spatial pattern of the sample elements and the number of nearest sample elements used in the estimation. As an illustration, the network of observation wells used to monitor the water table in the Equus Beds of Kansas is analyzed and an improved sampling pattern suggested. This example demonstrates the practical utility of the procedure, which can be applied equally well to other spatial sampling problems, as the procedure is not limited by the nature of the spatial function. ?? 1984 Plenum Publishing Corporation.
NASA Astrophysics Data System (ADS)
Li, Y.; Han, B.; Métivier, L.; Brossier, R.
2016-09-01
We investigate an optimal fourth-order staggered-grid finite-difference scheme for 3D frequency-domain viscoelastic wave modeling. An anti-lumped mass strategy is incorporated to minimize the numerical dispersion. The optimal finite-difference coefficients and the mass weighting coefficients are obtained by minimizing the misfit between the normalized phase velocities and the unity. An iterative damped least-squares method, the Levenberg-Marquardt algorithm, is utilized for the optimization. Dispersion analysis shows that the optimal fourth-order scheme presents less grid dispersion and anisotropy than the conventional fourth-order scheme with respect to different Poisson's ratios. Moreover, only 3.7 grid-points per minimum shear wavelength are required to keep the error of the group velocities below 1%. The memory cost is then greatly reduced due to a coarser sampling. A parallel iterative method named CARP-CG is used to solve the large ill-conditioned linear system for the frequency-domain modeling. Validations are conducted with respect to both the analytic viscoacoustic and viscoelastic solutions. Compared with the conventional fourth-order scheme, the optimal scheme generates wavefields having smaller error under the same discretization setups. Profiles of the wavefields are presented to confirm better agreement between the optimal results and the analytic solutions.
Optimal design of a hybridization scheme with a fuel cell using genetic optimization
NASA Astrophysics Data System (ADS)
Rodriguez, Marco A.
Fuel cell is one of the most dependable "green power" technologies, readily available for immediate application. It enables direct conversion of hydrogen and other gases into electric energy without any pollution of the environment. However, the efficient power generation is strictly stationary process that cannot operate under dynamic environment. Consequently, fuel cell becomes practical only within a specially designed hybridization scheme, capable of power storage and power management functions. The resultant technology could be utilized to its full potential only when both the fuel cell element and the entire hybridization scheme are optimally designed. The design optimization in engineering is among the most complex computational tasks due to its multidimensionality, nonlinearity, discontinuity and presence of constraints in the underlying optimization problem. this research aims at the optimal utilization of the fuel cell technology through the use of genetic optimization, and advance computing. This study implements genetic optimization in the definition of optimum hybridization rules for a PEM fuel cell/supercapacitor power system. PEM fuel cells exhibit high energy density but they are not intended for pulsating power draw applications. They work better in steady state operation and thus, are often hybridized. In a hybrid system, the fuel cell provides power during steady state operation while capacitors or batteries augment the power of the fuel cell during power surges. Capacitors and batteries can also be recharged when the motor is acting as a generator. Making analogies to driving cycles, three hybrid system operating modes are investigated: 'Flat' mode, 'Uphill' mode, and 'Downhill' mode. In the process of discovering the switching rules for these three modes, we also generate a model of a 30W PEM fuel cell. This study also proposes the optimum design of a 30W PEM fuel cell. The PEM fuel cell model and hybridization's switching rules are postulated
Evaluation on different sampling schemes for assessing indoor radon level in Hong Kong
NASA Astrophysics Data System (ADS)
Mui, K. W.; Wong, L. T.
In order to maintain an acceptable indoor air quality (IAQ), policies, strategies and guidelines on achieving the required IAQ have been developed worldwide. In Hong Kong, the Environmental Protection Department (HKEPD) has launched an IAQ certification scheme to promote an acceptable IAQ in workplaces. For the practical radon measurement, an 8-h continuous monitoring is proposed for the assessment purpose. However, the uncertainties and measurement efforts associated with the method have not been detailed. In this study, the probable errors and measurement efforts in measuring the indoor radon concentration by three proposed sampling schemes of various sampling periods have been investigated. Scheme A is to obtain an average concentration over a sampling period in an occupied period; Scheme B is to obtain an average concentration in two sampling periods from two sessions of the occupied period; and for Scheme C, the average concentration in two structural sampling periods from two sessions of the occupied period. In particular, a 1-year measurement of indoor radon concentration in a typical office building has been used as basis to evaluate the probable errors between the long-term average and those obtained by the three measurement schemes. At a certain confidence level, the results show that the measurement time required for Schemes B and C could be reduced significantly, when compared with Scheme A using continuous monitoring. It is recommended to specify the measurement uncertainty and effort in future codes, and the sampling schemes could be considered in determining the practical strategies for radon measurement.
An optimized quantum information splitting scheme with multiple controllers
NASA Astrophysics Data System (ADS)
Jiang, Min
2016-09-01
We propose an efficient scheme for splitting multi-qudit information with cooperative control of multiple agents. Each controller is assigned one controlling qudit, and he can monitor the state sharing of all multi-qudit information. Compared with the existing schemes, our scheme requires less resource consumption and approaches higher communication efficiency. In addition, our proposal involves only generalized Bell-state measurement, single-qudit measurement, one-qudit gates and a unitary-reduction operation, which makes it flexible and achievable for physical implementation.
Clever particle filters, sequential importance sampling and the optimal proposal
NASA Astrophysics Data System (ADS)
Snyder, Chris
2014-05-01
Particle filters rely on sequential importance sampling and it is well known that their performance can depend strongly on the choice of proposal distribution from which new ensemble members (particles) are drawn. The use of clever proposals has seen substantial recent interest in the geophysical literature, with schemes such as the implicit particle filter and the equivalent-weights particle filter. Both these schemes employ proposal distributions at time tk+1 that depend on the state at tk and the observations at time tk+1. I show that, beginning with particles drawn randomly from the conditional distribution of the state at tk given observations through tk, the optimal proposal (the distribution of the state at tk+1 given the state at tk and the observations at tk+1) minimizes the variance of the importance weights for particles at tk overall all possible proposal distributions. This means that bounds on the performance of the optimal proposal, such as those given by Snyder (2011), also bound the performance of the implicit and equivalent-weights particle filters. In particular, in spite of the fact that they may be dramatically more effective than other particle filters in specific instances, those schemes will suffer degeneracy (maximum importance weight approaching unity) unless the ensemble size is exponentially large in a quantity that, in the simplest case that all degrees of freedom in the system are i.i.d., is proportional to the system dimension. I will also discuss the behavior to be expected in more general cases, such as global numerical weather prediction, and how that behavior depends qualitatively on the observing network. Snyder, C., 2012: Particle filters, the "optimal" proposal and high-dimensional systems. Proceedings, ECMWF Seminar on Data Assimilation for Atmosphere and Ocean., 6-9 September 2011.
NASA Astrophysics Data System (ADS)
Cunha, G.; Redonnet, S.
2014-04-01
The present article aims at highlighting the strengths and weaknesses of the so-called spectral-like optimized (explicit central) finite-difference schemes, when the latter are used for numerically approximating spatial derivatives in aeroacoustics evolution problems. With that view, we first remind how differential operators can be approximated using explicit central finite-difference schemes. The possible spectral-like optimization of the latter is then discussed, the advantages and drawbacks of such an optimization being theoretically studied, before they are numerically quantified. For doing so, two popular spectral-like optimized schemes are assessed via a direct comparison against their standard counterparts, such a comparative exercise being conducted for several academic test cases. At the end, general conclusions are drawn, which allows us discussing the way spectral-like optimized schemes shall be preferred (or not) to standard ones, when it comes to simulate real-life aeroacoustics problems.
Optimization of Eosine Analyses in Water Samples
NASA Astrophysics Data System (ADS)
Kola, Liljana
2010-01-01
The fluorescence ability of Eosine enables its using as artificial tracer in the water system studies. The fluorescence intensity of fluorescent dyes in water samples depends on their physical and chemical properties, such as pH, temperature, presence of oxidants, etc. This paper presents the experience of the Center of Applied Nuclear Physics, Tirana, in this field. The problem is dealt with in relation to applying Eosine to trace and determine water movements within the karstic system and underground waters. We have used for this study the standard solutions of Eosine. The method we have elaborated to this purpose made it possible to optimize procedures we use to analyze samples for the presence of Eosine and measure its content, even in trace levels, by the means of a Perkin Elmer LS 55 Luminescence Spectrometer.
Optimization schemes for the inversion of Bouguer gravity anomalies
NASA Astrophysics Data System (ADS)
Zamora, Azucena
associated with structural changes [16]; therefore, it complements those geophysical methods with the same depth resolution that sample a different physical property (e.g. electromagnetic surveys sampling electric conductivity) or even those with different depth resolution sampling an alternative physical property (e.g. large scale seismic reflection surveys imaging the crust and top upper mantle using seismic velocity fields). In order to improve the resolution of Bouguer gravity anomalies, and reduce their ambiguity and uncertainty for the modeling of the shallow crust, we propose the implementation of primal-dual interior point methods for the optimization of density structure models through the introduction of physical constraints for transitional areas obtained from previously acquired geophysical data sets. This dissertation presents in Chapter 2 an initial forward model implementation for the calculation of Bouguer gravity anomalies in the Porphyry Copper-Molybdenum (Cu-Mo) Copper Flat Mine region located in Sierra County, New Mexico. In Chapter 3, we present a constrained optimization framework (using interior-point methods) for the inversion of 2-D models of Earth structures delineating density contrasts of anomalous bodies in uniform regions and/or boundaries between layers in layered environments. We implement the proposed algorithm using three different synthetic gravitational data sets with varying complexity. Specifically, we improve the 2-dimensional density structure models by getting rid of unacceptable solutions (geologically unfeasible models or those not satisfying the required constraints) given the reduction of the solution space. Chapter 4 shows the results from the implementation of our algorithm for the inversion of gravitational data obtained from the area surrounding the Porphyry Cu-Mo Cooper Flat Mine in Sierra County, NM. Information obtained from previous induced polarization surveys and core samples served as physical constraints for the
An efficient scheme for sampling fast dynamics at a low average data acquisition rate.
Philippe, A; Aime, S; Roger, V; Jelinek, R; Prévot, G; Berthier, L; Cipelletti, L
2016-02-24
We introduce a temporal scheme for data sampling, based on a variable delay between two successive data acquisitions. The scheme is designed so as to reduce the average data flow rate, while still retaining the information on the data evolution on fast time scales. The practical implementation of the scheme is discussed and demonstrated in light scattering and microscopy experiments that probe the dynamics of colloidal suspensions using CMOS or CCD cameras as detectors.
Honey Bee Mating Optimization Vector Quantization Scheme in Image Compression
NASA Astrophysics Data System (ADS)
Horng, Ming-Huwi
The vector quantization is a powerful technique in the applications of digital image compression. The traditionally widely used method such as the Linde-Buzo-Gray (LBG) algorithm always generated local optimal codebook. Recently, particle swarm optimization (PSO) is adapted to obtain the near-global optimal codebook of vector quantization. In this paper, we applied a new swarm algorithm, honey bee mating optimization, to construct the codebook of vector quantization. The proposed method is called the honey bee mating optimization based LBG (HBMO-LBG) algorithm. The results were compared with the other two methods that are LBG and PSO-LBG algorithms. Experimental results showed that the proposed HBMO-LBG algorithm is more reliable and the reconstructed images get higher quality than those generated form the other three methods.
Optimization of reference library used in content-based medical image retrieval scheme.
Park, Sang Cheol; Sukthankar, Rahul; Mummert, Lily; Satyanarayanan, Mahadev; Zheng, Bin
2007-11-01
Building an optimal image reference library is a critical step in developing the interactive computer-aided detection and diagnosis (I-CAD) systems of medical images using content-based image retrieval (CBIR) schemes. In this study, the authors conducted two experiments to investigate (1) the relationship between I-CAD performance and size of reference library and (2) a new reference selection strategy to optimize the library and improve I-CAD performance. The authors assembled a reference library that includes 3153 regions of interest (ROI) depicting either malignant masses (1592) or CAD-cued false-positive regions (1561) and an independent testing data set including 200 masses and 200 false-positive regions. A CBIR scheme using a distance-weighted K-nearest neighbor algorithm is applied to retrieve references that are considered similar to the testing sample from the library. The area under receiver operating characteristic curve (Az) is used as an index to evaluate the I-CAD performance. In the first experiment, the authors systematically increased reference library size and tested I-CAD performance. The result indicates that scheme performance improves initially from Az= 0.715 to 0.874 and then plateaus when the library size reaches approximately half of its maximum capacity. In the second experiment, based on the hypothesis that a ROI should be removed if it performs poorly compared to a group of similar ROIs in a large and diverse reference library, the authors applied a new strategy to identify "poorly effective" references. By removing 174 identified ROIs from the reference library, I-CAD performance significantly increases to Az = 0.914 (p < 0.01). The study demonstrates that increasing reference library size and removing poorly effective references can significantly improve I-CAD performance.
Optimal sampling with prior information of the image geometry in microfluidic MRI.
Han, S H; Cho, H; Paulsen, J L
2015-03-01
Recent advances in MRI acquisition for microscopic flows enable unprecedented sensitivity and speed in a portable NMR/MRI microfluidic analysis platform. However, the application of MRI to microfluidics usually suffers from prolonged acquisition times owing to the combination of the required high resolution and wide field of view necessary to resolve details within microfluidic channels. When prior knowledge of the image geometry is available as a binarized image, such as for microfluidic MRI, it is possible to reduce sampling requirements by incorporating this information into the reconstruction algorithm. The current approach to the design of the partial weighted random sampling schemes is to bias toward the high signal energy portions of the binarized image geometry after Fourier transformation (i.e. in its k-space representation). Although this sampling prescription is frequently effective, it can be far from optimal in certain limiting cases, such as for a 1D channel, or more generally yield inefficient sampling schemes at low degrees of sub-sampling. This work explores the tradeoff between signal acquisition and incoherent sampling on image reconstruction quality given prior knowledge of the image geometry for weighted random sampling schemes, finding that optimal distribution is not robustly determined by maximizing the acquired signal but from interpreting its marginal change with respect to the sub-sampling rate. We develop a corresponding sampling design methodology that deterministically yields a near optimal sampling distribution for image reconstructions incorporating knowledge of the image geometry. The technique robustly identifies optimal weighted random sampling schemes and provides improved reconstruction fidelity for multiple 1D and 2D images, when compared to prior techniques for sampling optimization given knowledge of the image geometry.
Optimal sampling with prior information of the image geometry in microfluidic MRI
NASA Astrophysics Data System (ADS)
Han, S. H.; Cho, H.; Paulsen, J. L.
2015-03-01
Recent advances in MRI acquisition for microscopic flows enable unprecedented sensitivity and speed in a portable NMR/MRI microfluidic analysis platform. However, the application of MRI to microfluidics usually suffers from prolonged acquisition times owing to the combination of the required high resolution and wide field of view necessary to resolve details within microfluidic channels. When prior knowledge of the image geometry is available as a binarized image, such as for microfluidic MRI, it is possible to reduce sampling requirements by incorporating this information into the reconstruction algorithm. The current approach to the design of the partial weighted random sampling schemes is to bias toward the high signal energy portions of the binarized image geometry after Fourier transformation (i.e. in its k-space representation). Although this sampling prescription is frequently effective, it can be far from optimal in certain limiting cases, such as for a 1D channel, or more generally yield inefficient sampling schemes at low degrees of sub-sampling. This work explores the tradeoff between signal acquisition and incoherent sampling on image reconstruction quality given prior knowledge of the image geometry for weighted random sampling schemes, finding that optimal distribution is not robustly determined by maximizing the acquired signal but from interpreting its marginal change with respect to the sub-sampling rate. We develop a corresponding sampling design methodology that deterministically yields a near optimal sampling distribution for image reconstructions incorporating knowledge of the image geometry. The technique robustly identifies optimal weighted random sampling schemes and provides improved reconstruction fidelity for multiple 1D and 2D images, when compared to prior techniques for sampling optimization given knowledge of the image geometry.
Optimal sampling with prior information of the image geometry in microfluidic MRI.
Han, S H; Cho, H; Paulsen, J L
2015-03-01
Recent advances in MRI acquisition for microscopic flows enable unprecedented sensitivity and speed in a portable NMR/MRI microfluidic analysis platform. However, the application of MRI to microfluidics usually suffers from prolonged acquisition times owing to the combination of the required high resolution and wide field of view necessary to resolve details within microfluidic channels. When prior knowledge of the image geometry is available as a binarized image, such as for microfluidic MRI, it is possible to reduce sampling requirements by incorporating this information into the reconstruction algorithm. The current approach to the design of the partial weighted random sampling schemes is to bias toward the high signal energy portions of the binarized image geometry after Fourier transformation (i.e. in its k-space representation). Although this sampling prescription is frequently effective, it can be far from optimal in certain limiting cases, such as for a 1D channel, or more generally yield inefficient sampling schemes at low degrees of sub-sampling. This work explores the tradeoff between signal acquisition and incoherent sampling on image reconstruction quality given prior knowledge of the image geometry for weighted random sampling schemes, finding that optimal distribution is not robustly determined by maximizing the acquired signal but from interpreting its marginal change with respect to the sub-sampling rate. We develop a corresponding sampling design methodology that deterministically yields a near optimal sampling distribution for image reconstructions incorporating knowledge of the image geometry. The technique robustly identifies optimal weighted random sampling schemes and provides improved reconstruction fidelity for multiple 1D and 2D images, when compared to prior techniques for sampling optimization given knowledge of the image geometry. PMID:25676820
Sampling scheme for pyrethroids on multiple surfaces on commercial aircrafts.
Mohan, Krishnan R; Weisel, Clifford P
2010-06-01
A wipe sampler for the collection of permethrin from soft and hard surfaces has been developed for use in aircraft. "Disinsection" or application of pesticides, predominantly pyrethrods, inside commercial aircraft is routinely required by some countries and is done on an as-needed basis by airlines resulting in potential pesticide dermal and inhalation exposures to the crew and passengers. A wipe method using filter paper and water was evaluated for both soft and hard aircraft surfaces. Permethrin was analyzed by GC/MS after its ultrasonication extraction from the sampling medium into hexane and volume reduction. Recoveries, based on spraying known levels of permethrin, were 80-100% from table trays, seat handles and rugs; and 40-50% from seat cushions. The wipe sampler is easy to use, requires minimum training, is compatible with the regulations on what can be brought through security for use on commercial aircraft, and readily adaptable for use in residential and other settings.
Hybrid optimization schemes for simulation-based problems.
Fowler, Katie; Gray, Genetha Anne; Griffin, Joshua D.
2010-05-01
The inclusion of computer simulations in the study and design of complex engineering systems has created a need for efficient approaches to simulation-based optimization. For example, in water resources management problems, optimization problems regularly consist of objective functions and constraints that rely on output from a PDE-based simulator. Various assumptions can be made to simplify either the objective function or the physical system so that gradient-based methods apply, however the incorporation of realistic objection functions can be accomplished given the availability of derivative-free optimization methods. A wide variety of derivative-free methods exist and each method has both advantages and disadvantages. Therefore, to address such problems, we propose a hybrid approach, which allows the combining of beneficial elements of multiple methods in order to more efficiently search the design space. Specifically, in this paper, we illustrate the capabilities of two novel algorithms; one which hybridizes pattern search optimization with Gaussian Process emulation and the other which hybridizes pattern search and a genetic algorithm. We describe the hybrid methods and give some numerical results for a hydrological application which illustrate that the hybrids find an optimal solution under conditions for which traditional optimal search methods fail.
Resource optimization scheme for multimedia-enabled wireless mesh networks.
Ali, Amjad; Ahmed, Muhammad Ejaz; Piran, Md Jalil; Suh, Doug Young
2014-08-08
Wireless mesh networking is a promising technology that can support numerous multimedia applications. Multimedia applications have stringent quality of service (QoS) requirements, i.e., bandwidth, delay, jitter, and packet loss ratio. Enabling such QoS-demanding applications over wireless mesh networks (WMNs) require QoS provisioning routing protocols that lead to the network resource underutilization problem. Moreover, random topology deployment leads to have some unused network resources. Therefore, resource optimization is one of the most critical design issues in multi-hop, multi-radio WMNs enabled with multimedia applications. Resource optimization has been studied extensively in the literature for wireless Ad Hoc and sensor networks, but existing studies have not considered resource underutilization issues caused by QoS provisioning routing and random topology deployment. Finding a QoS-provisioned path in wireless mesh networks is an NP complete problem. In this paper, we propose a novel Integer Linear Programming (ILP) optimization model to reconstruct the optimal connected mesh backbone topology with a minimum number of links and relay nodes which satisfies the given end-to-end QoS demands for multimedia traffic and identification of extra resources, while maintaining redundancy. We further propose a polynomial time heuristic algorithm called Link and Node Removal Considering Residual Capacity and Traffic Demands (LNR-RCTD). Simulation studies prove that our heuristic algorithm provides near-optimal results and saves about 20% of resources from being wasted by QoS provisioning routing and random topology deployment.
Resource Optimization Scheme for Multimedia-Enabled Wireless Mesh Networks
Ali, Amjad; Ahmed, Muhammad Ejaz; Piran, Md. Jalil; Suh, Doug Young
2014-01-01
Wireless mesh networking is a promising technology that can support numerous multimedia applications. Multimedia applications have stringent quality of service (QoS) requirements, i.e., bandwidth, delay, jitter, and packet loss ratio. Enabling such QoS-demanding applications over wireless mesh networks (WMNs) require QoS provisioning routing protocols that lead to the network resource underutilization problem. Moreover, random topology deployment leads to have some unused network resources. Therefore, resource optimization is one of the most critical design issues in multi-hop, multi-radio WMNs enabled with multimedia applications. Resource optimization has been studied extensively in the literature for wireless Ad Hoc and sensor networks, but existing studies have not considered resource underutilization issues caused by QoS provisioning routing and random topology deployment. Finding a QoS-provisioned path in wireless mesh networks is an NP complete problem. In this paper, we propose a novel Integer Linear Programming (ILP) optimization model to reconstruct the optimal connected mesh backbone topology with a minimum number of links and relay nodes which satisfies the given end-to-end QoS demands for multimedia traffic and identification of extra resources, while maintaining redundancy. We further propose a polynomial time heuristic algorithm called Link and Node Removal Considering Residual Capacity and Traffic Demands (LNR-RCTD). Simulation studies prove that our heuristic algorithm provides near-optimal results and saves about 20% of resources from being wasted by QoS provisioning routing and random topology deployment. PMID:25111241
Effect of different sampling schemes on the spatial placement of conservation reserves in Utah, USA
Bassett, S.D.; Edwards, T.C.
2003-01-01
We evaluated the effect of three different sampling schemes used to organize spatially explicit biological information had on the spatial placement of conservation reserves in Utah, USA. The three sampling schemes consisted of a hexagon representation developed by the EPA/EMAP program (statistical basis), watershed boundaries (ecological), and the current county boundaries of Utah (socio-political). Four decision criteria were used to estimate effects, including amount of area, length of edge, lowest number of contiguous reserves, and greatest number of terrestrial vertebrate species covered. A fifth evaluation criterion was the effect each sampling scheme had on the ability of the modeled conservation reserves to cover the six major ecoregions found in Utah. Of the three sampling schemes, county boundaries covered the greatest number of species, but also created the longest length of edge and greatest number of reserves. Watersheds maximized species coverage using the least amount of area. Hexagons and watersheds provide the least amount of edge and fewest number of reserves. Although there were differences in area, edge and number of reserves among the sampling schemes, all three schemes covered all the major ecoregions in Utah and their inclusive biodiversity. ?? 2003 Elsevier Science Ltd. All rights reserved.
Robinson, Y Harold; Rajaram, M
2015-01-01
Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique. PMID:26819966
Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks
Robinson, Y. Harold; Rajaram, M.
2015-01-01
Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique. PMID:26819966
Robinson, Y Harold; Rajaram, M
2015-01-01
Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique.
Finite volume schemes optimized for low numerical dispersion and their aeroacoustic applications
NASA Astrophysics Data System (ADS)
Nance, Douglas Vinson
1997-11-01
The field of computational aeroacoustics is concerned with the calculation of acoustic fluctuations in an aerodynamic flow field. Moreover, it is desirable to resolve the spectral content and directivity of the aeroacoustic field with high accuracy. For the purposes of the designer, it is preferable to endow a computational fluid dynamics code with some capability for predicting aeroacoustic information. If the prediction algorithm can be written within the current flow solver's structure, the costly acquisition of a new code is not necessary. In an effort to provide designers with this option, a new finite volume methodology is developed in the present work. Three families of upwind, finite volume schemes are developed and demonstrated for a series of aeroacoustics problems. These new low dispersion finite volume schemes are designed to mitigate numerical dispersion and dissipation errors in the computational space while achieving high formal orders of accuracy. Variable extrapolation stands as the framework for these methods. In this case, the cell face variables are interpolated from cell nodes by using a procedure that optimizes the stencil representation of flow field properties in terms of sinusoidal waves. This procedure renders an accurate representation of these properties for a higher range of numerical wavenumbers. In addition, an unsteady, farfield boundary treatment is proposed. This low reflectivity farfield boundary treatment is designed as an integral part of the finite volume discretization procedure. This technique is very robust and causes only minimal reflection at the farfield boundary. The low dispersion finite volume schemes have been applied to a number of aeroacoustics problems. The numerical results are shown and compared either to exact solutions or to the results computed by other schemes. Good agreement with the exact solutions is evident. Results are also shown for the problem of laminar vortex- shedding from a circular cylinder. The
Zou Xubo; Mathis, W.
2005-08-15
We propose a scheme to realize the optimal universal quantum cloning of the polarization state of the photons in context of a microwave cavity quantum electrodynamics. The scheme is based on the resonant interaction of three-level {lambda}-type atoms with two cavity modes. The operation requires atoms to fly one by one through the cavity. The interaction time between each of the atoms and the cavity is appropriately controlled by using a velocity selector. The scheme is deterministic, and is feasible by the current experimental technology.
NASA Astrophysics Data System (ADS)
Zou, Xubo; Mathis, W.
2005-08-01
We propose a scheme to realize the optimal universal quantum cloning of the polarization state of the photons in context of a microwave cavity quantum electrodynamics. The scheme is based on the resonant interaction of three-level Λ -type atoms with two cavity modes. The operation requires atoms to fly one by one through the cavity. The interaction time between each of the atoms and the cavity is appropriately controlled by using a velocity selector. The scheme is deterministic, and is feasible by the current experimental technology.
A numerical scheme for optimal transition paths of stochastic chemical kinetic systems
Liu Di
2008-10-01
We present a new framework for finding the optimal transition paths of metastable stochastic chemical kinetic systems with large system size. The optimal transition paths are identified to be the most probable paths according to the Large Deviation Theory of stochastic processes. Dynamical equations for the optimal transition paths are derived using the variational principle. A modified Minimum Action Method (MAM) is proposed as a numerical scheme to solve the optimal transition paths. Applications to Gene Regulatory Networks such as the toggle switch model and the Lactose Operon Model in Escherichia coli are presented as numerical examples.
Ball, Frank; Britton, Tom; Lyne, Owen
2004-09-01
This paper treats a stochastic model for an SIR (susceptible-->infective-->removed) multitype household epidemic. The community is assumed to be closed, individuals are of different types and each individual belongs to a household. Previously obtained probabilistic and inferential results for the model are used to derive the optimal vaccination scheme. By this is meant the scheme that vaccinates the fewest among all vaccination schemes that reduce the threshold parameter below 1. This is done for the situation where all model parameters are known and also for the case where parameters are estimated from an outbreak in the community prior to vaccination. It is shown that the algorithm which chooses vaccines sequentially, at each step selecting the individual which reduces the threshold parameter the most, is not in general an optimal scheme. As a consequence, explicit characterisation of the optimal scheme is only possible in certain special cases. Two different types of vaccine responses, leaky and all-or-nothing, are considered and compared for the problems mentioned above. The methods are illustrated with some numerical examples. PMID:15312742
Simultaneous optimization of dose distributions and fractionation schemes in particle radiotherapy
Unkelbach, Jan; Zeng, Chuan; Engelsman, Martijn
2013-09-15
Purpose: The paper considers the fractionation problem in intensity modulated proton therapy (IMPT). Conventionally, IMPT fields are optimized independently of the fractionation scheme. In this work, we discuss the simultaneous optimization of fractionation scheme and pencil beam intensities.Methods: This is performed by allowing for distinct pencil beam intensities in each fraction, which are optimized using objective and constraint functions based on biologically equivalent dose (BED). The paper presents a model that mimics an IMPT treatment with a single incident beam direction for which the optimal fractionation scheme can be determined despite the nonconvexity of the BED-based treatment planning problem.Results: For this model, it is shown that a small α/β ratio in the tumor gives rise to a hypofractionated treatment, whereas a large α/β ratio gives rise to hyperfractionation. It is further demonstrated that, for intermediate α/β ratios in the tumor, a nonuniform fractionation scheme emerges, in which it is optimal to deliver different dose distributions in subsequent fractions. The intuitive explanation for this phenomenon is as follows: By varying the dose distribution in the tumor between fractions, the same total BED can be achieved with a lower physical dose. If it is possible to achieve this dose variation in the tumor without varying the dose in the normal tissue (which would have an adverse effect), the reduction in physical dose may lead to a net reduction of the normal tissue BED. For proton therapy, this is indeed possible to some degree because the entrance dose is mostly independent of the range of the proton pencil beam.Conclusions: The paper provides conceptual insight into the interdependence of optimal fractionation schemes and the spatial optimization of dose distributions. It demonstrates the emergence of nonuniform fractionation schemes that arise from the standard BED model when IMPT fields and fractionation scheme are optimized
Sample size and optimal sample design in tuberculosis surveys
Sánchez-Crespo, J. L.
1967-01-01
Tuberculosis surveys sponsored by the World Health Organization have been carried out in different communities during the last few years. Apart from the main epidemiological findings, these surveys have provided basic statistical data for use in the planning of future investigations. In this paper an attempt is made to determine the sample size desirable in future surveys that include one of the following examinations: tuberculin test, direct microscopy, and X-ray examination. The optimum cluster sizes are found to be 100-150 children under 5 years of age in the tuberculin test, at least 200 eligible persons in the examination for excretors of tubercle bacilli (direct microscopy) and at least 500 eligible persons in the examination for persons with radiological evidence of pulmonary tuberculosis (X-ray). Modifications of the optimum sample size in combined surveys are discussed. PMID:5300008
NASA Astrophysics Data System (ADS)
Okayama, Hideaki; Onawa, Yosuke; Shimura, Daisuke; Yaegashi, Hiroki; Sasaki, Hironori
2016-08-01
We describe a Bragg grating with a phase shift section and a sampled grating scheme that converts input polarization to orthogonal polarization. A very narrow polarization-independent wavelength peak can be generated by phase shift structures and polarization-independent multiple diffraction peaks by sampled gratings. The characteristics of the device were examined by transfer matrix and finite-difference time-domain methods.
Optimal policy for labeling training samples
NASA Astrophysics Data System (ADS)
Lipsky, Lester; Lopresti, Daniel; Nagy, George
2013-01-01
Confirming the labels of automatically classified patterns is generally faster than entering new labels or correcting incorrect labels. Most labels assigned by a classifier, even if trained only on relatively few pre-labeled patterns, are correct. Therefore the overall cost of human labeling can be decreased by interspersing labeling and classification. Given a parameterized model of the error rate as an inverse power law function of the size of the training set, the optimal splits can be computed rapidly. Projected savings in operator time are over 60% for a range of empirical error functions for hand-printed digit classification with ten different classifiers.
NASA Astrophysics Data System (ADS)
Gall, Heather E.; Jafvert, Chad T.; Jenkinson, Byron
2010-11-01
Automated sample collection for water quality research and evaluation generally is performed by simple time-paced or flow-weighted sampling protocols. However, samples collected on strict time-paced or flow-weighted schemes may not adequately capture all elements of storm event hydrographs (i.e., rise, peak, and recession). This can result in inadequate information for calculating chemical mass flux over storm events. In this research, an algorithm was developed to guide automated sampling of hydrographs based on storm-specific information. A key element of the new "hydrograph-specific sampling scheme" is the use of a hydrograph recession model for predicting the hydrograph recession curve, during which flow-paced intervals are calculated for scheduling the remaining samples. The algorithm was tested at a tile drained Midwest agricultural site where real-time flow data were processed by a programmable datalogger that in turn activated an automated sampler at the appropriate sampling times to collect a total of twenty samples during each storm event independent of the number of sequential hydrographs generated. The utility of the algorithm was successfully tested with hydrograph data collected at both a tile drain and agricultural ditch, suggesting the potential for general applicability of the method. This sampling methodology is flexible in that the logic can be adapted for use with any hydrograph recession model; however, in this case a power law equation proved to be the most practical model.
The optimal sampling strategy for unfamiliar prey.
Sherratt, Thomas N
2011-07-01
Precisely how predators solve the problem of sampling unfamiliar prey types is central to our understanding of the evolution of a variety of antipredator defenses, ranging from Müllerian mimicry to polymorphism. When predators encounter a novel prey item then they must decide whether to take a risk and attack it, thereby gaining a potential meal and valuable information, or avoid such prey altogether. Moreover, if predators initially attack the unfamiliar prey, then at some point(s) they should decide to cease sampling if evidence mounts that the type is on average unprofitable to attack. Here, I cast this problem as a "two-armed bandit," the standard metaphor for exploration-exploitation trade-offs. I assume that as predators encounter and attack unfamiliar prey they use Bayesian inference to update both their beliefs as to the likelihood that individuals of this type are chemically defended, and the probability of seeing the prey type in the future. I concurrently use dynamic programming to identify the critical informational states at which predator should cease sampling. The model explains why predators sample more unprofitable prey before complete rejection when the prey type is common and explains why predators exhibit neophobia when the unfamiliar prey type is perceived to be rare.
Optimized finite-difference (DRP) schemes perform poorly for decaying or growing oscillations
NASA Astrophysics Data System (ADS)
Brambley, E. J.
2016-11-01
Computational aeroacoustics often use finite difference schemes optimized to require relatively few points per wavelength; such optimized schemes are often called Dispersion Relation Preserving (DRP). Similar techniques are also used outside aeroacoustics. Here the question is posed: what is the equivalent of points per wavelength for growing or decaying waves, and how well are such waves resolved numerically? Such non-constant-amplitude waves are common in aeroacoustics, such as the exponential decay caused by acoustic linings, the O (1 / r) decay of an expanding spherical wave, and the decay of high-azimuthal-order modes in the radial direction towards the centre of a cylindrical duct. It is shown that optimized spatial derivatives perform poorly for waves that are not of constant amplitude, under performing maximal-order schemes. An equivalent criterion to points per wavelength is proposed for non-constant-amplitude oscillations, reducing to the standard definition for constant-amplitude oscillations and valid even for pure growth or decay with no oscillation. Using this definition, coherent statements about points per wavelength necessary for a given accuracy can be made for maximal-order schemes applied to non-constant-amplitude oscillations. These features are illustrated through a numerical example of a one-dimensional wave propagating through a damping region.
NASA Astrophysics Data System (ADS)
Aristova, E. N.; Rogov, B. V.; Chikitkin, A. V.
2016-06-01
A hybrid scheme is proposed for solving the nonstationary inhomogeneous transport equation. The hybridization procedure is based on two baseline schemes: (1) a bicompact one that is fourth-order accurate in all space variables and third-order accurate in time and (2) a monotone first-order accurate scheme from the family of short characteristic methods with interpolation over illuminated faces. It is shown that the first-order accurate scheme has minimal dissipation, so it is called optimal. The solution of the hybrid scheme depends locally on the solutions of the baseline schemes at each node of the space-time grid. A monotonization procedure is constructed continuously and uniformly in all mesh cells so as to keep fourth-order accuracy in space and third-order accuracy in time in domains where the solution is smooth, while maintaining a high level of accuracy in domains of discontinuous solution. Due to its logical simplicity and uniformity, the algorithm is well suited for supercomputer simulation.
High-order sampling schemes for path integrals and Gaussian chain simulations of polymers
Müser, Martin H.; Müller, Marcus
2015-05-07
In this work, we demonstrate that path-integral schemes, derived in the context of many-body quantum systems, benefit the simulation of Gaussian chains representing polymers. Specifically, we show how to decrease discretization corrections with little extra computation from the usual O(1/P{sup 2}) to O(1/P{sup 4}), where P is the number of beads representing the chains. As a consequence, high-order integrators necessitate much smaller P than those commonly used. Particular emphasis is placed on the questions of how to maintain this rate of convergence for open polymers and for polymers confined by a hard wall as well as how to ensure efficient sampling. The advantages of the high-order sampling schemes are illustrated by studying the surface tension of a polymer melt and the interface tension in a binary homopolymers blend.
Optimal flexible sample size design with robust power.
Zhang, Lanju; Cui, Lu; Yang, Bo
2016-08-30
It is well recognized that sample size determination is challenging because of the uncertainty on the treatment effect size. Several remedies are available in the literature. Group sequential designs start with a sample size based on a conservative (smaller) effect size and allow early stop at interim looks. Sample size re-estimation designs start with a sample size based on an optimistic (larger) effect size and allow sample size increase if the observed effect size is smaller than planned. Different opinions favoring one type over the other exist. We propose an optimal approach using an appropriate optimality criterion to select the best design among all the candidate designs. Our results show that (1) for the same type of designs, for example, group sequential designs, there is room for significant improvement through our optimization approach; (2) optimal promising zone designs appear to have no advantages over optimal group sequential designs; and (3) optimal designs with sample size re-estimation deliver the best adaptive performance. We conclude that to deal with the challenge of sample size determination due to effect size uncertainty, an optimal approach can help to select the best design that provides most robust power across the effect size range of interest. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26999385
Optimization of Compton-suppression and summing schemes for the TIGRESS HPGe detector array
NASA Astrophysics Data System (ADS)
Schumaker, M. A.; Svensson, C. E.; Andreoiu, C.; Andreyev, A.; Austin, R. A. E.; Ball, G. C.; Bandyopadhyay, D.; Boston, A. J.; Chakrawarthy, R. S.; Churchman, R.; Drake, T. E.; Finlay, P.; Garrett, P. E.; Grinyer, G. F.; Hackman, G.; Hyland, B.; Jones, B.; Maharaj, R.; Morton, A. C.; Pearson, C. J.; Phillips, A. A.; Sarazin, F.; Scraggs, H. C.; Smith, M. B.; Valiente-Dobón, J. J.; Waddington, J. C.; Watters, L. M.
2007-04-01
Methods of optimizing the performance of an array of Compton-suppressed, segmented HPGe clover detectors have been developed which rely on the physical position sensitivity of both the HPGe crystals and the Compton-suppression shields. These relatively simple analysis procedures promise to improve the precision of experiments with the TRIUMF-ISAC Gamma-Ray Escape-Suppressed Spectrometer (TIGRESS). Suppression schemes will improve the efficiency and peak-to-total ratio of TIGRESS for high γ-ray multiplicity events by taking advantage of the 20-fold segmentation of the Compton-suppression shields, while the use of different summing schemes will improve results for a wide range of experimental conditions. The benefits of these methods are compared for many γ-ray energies and multiplicities using a GEANT4 simulation, and the optimal physical configuration of the TIGRESS array under each set of conditions is determined.
Agrawal, Gaurav; Kawajiri, Yoshiaki
2012-05-18
Over the past decade, many modifications have been proposed in simulated moving bed (SMB) chromatography in order to effectively separate a binary mixture. However, the separation of multi-component mixtures using SMB is still one of the major challenges. In addition, the performance of SMB system highly depends on its operating conditions. Our study address this issue by formulating a multi-objective optimization problem that maximizes the productivity and purity of intermediate eluting component at the same time. A number of optimized isocractic ternary SMB operating schemes are compared both in terms of productivity and amount of desorbent to feed ratio. Furthermore, we propose a generalized full cycle (GFC) formulation based on superstructure formulation encompassing numerous operating schemes proposed in the literature. We also demonstrate that this approach has a potential to find the best ternary separation strategy among various alternatives. PMID:22498352
Comparison of rainfall sampling schemes using a calibrated stochastic rainfall generator
Welles, E.
1994-12-31
Accurate rainfall measurements are critical to river flow predictions. Areal and gauge rainfall measurements create different descriptions of the same storms. The purpose of this study is to characterize those differences. A stochastic rainfall generator was calibrated using an automatic search algorithm. Statistics describing several rainfall characteristics of interest were used in the error function. The calibrated model was then used to generate storms which were exhaustively sampled, sparsely sampled and sampled areally with 4 x 4 km grids. The sparsely sampled rainfall was also kriged to 4 x 4 km blocks. The differences between the four schemes were characterized by comparing statistics computed from each of the sampling methods. The possibility of predicting areal statistics from gauge statistics was explored. It was found that areally measured storms appeared to move more slowly, appeared larger, appeared less intense and have shallower intensity gradients.
NASA Astrophysics Data System (ADS)
Schoettle, U. M.; Hillesheimer, M.
1991-08-01
An iterative multistep procedure for performance optimization of launch vehicles is described, which is being developed to support trade-off and sensitivity studies. Two major steps involved in the automated technique are the optimum trajectory shaping employing approximate control models and the vehicle design. Both aspects are discussed in this paper. Simulation examples are presented, first to demonstrate the approach taken for flight path optimization; second, to verify the coupled trajectory and design optimization procedure; and finally, to assess the impact of different mission requirements on an airbreathing Saenger-type vehicle.
Optimization of Dengue Epidemics: A Test Case with Different Discretization Schemes
NASA Astrophysics Data System (ADS)
Rodrigues, Helena Sofia; Monteiro, M. Teresa T.; Torres, Delfim F. M.
2009-09-01
The incidence of Dengue epidemiologic disease has grown in recent decades. In this paper an application of optimal control in Dengue epidemics is presented. The mathematical model includes the dynamic of Dengue mosquito, the affected persons, the people's motivation to combat the mosquito and the inherent social cost of the disease, such as cost with ill individuals, educations and sanitary campaigns. The dynamic model presents a set of nonlinear ordinary differential equations. The problem was discretized through Euler and Runge Kutta schemes, and solved using nonlinear optimization packages. The computational results as well as the main conclusions are shown.
Xing, Changhu; Jensen, Colby; Folsom, Charles; Ban, Heng; Marshall, Douglas W.
2014-01-01
In the guarded cut-bar technique, a guard surrounding the measured sample and reference (meter) bars is temperature controlled to carefully regulate heat losses from the sample and reference bars. Guarding is typically carried out by matching the temperature profiles between the guard and the test stack of sample and meter bars. Problems arise in matching the profiles, especially when the thermal conductivitiesof the meter bars and of the sample differ, as is usually the case. In a previous numerical study, the applied guarding condition (guard temperature profile) was found to be an important factor in measurement accuracy. Different from the linear-matched or isothermal schemes recommended in literature, the optimal guarding condition is dependent on the system geometry and thermal conductivity ratio of sample to meter bar. To validate the numerical results, an experimental study was performed to investigate the resulting error under different guarding conditions using stainless steel 304 as both the sample and meter bars. The optimal guarding condition was further verified on a certified reference material, pyroceram 9606, and 99.95% pure iron whose thermal conductivities are much smaller and much larger, respectively, than that of the stainless steel meter bars. Additionally, measurements are performed using three different inert gases to show the effect of the insulation effective thermal conductivity on measurement error, revealing low conductivity, argon gas, gives the lowest error sensitivity when deviating from the optimal condition. The result of this study provides a general guideline for the specific measurement method and for methods requiring optimal guarding or insulation.
Sampling optimization for printer characterization by direct search.
Bianco, Simone; Schettini, Raimondo
2012-12-01
Printer characterization usually requires many printer inputs and corresponding color measurements of the printed outputs. In this brief, a sampling optimization for printer characterization on the basis of direct search is proposed to maintain high color accuracy with a reduction in the number of characterization samples required. The proposed method is able to match a given level of color accuracy requiring, on average, a characterization set cardinality which is almost one-fourth of that required by the uniform sampling, while the best method in the state of the art needs almost one-third. The number of characterization samples required can be further reduced if the proposed algorithm is coupled with a sequential optimization method that refines the sample values in the device-independent color space. The proposed sampling optimization method is extended to deal with multiple substrates simultaneously, giving statistically better colorimetric accuracy (at the α = 0.05 significance level) than sampling optimization techniques in the state of the art optimized for each individual substrate, thus allowing use of a single set of characterization samples for multiple substrates.
In-depth analysis of sampling optimization methods
NASA Astrophysics Data System (ADS)
Lee, Honggoo; Han, Sangjun; Kim, Myoungsoo; Habets, Boris; Buhl, Stefan; Guhlemann, Steffen; Rößiger, Martin; Bellmann, Enrico; Kim, Seop
2016-03-01
High order overlay and alignment models require good coverage of overlay or alignment marks on the wafer. But dense sampling plans are not possible for throughput reasons. Therefore, sampling plan optimization has become a key issue. We analyze the different methods for sampling optimization and discuss the different knobs to fine-tune the methods to constraints of high volume manufacturing. We propose a method to judge sampling plan quality with respect to overlay performance, run-to-run stability and dispositioning criteria using a number of use cases from the most advanced lithography processes.
Optimal sample size allocation for Welch's test in one-way heteroscedastic ANOVA.
Shieh, Gwowen; Jan, Show-Li
2015-06-01
The determination of an adequate sample size is a vital aspect in the planning stage of research studies. A prudent strategy should incorporate all of the critical factors and cost considerations into sample size calculations. This study concerns the allocation schemes of group sizes for Welch's test in a one-way heteroscedastic ANOVA. Optimal allocation approaches are presented for minimizing the total cost while maintaining adequate power and for maximizing power performance for a fixed cost. The commonly recommended ratio of sample sizes is proportional to the ratio of the population standard deviations or the ratio of the population standard deviations divided by the square root of the ratio of the unit sampling costs. Detailed numerical investigations have shown that these usual allocation methods generally do not give the optimal solution. The suggested procedures are illustrated using an example of the cost-efficiency evaluation in multidisciplinary pain centers.
Li, Jianzhong
2014-04-21
In this paper, a novel secure optimal image watermarking scheme using an encrypted gyrator transform computer generated hologram (CGH) in the contourlet domain is presented. A new encrypted CGH technique, which is based on the gyrator transform, the random phase mask, the three-step phase-shifting interferometry and the Fibonacci transform, has been proposed to produce a hologram of a watermark first. With the huge key space of the encrypted CGH, the security strength of the watermarking system is enhanced. To achieve better imperceptibility, an improved quantization embedding algorithm is proposed to embed the encrypted CGH into the low frequency sub-band of the contourlet-transformed host image. In order to obtain the highest possible robustness without losing the imperceptibility, particle swarm optimization algorithm is employed to search the optimal embedding parameter of the watermarking system. In comparison with other method, the proposed watermarking scheme offers better performances for both imperceptibility and robustness. Experimental results demonstrate that the proposed image watermarking is not only secure and invisible, but also robust against a variety of attacks.
Li, Jianzhong
2014-04-21
In this paper, a novel secure optimal image watermarking scheme using an encrypted gyrator transform computer generated hologram (CGH) in the contourlet domain is presented. A new encrypted CGH technique, which is based on the gyrator transform, the random phase mask, the three-step phase-shifting interferometry and the Fibonacci transform, has been proposed to produce a hologram of a watermark first. With the huge key space of the encrypted CGH, the security strength of the watermarking system is enhanced. To achieve better imperceptibility, an improved quantization embedding algorithm is proposed to embed the encrypted CGH into the low frequency sub-band of the contourlet-transformed host image. In order to obtain the highest possible robustness without losing the imperceptibility, particle swarm optimization algorithm is employed to search the optimal embedding parameter of the watermarking system. In comparison with other method, the proposed watermarking scheme offers better performances for both imperceptibility and robustness. Experimental results demonstrate that the proposed image watermarking is not only secure and invisible, but also robust against a variety of attacks. PMID:24787882
McGregor, D.A.
1993-07-01
The purpose of the Human Genome Project is outlined followed by a discussion of electrophoresis in slab gels and capillaries and its application to deoxyribonucleic acid (DNA). Techniques used to modify electroosmotic flow in capillaries are addressed. Several separation and detection schemes for DNA via gel and capillary electrophoresis are described. Emphasis is placed on the elucidation of DNA fragment size in real time and shortening separation times to approximate real time monitoring. The migration of DNA fragment bands through a slab gel can be monitored by UV absorption at 254 nm and imaged by a charge coupled device (CCD) camera. Background correction and immediate viewing of band positions to interactively change the field program in pulsed-field gel electrophoresis are possible throughout the separation. The use of absorption removes the need for staining or radioisotope labeling thereby simplifying sample preparation and reducing hazardous waste generation. This leaves the DNA in its native state and further analysis can be performed without de-staining. The optimization of several parameters considerably reduces total analysis time. DNA from 2 kb to 850 kb can be separated in 3 hours on a 7 cm gel with interactive control of the pulse time, which is 10 times faster than the use of a constant field program. The separation of {Phi}X174RF DNA-HaeIII fragments is studied in a 0.5% methyl cellulose polymer solution as a function of temperature and applied voltage. The migration times decreased with both increasing temperature and increasing field strength, as expected. The relative migration rates of the fragments do not change with temperature but are affected by the applied field. Conditions were established for the separation of the 271/281 bp fragments, even without the addition of intercalating agents. At 700 V/cm and 20{degrees}C, all fragments are separated in less than 4 minutes with an average plate number of 2.5 million per meter.
NASA Astrophysics Data System (ADS)
Jacobson, Gloria; Rella, Chris; Farinas, Alejandro
2014-05-01
Technological advancement of instrumentation in atmospheric and other geoscience disciplines over the past decade has lead to a shift from discrete sample analysis to continuous, in-situ monitoring. Standard error analysis used for discrete measurements is not sufficient to assess and compare the error contribution of noise and drift from continuous-measurement instruments, and a different statistical analysis approach should be applied. The Allan standard deviation analysis technique developed for atomic clock stability assessment by David W. Allan [1] can be effectively and gainfully applied to continuous measurement instruments. As an example, P. Werle et al has applied these techniques to look at signal averaging for atmospheric monitoring by Tunable Diode-Laser Absorption Spectroscopy (TDLAS) [2]. This presentation will build on, and translate prior foundational publications to provide contextual definitions and guidelines for the practical application of this analysis technique to continuous scientific measurements. The specific example of a Picarro G2401 Cavity Ringdown Spectroscopy (CRDS) analyzer used for continuous, atmospheric monitoring of CO2, CH4 and CO will be used to define the basics features the Allan deviation, assess factors affecting the analysis, and explore the time-series to Allan deviation plot translation for different types of instrument noise (white noise, linear drift, and interpolated data). In addition, the useful application of using an Allan deviation to optimize and predict the performance of different calibration schemes will be presented. Even though this presentation will use the specific example of the Picarro G2401 CRDS Analyzer for atmospheric monitoring, the objective is to present the information such that it can be successfully applied to other instrument sets and disciplines. [1] D.W. Allan, "Statistics of Atomic Frequency Standards," Proc, IEEE, vol. 54, pp 221-230, Feb 1966 [2] P. Werle, R. Miicke, F. Slemr, "The Limits
NASA Astrophysics Data System (ADS)
Kim, Soo Mee; Lee, Jae Sung; Lee, Chun Sik; Kim, Chan Hyeong; Lee, Myung Chul; Lee, Dong Soo; Lee, Soo-Jin
2010-09-01
Although the ordered subset expectation maximization (OSEM) algorithm does not converge to a true maximum likelihood solution, it is known to provide a good solution if the projections that constitute each subset are reasonably balanced. The Compton scattered data can be allocated to subsets using scattering angles (SA) or detected positions (DP) or a combination of the two (AP (angles and positions)). To construct balanced subsets, the data were first arranged using three ordering schemes: the random ordering scheme (ROS), the multilevel ordering scheme (MLS) and the weighted-distance ordering scheme (WDS). The arranged data were then split into J subsets. To compare the three ordering schemes, we calculated the coefficients of variation (CVs) of angular and positional differences between the arranged data and the percentage errors between mathematical phantoms and reconstructed images. All ordering schemes showed an order-of-magnitude acceleration over the standard EM, and their computation times were similar. The SA-based MLS and the DP-based WDS led to the best-balanced subsets (they provided the largest angular and positional differences for SA- and DP-based arrangements, respectively). The WDS exhibited minimum CVs for both the SA- and DP-based arrangements (the deviation in mean angular and positional differences between the ordered subsets was smallest). The combination of AP and WDS yielded the best results with the lowest percentage errors by providing larger and more uniform angular and positional differences for the SA and DP arrangements, and thus, is probably optimal Compton camera reconstruction using OSEM.
Kim, Soo Mee; Lee, Jae Sung; Lee, Chun Sik; Kim, Chan Hyeong; Lee, Myung Chul; Lee, Dong Soo; Lee, Soo-Jin
2010-09-01
Although the ordered subset expectation maximization (OSEM) algorithm does not converge to a true maximum likelihood solution, it is known to provide a good solution if the projections that constitute each subset are reasonably balanced. The Compton scattered data can be allocated to subsets using scattering angles (SA) or detected positions (DP) or a combination of the two (AP (angles and positions)). To construct balanced subsets, the data were first arranged using three ordering schemes: the random ordering scheme (ROS), the multilevel ordering scheme (MLS) and the weighted-distance ordering scheme (WDS). The arranged data were then split into J subsets. To compare the three ordering schemes, we calculated the coefficients of variation (CVs) of angular and positional differences between the arranged data and the percentage errors between mathematical phantoms and reconstructed images. All ordering schemes showed an order-of-magnitude acceleration over the standard EM, and their computation times were similar. The SA-based MLS and the DP-based WDS led to the best-balanced subsets (they provided the largest angular and positional differences for SA- and DP-based arrangements, respectively). The WDS exhibited minimum CVs for both the SA- and DP-based arrangements (the deviation in mean angular and positional differences between the ordered subsets was smallest). The combination of AP and WDS yielded the best results with the lowest percentage errors by providing larger and more uniform angular and positional differences for the SA and DP arrangements, and thus, is probably optimal Compton camera reconstruction using OSEM.
Tan, Maxine; Pu, Jiantao; Zheng, Bin
2014-01-01
Purpose: Selecting optimal features from a large image feature pool remains a major challenge in developing computer-aided detection (CAD) schemes of medical images. The objective of this study is to investigate a new approach to significantly improve efficacy of image feature selection and classifier optimization in developing a CAD scheme of mammographic masses. Methods: An image dataset including 1600 regions of interest (ROIs) in which 800 are positive (depicting malignant masses) and 800 are negative (depicting CAD-generated false positive regions) was used in this study. After segmentation of each suspicious lesion by a multilayer topographic region growth algorithm, 271 features were computed in different feature categories including shape, texture, contrast, isodensity, spiculation, local topological features, as well as the features related to the presence and location of fat and calcifications. Besides computing features from the original images, the authors also computed new texture features from the dilated lesion segments. In order to select optimal features from this initial feature pool and build a highly performing classifier, the authors examined and compared four feature selection methods to optimize an artificial neural network (ANN) based classifier, namely: (1) Phased Searching with NEAT in a Time-Scaled Framework, (2) A sequential floating forward selection (SFFS) method, (3) A genetic algorithm (GA), and (4) A sequential forward selection (SFS) method. Performances of the four approaches were assessed using a tenfold cross validation method. Results: Among these four methods, SFFS has highest efficacy, which takes 3%–5% of computational time as compared to GA approach, and yields the highest performance level with the area under a receiver operating characteristic curve (AUC) = 0.864 ± 0.034. The results also demonstrated that except using GA, including the new texture features computed from the dilated mass segments improved the AUC
A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.
Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong
2015-01-01
This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme. PMID:26690571
A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks
Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong
2015-01-01
This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme. PMID:26690571
A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.
Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong
2015-01-01
This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme.
Kumar, Navneet; Raj Chelliah, Thanga; Srivastava, S P
2015-07-01
Model Based Control (MBC) is one of the energy optimal controllers used in vector-controlled Induction Motor (IM) for controlling the excitation of motor in accordance with torque and speed. MBC offers energy conservation especially at part-load operation, but it creates ripples in torque and speed during load transition, leading to poor dynamic performance of the drive. This study investigates the opportunity for improving dynamic performance of a three-phase IM operating with MBC and proposes three control schemes: (i) MBC with a low pass filter (ii) torque producing current (iqs) injection in the output of speed controller (iii) Variable Structure Speed Controller (VSSC). The pre and post operation of MBC during load transition is also analyzed. The dynamic performance of a 1-hp, three-phase squirrel-cage IM with mine-hoist load diagram is tested. Test results are provided for the conventional field-oriented (constant flux) control and MBC (adjustable excitation) with proposed schemes. The effectiveness of proposed schemes is also illustrated for parametric variations. The test results and subsequent analysis confer that the motor dynamics improves significantly with all three proposed schemes in terms of overshoot/undershoot peak amplitude of torque and DC link power in addition to energy saving during load transitions. PMID:25820090
Optimal Sampling Strategies for Detecting Zoonotic Disease Epidemics
Ferguson, Jake M.; Langebrake, Jessica B.; Cannataro, Vincent L.; Garcia, Andres J.; Hamman, Elizabeth A.; Martcheva, Maia; Osenberg, Craig W.
2014-01-01
The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests. PMID:24968100
Rapidly optimizing an aptamer based BoNT sensor by feedback system control (FSC) scheme.
Wei, Fang; Bai, Bin; Ho, Chih-Ming
2011-12-15
The sensitivity and detection time of an aptamer based biosensor for detecting botulinum neurotoxin (BoNT) depend upon the formation of proper tertiary architecture of aptamer, which closely correlates with the combinatorial effects of multiple types of ions and their concentrations presented in the buffer. Finding the optimal conditions for four different ions at 12 different concentrations, 20,736 possible combinations, by brute force is an extremely laborious and time-consuming task. Here, we introduce a feedback system control (FSC) scheme that can rapidly identify the best combination of components to form the optimal aptamer structure binding to a target molecule. In this study, rapid identification of optimized ionic combinations for electrochemical aptasensor of BoNT type A (BoNT/A) detection has been achieved. Only about 10 iterations with about 50 tests in each iteration are needed to identify the optimal ionic concentration out of the 20,736 possibilities. The most exciting finding was that a very short detection time and high sensitivity could be achieved with the optimized combinational ion buffer. Only a 5-min detection time, compared with hours or even days, was needed for aptamer-based BoNT/A detection with a limit of detection of 40 pg/ml. The methodologies described here can be applied to other multi-parameter chemical systems, which should significantly improve the rate of parameter optimization.
An, Yongkai; Lu, Wenxi; Cheng, Weiguo
2015-07-30
This paper introduces a surrogate model to identify an optimal exploitation scheme, while the western Jilin province was selected as the study area. A numerical simulation model of groundwater flow was established first, and four exploitation wells were set in the Tongyu county and Qian Gorlos county respectively so as to supply water to Daan county. Second, the Latin Hypercube Sampling (LHS) method was used to collect data in the feasible region for input variables. A surrogate model of the numerical simulation model of groundwater flow was developed using the regression kriging method. An optimization model was established to search an optimal groundwater exploitation scheme using the minimum average drawdown of groundwater table and the minimum cost of groundwater exploitation as multi-objective functions. Finally, the surrogate model was invoked by the optimization model in the process of solving the optimization problem. Results show that the relative error and root mean square error of the groundwater table drawdown between the simulation model and the surrogate model for 10 validation samples are both lower than 5%, which is a high approximation accuracy. The contrast between the surrogate-based simulation optimization model and the conventional simulation optimization model for solving the same optimization problem, shows the former only needs 5.5 hours, and the latter needs 25 days. The above results indicate that the surrogate model developed in this study could not only considerably reduce the computational burden of the simulation optimization process, but also maintain high computational accuracy. This can thus provide an effective method for identifying an optimal groundwater exploitation scheme quickly and accurately.
An, Yongkai; Lu, Wenxi; Cheng, Weiguo
2015-01-01
This paper introduces a surrogate model to identify an optimal exploitation scheme, while the western Jilin province was selected as the study area. A numerical simulation model of groundwater flow was established first, and four exploitation wells were set in the Tongyu county and Qian Gorlos county respectively so as to supply water to Daan county. Second, the Latin Hypercube Sampling (LHS) method was used to collect data in the feasible region for input variables. A surrogate model of the numerical simulation model of groundwater flow was developed using the regression kriging method. An optimization model was established to search an optimal groundwater exploitation scheme using the minimum average drawdown of groundwater table and the minimum cost of groundwater exploitation as multi-objective functions. Finally, the surrogate model was invoked by the optimization model in the process of solving the optimization problem. Results show that the relative error and root mean square error of the groundwater table drawdown between the simulation model and the surrogate model for 10 validation samples are both lower than 5%, which is a high approximation accuracy. The contrast between the surrogate-based simulation optimization model and the conventional simulation optimization model for solving the same optimization problem, shows the former only needs 5.5 hours, and the latter needs 25 days. The above results indicate that the surrogate model developed in this study could not only considerably reduce the computational burden of the simulation optimization process, but also maintain high computational accuracy. This can thus provide an effective method for identifying an optimal groundwater exploitation scheme quickly and accurately. PMID:26264008
An, Yongkai; Lu, Wenxi; Cheng, Weiguo
2015-08-01
This paper introduces a surrogate model to identify an optimal exploitation scheme, while the western Jilin province was selected as the study area. A numerical simulation model of groundwater flow was established first, and four exploitation wells were set in the Tongyu county and Qian Gorlos county respectively so as to supply water to Daan county. Second, the Latin Hypercube Sampling (LHS) method was used to collect data in the feasible region for input variables. A surrogate model of the numerical simulation model of groundwater flow was developed using the regression kriging method. An optimization model was established to search an optimal groundwater exploitation scheme using the minimum average drawdown of groundwater table and the minimum cost of groundwater exploitation as multi-objective functions. Finally, the surrogate model was invoked by the optimization model in the process of solving the optimization problem. Results show that the relative error and root mean square error of the groundwater table drawdown between the simulation model and the surrogate model for 10 validation samples are both lower than 5%, which is a high approximation accuracy. The contrast between the surrogate-based simulation optimization model and the conventional simulation optimization model for solving the same optimization problem, shows the former only needs 5.5 hours, and the latter needs 25 days. The above results indicate that the surrogate model developed in this study could not only considerably reduce the computational burden of the simulation optimization process, but also maintain high computational accuracy. This can thus provide an effective method for identifying an optimal groundwater exploitation scheme quickly and accurately. PMID:26264008
Lei, Bingbing; Lu, Wenke; Zhu, Changchun; Liu, Qinghong; Zhang, Haoxin
2014-08-01
In this paper, we propose a novel optimal sensitivity design scheme for the yarn tension sensor using surface acoustic wave (SAW) device. In order to obtain the best sensitivity, the regression model between the size of the SAW yarn tension sensor substrate and the sensitivity of the SAW yarn tension sensor was established using the least square method. The model was validated too. Through analyzing the correspondence between the regression function monotonicity and its partial derivative sign, the effect of the SAW yarn tension sensor substrate size on the sensitivity of the SAW yarn tension sensor was investigated. Based on the regression model, a linear programming model was established to gain the optimal sensitivity of the SAW yarn tension sensor. The linear programming result shows that the maximum sensitivity will be achieved when the SAW yarn tension sensor substrate length is equal to 15 mm and its width is equal to 3mm within a fixed interval of the substrate size. An experiment of SAW yarn tension sensor about 15 mm long and 3mm wide was presented. Experimental results show that the maximum sensitivity 1982.39 Hz/g was accomplished, which confirms that the optimal sensitivity design scheme is useful and effective.
Scheme for the implementation of 1 → 3 optimal phase-covariant quantum cloning in ion-trap systems
NASA Astrophysics Data System (ADS)
Yang, Rong-Can; Li, Hong-Cai; Lin, Xiu; Huang, Zhi-Ping; Xie, Hong
2008-03-01
This paper proposes a scheme for the implementation of 1 → 3 optimal phase-covariant quantum cloning with trapped ions. In the present protocol, the required time for the whole procedure is short due to the resonant interaction, which is important in view of decoherence. Furthermore, the scheme is feasible based on current technologies.
NASA Astrophysics Data System (ADS)
Yang, Rong-Can; Li, Hong-Cai; Lin, Xiu; Huang, Zhi-Ping; Xie, Hong
2008-06-01
We propose a simple scheme for the implementation of the ancillary-free 1 → 3 optimal phase-covariant quantum cloning for x-y equatorial qubits in ion-trap system. In the scheme, the vibrational mode is only virtually excited, which is very important in view of decoherence. The present proposal can be realized based on current available technologies.
NASA Technical Reports Server (NTRS)
Vatsa, Veer N.; Carpenter, Mark H.; Lockard, David P.
2009-01-01
Recent experience in the application of an optimized, second-order, backward-difference (BDF2OPT) temporal scheme is reported. The primary focus of the work is on obtaining accurate solutions of the unsteady Reynolds-averaged Navier-Stokes equations over long periods of time for aerodynamic problems of interest. The baseline flow solver under consideration uses a particular BDF2OPT temporal scheme with a dual-time-stepping algorithm for advancing the flow solutions in time. Numerical difficulties are encountered with this scheme when the flow code is run for a large number of time steps, a behavior not seen with the standard second-order, backward-difference, temporal scheme. Based on a stability analysis, slight modifications to the BDF2OPT scheme are suggested. The performance and accuracy of this modified scheme is assessed by comparing the computational results with other numerical schemes and experimental data.
Cao, Tong; Chen, Liao; Yu, Yu; Zhang, Xinliang
2014-12-29
We propose and experimentally demonstrate a novel scheme which can simultaneously realize wavelength-preserving and phase-preserving amplitude noise compression of a 40 Gb/s distorted non-return-to-zero differential-phase-shift keying (NRZ-DPSK) signal. In the scheme, two semiconductor optical amplifiers (SOAs) are exploited. The first one (SOA1) is used to generate the inverted signal based on SOA's transient cross-phase modulation (T-XPM) effect and the second one (SOA2) to regenerate the distorted NRZ-DPSK signal using SOA's cross-gain compression (XGC) effect. In the experiment, the bit error ratio (BER) measurements show that power penalties of constructive and destructive demodulation at BER of 10^{-9} are -1.75 and -1.01 dB, respectively. As the nonlinear effects and the requirements of the two SOAs are completely different, quantum-well (QW) structures has been separately optimized. A complicated theoretical model by combining QW band structure calculation with SOA's dynamic model is exploited to optimize the SOAs, in which both interband effect (carrier density variation) and intraband effect (carrier temperature variation) are taken into account. Regarding SOA1, we choose the tensile strained QW structure and large optical confinement factor to enhance the T-XPM effect. Regarding SOA2, the compressively strained QW structure is selected to reduce the impact of excess phase noise induced by amplitude fluctuations. Exploiting the optimized QW SOAs, better amplitude regeneration performance is demonstrated successfully through numerical simulation. The proposed scheme is intrinsically stable comparing with the interferometer structure and can be integrated on a chip, making it a practical candidate for all-optical amplitude regeneration of high-speed NRZ-DPSK signal. PMID:25607178
GENERAL: Optimal Schemes of Teleportation One-Particle State by a Three-Particle General W State
NASA Astrophysics Data System (ADS)
Zha, Xin-Wei; Song, Hai-Yang
2010-05-01
Recently, Xiu et al. [Common. Theor. Phys. 49 (2008) 905] proposed two schemes of teleporting an N particle arbitrary and unknown state when N groups of three particle general W states are utilized as quantum channels. They gave the maximal probability of successful teleportation. Here we find that their operation is not the optimal and the successful probability of the teleportation is not maximum. Moreover, we give the optimal schemes operation and obtain maximal successful probability for teleportation.
Optimal control, investment and utilization schemes for energy storage under uncertainty
NASA Astrophysics Data System (ADS)
Mirhosseini, Niloufar Sadat
Energy storage has the potential to offer new means for added flexibility on the electricity systems. This flexibility can be used in a number of ways, including adding value towards asset management, power quality and reliability, integration of renewable resources and energy bill savings for the end users. However, uncertainty about system states and volatility in system dynamics can complicate the question of when to invest in energy storage and how best to manage and utilize it. This work proposes models to address different problems associated with energy storage within a microgrid, including optimal control, investment, and utilization. Electric load, renewable resources output, storage technology cost and electricity day-ahead and spot prices are the factors that bring uncertainty to the problem. A number of analytical methodologies have been adopted to develop the aforementioned models. Model Predictive Control and discretized dynamic programming, along with a new decomposition algorithm are used to develop optimal control schemes for energy storage for two different levels of renewable penetration. Real option theory and Monte Carlo simulation, coupled with an optimal control approach, are used to obtain optimal incremental investment decisions, considering multiple sources of uncertainty. Two stage stochastic programming is used to develop a novel and holistic methodology, including utilization of energy storage within a microgrid, in order to optimally interact with energy market. Energy storage can contribute in terms of value generation and risk reduction for the microgrid. The integration of the models developed here are the basis for a framework which extends from long term investments in storage capacity to short term operational control (charge/discharge) of storage within a microgrid. In particular, the following practical goals are achieved: (i) optimal investment on storage capacity over time to maximize savings during normal and emergency
Optimization of enrichment processes of pentachlorophenol (PCP) from water samples.
Li, Ping; Liu, Jun-xin
2004-01-01
The method of enriching PCP(pentachlorophenol) from aquatic environment by solid phase extraction(SPE) was studied. Several factors affecting the recoveries of PCP, including sample pH, eluting solvent, eluting volume and flow rate of water sample, were optimized by orthogonal array design(OAD). The optimized results were sample pH 4; eluting solvent, 100% methanol; eluting solvent volume, 2 ml and flow rate of water sample, 4 ml/min. A comparison is made between SPE and liquid-liquid extraction(LLE) method. The recoveries of PCP were in the range of 87.6%-133.6% and 79%-120.3% for SPE and LLE, respectively. Important advantages of the SPE compared with the LLE include the short extraction time and reduced consumption of organic solvents. SPE can replace LLE for isolating and concentrating PCP from water samples.
Schwientek, Marc; Guillet, Gaëlle; Rügner, Hermann; Kuch, Bertram; Grathwohl, Peter
2016-01-01
Increasing numbers of organic micropollutants are emitted into rivers via municipal wastewaters. Due to their persistence many pollutants pass wastewater treatment plants without substantial removal. Transport and fate of pollutants in receiving waters and export to downstream ecosystems is not well understood. In particular, a better knowledge of processes governing their environmental behavior is needed. Although a lot of data are available concerning the ubiquitous presence of micropollutants in rivers, accurate data on transport and removal rates are lacking. In this paper, a mass balance approach is presented, which is based on the Lagrangian sampling scheme, but extended to account for precise transport velocities and mixing along river stretches. The calculated mass balances allow accurate quantification of pollutants' reactivity along river segments. This is demonstrated for representative members of important groups of micropollutants, e.g. pharmaceuticals, musk fragrances, flame retardants, and pesticides. A model-aided analysis of the measured data series gives insight into the temporal dynamics of removal processes. The occurrence of different removal mechanisms such as photooxidation, microbial degradation, and volatilization is discussed. The results demonstrate, that removal processes are highly variable in time and space and this has to be considered for future studies. The high precision sampling scheme presented could be a powerful tool for quantifying removal processes under different boundary conditions and in river segments with contrasting properties.
Schwientek, Marc; Guillet, Gaëlle; Rügner, Hermann; Kuch, Bertram; Grathwohl, Peter
2016-01-01
Increasing numbers of organic micropollutants are emitted into rivers via municipal wastewaters. Due to their persistence many pollutants pass wastewater treatment plants without substantial removal. Transport and fate of pollutants in receiving waters and export to downstream ecosystems is not well understood. In particular, a better knowledge of processes governing their environmental behavior is needed. Although a lot of data are available concerning the ubiquitous presence of micropollutants in rivers, accurate data on transport and removal rates are lacking. In this paper, a mass balance approach is presented, which is based on the Lagrangian sampling scheme, but extended to account for precise transport velocities and mixing along river stretches. The calculated mass balances allow accurate quantification of pollutants' reactivity along river segments. This is demonstrated for representative members of important groups of micropollutants, e.g. pharmaceuticals, musk fragrances, flame retardants, and pesticides. A model-aided analysis of the measured data series gives insight into the temporal dynamics of removal processes. The occurrence of different removal mechanisms such as photooxidation, microbial degradation, and volatilization is discussed. The results demonstrate, that removal processes are highly variable in time and space and this has to be considered for future studies. The high precision sampling scheme presented could be a powerful tool for quantifying removal processes under different boundary conditions and in river segments with contrasting properties. PMID:26283620
NASA Astrophysics Data System (ADS)
Zhan, Xi-Sheng; Guan, Zhi-Hong; Zhang, Xian-He; Yuan, Fu-Shun
2015-02-01
This paper investigates the issue of the optimal tracking performance for multiple-input multiple-output linear time-invariant continuous-time systems with power constrained. An H2 criterion of the error signal and the signal of the input channel are used as a measure for the tracking performance. A code scheme is introduced as a means of integrating controller and channel design to obtain the optimal tracking performance. It is shown that the optimal tracking performance index consists of two parts, one depends on the non-minimum phase zeros and zero direction of the given plant, as well as the reference input signal, while the other depends on the unstable poles and pole direction of the given plant, as well as on the bandwidth and additive white noise of a communication channel. It is also shown that when the communication does not exist, the optimal tracking performance reduces to the existing normal tracking performance of the control system. The results show how the optimal tracking performance is limited by the bandwidth and additive white noise of the communication channel. A typical example is given to illustrate the theoretical results.
A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme
NASA Astrophysics Data System (ADS)
Ghoman, Satyajit S.
The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness. The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M 3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M 3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE. The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M 3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of
Qarri, Flora; Lazo, Pranvera; Bekteshi, Lirim; Stafilov, Trajce; Frontasyeva, Marina; Harmens, Harry
2015-02-01
The atmospheric deposition of heavy metals in Albania was investigated by using a carpet-forming moss species (Hypnum cupressiforme) as bioindicator. Sampling was done in the dry seasons of autumn 2010 and summer 2011. Two different sampling schemes are discussed in this paper: a random sampling scheme with 62 sampling sites distributed over the whole territory of Albania and systematic sampling scheme with 44 sampling sites distributed over the same territory. Unwashed, dried samples were totally digested by using microwave digestion, and the concentrations of metal elements were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES) and AAS (Cd and As). Twelve elements, such as conservative and trace elements (Al and Fe and As, Cd, Cr, Cu, Ni, Mn, Pb, V, Zn, and Li), were measured in moss samples. Li as typical lithogenic element is also included. The results reflect local emission points. The median concentrations and statistical parameters of elements were discussed by comparing two sampling schemes. The results of both sampling schemes are compared with the results of other European countries. Different levels of the contamination valuated by the respective contamination factor (CF) of each element are obtained for both sampling schemes, while the local emitters identified like iron-chromium metallurgy and cement industry, oil refinery, mining industry, and transport have been the same for both sampling schemes. In addition, the natural sources, from the accumulation of these metals in mosses caused by metal-enriched soil, associated with wind blowing soils were pointed as another possibility of local emitting factors.
Urine sampling and collection system optimization and testing
NASA Technical Reports Server (NTRS)
Fogal, G. L.; Geating, J. A.; Koesterer, M. G.
1975-01-01
A Urine Sampling and Collection System (USCS) engineering model was developed to provide for the automatic collection, volume sensing and sampling of urine from each micturition. The purpose of the engineering model was to demonstrate verification of the system concept. The objective of the optimization and testing program was to update the engineering model, to provide additional performance features and to conduct system testing to determine operational problems. Optimization tasks were defined as modifications to minimize system fluid residual and addition of thermoelectric cooling.
NASA Astrophysics Data System (ADS)
Zhang, S.; Yin, J.; Zhang, H. W.; Chen, B. S.
2016-03-01
Phoxonic crystal (PXC) is a promising artificial periodic material for optomechanical systems and acousto-optical devices. The multi-objective topology optimization of dual phononic and photonic max relative bandgaps in a kind of two-dimensional (2D) PXC is investigated to find the regular pattern of topological configurations. In order to improve the efficiency, a multi-level substructure scheme is proposed to analyze phononic and photonic band structures, which is stable, efficient and less memory-consuming. The efficient and reliable numerical algorithm provides a powerful tool to optimize and design crystal devices. The results show that with the reduction of the relative phononic bandgap (PTBG), the central dielectric scatterer becomes smaller and the dielectric veins of cross-connections between different dielectric scatterers turn into the horizontal and vertical shape gradually. These characteristics can be of great value to the design and synthesis of new materials with different topological configurations for applications of the PXC.
Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation.
Yuan, Haidong; Fung, Chi-Hang Fred
2015-09-11
Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.
Optimal variable flip angle schemes for dynamic acquisition of exchanging hyperpolarized substrates
NASA Astrophysics Data System (ADS)
Xing, Yan; Reed, Galen D.; Pauly, John M.; Kerr, Adam B.; Larson, Peder E. Z.
2013-09-01
In metabolic MRI with hyperpolarized contrast agents, the signal levels vary over time due to T1 decay, T2 decay following RF excitations, and metabolic conversion. Efficient usage of the nonrenewable hyperpolarized magnetization requires specialized RF pulse schemes. In this work, we introduce two novel variable flip angle schemes for dynamic hyperpolarized MRI in which the flip angle is varied between excitations and between metabolites. These were optimized to distribute the magnetization relatively evenly throughout the acquisition by accounting for T1 decay, prior RF excitations, and metabolic conversion. Simulation results are presented to confirm the flip angle designs and evaluate the variability of signal dynamics across typical ranges of T1 and metabolic conversion. They were implemented using multiband spectral-spatial RF pulses to independently modulate the flip angle at various chemical shift frequencies. With these schemes we observed increased SNR of [1-13C]lactate generated from [1-13C]pyruvate, particularly at later time points. This will allow for improved characterization of tissue perfusion and metabolic profiles in dynamic hyperpolarized MRI.
spsann - optimization of sample patterns using spatial simulated annealing
NASA Astrophysics Data System (ADS)
Samuel-Rosa, Alessandro; Heuvelink, Gerard; Vasques, Gustavo; Anjos, Lúcia
2015-04-01
There are many algorithms and computer programs to optimize sample patterns, some private and others publicly available. A few have only been presented in scientific articles and text books. This dispersion and somewhat poor availability is holds back to their wider adoption and further development. We introduce spsann, a new R-package for the optimization of sample patterns using spatial simulated annealing. R is the most popular environment for data processing and analysis. Spatial simulated annealing is a well known method with widespread use to solve optimization problems in the soil and geo-sciences. This is mainly due to its robustness against local optima and easiness of implementation. spsann offers many optimizing criteria for sampling for variogram estimation (number of points or point-pairs per lag distance class - PPL), trend estimation (association/correlation and marginal distribution of the covariates - ACDC), and spatial interpolation (mean squared shortest distance - MSSD). spsann also includes the mean or maximum universal kriging variance (MUKV) as an optimizing criterion, which is used when the model of spatial variation is known. PPL, ACDC and MSSD were combined (PAN) for sampling when we are ignorant about the model of spatial variation. spsann solves this multi-objective optimization problem scaling the objective function values using their maximum absolute value or the mean value computed over 1000 random samples. Scaled values are aggregated using the weighted sum method. A graphical display allows to follow how the sample pattern is being perturbed during the optimization, as well as the evolution of its energy state. It is possible to start perturbing many points and exponentially reduce the number of perturbed points. The maximum perturbation distance reduces linearly with the number of iterations. The acceptance probability also reduces exponentially with the number of iterations. R is memory hungry and spatial simulated annealing is a
Optimization of protein samples for NMR using thermal shift assays.
Kozak, Sandra; Lercher, Lukas; Karanth, Megha N; Meijers, Rob; Carlomagno, Teresa; Boivin, Stephane
2016-04-01
Maintaining a stable fold for recombinant proteins is challenging, especially when working with highly purified and concentrated samples at temperatures >20 °C. Therefore, it is worthwhile to screen for different buffer components that can stabilize protein samples. Thermal shift assays or ThermoFluor(®) provide a high-throughput screening method to assess the thermal stability of a sample under several conditions simultaneously. Here, we describe a thermal shift assay that is designed to optimize conditions for nuclear magnetic resonance studies, which typically require stable samples at high concentration and ambient (or higher) temperature. We demonstrate that for two challenging proteins, the multicomponent screen helped to identify ingredients that increased protein stability, leading to clear improvements in the quality of the spectra. Thermal shift assays provide an economic and time-efficient method to find optimal conditions for NMR structural studies. PMID:26984476
Optimal procedures for detecting analytic bias using patient samples.
Smith, F A; Kroft, S H
1997-09-01
We recently described the performance characteristics of the exponentially adjusted moving mean (EAMM), a patient-data, moving block mean procedure, which is a generalized algorithm that unifies Bull's algorithm and the classic average of normals (AON) procedure. Herein we describe the trend EAMM (TEAMM), a continuous signal analog of the EAMM procedure related to classic trend analysis. Using computer simulation, we have compared EAMM and TEAMM over a range of biases for various sample sizes (N or equivalent smoothing factor alpha) and exponential parameters (P) under conditions of equivalent false rejection (fixed on a per patient sample basis). We found optimal pairs of N and P for each level of bias by determination of minimum mean patient samples to rejection. Overall optimal algorithms were determined through calculation of undetected lost medical utility (ULMU), a novel function that quantifies the medical damage due to analytic bias. The ULMU function was calculated based on lost test specificity in a normal population. We found that optimized TEAMM was superior to optimized EAMM for all levels of analytic bias. If these observations hold true for non-Gaussian populations, TEAMM procedures are the method of choice for detecting bias using patient samples or as an event gauge to trigger use of known-value control materials.
Optimizing Sampling Efficiency for Biomass Estimation Across NEON Domains
NASA Astrophysics Data System (ADS)
Abercrombie, H. H.; Meier, C. L.; Spencer, J. J.
2013-12-01
Over the course of 30 years, the National Ecological Observatory Network (NEON) will measure plant biomass and productivity across the U.S. to enable an understanding of terrestrial carbon cycle responses to ecosystem change drivers. Over the next several years, prior to operational sampling at a site, NEON will complete construction and characterization phases during which a limited amount of sampling will be done at each site to inform sampling designs, and guide standardization of data collection across all sites. Sampling biomass in 60+ sites distributed among 20 different eco-climatic domains poses major logistical and budgetary challenges. Traditional biomass sampling methods such as clip harvesting and direct measurements of Leaf Area Index (LAI) involve collecting and processing plant samples, and are time and labor intensive. Possible alternatives include using indirect sampling methods for estimating LAI such as digital hemispherical photography (DHP) or using a LI-COR 2200 Plant Canopy Analyzer. These LAI estimations can then be used as a proxy for biomass. The biomass estimates calculated can then inform the clip harvest sampling design during NEON operations, optimizing both sample size and number so that standardized uncertainty limits can be achieved with a minimum amount of sampling effort. In 2011, LAI and clip harvest data were collected from co-located sampling points at the Central Plains Experimental Range located in northern Colorado, a short grass steppe ecosystem that is the NEON Domain 10 core site. LAI was measured with a LI-COR 2200 Plant Canopy Analyzer. The layout of the sampling design included four, 300 meter transects, with clip harvests plots spaced every 50m, and LAI sub-transects spaced every 10m. LAI was measured at four points along 6m sub-transects running perpendicular to the 300m transect. Clip harvest plots were co-located 4m from corresponding LAI transects, and had dimensions of 0.1m by 2m. We conducted regression analyses
Menezes, Angela; Woods, Kate; Chanthongthip, Anisone; Dittrich, Sabine; Opoku-Boateng, Agatha; Kimuli, Maimuna; Chalker, Victoria
2016-01-01
Background Rapid typing of Leptospira is currently impaired by requiring time consuming culture of leptospires. The objective of this study was to develop an assay that provides multilocus sequence typing (MLST) data direct from patient specimens while minimising costs for subsequent sequencing. Methodology and Findings An existing PCR based MLST scheme was modified by designing nested primers including anchors for facilitated subsequent sequencing. The assay was applied to various specimen types from patients diagnosed with leptospirosis between 2014 and 2015 in the United Kingdom (UK) and the Lao Peoples Democratic Republic (Lao PDR). Of 44 clinical samples (23 serum, 6 whole blood, 3 buffy coat, 12 urine) PCR positive for pathogenic Leptospira spp. at least one allele was amplified in 22 samples (50%) and used for phylogenetic inference. Full allelic profiles were obtained from ten specimens, representing all sample types (23%). No nonspecific amplicons were observed in any of the samples. Of twelve PCR positive urine specimens three gave full allelic profiles (25%) and two a partial profile. Phylogenetic analysis allowed for species assignment. The predominant species detected was L. interrogans (10/14 and 7/8 from UK and Lao PDR, respectively). All other species were detected in samples from only one country (Lao PDR: L. borgpetersenii [1/8]; UK: L. kirschneri [1/14], L. santarosai [1/14], L. weilii [2/14]). Conclusion Typing information of pathogenic Leptospira spp. was obtained directly from a variety of clinical samples using a modified MLST assay. This assay negates the need for time-consuming culture of Leptospira prior to typing and will be of use both in surveillance, as single alleles enable species determination, and outbreaks for the rapid identification of clusters. PMID:27654037
The dependence of optimal fractionation schemes on the spatial dose distribution
NASA Astrophysics Data System (ADS)
Unkelbach, Jan; Craft, David; Salari, Ehsan; Ramakrishnan, Jagdish; Bortfeld, Thomas
2013-01-01
We consider the fractionation problem in radiation therapy. Tumor sites in which the dose-limiting organ at risk (OAR) receives a substantially lower dose than the tumor, bear potential for hypofractionation even if the α/β-ratio of the tumor is larger than the α/β-ratio of the OAR. In this work, we analyze the interdependence of the optimal fractionation scheme and the spatial dose distribution in the OAR. In particular, we derive a criterion under which a hypofractionation regimen is indicated for both a parallel and a serial OAR. The approach is based on the concept of the biologically effective dose (BED). For a hypothetical homogeneously irradiated OAR, it has been shown that hypofractionation is suggested by the BED model if the α/β-ratio of the OAR is larger than α/β-ratio of the tumor times the sparing factor, i.e. the ratio of the dose received by the tumor and the OAR. In this work, we generalize this result to inhomogeneous dose distributions in the OAR. For a parallel OAR, we determine the optimal fractionation scheme by minimizing the integral BED in the OAR for a fixed BED in the tumor. For a serial structure, we minimize the maximum BED in the OAR. This leads to analytical expressions for an effective sparing factor for the OAR, which provides a criterion for hypofractionation. The implications of the model are discussed for lung tumor treatments. It is shown that the model supports hypofractionation for small tumors treated with rotation therapy, i.e. highly conformal techniques where a large volume of lung tissue is exposed to low but nonzero dose. For larger tumors, the model suggests hyperfractionation. We further discuss several non-intuitive interdependencies between optimal fractionation and the spatial dose distribution. For instance, lowering the dose in the lung via proton therapy does not necessarily provide a biological rationale for hypofractionation.
Optimization of tapered fiber sample for laser cooling of solids
NASA Astrophysics Data System (ADS)
Nemova, Galina; Kashyap, Raman
2009-02-01
The physical mechanism of radiation cooling by anti-Stokes fluorescence was originally proposed in 1929 and experimentally observed in solid materials in 1995 by Epstein's research team in ytterbium-doped ZBLANP glass. Some specific combinations of the ions, host materials, and the wavelength of the incident radiation can provide anti-Stokes interaction resulting in phonon absorption accompanied by the cooling of the host material. Although the optical cooling of the Yb3+-doped ZBLANP sample was already observed there are broad possibilities for its improvement to increase the temperature-drop of the sample by optimization of the geometrical parameters of the cooling sample. We propose a theoretical model for an optimized tapered fiber structure for use as a sample in anti-Stokes laser cooling of solids. This tapered fiber has a fluorozirconate glass ZBLANP with a core doped with Yb3+ or Tm3+ ions. As evident from the results of our work, the appropriate choice of the fiber core and the fiber cladding radii can significantly increase the temperature-drop of the sample for any fixed pump power. The value of the maximum of the temperature-drop of the sample increases with an increase in the pump power. The depletion of the pump power causes a temperature gradient along the length of the cooled sample.
SamACO: variable sampling ant colony optimization algorithm for continuous optimization.
Hu, Xiao-Min; Zhang, Jun; Chung, Henry Shu-Hung; Li, Yun; Liu, Ou
2010-12-01
An ant colony optimization (ACO) algorithm offers algorithmic techniques for optimization by simulating the foraging behavior of a group of ants to perform incremental solution constructions and to realize a pheromone laying-and-following mechanism. Although ACO is first designed for solving discrete (combinatorial) optimization problems, the ACO procedure is also applicable to continuous optimization. This paper presents a new way of extending ACO to solving continuous optimization problems by focusing on continuous variable sampling as a key to transforming ACO from discrete optimization to continuous optimization. The proposed SamACO algorithm consists of three major steps, i.e., the generation of candidate variable values for selection, the ants' solution construction, and the pheromone update process. The distinct characteristics of SamACO are the cooperation of a novel sampling method for discretizing the continuous search space and an efficient incremental solution construction method based on the sampled values. The performance of SamACO is tested using continuous numerical functions with unimodal and multimodal features. Compared with some state-of-the-art algorithms, including traditional ant-based algorithms and representative computational intelligence algorithms for continuous optimization, the performance of SamACO is seen competitive and promising.
Zhang, Yichuan; Wang, Jiangping
2015-07-01
Rivers serve as a highly valued component in ecosystem and urban infrastructures. River planning should follow basic principles of maintaining or reconstructing the natural landscape and ecological functions of rivers. Optimization of planning scheme is a prerequisite for successful construction of urban rivers. Therefore, relevant studies on optimization of scheme for natural ecology planning of rivers is crucial. In the present study, four planning schemes for Zhaodingpal River in Xinxiang City, Henan Province were included as the objects for optimization. Fourteen factors that influenced the natural ecology planning of urban rivers were selected from five aspects so as to establish the ANP model. The data processing was done using Super Decisions software. The results showed that important degree of scheme 3 was highest. A scientific, reasonable and accurate evaluation of schemes could be made by ANP method on natural ecology planning of urban rivers. This method could be used to provide references for sustainable development and construction of urban rivers. ANP method is also suitable for optimization of schemes for urban green space planning and design.
Advanced overlay: sampling and modeling for optimized run-to-run control
NASA Astrophysics Data System (ADS)
Subramany, Lokesh; Chung, WoongJae; Samudrala, Pavan; Gao, Haiyong; Aung, Nyan; Gomez, Juan Manuel; Gutjahr, Karsten; Park, DongSuk; Snow, Patrick; Garcia-Medina, Miguel; Yap, Lipkong; Demirer, Onur Nihat; Pierson, Bill; Robinson, John C.
2016-03-01
In recent years overlay (OVL) control schemes have become more complicated in order to meet the ever shrinking margins of advanced technology nodes. As a result, this brings up new challenges to be addressed for effective run-to- run OVL control. This work addresses two of these challenges by new advanced analysis techniques: (1) sampling optimization for run-to-run control and (2) bias-variance tradeoff in modeling. The first challenge in a high order OVL control strategy is to optimize the number of measurements and the locations on the wafer, so that the "sample plan" of measurements provides high quality information about the OVL signature on the wafer with acceptable metrology throughput. We solve this tradeoff between accuracy and throughput by using a smart sampling scheme which utilizes various design-based and data-based metrics to increase model accuracy and reduce model uncertainty while avoiding wafer to wafer and within wafer measurement noise caused by metrology, scanner or process. This sort of sampling scheme, combined with an advanced field by field extrapolated modeling algorithm helps to maximize model stability and minimize on product overlay (OPO). Second, the use of higher order overlay models means more degrees of freedom, which enables increased capability to correct for complicated overlay signatures, but also increases sensitivity to process or metrology induced noise. This is also known as the bias-variance trade-off. A high order model that minimizes the bias between the modeled and raw overlay signature on a single wafer will also have a higher variation from wafer to wafer or lot to lot, that is unless an advanced modeling approach is used. In this paper, we characterize the bias-variance trade off to find the optimal scheme. The sampling and modeling solutions proposed in this study are validated by advanced process control (APC) simulations to estimate run-to-run performance, lot-to-lot and wafer-to- wafer model term monitoring to
Michaelis-Menten reaction scheme as a unified approach towards the optimal restart problem.
Rotbart, Tal; Reuveni, Shlomi; Urbakh, Michael
2015-12-01
We study the effect of restart, and retry, on the mean completion time of a generic process. The need to do so arises in various branches of the sciences and we show that it can naturally be addressed by taking advantage of the classical reaction scheme of Michaelis and Menten. Stopping a process in its midst-only to start it all over again-may prolong, leave unchanged, or even shorten the time taken for its completion. Here we are interested in the optimal restart problem, i.e., in finding a restart rate which brings the mean completion time of a process to a minimum. We derive the governing equation for this problem and show that it is exactly solvable in cases of particular interest. We then continue to discover regimes at which solutions to the problem take on universal, details independent forms which further give rise to optimal scaling laws. The formalism we develop, and the results obtained, can be utilized when optimizing stochastic search processes and randomized computer algorithms. An immediate connection with kinetic proofreading is also noted and discussed.
NASA Astrophysics Data System (ADS)
Liu, Feng; Beck, Barbara L.; Fitzsimmons, Jeffrey R.; Blackband, Stephen J.; Crozier, Stuart
2005-11-01
In this paper, numerical simulations are used in an attempt to find optimal source profiles for high frequency radiofrequency (RF) volume coils. Biologically loaded, shielded/unshielded circular and elliptical birdcage coils operating at 170 MHz, 300 MHz and 470 MHz are modelled using the FDTD method for both 2D and 3D cases. Taking advantage of the fact that some aspects of the electromagnetic system are linear, two approaches have been proposed for the determination of the drives for individual elements in the RF resonator. The first method is an iterative optimization technique with a kernel for the evaluation of RF fields inside an imaging plane of a human head model using pre-characterized sensitivity profiles of the individual rungs of a resonator; the second method is a regularization-based technique. In the second approach, a sensitivity matrix is explicitly constructed and a regularization procedure is employed to solve the ill-posed problem. Test simulations show that both methods can improve the B1-field homogeneity in both focused and non-focused scenarios. While the regularization-based method is more efficient, the first optimization method is more flexible as it can take into account other issues such as controlling SAR or reshaping the resonator structures. It is hoped that these schemes and their extensions will be useful for the determination of multi-element RF drives in a variety of applications.
Michaelis-Menten reaction scheme as a unified approach towards the optimal restart problem
NASA Astrophysics Data System (ADS)
Rotbart, Tal; Reuveni, Shlomi; Urbakh, Michael
2015-12-01
We study the effect of restart, and retry, on the mean completion time of a generic process. The need to do so arises in various branches of the sciences and we show that it can naturally be addressed by taking advantage of the classical reaction scheme of Michaelis and Menten. Stopping a process in its midst—only to start it all over again—may prolong, leave unchanged, or even shorten the time taken for its completion. Here we are interested in the optimal restart problem, i.e., in finding a restart rate which brings the mean completion time of a process to a minimum. We derive the governing equation for this problem and show that it is exactly solvable in cases of particular interest. We then continue to discover regimes at which solutions to the problem take on universal, details independent forms which further give rise to optimal scaling laws. The formalism we develop, and the results obtained, can be utilized when optimizing stochastic search processes and randomized computer algorithms. An immediate connection with kinetic proofreading is also noted and discussed.
163 years of refinement: the British Geological Survey sample registration scheme
NASA Astrophysics Data System (ADS)
Howe, M. P.
2011-12-01
The British Geological Survey manages the largest UK geoscience samples collection, including: - 15,000 onshore boreholes, including over 250 km of drillcore - Vibrocores, gravity cores and grab samples from over 32,000 UK marine sample stations. 640 boreholes - Over 3 million UK fossils, including a "type and stratigraphic" reference collection of 250,000 fossils, 30,000 of which are "type, figured or cited" - Comprehensive microfossil collection, including many borehole samples - 290km of drillcore and 4.5 million cuttings samples from over 8000 UK continental shelf hydrocarbon wells - Over one million mineralogical and petrological samples, including 200,00 thin sections The current registration scheme was introduced in 1848 and is similar to that used by Charles Darwin on the Beagle. Every Survey collector or geologist has been issue with a unique prefix code of one or more letters and these were handwritten on preprinted numbers, arranged in books of 1 - 5,000 and 5,001 to 10,000. Similar labels are now computer printed. Other prefix codes are used for corporate collections, such as borehole samples, thin sections, microfossils, macrofossil sections, museum reference fossils, display quality rock samples and fossil casts. Such numbers infer significant immediate information to the curator, without the need to consult detailed registers. The registration numbers have been recorded in a series of over 1,000 registers, complete with metadata including sample ID, locality, horizon, collector and date. Citations are added as appropriate. Parent-child relationships are noted when re-registering subsubsamples. For example, a borehole sample BDA1001 could have been subsampled for a petrological thin section and off-cut (E14159), a fossil thin section (PF365), micropalynological slides (MPA273), one of which included a new holotype (MPK111), and a figured macrofossil (GSE1314). All main corporate collection now have publically-available online databases, such as Palaeo
Salomon, Julien; Turinici, Gabriel
2006-02-21
Numerical simulations of (bilinear) quantum control often rely on either monotonically convergent algorithms or tracking schemes. However, despite their mathematical simplicity, very limited intuitive understanding exists at this time to explain the former type of algorithms. Departing from the usual mathematical formalization, we present in this paper an interpretation of the monotonic algorithms as finite horizon, local in time, tracking schemes. Our purpose is not to present a new class of procedures but rather to introduce the necessary rigorous framework that supports this interpretation. As a by-product we show that at each instant, estimates of the future quality of the current control field are available and used in the optimization. When the target is expressed as reaching a prescribed final state, we also present an intuitive geometrical interpretation as the minimization of the distance between two correlated trajectories: one starting from the given initial state and the other backward in time from the target state. As an illustration, a stochastic monotonic algorithm is introduced. Numerical discretizations of the two procedures are also presented. PMID:16497025
NASA Astrophysics Data System (ADS)
Salomon, Julien; Turinici, Gabriel
2006-02-01
Numerical simulations of (bilinear) quantum control often rely on either monotonically convergent algorithms or tracking schemes. However, despite their mathematical simplicity, very limited intuitive understanding exists at this time to explain the former type of algorithms. Departing from the usual mathematical formalization, we present in this paper an interpretation of the monotonic algorithms as finite horizon, local in time, tracking schemes. Our purpose is not to present a new class of procedures but rather to introduce the necessary rigorous framework that supports this interpretation. As a by-product we show that at each instant, estimates of the future quality of the current control field are available and used in the optimization. When the target is expressed as reaching a prescribed final state, we also present an intuitive geometrical interpretation as the minimization of the distance between two correlated trajectories: one starting from the given initial state and the other backward in time from the target state. As an illustration, a stochastic monotonic algorithm is introduced. Numerical discretizations of the two procedures are also presented.
Layered HEVC/H.265 video transmission scheme based on hierarchical QAM optimization
NASA Astrophysics Data System (ADS)
Feng, Weidong; Zhou, Cheng; Xiong, Chengyi; Chen, Shaobo; Wang, Junxi
2015-12-01
High Efficiency Video Coding (HEVC) is the state-of-art video compression standard which fully support scalability features and is able to generate layered video streams with unequal importance. Unfortunately, when the base layer (BL) which is more importance to the stream is lost during the transmission, the enhancement layer (EL) based on the base layer must be discarded by receiver. Obviously, using the same transmittal strategies for BL and EL is unreasonable. This paper proposed an unequal error protection (UEP) system using different hierarchical amplitude modulation (HQAM). The BL data with high priority are mapped into the most reliable HQAM mode and the EL data with low priority are mapped into HQAM mode with fast transmission efficiency. Simulations on scalable HEVC codec show that the proposed optimized video transmission system is more attractive than the traditional equal error protection (EEP) scheme because it effectively balances the transmission efficiency and reconstruction video quality.
Optimal regulation in systems with stochastic time sampling
NASA Technical Reports Server (NTRS)
Montgomery, R. C.; Lee, P. S.
1980-01-01
An optimal control theory that accounts for stochastic variable time sampling in a distributed microprocessor based flight control system is presented. The theory is developed by using a linear process model for the airplane dynamics and the information distribution process is modeled as a variable time increment process where, at the time that information is supplied to the control effectors, the control effectors know the time of the next information update only in a stochastic sense. An optimal control problem is formulated and solved for the control law that minimizes the expected value of a quadratic cost function. The optimal cost obtained with a variable time increment Markov information update process where the control effectors know only the past information update intervals and the Markov transition mechanism is almost identical to that obtained with a known and uniform information update interval.
Singal, Ashok K.
2014-07-01
We examine the consistency of the unified scheme of Fanaroff-Riley type II radio galaxies and quasars with their observed number and size distributions in the 3CRR sample. We separate the low-excitation galaxies from the high-excitation ones, as the former might not harbor a quasar within and thus may not be partaking in the unified scheme models. In the updated 3CRR sample, at low redshifts (z < 0.5), the relative number and luminosity distributions of high-excitation galaxies and quasars roughly match the expectations from the orientation-based unified scheme model. However, a foreshortening in the observed sizes of quasars, which is a must in the orientation-based model, is not seen with respect to radio galaxies even when the low-excitation galaxies are excluded. This dashes the hope that the unified scheme might still work if one includes only the high-excitation galaxies.
Classifier-Guided Sampling for Complex Energy System Optimization
Backlund, Peter B.; Eddy, John P.
2015-09-01
This report documents the results of a Laboratory Directed Research and Development (LDRD) effort enti tled "Classifier - Guided Sampling for Complex Energy System Optimization" that was conducted during FY 2014 and FY 2015. The goal of this proj ect was to develop, implement, and test major improvements to the classifier - guided sampling (CGS) algorithm. CGS is type of evolutionary algorithm for perform ing search and optimization over a set of discrete design variables in the face of one or more objective functions. E xisting evolutionary algorithms, such as genetic algorithms , may require a large number of o bjecti ve function evaluations to identify optimal or near - optimal solutions . Reducing the number of evaluations can result in significant time savings, especially if the objective function is computationally expensive. CGS reduce s the evaluation count by us ing a Bayesian network classifier to filter out non - promising candidate designs , prior to evaluation, based on their posterior probabilit ies . In this project, b oth the single - objective and multi - objective version s of the CGS are developed and tested on a set of benchm ark problems. As a domain - specific case study, CGS is used to design a microgrid for use in islanded mode during an extended bulk power grid outage.
Efficient infill sampling for unconstrained robust optimization problems
NASA Astrophysics Data System (ADS)
Rehman, Samee Ur; Langelaar, Matthijs
2016-08-01
A novel infill sampling criterion is proposed for efficient estimation of the global robust optimum of expensive computer simulation based problems. The algorithm is especially geared towards addressing problems that are affected by uncertainties in design variables and problem parameters. The method is based on constructing metamodels using Kriging and adaptively sampling the response surface via a principle of expected improvement adapted for robust optimization. Several numerical examples and an engineering case study are used to demonstrate the ability of the algorithm to estimate the global robust optimum using a limited number of expensive function evaluations.
Learning approach to sampling optimization: Applications in astrodynamics
NASA Astrophysics Data System (ADS)
Henderson, Troy Allen
A new, novel numerical optimization algorithm is developed, tested, and used to solve difficult numerical problems from the field of astrodynamics. First, a brief review of optimization theory is presented and common numerical optimization techniques are discussed. Then, the new method, called the Learning Approach to Sampling Optimization (LA) is presented. Simple, illustrative examples are given to further emphasize the simplicity and accuracy of the LA method. Benchmark functions in lower dimensions are studied and the LA is compared, in terms of performance, to widely used methods. Three classes of problems from astrodynamics are then solved. First, the N-impulse orbit transfer and rendezvous problems are solved by using the LA optimization technique along with derived bounds that make the problem computationally feasible. This marriage between analytical and numerical methods allows an answer to be found for an order of magnitude greater number of impulses than are currently published. Next, the N-impulse work is applied to design periodic close encounters (PCE) in space. The encounters are defined as an open rendezvous, meaning that two spacecraft must be at the same position at the same time, but their velocities are not necessarily equal. The PCE work is extended to include N-impulses and other constraints, and new examples are given. Finally, a trajectory optimization problem is solved using the LA algorithm and comparing performance with other methods based on two models---with varying complexity---of the Cassini-Huygens mission to Saturn. The results show that the LA consistently outperforms commonly used numerical optimization algorithms.
NASA Astrophysics Data System (ADS)
Schwientek, Marc; Guillet, Gaelle; Kuch, Bertram; Rügner, Hermann; Grathwohl, Peter
2014-05-01
Xenobiotic contaminants such as pharmaceuticals or personal care products typically are continuously introduced into the receiving water bodies via wastewater treatment plant (WWTP) outfalls and, episodically, via combined sewer overflows in the case of precipitation events. Little is known about how these chemicals behave in the environment and how they affect ecosystems and human health. Examples of traditional persistent organic pollutants reveal, that they may still be present in the environment even decades after they have been released. In this study a sampling strategy was developed which gives valuable insights into the environmental behaviour of xenobiotic chemicals. The method is based on the Lagrangian sampling scheme by which a parcel of water is sampled repeatedly as it moves downstream while chemical, physical, and hydrologic processes altering the characteristics of the water mass can be investigated. The Steinlach is a tributary of the River Neckar in Southwest Germany with a catchment area of 140 km². It receives the effluents of a WWTP with 99,000 inhabitant equivalents 4 km upstream of its mouth. The varying flow rate of effluents induces temporal patterns of electrical conductivity in the river water which enable to track parcels of water along the subsequent urban river section. These parcels of water were sampled a) close to the outlet of the WWTP and b) 4 km downstream at the confluence with the Neckar. Sampling was repeated at a 15 min interval over a complete diurnal cycle and 2 h composite samples were prepared. A model-based analysis demonstrated, on the one hand, that substances behaved reactively to a varying extend along the studied river section. On the other hand, it revealed that the observed degradation rates are likely dependent on the time of day. Some chemicals were degraded mainly during daytime (e.g. the disinfectant Triclosan or the phosphorous flame retardant TDCP), others as well during nighttime (e.g. the musk fragrance
Simultaneous beam sampling and aperture shape optimization for SPORT
Zarepisheh, Masoud; Li, Ruijiang; Xing, Lei; Ye, Yinyu
2015-02-15
Purpose: Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: The authors build a mathematical model with the fundamental station point parameters as the decision variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. Results: A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and
The Quasar Fraction in Low-Frequency Selected Complete Samples and Implications for Unified Schemes
NASA Technical Reports Server (NTRS)
Willott, Chris J.; Rawlings, Steve; Blundell, Katherine M.; Lacy, Mark
2000-01-01
Low-frequency radio surveys are ideal for selecting orientation-independent samples of extragalactic sources because the sample members are selected by virtue of their isotropic steep-spectrum extended emission. We use the new 7C Redshift Survey along with the brighter 3CRR and 6C samples to investigate the fraction of objects with observed broad emission lines - the 'quasar fraction' - as a function of redshift and of radio and narrow emission line luminosity. We find that the quasar fraction is more strongly dependent upon luminosity (both narrow line and radio) than it is on redshift. Above a narrow [OII] emission line luminosity of log(base 10) (L(sub [OII])/W) approximately > 35 [or radio luminosity log(base 10) (L(sub 151)/ W/Hz.sr) approximately > 26.5], the quasar fraction is virtually independent of redshift and luminosity; this is consistent with a simple unified scheme with an obscuring torus with a half-opening angle theta(sub trans) approximately equal 53 deg. For objects with less luminous narrow lines, the quasar fraction is lower. We show that this is not due to the difficulty of detecting lower-luminosity broad emission lines in a less luminous, but otherwise similar, quasar population. We discuss evidence which supports at least two probable physical causes for the drop in quasar fraction at low luminosity: (i) a gradual decrease in theta(sub trans) and/or a gradual increase in the fraction of lightly-reddened (0 approximately < A(sub V) approximately < 5) lines-of-sight with decreasing quasar luminosity; and (ii) the emergence of a distinct second population of low luminosity radio sources which, like M8T, lack a well-fed quasar nucleus and may well lack a thick obscuring torus.
Optimized robust plasma sampling for glomerular filtration rate studies.
Murray, Anthony W; Gannon, Mark A; Barnfield, Mark C; Waller, Michael L
2012-09-01
In the presence of abnormal fluid collection (e.g. ascites), the measurement of glomerular filtration rate (GFR) based on a small number (1-4) of plasma samples fails. This study investigated how a few samples will allow adequate characterization of plasma clearance to give a robust and accurate GFR measurement. A total of 68 nine-sample GFR tests (from 45 oncology patients) with abnormal clearance of a glomerular tracer were audited to develop a Monte Carlo model. This was used to generate 20 000 synthetic but clinically realistic clearance curves, which were sampled at the 10 time points suggested by the British Nuclear Medicine Society. All combinations comprising between four and 10 samples were then used to estimate the area under the clearance curve by nonlinear regression. The audited clinical plasma curves were all well represented pragmatically as biexponential curves. The area under the curve can be well estimated using as few as five judiciously timed samples (5, 10, 15, 90 and 180 min). Several seven-sample schedules (e.g. 5, 10, 15, 60, 90, 180 and 240 min) are tolerant to any one sample being discounted without significant loss of accuracy or precision. A research tool has been developed that can be used to estimate the accuracy and precision of any pattern of plasma sampling in the presence of 'third-space' kinetics. This could also be used clinically to estimate the accuracy and precision of GFR calculated from mistimed or incomplete sets of samples. It has been used to identify optimized plasma sampling schedules for GFR measurement. PMID:22825040
Geminal embedding scheme for optimal atomic basis set construction in correlated calculations
Sorella, S.; Devaux, N.; Dagrada, M.; Mazzola, G.; Casula, M.
2015-12-28
We introduce an efficient method to construct optimal and system adaptive basis sets for use in electronic structure and quantum Monte Carlo calculations. The method is based on an embedding scheme in which a reference atom is singled out from its environment, while the entire system (atom and environment) is described by a Slater determinant or its antisymmetrized geminal power (AGP) extension. The embedding procedure described here allows for the systematic and consistent contraction of the primitive basis set into geminal embedded orbitals (GEOs), with a dramatic reduction of the number of variational parameters necessary to represent the many-body wave function, for a chosen target accuracy. Within the variational Monte Carlo method, the Slater or AGP part is determined by a variational minimization of the energy of the whole system in presence of a flexible and accurate Jastrow factor, representing most of the dynamical electronic correlation. The resulting GEO basis set opens the way for a fully controlled optimization of many-body wave functions in electronic structure calculation of bulk materials, namely, containing a large number of electrons and atoms. We present applications on the water molecule, the volume collapse transition in cerium, and the high-pressure liquid hydrogen.
An optimal scaling scheme for DCO-OFDM based visible light communications
NASA Astrophysics Data System (ADS)
Jiang, Rui; Wang, Qi; Wang, Fang; Dai, Linglong; Wang, Zhaocheng
2015-12-01
DC-biased optical orthogonal frequency-division multiplexing (DCO-OFDM) is widely used in visible light communication (VLC) systems to provide high data rate transmission. As intensity modulation with direct detection (IM/DD) is employed to modulate the OFDM signal, scale up the amplitude of the signal can increase the effective transmitted electrical power whereas more signals are likely to be clipped due to the limited dynamic range of LEDs, resulting in severe clipping distortion. Thus, it is crucial to scale the signal to find a tradeoff between the effective electrical power and the clipping distortion. In this paper, an optimal scaling scheme is proposed to maximize the received signal-to-noise-plus-distortion ratio (SNDR) with the constraint of the radiated optical power in a practical scenario where DC bias is fixed for a desired dimming level. Simulation results show that the system with the optimal scaling factor outperforms that with fixed scaling factor under different equivalent noise power in terms of the bit error ratio (BER) performance.
NASA Technical Reports Server (NTRS)
Moerder, Daniel D.
1987-01-01
A concept for optimally designing output feedback controllers for plants whose dynamics exhibit gross changes over their operating regimes was developed. This was to formulate the design problem in such a way that the implemented feedback gains vary as the output of a dynamical system whose independent variable is a scalar parameterization of the plant operating point. The results of this effort include derivation of necessary conditions for optimality for the general problem formulation, and for several simplified cases. The question of existence of a solution to the design problem was also examined, and it was shown that the class of gain variation schemes developed are capable of achieving gain variation histories which are arbitrarily close to the unconstrained gain solution for each point in the plant operating range. The theory was implemented in a feedback design algorithm, which was exercised in a numerical example. The results are applicable to the design of practical high-performance feedback controllers for plants whose dynamics vary significanly during operation. Many aerospace systems fall into this category.
Accelerated Simplified Swarm Optimization with Exploitation Search Scheme for Data Clustering
Yeh, Wei-Chang; Lai, Chyh-Ming
2015-01-01
Data clustering is commonly employed in many disciplines. The aim of clustering is to partition a set of data into clusters, in which objects within the same cluster are similar and dissimilar to other objects that belong to different clusters. Over the past decade, the evolutionary algorithm has been commonly used to solve clustering problems. This study presents a novel algorithm based on simplified swarm optimization, an emerging population-based stochastic optimization approach with the advantages of simplicity, efficiency, and flexibility. This approach combines variable vibrating search (VVS) and rapid centralized strategy (RCS) in dealing with clustering problem. VVS is an exploitation search scheme that can refine the quality of solutions by searching the extreme points nearby the global best position. RCS is developed to accelerate the convergence rate of the algorithm by using the arithmetic average. To empirically evaluate the performance of the proposed algorithm, experiments are examined using 12 benchmark datasets, and corresponding results are compared with recent works. Results of statistical analysis indicate that the proposed algorithm is competitive in terms of the quality of solutions. PMID:26348483
Ramezanpour, HR; Setayeshi, S; Akbari, ME
2011-01-01
Background Determining the optimal and effective scheme for administrating the chemotherapy agents in breast cancer is the main goal of this scientific research. The most important issue here is the amount of drug or radiation administrated in chemotherapy and radiotherapy for increasing patient's survival. This is because in these cases, the therapy not only kills the tumor cells, but also kills some of the healthy tissues and causes serious damages. In this paper we investigate optimal drug scheduling effect for breast cancer model which consist of nonlinear ordinary differential time-delay equations. Methods In this paper, a mathematical model of breast cancer tumors is discussed and then optimal control theory is applied to find out the optimal drug adjustment as an input control of system. Finally we use Sensitivity Approach (SA) to solve the optimal control problem. Results The goal of this paper is to determine optimal and effective scheme for administering the chemotherapy agent, so that the tumor is eradicated, while the immune systems remains above a suitable level. Simulation results confirm the effectiveness of our proposed procedure. Conclusion In this paper a new scheme is proposed to design a therapy protocol for chemotherapy in Breast Cancer. In contrast to traditional pulse drug delivery, a continuous process is offered and optimized, according to the optimal control theory for time-delay systems. PMID:26322192
Sampling optimization for printer characterization by greedy search.
Morovic, Ján; Arnabat, Jordi; Richard, Yvan; Albarrán, Angel
2010-10-01
Printer color characterization, e.g., in the form of an ICC output profile or other proprietary mechanism linking printer RGB/CMYK inputs to resulting colorimetry, is fundamental to a printing system delivering output that is acceptable to its recipients. Due to the inherently nonlinear and complex relationship between a printing system's inputs and the resulting color output, color characterization typically requires a large sample of printer inputs (e.g., RGB/CMYK) and corresponding color measurements of printed output. Simple sampling techniques here lead to inefficiency and a low return for increases in sampling density. While effective solutions have been proposed to this problem very recently, they either do not exploit the full possibilities of the 3-D/4-D space being sampled or they make assumptions about the underlying relationship being sampled . The approach presented here does not make assumptions beyond those inherent in the subsequent tessellation and interpolation applied to the resulting samples. Instead, the tradeoff here is the great computational cost of the initial optimization, which, however, only needs to be performed during the printing system's engineering and is transparent to its end users. Results show a significant reduction in the number of samples needed to match a given level of color accuracy.
Determining the Bayesian optimal sampling strategy in a hierarchical system.
Grace, Matthew D.; Ringland, James T.; Boggs, Paul T.; Pebay, Philippe Pierre
2010-09-01
Consider a classic hierarchy tree as a basic model of a 'system-of-systems' network, where each node represents a component system (which may itself consist of a set of sub-systems). For this general composite system, we present a technique for computing the optimal testing strategy, which is based on Bayesian decision analysis. In previous work, we developed a Bayesian approach for computing the distribution of the reliability of a system-of-systems structure that uses test data and prior information. This allows for the determination of both an estimate of the reliability and a quantification of confidence in the estimate. Improving the accuracy of the reliability estimate and increasing the corresponding confidence require the collection of additional data. However, testing all possible sub-systems may not be cost-effective, feasible, or even necessary to achieve an improvement in the reliability estimate. To address this sampling issue, we formulate a Bayesian methodology that systematically determines the optimal sampling strategy under specified constraints and costs that will maximally improve the reliability estimate of the composite system, e.g., by reducing the variance of the reliability distribution. This methodology involves calculating the 'Bayes risk of a decision rule' for each available sampling strategy, where risk quantifies the relative effect that each sampling strategy could have on the reliability estimate. A general numerical algorithm is developed and tested using an example multicomponent system. The results show that the procedure scales linearly with the number of components available for testing.
Optimization of sampling pattern and the design of Fourier ptychographic illuminator.
Guo, Kaikai; Dong, Siyuan; Nanda, Pariksheet; Zheng, Guoan
2015-03-01
Fourier ptychography (FP) is a recently developed imaging approach that facilitates high-resolution imaging beyond the cutoff frequency of the employed optics. In the original FP approach, a periodic LED array is used for sample illumination, and therefore, the scanning pattern is a uniform grid in the Fourier space. Such a uniform sampling scheme leads to 3 major problems for FP, namely: 1) it requires a large number of raw images, 2) it introduces the raster grid artefacts in the reconstruction process, and 3) it requires a high-dynamic-range detector. Here, we investigate scanning sequences and sampling patterns to optimize the FP approach. For most biological samples, signal energy is concentrated at low-frequency region, and as such, we can perform non-uniform Fourier sampling in FP by considering the signal structure. In contrast, conventional ptychography perform uniform sampling over the entire real space. To implement the non-uniform Fourier sampling scheme in FP, we have designed and built an illuminator using LEDs mounted on a 3D-printed plastic case. The advantages of this illuminator are threefold in that: 1) it reduces the number of image acquisitions by at least 50% (68 raw images versus 137 in the original FP setup), 2) it departs from the translational symmetry of sampling to solve the raster grid artifact problem, and 3) it reduces the dynamic range of the captured images 6 fold. The results reported in this paper significantly shortened acquisition time and improved quality of FP reconstructions. It may provide new insights for developing Fourier ptychographic imaging platforms and find important applications in digital pathology. PMID:25836839
A General Investigation of Optimized Atmospheric Sample Duration
Eslinger, Paul W.; Miley, Harry S.
2012-11-28
ABSTRACT The International Monitoring System (IMS) consists of up to 80 aerosol and xenon monitoring systems spaced around the world that have collection systems sensitive enough to detect nuclear releases from underground nuclear tests at great distances (CTBT 1996; CTBTO 2011). Although a few of the IMS radionuclide stations are closer together than 1,000 km (such as the stations in Kuwait and Iran), many of them are 2,000 km or more apart. In the absence of a scientific basis for optimizing the duration of atmospheric sampling, historically scientists used a integration times from 24 hours to 14 days for radionuclides (Thomas et al. 1977). This was entirely adequate in the past because the sources of signals were far away and large, meaning that they were smeared over many days by the time they had travelled 10,000 km. The Fukushima event pointed out the unacceptable delay time (72 hours) between the start of sample acquisition and final data being shipped. A scientific basis for selecting a sample duration time is needed. This report considers plume migration of a nondecaying tracer using archived atmospheric data for 2011 in the HYSPLIT (Draxler and Hess 1998; HYSPLIT 2011) transport model. We present two related results: the temporal duration of the majority of the plume as a function of distance and the behavior of the maximum plume concentration as a function of sample collection duration and distance. The modeled plume behavior can then be combined with external information about sampler design to optimize sample durations in a sampling network.
Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria
NASA Technical Reports Server (NTRS)
Chien, Steve A.; Thompson, David R.; Hsiang, Kian
2013-01-01
This work was designed to find a way to optimally (or near optimally) sample spatiotemporal phenomena based on limited sensing capability, and to create a model that can be run to estimate uncertainties, as well as to estimate covariances. The goal was to maximize (or minimize) some function of the overall uncertainty. The uncertainties and covariances were modeled presuming a parametric distribution, and then the model was used to approximate the overall information gain, and consequently, the objective function from each potential sense. These candidate sensings were then crosschecked against operation costs and feasibility. Consequently, an operations plan was derived that combined both operational constraints/costs and sensing gain. Probabilistic modeling was used to perform an approximate inversion of the model, which enabled calculation of sensing gains, and subsequent combination with operational costs. This incorporation of operations models to assess cost and feasibility for specific classes of vehicles is unique.
Fixed-sample optimization using a probability density function
Barnett, R.N.; Sun, Zhiwei; Lester, W.A. Jr. |
1997-12-31
We consider the problem of optimizing parameters in a trial function that is to be used in fixed-node diffusion Monte Carlo calculations. We employ a trial function with a Boys-Handy correlation function and a one-particle basis set of high quality. By employing sample points picked from a positive definite distribution, parameters that determine the nodes of the trial function can be varied without introducing singularities into the optimization. For CH as a test system, we find that a trial function of high quality is obtained and that this trial function yields an improved fixed-node energy. This result sheds light on the important question of how to improve the nodal structure and, thereby, the accuracy of diffusion Monte Carlo.
NASA Astrophysics Data System (ADS)
Izzuan Jaafar, Hazriq; Mohd Ali, Nursabillilah; Mohamed, Z.; Asmiza Selamat, Nur; Faiz Zainal Abidin, Amar; Jamian, J. J.; Kassim, Anuar Mohamed
2013-12-01
This paper presents development of an optimal PID and PD controllers for controlling the nonlinear gantry crane system. The proposed Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is adopted in obtaining five optimal controller gains. The optimal gains are tested on a control structure that combines PID and PD controllers to examine system responses including trolley displacement and payload oscillation. The dynamic model of gantry crane system is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of system in terms of settling time (Ts), steady state error (SSE) and overshoot (OS). This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the various desired position.
Gossner, Martin M.; Struwe, Jan-Frederic; Sturm, Sarah; Max, Simeon; McCutcheon, Michelle; Weisser, Wolfgang W.; Zytynska, Sharon E.
2016-01-01
There is a great demand for standardising biodiversity assessments in order to allow optimal comparison across research groups. For invertebrates, pitfall or flight-interception traps are commonly used, but sampling solution differs widely between studies, which could influence the communities collected and affect sample processing (morphological or genetic). We assessed arthropod communities with flight-interception traps using three commonly used sampling solutions across two forest types and two vertical strata. We first considered the effect of sampling solution and its interaction with forest type, vertical stratum, and position of sampling jar at the trap on sample condition and community composition. We found that samples collected in copper sulphate were more mouldy and fragmented relative to other solutions which might impair morphological identification, but condition depended on forest type, trap type and the position of the jar. Community composition, based on order-level identification, did not differ across sampling solutions and only varied with forest type and vertical stratum. Species richness and species-level community composition, however, differed greatly among sampling solutions. Renner solution was highly attractant for beetles and repellent for true bugs. Secondly, we tested whether sampling solution affects subsequent molecular analyses and found that DNA barcoding success was species-specific. Samples from copper sulphate produced the fewest successful DNA sequences for genetic identification, and since DNA yield or quality was not particularly reduced in these samples additional interactions between the solution and DNA must also be occurring. Our results show that the choice of sampling solution should be an important consideration in biodiversity studies. Due to the potential bias towards or against certain species by Ethanol-containing sampling solution we suggest ethylene glycol as a suitable sampling solution when genetic analysis
Gossner, Martin M; Struwe, Jan-Frederic; Sturm, Sarah; Max, Simeon; McCutcheon, Michelle; Weisser, Wolfgang W; Zytynska, Sharon E
2016-01-01
There is a great demand for standardising biodiversity assessments in order to allow optimal comparison across research groups. For invertebrates, pitfall or flight-interception traps are commonly used, but sampling solution differs widely between studies, which could influence the communities collected and affect sample processing (morphological or genetic). We assessed arthropod communities with flight-interception traps using three commonly used sampling solutions across two forest types and two vertical strata. We first considered the effect of sampling solution and its interaction with forest type, vertical stratum, and position of sampling jar at the trap on sample condition and community composition. We found that samples collected in copper sulphate were more mouldy and fragmented relative to other solutions which might impair morphological identification, but condition depended on forest type, trap type and the position of the jar. Community composition, based on order-level identification, did not differ across sampling solutions and only varied with forest type and vertical stratum. Species richness and species-level community composition, however, differed greatly among sampling solutions. Renner solution was highly attractant for beetles and repellent for true bugs. Secondly, we tested whether sampling solution affects subsequent molecular analyses and found that DNA barcoding success was species-specific. Samples from copper sulphate produced the fewest successful DNA sequences for genetic identification, and since DNA yield or quality was not particularly reduced in these samples additional interactions between the solution and DNA must also be occurring. Our results show that the choice of sampling solution should be an important consideration in biodiversity studies. Due to the potential bias towards or against certain species by Ethanol-containing sampling solution we suggest ethylene glycol as a suitable sampling solution when genetic analysis
Mielke, Steven L; Truhlar, Donald G
2016-01-21
Using Feynman path integrals, a molecular partition function can be written as a double integral with the inner integral involving all closed paths centered at a given molecular configuration, and the outer integral involving all possible molecular configurations. In previous work employing Monte Carlo methods to evaluate such partition functions, we presented schemes for importance sampling and stratification in the molecular configurations that constitute the path centroids, but we relied on free-particle paths for sampling the path integrals. At low temperatures, the path sampling is expensive because the paths can travel far from the centroid configuration. We now present a scheme for importance sampling of whole Feynman paths based on harmonic information from an instantaneous normal mode calculation at the centroid configuration, which we refer to as harmonically guided whole-path importance sampling (WPIS). We obtain paths conforming to our chosen importance function by rejection sampling from a distribution of free-particle paths. Sample calculations on CH4 demonstrate that at a temperature of 200 K, about 99.9% of the free-particle paths can be rejected without integration, and at 300 K, about 98% can be rejected. We also show that it is typically possible to reduce the overhead associated with the WPIS scheme by sampling the paths using a significantly lower-order path discretization than that which is needed to converge the partition function.
Mielke, Steven L; Truhlar, Donald G
2016-01-21
Using Feynman path integrals, a molecular partition function can be written as a double integral with the inner integral involving all closed paths centered at a given molecular configuration, and the outer integral involving all possible molecular configurations. In previous work employing Monte Carlo methods to evaluate such partition functions, we presented schemes for importance sampling and stratification in the molecular configurations that constitute the path centroids, but we relied on free-particle paths for sampling the path integrals. At low temperatures, the path sampling is expensive because the paths can travel far from the centroid configuration. We now present a scheme for importance sampling of whole Feynman paths based on harmonic information from an instantaneous normal mode calculation at the centroid configuration, which we refer to as harmonically guided whole-path importance sampling (WPIS). We obtain paths conforming to our chosen importance function by rejection sampling from a distribution of free-particle paths. Sample calculations on CH4 demonstrate that at a temperature of 200 K, about 99.9% of the free-particle paths can be rejected without integration, and at 300 K, about 98% can be rejected. We also show that it is typically possible to reduce the overhead associated with the WPIS scheme by sampling the paths using a significantly lower-order path discretization than that which is needed to converge the partition function. PMID:26801023
Continuous quality control of the blood sampling procedure using a structured observation scheme
Seemann, Tine Lindberg; Nybo, Mads
2016-01-01
Introduction An observational study was conducted using a structured observation scheme to assess compliance with the local phlebotomy guideline, to identify necessary focus items, and to investigate whether adherence to the phlebotomy guideline improved. Materials and methods The questionnaire from the EFLM Working Group for the Preanalytical Phase was adapted to local procedures. A pilot study of three months duration was conducted. Based on this, corrective actions were implemented and a follow-up study was conducted. All phlebotomists at the Department of Clinical Biochemistry and Pharmacology were observed. Three blood collections by each phlebotomist were observed at each session conducted at the phlebotomy ward and the hospital wards, respectively. Error frequencies were calculated for the phlebotomy ward and the hospital wards and for the two study phases. Results A total of 126 blood drawings by 39 phlebotomists were observed in the pilot study, while 84 blood drawings by 34 phlebotomists were observed in the follow-up study. In the pilot study, the three major error items were hand hygiene (42% error), mixing of samples (22%), and order of draw (21%). Minor significant differences were found between the two settings. After focus on the major aspects, the follow-up study showed significant improvement for all three items at both settings (P < 0.01, P < 0.01, and P = 0.01, respectively). Conclusion Continuous quality control of the phlebotomy procedure revealed a number of items not conducted in compliance with the local phlebotomy guideline. It supported significant improvements in the adherence to the recommended phlebotomy procedures and facilitated documentation of the phlebotomy quality. PMID:27812302
Optimal Sample Complexity for Blind Gain and Phase Calibration
NASA Astrophysics Data System (ADS)
Li, Yanjun; Lee, Kiryung; Bresler, Yoram
2016-11-01
Blind gain and phase calibration (BGPC) is a structured bilinear inverse problem, which arises in many applications, including inverse rendering in computational relighting (albedo estimation with unknown lighting), blind phase and gain calibration in sensor array processing, and multichannel blind deconvolution. The fundamental question of the uniqueness of the solutions to such problems has been addressed only recently. In a previous paper, we proposed studying the identifiability in bilinear inverse problems up to transformation groups. In particular, we studied several special cases of blind gain and phase calibration, including the cases of subspace and joint sparsity models on the signals, and gave sufficient and necessary conditions for identifiability up to certain transformation groups. However, there were gaps between the sample complexities in the sufficient conditions and the necessary conditions. In this paper, under a mild assumption that the signals and models are generic, we bridge the gaps by deriving tight sufficient conditions with optimal sample complexities.
Decision Models for Determining the Optimal Life Test Sampling Plans
NASA Astrophysics Data System (ADS)
Nechval, Nicholas A.; Nechval, Konstantin N.; Purgailis, Maris; Berzins, Gundars; Strelchonok, Vladimir F.
2010-11-01
Life test sampling plan is a technique, which consists of sampling, inspection, and decision making in determining the acceptance or rejection of a batch of products by experiments for examining the continuous usage time of the products. In life testing studies, the lifetime is usually assumed to be distributed as either a one-parameter exponential distribution, or a two-parameter Weibull distribution with the assumption that the shape parameter is known. Such oversimplified assumptions can facilitate the follow-up analyses, but may overlook the fact that the lifetime distribution can significantly affect the estimation of the failure rate of a product. Moreover, sampling costs, inspection costs, warranty costs, and rejection costs are all essential, and ought to be considered in choosing an appropriate sampling plan. The choice of an appropriate life test sampling plan is a crucial decision problem because a good plan not only can help producers save testing time, and reduce testing cost; but it also can positively affect the image of the product, and thus attract more consumers to buy it. This paper develops the frequentist (non-Bayesian) decision models for determining the optimal life test sampling plans with an aim of cost minimization by identifying the appropriate number of product failures in a sample that should be used as a threshold in judging the rejection of a batch. The two-parameter exponential and Weibull distributions with two unknown parameters are assumed to be appropriate for modelling the lifetime of a product. A practical numerical application is employed to demonstrate the proposed approach.
Conditional sampling schemes based on the Variable Interval Time Averaging (VITA) algorithm
NASA Astrophysics Data System (ADS)
Morrison, J. F.; Tsai, H. M.; Bradshaw, P.
1986-08-01
The variable interval time averaging (VITA) algorithm was tested in a variety of boundary layers for its ability to detect motions principally involved in the production of shear stress. A VITA+LEVEL scheme (which uses a variance and level criterion) was devised and is shown to produce length scale statistics that are independent of the conditioning criteria, where those from the VITA scheme are not.
Aflatoonian, A; Baghianimoghadam, B; Abdoli, A; Partovi, P; Hemmati, P; Tabibnejad, N; Harasym, P
2012-01-01
Objectives: to present our first experience in scheme development based on CPC philosophy in Iran. Hypothesis: One of the most important reasons of an obvious gap between medical education and professional expectations (outcomes) encountered by recent medical graduates is due to applying conventional curricula, which rely on hypothetical-deductive reasoning model. The University of Calgary has implemented a new curriculum which is organized according to 125 ways in which patients may present to a physician. In this study we will present our first experience in scheme development based on CPC philosophy in Iran. Methods: In 2007, research and clinical center for infertility (Yazd University of medical sciences, IRAN), began developing a full module for infertility (lesson plan) with fourteen components based on the new curricular philosophy. We recruited a scheme of infertility according to a specific way. Results: Thus, at the first step of the module creation, a scheme was made as the most important mainstay of presentation module, i.e. a structured scheme that includes all causative diseases of infertility. Conclusions: Any effort in the organization of knowledge around schemes including in the domain of infertility would be valuable to meet some of the standards of WFME. Also, development of modules, by the teams composed of experts and students, can improve the quality of medical education. PMID:22574082
A test of an optimal stomatal conductance scheme within the CABLE Land Surface Model
NASA Astrophysics Data System (ADS)
De Kauwe, M. G.; Kala, J.; Lin, Y.-S.; Pitman, A. J.; Medlyn, B. E.; Duursma, R. A.; Abramowitz, G.; Wang, Y.-P.; Miralles, D. G.
2014-10-01
Stomatal conductance (gs) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We therefore constrained the key model parameter "g1" which represents a plants water use strategy by PFT based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960-1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal models in conjunction with PFT parameterisations resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance when compared to upscaled data products was not degraded, though the new stomatal conductance scheme did not noticeably change existing model-data biases. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.
Inhibition of viscous fluid fingering: A variational scheme for optimal flow rates
NASA Astrophysics Data System (ADS)
Miranda, Jose; Dias, Eduardo; Alvarez-Lacalle, Enrique; Carvalho, Marcio
2012-11-01
Conventional viscous fingering flow in radial Hele-Shaw cells employs a constant injection rate, resulting in the emergence of branched interfacial shapes. The search for mechanisms to prevent the development of these bifurcated morphologies is relevant to a number of areas in science and technology. A challenging problem is how best to choose the pumping rate in order to restrain growth of interfacial amplitudes. We use an analytical variational scheme to look for the precise functional form of such an optimal flow rate. We find it increases linearly with time in a specific manner so that interface disturbances are minimized. Experiments and nonlinear numerical simulations support the effectiveness of this particularly simple, but not at all obvious, pattern controlling process. J.A.M., E.O.D. and M.S.C. thank CNPq/Brazil for financial support. E.A.L. acknowledges support from Secretaria de Estado de IDI Spain under project FIS2011-28820-C02-01.
Gizaw, S; van Arendonk, J A M; Valle-Zárate, A; Haile, A; Rischkowsky, B; Dessie, T; Mwai, A O
2014-10-01
A simulation study was conducted to optimize a cooperative village-based sheep breeding scheme for Menz sheep of Ethiopia. Genetic gains and profits were estimated under nine levels of farmers' participation and three scenarios of controlled breeding achieved in the breeding programme, as well as under three cooperative flock sizes, ewe to ram mating ratios and durations of ram use for breeding. Under fully controlled breeding, that is, when there is no gene flow between participating (P) and non-participating (NP) flocks, profits ranged from Birr 36.9 at 90% of participation to Birr 21.3 at 10% of participation. However, genetic progress was not affected adversely. When there was gene flow from the NP to P flocks, profits declined from Birr 28.6 to Birr -3.7 as participation declined from 90 to 10%. Under the two-way gene flow model (i.e. when P and NP flocks are herded mixed in communal grazing areas), NP flocks benefited from the genetic gain achieved in the P flocks, but the benefits declined sharply when participation declined beyond 60%. Our results indicate that a cooperative breeding group can be established with as low as 600 breeding ewes mated at a ratio of 45 ewes to one ram, and the rams being used for breeding for a period of two years. This study showed that farmer cooperation is crucial to effect genetic improvement under smallholder low-input sheep farming systems.
NASA Astrophysics Data System (ADS)
Tan, Sirui; Huang, Lianjie
2014-11-01
For modeling scalar-wave propagation in geophysical problems using finite-difference schemes, optimizing the coefficients of the finite-difference operators can reduce numerical dispersion. Most optimized finite-difference schemes for modeling seismic-wave propagation suppress only spatial but not temporal dispersion errors. We develop a novel optimized finite-difference scheme for numerical scalar-wave modeling to control dispersion errors not only in space but also in time. Our optimized scheme is based on a new stencil that contains a few more grid points than the standard stencil. We design an objective function for minimizing relative errors of phase velocities of waves propagating in all directions within a given range of wavenumbers. Dispersion analysis and numerical examples demonstrate that our optimized finite-difference scheme is computationally up to 2.5 times faster than the optimized schemes using the standard stencil to achieve the similar modeling accuracy for a given 2D or 3D problem. Compared with the high-order finite-difference scheme using the same new stencil, our optimized scheme reduces 50 percent of the computational cost to achieve the similar modeling accuracy. This new optimized finite-difference scheme is particularly useful for large-scale 3D scalar-wave modeling and inversion.
Tan, Sirui; Huang, Lianjie
2014-11-01
For modeling scalar-wave propagation in geophysical problems using finite-difference schemes, optimizing the coefficients of the finite-difference operators can reduce numerical dispersion. Most optimized finite-difference schemes for modeling seismic-wave propagation suppress only spatial but not temporal dispersion errors. We develop a novel optimized finite-difference scheme for numerical scalar-wave modeling to control dispersion errors not only in space but also in time. Our optimized scheme is based on a new stencil that contains a few more grid points than the standard stencil. We design an objective function for minimizing relative errors of phase velocities of waves propagating in all directions within a given range of wavenumbers. Dispersion analysis and numerical examples demonstrate that our optimized finite-difference scheme is computationally up to 2.5 times faster than the optimized schemes using the standard stencil to achieve the similar modeling accuracy for a given 2D or 3D problem. Compared with the high-order finite-difference scheme using the same new stencil, our optimized scheme reduces 50 percent of the computational cost to achieve the similar modeling accuracy. This new optimized finite-difference scheme is particularly useful for large-scale 3D scalar-wave modeling and inversion.
Optimization of Evans blue quantitation in limited rat tissue samples
NASA Astrophysics Data System (ADS)
Wang, Hwai-Lee; Lai, Ted Weita
2014-10-01
Evans blue dye (EBD) is an inert tracer that measures plasma volume in human subjects and vascular permeability in animal models. Quantitation of EBD can be difficult when dye concentration in the sample is limited, such as when extravasated dye is measured in the blood-brain barrier (BBB) intact brain. The procedure described here used a very small volume (30 µl) per sample replicate, which enabled high-throughput measurements of the EBD concentration based on a standard 96-well plate reader. First, ethanol ensured a consistent optic path length in each well and substantially enhanced the sensitivity of EBD fluorescence spectroscopy. Second, trichloroacetic acid (TCA) removed false-positive EBD measurements as a result of biological solutes and partially extracted EBD into the supernatant. Moreover, a 1:2 volume ratio of 50% TCA ([TCA final] = 33.3%) optimally extracted EBD from the rat plasma protein-EBD complex in vitro and in vivo, and 1:2 and 1:3 weight-volume ratios of 50% TCA optimally extracted extravasated EBD from the rat brain and liver, respectively, in vivo. This procedure is particularly useful in the detection of EBD extravasation into the BBB-intact brain, but it can also be applied to detect dye extravasation into tissues where vascular permeability is less limiting.
Optimal CCD readout by digital correlated double sampling
NASA Astrophysics Data System (ADS)
Alessandri, C.; Abusleme, A.; Guzman, D.; Passalacqua, I.; Alvarez-Fontecilla, E.; Guarini, M.
2016-01-01
Digital correlated double sampling (DCDS), a readout technique for charge-coupled devices (CCD), is gaining popularity in astronomical applications. By using an oversampling ADC and a digital filter, a DCDS system can achieve a better performance than traditional analogue readout techniques at the expense of a more complex system analysis. Several attempts to analyse and optimize a DCDS system have been reported, but most of the work presented in the literature has been experimental. Some approximate analytical tools have been presented for independent parameters of the system, but the overall performance and trade-offs have not been yet modelled. Furthermore, there is disagreement among experimental results that cannot be explained by the analytical tools available. In this work, a theoretical analysis of a generic DCDS readout system is presented, including key aspects such as the signal conditioning stage, the ADC resolution, the sampling frequency and the digital filter implementation. By using a time-domain noise model, the effect of the digital filter is properly modelled as a discrete-time process, thus avoiding the imprecision of continuous-time approximations that have been used so far. As a result, an accurate, closed-form expression for the signal-to-noise ratio at the output of the readout system is reached. This expression can be easily optimized in order to meet a set of specifications for a given CCD, thus providing a systematic design methodology for an optimal readout system. Simulated results are presented to validate the theory, obtained with both time- and frequency-domain noise generation models for completeness.
Neuro-genetic system for optimization of GMI samples sensitivity.
Pitta Botelho, A C O; Vellasco, M M B R; Hall Barbosa, C R; Costa Silva, E
2016-03-01
Magnetic sensors are largely used in several engineering areas. Among them, magnetic sensors based on the Giant Magnetoimpedance (GMI) effect are a new family of magnetic sensing devices that have a huge potential for applications involving measurements of ultra-weak magnetic fields. The sensitivity of magnetometers is directly associated with the sensitivity of their sensing elements. The GMI effect is characterized by a large variation of the impedance (magnitude and phase) of a ferromagnetic sample, when subjected to a magnetic field. Recent studies have shown that phase-based GMI magnetometers have the potential to increase the sensitivity by about 100 times. The sensitivity of GMI samples depends on several parameters, such as sample length, external magnetic field, DC level and frequency of the excitation current. However, this dependency is yet to be sufficiently well-modeled in quantitative terms. So, the search for the set of parameters that optimizes the samples sensitivity is usually empirical and very time consuming. This paper deals with this problem by proposing a new neuro-genetic system aimed at maximizing the impedance phase sensitivity of GMI samples. A Multi-Layer Perceptron (MLP) Neural Network is used to model the impedance phase and a Genetic Algorithm uses the information provided by the neural network to determine which set of parameters maximizes the impedance phase sensitivity. The results obtained with a data set composed of four different GMI sample lengths demonstrate that the neuro-genetic system is able to correctly and automatically determine the set of conditioning parameters responsible for maximizing their phase sensitivities.
Sampling plan optimization for detection of lithography and etch CD process excursions
NASA Astrophysics Data System (ADS)
Elliott, Richard C.; Nurani, Raman K.; Lee, Sung Jin; Ortiz, Luis G.; Preil, Moshe E.; Shanthikumar, J. G.; Riley, Trina; Goodwin, Greg A.
2000-06-01
Effective sample planning requires a careful combination of statistical analysis and lithography engineering. In this paper, we present a complete sample planning methodology including baseline process characterization, determination of the dominant excursion mechanisms, and selection of sampling plans and control procedures to effectively detect the yield- limiting excursions with a minimum of added cost. We discuss the results of our novel method in identifying critical dimension (CD) process excursions and present several examples of poly gate Photo and Etch CD excursion signatures. Using these results in a Sample Planning model, we determine the optimal sample plan and statistical process control (SPC) chart metrics and limits for detecting these excursions. The key observations are that there are many different yield- limiting excursion signatures in photo and etch, and that a given photo excursion signature turns into a different excursion signature at etch with different yield and performance impact. In particular, field-to-field variance excursions are shown to have a significant impact on yield. We show how current sampling plan and monitoring schemes miss these excursions and suggest an improved procedure for effective detection of CD process excursions.
Jiang, Hai-ming; Xie, Kang; Wang, Ya-fei
2010-05-24
An effective pump scheme for the design of broadband and flat gain spectrum Raman fiber amplifiers is proposed. This novel approach uses a new shooting algorithm based on a modified Newton-Raphson method and a contraction factor to solve the two point boundary problems of Raman coupled equations more stably and efficiently. In combination with an improved particle swarm optimization method, which improves the efficiency and convergence rate by introducing a new parameter called velocity acceptability probability, this scheme optimizes the wavelengths and power levels for the pumps quickly and accurately. Several broadband Raman fiber amplifiers in C+L band with optimized pump parameters are designed. An amplifier of 4 pumps is designed to deliver an average on-off gain of 13.3 dB for a bandwidth of 80 nm, with about +/-0.5 dB in band maximum gain ripples.
NASA Astrophysics Data System (ADS)
Heckmann, Tobias; Gegg, Katharina; Becht, Michael
2013-04-01
Statistical approaches to landslide susceptibility modelling on the catchment and regional scale are used very frequently compared to heuristic and physically based approaches. In the present study, we deal with the problem of the optimal sample size for a logistic regression model. More specifically, a stepwise approach has been chosen in order to select those independent variables (from a number of derivatives of a digital elevation model and landcover data) that explain best the spatial distribution of debris flow initiation zones in two neighbouring central alpine catchments in Austria (used mutually for model calculation and validation). In order to minimise problems arising from spatial autocorrelation, we sample a single raster cell from each debris flow initiation zone within an inventory. In addition, as suggested by previous work using the "rare events logistic regression" approach, we take a sample of the remaining "non-event" raster cells. The recommendations given in the literature on the size of this sample appear to be motivated by practical considerations, e.g. the time and cost of acquiring data for non-event cases, which do not apply to the case of spatial data. In our study, we aim at finding empirically an "optimal" sample size in order to avoid two problems: First, a sample too large will violate the independent sample assumption as the independent variables are spatially autocorrelated; hence, a variogram analysis leads to a sample size threshold above which the average distance between sampled cells falls below the autocorrelation range of the independent variables. Second, if the sample is too small, repeated sampling will lead to very different results, i.e. the independent variables and hence the result of a single model calculation will be extremely dependent on the choice of non-event cells. Using a Monte-Carlo analysis with stepwise logistic regression, 1000 models are calculated for a wide range of sample sizes. For each sample size
Optimal Extraction with Sub-sampled Line-Spread Functions
NASA Technical Reports Server (NTRS)
Collins, Nicholas R.; Gull, Theodore; Bowers, Chuck; Lindler, Don
2002-01-01
STIS long-slit medium resolution spectra reduced in CALSTIS extended-source mode with narrow extraction heights (GWIDTH=3 pixels) show photometric uncertainties of +/- 3% relative to point-source extractions. These uncertainties are introduced through interpolation in the spectral image rectification processing stage, and are correlated with the number of pixel crossings the spectral profile core encounters in the spatial direction. The line-spread-function may be determined as a function of pixel crossing- position from calibration data sub-sampled in the spatial direction. This line spread function will be applied to science data to perform optimal extractions and point- source de-blending. Wavelength and breathing effects will be studied. Viability of the method to de-convolve extended source 'blobs' will be investigated.
Optimization for Peptide Sample Preparation for Urine Peptidomics
Sigdel, Tara K.; Nicora, Carrie D.; Hsieh, Szu-Chuan; Dai, Hong; Qian, Weijun; Camp, David G.; Sarwal, Minnie M.
2014-02-25
when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.
Fine chemical manipulations of microscopic liquid samples. 2. Consuming and nonconsuming schemes.
Lu, H; Matsumoto, T; Gratzl, M
1999-11-01
Microscopic liquid particles can be manipulated chemically using a suitable diffusional microburet (DMB), whose tiny tip plugged with a diffusion membrane acts as a well-defined diffusional transfer channel. In part 1 of this work (Gratzl et al. Anal. Chem. 1999, 71, 2751-2756), we discussed the simplest DMB-based operation: addition, i.e., loading a droplet with a chemical that accumulates there without any chemical reaction occurring. Since in this process no consumption of the delivered molecules in the target droplet takes place, addition is a nonconsuming scheme. In this work, another type of nonconsuming scheme is explored, which is the subtraction of a substance from droplets via a DMB. This process has no analogy among macroscopic chemical operations. Both addition and subtraction occur according to an exponential asymptotic process when diffusion is at quasisteady state inside the DMB tip. These nonconsuming operations were characterized using the transport of microscopic quantities of Lucifer Yellow CH, a fluorescent dye, under a fluorescent microscope. The third basic type of chemical manipulation is when the substance delivered by a DMB is consumed in the target droplet instantaneously by a fast chemical reaction. This consuming scheme was studied by delivering EDTA into droplets containing Pb2+ ions and a color indicator. These microscopic titrations were monitored using gray scale transmittance images of the droplets as recorded versus time. A unified theory of the three basic DMB operations is also presented. PMID:10565280
Minimization of total overlay errors on product wafers using an advanced optimization scheme
NASA Astrophysics Data System (ADS)
Levinson, Harry J.; Preil, Moshe E.; Lord, Patrick J.
1997-07-01
The matching of wafer steppers is accomplished typically by patterning two successive layers, using different steppers of interest for each layer, and measuring the overlay at many points in the exposure field. Matching is considered to be optimized when some metric, such the sum-of-squares of overlay errors, is minimized over all measured points within the field. This is to be contrasted to the situation which arises during the in-line measurement of overlay errors in production, where a far more limited sampling of points is involved. There are several consequences to limited sampling. Adjustable intrafield overlay components, such as magnification, may appear to vary up to several parts-per- million as a consequence of varying chip size. These variations are substantially larger than the normal variations of these components for fixed field sizes, and so have significant consequences for the application of statistical methodologies to the control of overlay components. The width of the distribution of overlay errors across the field may typically increase between 10 to 20 nm (3(sigma) ), with even larger increases in mean shifts, all varying with field size. Reticles may also introduce similar variations, both random and systematic. Reticle beam-writer errors lead to systematic intrafield errors, particularly asymmetric field magnification and field skew. Steppers may compensate for these systematic reticle errors, and step- and-scan systems are more effective at this compensation than step-and-repeat machines. For steppers which have process dependent alignment, this compensation must be determined on products, which leads back to the problems associated with limited sampling. Correction for the overlay errors induced by limited sampling may be accomplished by look-up tables incorporated into the overlay analysis software. For each pair of steppers and each sampling plan, corrections can be applied at each measurement point in order to bring the full field and
NASA Astrophysics Data System (ADS)
Jin, Zhao; Ji, Yan-Qiang; Zhu, Ai-Dong; Wang, Hong-Fu; Zhang, Shou
2014-03-01
We present a scheme to implement an optimal symmetric 1→2 economical phase-covariant quantum cloning machine (EPCCM) with quantum dot (QD) spins in optical microcavities by using a photon as a data bus. The EPCCM copies deterministically the quantum states on southern or northern Bloch hemisphere from one QD spin to two with an optimal fidelity. By analyzing the fidelity of quantum cloning we confirm that it is robust against the dissipation caused by cavity decay, side leakage and dipole decay. For a strong coupling regime, the cloning fidelity approaches a stable optimal bound. Even in a weak coupling regime, it can also achieve a satisfactory high value close to the optimal bound.
Li, Hui-zhen; Tao, Dong-liang; Qi, Jian; Wu, Jin-guang; Xu, Yi-zhuang; Noda, Isao
2014-04-24
Two-dimensional (2D) synchronous spectroscopy together with a new approach called "Orthogonal Sample Design Scheme" was used to study the dipole-dipole interactions in two representative ternary chemical systems (N,N-dimethyllformamide (DMF)/CH3COOC2H5/CCl4 and C60/CH3COOC2H5/CCl4). For the first system, dipole-dipole interactions among carbonyl groups from DMF and CH3COOC2H5 are characterized by using the cross peak in 2D Fourier Transform Infrared Radiation (FT-IR) spectroscopy. For the second system, intermolecular interaction among π-π transition from C60 and vibration transition from the carbonyl band of ethyl acetate is probed by using 2D spectra. The experimental results demonstrate that "Orthogonal Sample Design Scheme" can effectively remove interfering part that is not relevant to intermolecular interaction. Additional procedures are carried out to preclude the possibilities of producing interfering cross peaks by other reasons, such as experimental errors. Dipole-dipole interactions that manifest in the form of deviation from the Beer-Lambert law generate distinct cross peaks visualized in the resultant 2D synchronous spectra of the two chemical systems. This work demonstrates that 2D synchronous spectra coupled with orthogonal sample design scheme provide us an applicable experimental approach to probing and characterizing dipole-dipole interactions in complex molecular systems. PMID:24582337
Molak, Martyna; Lorenzen, Eline D; Shapiro, Beth; Ho, Simon Y W
2013-02-01
In recent years, ancient DNA has increasingly been used for estimating molecular timescales, particularly in studies of substitution rates and demographic histories. Molecular clocks can be calibrated using temporal information from ancient DNA sequences. This information comes from the ages of the ancient samples, which can be estimated by radiocarbon dating the source material or by dating the layers in which the material was deposited. Both methods involve sources of uncertainty. The performance of bayesian phylogenetic inference depends on the information content of the data set, which includes variation in the DNA sequences and the structure of the sample ages. Various sources of estimation error can reduce our ability to estimate rates and timescales accurately and precisely. We investigated the impact of sample-dating uncertainties on the estimation of evolutionary timescale parameters using the software BEAST. Our analyses involved 11 published data sets and focused on estimates of substitution rate and root age. We show that, provided that samples have been accurately dated and have a broad temporal span, it might be unnecessary to account for sample-dating uncertainty in Bayesian phylogenetic analyses of ancient DNA. We also investigated the sample size and temporal span of the ancient DNA sequences needed to estimate phylogenetic timescales reliably. Our results show that the range of sample ages plays a crucial role in determining the quality of the results but that accurate and precise phylogenetic estimates of timescales can be made even with only a few ancient sequences. These findings have important practical consequences for studies of molecular rates, timescales, and population dynamics.
Martian Radiative Transfer Modeling Using the Optimal Spectral Sampling Method
NASA Technical Reports Server (NTRS)
Eluszkiewicz, J.; Cady-Pereira, K.; Uymin, G.; Moncet, J.-L.
2005-01-01
The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer (TES) spectra. While the caps will provide the initial focus area for applying the new model, it is hoped that the model will be of interest to the wider Mars remote sensing community.
40 CFR 761.316 - Interpreting PCB concentration measurements resulting from this sampling scheme.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 32 2013-07-01 2013-07-01 false Interpreting PCB concentration... Â§ 761.79(b)(3) § 761.316 Interpreting PCB concentration measurements resulting from this sampling... concentration measured in that sample. If the sample surface concentration is not equal to or lower than...
40 CFR 761.316 - Interpreting PCB concentration measurements resulting from this sampling scheme.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Interpreting PCB concentration... Â§ 761.79(b)(3) § 761.316 Interpreting PCB concentration measurements resulting from this sampling... concentration measured in that sample. If the sample surface concentration is not equal to or lower than...
40 CFR 761.316 - Interpreting PCB concentration measurements resulting from this sampling scheme.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 31 2014-07-01 2014-07-01 false Interpreting PCB concentration... Â§ 761.79(b)(3) § 761.316 Interpreting PCB concentration measurements resulting from this sampling... concentration measured in that sample. If the sample surface concentration is not equal to or lower than...
40 CFR 761.316 - Interpreting PCB concentration measurements resulting from this sampling scheme.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 31 2011-07-01 2011-07-01 false Interpreting PCB concentration... Â§ 761.79(b)(3) § 761.316 Interpreting PCB concentration measurements resulting from this sampling... concentration measured in that sample. If the sample surface concentration is not equal to or lower than...
40 CFR 761.316 - Interpreting PCB concentration measurements resulting from this sampling scheme.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 32 2012-07-01 2012-07-01 false Interpreting PCB concentration... Â§ 761.79(b)(3) § 761.316 Interpreting PCB concentration measurements resulting from this sampling... concentration measured in that sample. If the sample surface concentration is not equal to or lower than...
Zhang, Zhen; Zhang, Qianwu; Chen, Jian; Li, Yingchun; Song, Yingxiong
2016-06-13
A low-complexity joint symbol synchronization and SFO estimation scheme for asynchronous optical IMDD OFDM systems based on only one training symbol is proposed. Numerical simulations and experimental demonstrations are also under taken to evaluate the performance of the mentioned scheme. The experimental results show that robust and precise symbol synchronization and the SFO estimation can be achieved simultaneously at received optical power as low as -20dBm in asynchronous OOFDM systems. SFO estimation accuracy in MSE can be lower than 1 × 10^{-11} under SFO range from -60ppm to 60ppm after 25km SSMF transmission. Optimal System performance can be maintained until cumulate number of employed frames for calculation is less than 50 under above-mentioned conditions. Meanwhile, the proposed joint scheme has a low level of operation complexity comparing with existing methods, when the symbol synchronization and SFO estimation are considered together. Above-mentioned results can give an important reference in practical system designs. PMID:27410279
Ward, Michael B; Reuter, Stephanie E; Martin, Jennifer H
2016-10-01
Tyrosine kinase inhibitors have been marketed as a fixed dose, 'one size fits all' treatment strategy. Physicians have also been interested in this method of dosing, knowing the complex planning of other current cancer therapies administered on a mg/m(2) or mg/kg basis and subsequent occurrence of dosing error or concern for underdosing. The 'simple and safe' strategy of a single dose of tyrosine kinase inhibitor for cancer has thus been widely adopted. However, the benefits purported to exist in the clinical trials do not appear to be borne out in clinical practice, particularly in solid tumours. In order to investigate whether pharmacokinetic variability is a contributor to the variable outcomes, pharmacokinetic targets to enable individualisation of tyrosine kinase inhibitor administration are now emerging. Evidence suggests there is not a clear relationship of a single dose to maximum plasma concentration (C max), steady-state trough concentration (C trough) or area under the curve (AUC). Furthermore, a significant number of questions remain related to the specific timing and frequency of sample collection required to achieve optimal outcomes. This article reviews the wide variability in the literature on this topic, specifically the different pharmacokinetic targets of the same drug for different cancers, for different states of cancer, and changing pharmacokinetic parameters over a treatment interval in cancer. It appears the optimal sampling times to enable appropriate dose recommendations across patients and diseases may vary, and are not always trough concentrations at steady state. Importantly, the need to be pragmatic in a clinical setting is paramount. Lastly, international collaborations to increase sample size are highly recommended to ensure enough patients are sampled to be sure of a clinical benefit from this concentration-directed methodology.
Ward, Michael B; Reuter, Stephanie E; Martin, Jennifer H
2016-10-01
Tyrosine kinase inhibitors have been marketed as a fixed dose, 'one size fits all' treatment strategy. Physicians have also been interested in this method of dosing, knowing the complex planning of other current cancer therapies administered on a mg/m(2) or mg/kg basis and subsequent occurrence of dosing error or concern for underdosing. The 'simple and safe' strategy of a single dose of tyrosine kinase inhibitor for cancer has thus been widely adopted. However, the benefits purported to exist in the clinical trials do not appear to be borne out in clinical practice, particularly in solid tumours. In order to investigate whether pharmacokinetic variability is a contributor to the variable outcomes, pharmacokinetic targets to enable individualisation of tyrosine kinase inhibitor administration are now emerging. Evidence suggests there is not a clear relationship of a single dose to maximum plasma concentration (C max), steady-state trough concentration (C trough) or area under the curve (AUC). Furthermore, a significant number of questions remain related to the specific timing and frequency of sample collection required to achieve optimal outcomes. This article reviews the wide variability in the literature on this topic, specifically the different pharmacokinetic targets of the same drug for different cancers, for different states of cancer, and changing pharmacokinetic parameters over a treatment interval in cancer. It appears the optimal sampling times to enable appropriate dose recommendations across patients and diseases may vary, and are not always trough concentrations at steady state. Importantly, the need to be pragmatic in a clinical setting is paramount. Lastly, international collaborations to increase sample size are highly recommended to ensure enough patients are sampled to be sure of a clinical benefit from this concentration-directed methodology. PMID:27085335
Bayesian assessment of the expected data impact on prediction confidence in optimal sampling design
NASA Astrophysics Data System (ADS)
Leube, P. C.; Geiges, A.; Nowak, W.
2012-02-01
Incorporating hydro(geo)logical data, such as head and tracer data, into stochastic models of (subsurface) flow and transport helps to reduce prediction uncertainty. Because of financial limitations for investigation campaigns, information needs toward modeling or prediction goals should be satisfied efficiently and rationally. Optimal design techniques find the best one among a set of investigation strategies. They optimize the expected impact of data on prediction confidence or related objectives prior to data collection. We introduce a new optimal design method, called PreDIA(gnosis) (Preposterior Data Impact Assessor). PreDIA derives the relevant probability distributions and measures of data utility within a fully Bayesian, generalized, flexible, and accurate framework. It extends the bootstrap filter (BF) and related frameworks to optimal design by marginalizing utility measures over the yet unknown data values. PreDIA is a strictly formal information-processing scheme free of linearizations. It works with arbitrary simulation tools, provides full flexibility concerning measurement types (linear, nonlinear, direct, indirect), allows for any desired task-driven formulations, and can account for various sources of uncertainty (e.g., heterogeneity, geostatistical assumptions, boundary conditions, measurement values, model structure uncertainty, a large class of model errors) via Bayesian geostatistics and model averaging. Existing methods fail to simultaneously provide these crucial advantages, which our method buys at relatively higher-computational costs. We demonstrate the applicability and advantages of PreDIA over conventional linearized methods in a synthetic example of subsurface transport. In the example, we show that informative data is often invisible for linearized methods that confuse zero correlation with statistical independence. Hence, PreDIA will often lead to substantially better sampling designs. Finally, we extend our example to specifically
NASA Astrophysics Data System (ADS)
Rasmussen, Troels Hels; Wang, Yang Min; Kjærgaard, Thomas; Kristensen, Kasper
2016-05-01
We augment the recently introduced same number of optimized parameters (SNOOP) scheme [K. Kristensen et al., J. Chem. Phys. 142, 114116 (2015)] for calculating interaction energies of molecular dimers with an F12 correction and generalize the method to enable the determination of interaction energies of general molecular clusters. The SNOOP, uncorrected (UC), and counterpoise (CP) schemes with/without an F12 correction are compared for the S22 test set of Jurečka et al. [Phys. Chem. Chem. Phys. 8, 1985 (2006)]—which consists of 22 molecular dimers of biological importance—and for water and methane molecular clusters. The calculations have been performed using the Resolution of the Identity second-order Møller-Plesset perturbation theory method. We conclude from the results that the SNOOP scheme generally yields interaction energies closer to the complete basis set limit value than the UC and CP approaches, regardless of whether the F12 correction is applied or not. Specifically, using the SNOOP scheme with an F12 correction yields the computationally most efficient way of achieving accurate results at low basis set levels. These conclusions hold both for molecular dimers and more general molecular clusters.
A New Robust Bandpass Sampling Scheme for Multiple RF Signals in SDR System
NASA Astrophysics Data System (ADS)
Chi, Chen; Zhang, Yu; Yang, Zhixing
Software defined radio (SDR) technology has been widely applied for its powerful universality and flexibility in the past decade. To address the issue of bandpass sampling of multiband signals, a novel and efficient method of finding the minimum valid sampling frequency is proposed. Since there are frequency deviations due to the channel effect and hardware instability in actual systems, we also consider the guard-bands between downconverted signal spectra in determining the minimum sampling frequency. In addition, the case that the spectra within the sampled bandwidth are located in inverse placement can be avoided by our proposed method, which will reduce the complexity of the succeeding digital signal process significantly. Simulation results illustrate that the proper minimum sampling frequency can be determined rapidly and accurately.
NASA Astrophysics Data System (ADS)
O'Connor, Sean M.; Lynch, Jerome P.; Gilbert, Anna C.
2013-04-01
Wireless sensors have emerged to offer low-cost sensors with impressive functionality (e.g., data acquisition, computing, and communication) and modular installations. Such advantages enable higher nodal densities than tethered systems resulting in increased spatial resolution of the monitoring system. However, high nodal density comes at a cost as huge amounts of data are generated, weighing heavy on power sources, transmission bandwidth, and data management requirements, often making data compression necessary. The traditional compression paradigm consists of high rate (>Nyquist) uniform sampling and storage of the entire target signal followed by some desired compression scheme prior to transmission. The recently proposed compressed sensing (CS) framework combines the acquisition and compression stage together, thus removing the need for storage and operation of the full target signal prior to transmission. The effectiveness of the CS approach hinges on the presence of a sparse representation of the target signal in a known basis, similarly exploited by several traditional compressive sensing applications today (e.g., imaging, MRI). Field implementations of CS schemes in wireless SHM systems have been challenging due to the lack of commercially available sensing units capable of sampling methods (e.g., random) consistent with the compressed sensing framework, often moving evaluation of CS techniques to simulation and post-processing. The research presented here describes implementation of a CS sampling scheme to the Narada wireless sensing node and the energy efficiencies observed in the deployed sensors. Of interest in this study is the compressibility of acceleration response signals collected from a multi-girder steel-concrete composite bridge. The study shows the benefit of CS in reducing data requirements while ensuring data analysis on compressed data remain accurate.
NASA Astrophysics Data System (ADS)
Felten, Frederic; Lund, Thomas
2001-11-01
The incompressible collocated mesh is often preferred over the staggered mesh scheme for turbulence simulation due to its slightly simpler form in curvilinear coordinates. Many researchers have used an upwind interpolation for the momentum, citing problems with numerical oscillations if centered interpolations are used. Analysis reveals that second order centered interpolations result in a kinetic energy conservation error, which can act as a source for numerical oscillations. Analysis also shows that a simple first order centered interpolation does not produce a kinetic energy conservation error. Various momentum interpolation operators are used in an inviscid simulation of the flow over an airfoil, as well as for simulations of turbulent channel flow. In the case of the airfoil, oscillations are present with the second order centered interpolation, but are absent for both the first order centered and the second order upwind schemes. The dissipative effects of the upwind interpolations degrade the results of the channel flow simulations, while both the first and second order centered interpolations yield good results. This work suggests that numerical oscillations can be controlled with a non-dissipative algorithm through the proper choice of the interpolation scheme.
Ricci, M; Sciarrino, F; Sias, C; De Martini, F
2004-01-30
By a significant modification of the standard protocol of quantum state teleportation, two processes "forbidden" by quantum mechanics in their exact form, the universal NOT gate and the universal optimal quantum cloning machine, have been implemented contextually and optimally by a fully linear method. In particular, the first experimental demonstration of the tele-UNOT gate, a novel quantum information protocol, has been reported. The experimental results are found in full agreement with theory.
Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A
2009-02-26
The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.
Optimized Linear Prediction for Radial Sampled Multidimensional NMR Experiments
Gledhill, John M.; Kasinath, Vignesh; Wand, A. Joshua
2011-01-01
Radial sampling in multidimensional NMR experiments offers greatly decreased acquisition times while also providing an avenue for increased sensitivity. Digital resolution remains concern and depends strongly upon the extent of sampling of individual radial angles. Truncated time domain data leads to spurious peaks (artifacts) upon FT and 2D FT. Linear prediction is commonly employed to improve resolution in Cartesian sampled NMR experiments. Here, we adapt the linear prediction method to radial sampling. Significantly more accurate estimates of linear prediction coefficients are obtained by combining quadrature frequency components from the multiple angle spectra. This approach results in significant improvement in both resolution and removal of spurious peaks as compared to traditional linear prediction methods applied to radial sampled data. The ‘averaging linear prediction’ (ALP) method is demonstrated as a general tool for resolution improvement in multidimensional radial sampled experiments. PMID:21767968
Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr.; Giunta, Anthony Andrew
2006-01-01
Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and
NASA Astrophysics Data System (ADS)
Kala, J.; De Kauwe, M. G.; Pitman, A. J.; Lorenz, R.; Medlyn, B. E.; Wang, Y.-P.; Lin, Y.-S.; Abramowitz, G.
2015-12-01
We implement a new stomatal conductance scheme, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLEv2.0.1) land surface model. Coupled land-atmosphere simulations are then performed using CABLEv2.0.1 within the Australian Community Climate and Earth Systems Simulator (ACCESSv1.3b) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5-1.0 mm day-1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology of warm extremes and improve existing biases by 10-20 %. The bias in minimum temperatures is however degraded but, overall, this is outweighed by the improvement in maximum temperatures as there is a net improvement in the diurnal temperature range in this region. In other regions such as parts of South and North America where ACCESSv1.3b has known large positive biases in both maximum and minimum temperatures (~ 5 to 10 °C), the new scheme degrades this bias by up to 1 °C. We conclude that, although several large biases remain in ACCESSv1.3b for temperature extremes, the improvements in the global climate model over large parts of the boreal forests during the Northern Hemisphere summer which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development
David, Sophia; Mentasti, Massimo; Tewolde, Rediat; Aslett, Martin; Harris, Simon R; Afshar, Baharak; Underwood, Anthony; Fry, Norman K; Parkhill, Julian; Harrison, Timothy G
2016-08-01
Sequence-based typing (SBT), analogous to multilocus sequence typing (MLST), is the current "gold standard" typing method for investigation of legionellosis outbreaks caused by Legionella pneumophila However, as common sequence types (STs) cause many infections, some investigations remain unresolved. In this study, various whole-genome sequencing (WGS)-based methods were evaluated according to published guidelines, including (i) a single nucleotide polymorphism (SNP)-based method, (ii) extended MLST using different numbers of genes, (iii) determination of gene presence or absence, and (iv) a kmer-based method. L. pneumophila serogroup 1 isolates (n = 106) from the standard "typing panel," previously used by the European Society for Clinical Microbiology Study Group on Legionella Infections (ESGLI), were tested together with another 229 isolates. Over 98% of isolates were considered typeable using the SNP- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50 genes) to 86.8% (1,455 genes), while only 41.5% produced a full profile with the gene presence/absence scheme. Replicates demonstrated that all methods offer 100% reproducibility. Indices of discrimination range from 0.972 (ribosomal MLST) to 0.999 (SNP based), and all values were higher than that achieved with SBT (0.940). Epidemiological concordance is generally inversely related to discriminatory power. We propose that an extended MLST scheme with ∼50 genes provides optimal epidemiological concordance while substantially improving the discrimination offered by SBT and can be used as part of a hierarchical typing scheme that should maintain backwards compatibility and increase discrimination where necessary. This analysis will be useful for the ESGLI to design a scheme that has the potential to become the new gold standard typing method for L. pneumophila. PMID:27280420
Mentasti, Massimo; Tewolde, Rediat; Aslett, Martin; Harris, Simon R.; Afshar, Baharak; Underwood, Anthony; Harrison, Timothy G.
2016-01-01
Sequence-based typing (SBT), analogous to multilocus sequence typing (MLST), is the current “gold standard” typing method for investigation of legionellosis outbreaks caused by Legionella pneumophila. However, as common sequence types (STs) cause many infections, some investigations remain unresolved. In this study, various whole-genome sequencing (WGS)-based methods were evaluated according to published guidelines, including (i) a single nucleotide polymorphism (SNP)-based method, (ii) extended MLST using different numbers of genes, (iii) determination of gene presence or absence, and (iv) a kmer-based method. L. pneumophila serogroup 1 isolates (n = 106) from the standard “typing panel,” previously used by the European Society for Clinical Microbiology Study Group on Legionella Infections (ESGLI), were tested together with another 229 isolates. Over 98% of isolates were considered typeable using the SNP- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50 genes) to 86.8% (1,455 genes), while only 41.5% produced a full profile with the gene presence/absence scheme. Replicates demonstrated that all methods offer 100% reproducibility. Indices of discrimination range from 0.972 (ribosomal MLST) to 0.999 (SNP based), and all values were higher than that achieved with SBT (0.940). Epidemiological concordance is generally inversely related to discriminatory power. We propose that an extended MLST scheme with ∼50 genes provides optimal epidemiological concordance while substantially improving the discrimination offered by SBT and can be used as part of a hierarchical typing scheme that should maintain backwards compatibility and increase discrimination where necessary. This analysis will be useful for the ESGLI to design a scheme that has the potential to become the new gold standard typing method for L. pneumophila. PMID:27280420
Density and level set-XFEM schemes for topology optimization of 3-D structures
NASA Astrophysics Data System (ADS)
Villanueva, Carlos H.; Maute, Kurt
2014-07-01
As the capabilities of additive manufacturing techniques increase, topology optimization provides a promising approach to design geometrically sophisticated structures. Traditional topology optimization methods aim at finding conceptual designs, but they often do not resolve sufficiently the geometry and the structural response such that the optimized designs can be directly used for manufacturing. To overcome these limitations, this paper studies the viability of the extended finite element method (XFEM) in combination with the level-set method (LSM) for topology optimization of three dimensional structures. The LSM describes the geometry by defining the nodal level set values via explicit functions of the optimization variables. The structural response is predicted by a generalized version of the XFEM. The LSM-XFEM approach is compared against results from a traditional Solid Isotropic Material with Penalization method for two-phase "solid-void" and "solid-solid" problems. The numerical results demonstrate that the LSM-XFEM approach describes crisply the geometry and predicts the structural response with acceptable accuracy even on coarse meshes.
A global earthquake discrimination scheme to optimize ground-motion prediction equation selection
Garcia, Daniel; Wald, David J.; Hearne, Michael
2012-01-01
We present a new automatic earthquake discrimination procedure to determine in near-real time the tectonic regime and seismotectonic domain of an earthquake, its most likely source type, and the corresponding ground-motion prediction equation (GMPE) class to be used in the U.S. Geological Survey (USGS) Global ShakeMap system. This method makes use of the Flinn–Engdahl regionalization scheme, seismotectonic information (plate boundaries, global geology, seismicity catalogs, and regional and local studies), and the source parameters available from the USGS National Earthquake Information Center in the minutes following an earthquake to give the best estimation of the setting and mechanism of the event. Depending on the tectonic setting, additional criteria based on hypocentral depth, style of faulting, and regional seismicity may be applied. For subduction zones, these criteria include the use of focal mechanism information and detailed interface models to discriminate among outer-rise, upper-plate, interface, and intraslab seismicity. The scheme is validated against a large database of recent historical earthquakes. Though developed to assess GMPE selection in Global ShakeMap operations, we anticipate a variety of uses for this strategy, from real-time processing systems to any analysis involving tectonic classification of sources from seismic catalogs.
Progress Towards Optimally Efficient Schemes for Monte Carlo Thermal Radiation Transport
Smedley-Stevenson, R P; Brooks III, E D
2007-09-26
In this summary we review the complementary research being undertaken at AWE and LLNL aimed at developing optimally efficient algorithms for Monte Carlo thermal radiation transport based on the difference formulation. We conclude by presenting preliminary results on the application of Newton-Krylov methods for solving the Symbolic Implicit Monte Carlo (SIMC) energy equation.
NASA Astrophysics Data System (ADS)
Akmaev, R. a.
1999-04-01
In Part 1 of this work ([Akmaev, 1999]), an overview of the theory of optimal interpolation (OI) ([Gandin, 1963]) and related techniques of data assimilation based on linear optimal estimation ([Liebelt, 1967]; [Catlin, 1989]; [Mendel, 1995]) is presented. The approach implies the use in data analysis of additional statistical information in the form of statistical moments, e.g., the mean and covariance (correlation). The a priori statistical characteristics, if available, make it possible to constrain expected errors and obtain optimal in some sense estimates of the true state from a set of observations in a given domain in space and/or time. The primary objective of OI is to provide estimates away from the observations, i.e., to fill in data voids in the domain under consideration. Additionally, OI performs smoothing suppressing the noise, i.e., the spectral components that are presumably not present in the true signal. Usually, the criterion of optimality is minimum variance of the expected errors and the whole approach may be considered constrained least squares or least squares with a priori information. Obviously, data assimilation techniques capable of incorporating any additional information are potentially superior to techniques that have no access to such information as, for example, the conventional least squares (e.g., [Liebelt, 1967]; [Weisberg, 1985]; [Press et al., 1992]; [Mendel, 1995]).
Optimized design and analysis of sparse-sampling FMRI experiments.
Perrachione, Tyler K; Ghosh, Satrajit S
2013-01-01
Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase
Ant colony optimization as a method for strategic genotype sampling.
Spangler, M L; Robbins, K R; Bertrand, J K; Macneil, M; Rekaya, R
2009-06-01
A simulation study was carried out to develop an alternative method of selecting animals to be genotyped. Simulated pedigrees included 5000 animals, each assigned genotypes for a bi-allelic single nucleotide polymorphism (SNP) based on assumed allelic frequencies of 0.7/0.3 and 0.5/0.5. In addition to simulated pedigrees, two beef cattle pedigrees, one from field data and the other from a research population, were used to test selected methods using simulated genotypes. The proposed method of ant colony optimization (ACO) was evaluated based on the number of alleles correctly assigned to ungenotyped animals (AK(P)), the probability of assigning true alleles (AK(G)) and the probability of correctly assigning genotypes (APTG). The proposed animal selection method of ant colony optimization was compared to selection using the diagonal elements of the inverse of the relationship matrix (A(-1)). Comparisons of these two methods showed that ACO yielded an increase in AK(P) ranging from 4.98% to 5.16% and an increase in APTG from 1.6% to 1.8% using simulated pedigrees. Gains in field data and research pedigrees were slightly lower. These results suggest that ACO can provide a better genotyping strategy, when compared to A(-1), with different pedigree sizes and structures. PMID:19220227
Time-optimal path planning in dynamic flows using level set equations: theory and schemes
NASA Astrophysics Data System (ADS)
Lolla, Tapovan; Lermusiaux, Pierre F. J.; Ueckermann, Mattheus P.; Haley, Patrick J.
2014-10-01
We develop an accurate partial differential equation-based methodology that predicts the time-optimal paths of autonomous vehicles navigating in any continuous, strong, and dynamic ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-optimal path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-optimal paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.
Time-optimal path planning in dynamic flows using level set equations: theory and schemes
NASA Astrophysics Data System (ADS)
Lolla, Tapovan; Lermusiaux, Pierre F. J.; Ueckermann, Mattheus P.; Haley, Patrick J.
2014-09-01
We develop an accurate partial differential equation-based methodology that predicts the time-optimal paths of autonomous vehicles navigating in any continuous, strong, and dynamic ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-optimal path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-optimal paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.
Jiang, Yuyi; Shao, Zhiqing; Guo, Yi
2014-01-01
A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems. PMID:25143977
Jiang, Yuyi; Shao, Zhiqing; Guo, Yi
2014-01-01
A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems.
Sample of CFD optimization of a centrifugal compressor stage
NASA Astrophysics Data System (ADS)
Galerkin, Y.; Drozdov, A.
2015-08-01
Industrial centrifugal compressor stage is a complicated object for gas dynamic design when the goal is to achieve maximum efficiency. The Authors analyzed results of CFD performance modeling (NUMECA Fine Turbo calculations). Performance prediction in a whole was modest or poor in all known cases. Maximum efficiency prediction was quite satisfactory to the contrary. Flow structure in stator elements was in a good agreement with known data. The intermediate type stage “3D impeller + vaneless diffuser+ return channel” was designed with principles well proven for stages with 2D impellers. CFD calculations of vaneless diffuser candidates demonstrated flow separation in VLD with constant width. The candidate with symmetrically tampered inlet part b3 / b2 = 0,73 appeared to be the best. Flow separation takes place in the crossover with standard configuration. The alternative variant was developed and numerically tested. The obtained experience was formulated as corrected design recommendations. Several candidates of the impeller were compared by maximum efficiency of the stage. The variant with gas dynamic standard principles of blade cascade design appeared to be the best. Quasi - 3D non-viscid calculations were applied to optimize blade velocity diagrams - non-incidence inlet, control of the diffusion factor and of average blade load. “Geometric” principle of blade formation with linear change of blade angles along its length appeared to be less effective. Candidates’ with different geometry parameters were designed by 6th math model version and compared. The candidate with optimal parameters - number of blades, inlet diameter and leading edge meridian position - is 1% more effective than the stage of the initial design.
Optimization conditions of samples saponification for tocopherol analysis.
Souza, Aloisio Henrique Pereira; Gohara, Aline Kirie; Rodrigues, Ângela Claudia; Ströher, Gisely Luzia; Silva, Danielle Cristina; Visentainer, Jesuí Vergílio; Souza, Nilson Evelázio; Matsushita, Makoto
2014-09-01
A full factorial design 2(2) (two factors at two levels) with duplicates was performed to investigate the influence of the factors agitation time (2 and 4 h) and the percentage of KOH (60% and 80% w/v) in the saponification of samples for the determination of α, β and γ+δ-tocopherols. The study used samples of peanuts (cultivar armadillo), produced and marketed in Maringá, PR. The factors % KOH and agitation time were significant, and an increase in their values contributed negatively to the responses. The interaction effect was not significant for the response δ-tocopherol, and the contribution of this effect to the other responses was positive, but less than 10%. The ANOVA and response surfaces analysis showed that the most efficient saponification procedure was obtained using a 60% (w/v) solution of KOH and with an agitation time of 2 h.
Determination and optimization of spatial samples for distributed measurements.
Huo, Xiaoming; Tran, Hy D.; Shilling, Katherine Meghan; Kim, Heeyong
2010-10-01
There are no accepted standards for determining how many measurements to take during part inspection or where to take them, or for assessing confidence in the evaluation of acceptance based on these measurements. The goal of this work was to develop a standard method for determining the number of measurements, together with the spatial distribution of measurements and the associated risks for false acceptance and false rejection. Two paths have been taken to create a standard method for selecting sampling points. A wavelet-based model has been developed to select measurement points and to determine confidence in the measurement after the points are taken. An adaptive sampling strategy has been studied to determine implementation feasibility on commercial measurement equipment. Results using both real and simulated data are presented for each of the paths.
Inference for optimal dynamic treatment regimes using an adaptive m-out-of-n bootstrap scheme.
Chakraborty, Bibhas; Laber, Eric B; Zhao, Yingqi
2013-09-01
A dynamic treatment regime consists of a set of decision rules that dictate how to individualize treatment to patients based on available treatment and covariate history. A common method for estimating an optimal dynamic treatment regime from data is Q-learning which involves nonsmooth operations of the data. This nonsmoothness causes standard asymptotic approaches for inference like the bootstrap or Taylor series arguments to breakdown if applied without correction. Here, we consider the m-out-of-n bootstrap for constructing confidence intervals for the parameters indexing the optimal dynamic regime. We propose an adaptive choice of m and show that it produces asymptotically correct confidence sets under fixed alternatives. Furthermore, the proposed method has the advantage of being conceptually and computationally much simple than competing methods possessing this same theoretical property. We provide an extensive simulation study to compare the proposed method with currently available inference procedures. The results suggest that the proposed method delivers nominal coverage while being less conservative than alternatives. The proposed methods are implemented in the qLearn R-package and have been made available on the Comprehensive R-Archive Network (http://cran.r-project.org/). Analysis of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study is used as an illustrative example.
Optimized Sampling Strategies For Non-Proliferation Monitoring: Report
Kurzeja, R.; Buckley, R.; Werth, D.; Chiswell, S.
2015-10-20
Concentration data collected from the 2013 H-Canyon effluent reprocessing experiment were reanalyzed to improve the source term estimate. When errors in the model-predicted wind speed and direction were removed, the source term uncertainty was reduced to 30% of the mean. This explained the factor of 30 difference between the source term size derived from data at 5 km and 10 km downwind in terms of the time history of dissolution. The results show a path forward to develop a sampling strategy for quantitative source term calculation.
Optimal sampling of visual information for lightness judgments
Toscani, Matteo; Valsecchi, Matteo; Gegenfurtner, Karl R.
2013-01-01
The variable resolution and limited processing capacity of the human visual system requires us to sample the world with eye movements and attentive processes. Here we show that where observers look can strongly modulate their reports of simple surface attributes, such as lightness. When observers matched the color of natural objects they based their judgments on the brightest parts of the objects; at the same time, they tended to fixate points with above-average luminance. When we forced participants to fixate a specific point on the object using a gaze-contingent display setup, the matched lightness was higher when observers fixated bright regions. This finding indicates a causal link between the luminance of the fixated region and the lightness match for the whole object. Simulations with rendered physical lighting show that higher values in an object’s luminance distribution are particularly informative about reflectance. This sampling strategy is an efficient and simple heuristic for the visual system to achieve accurate and invariant judgments of lightness. PMID:23776251
Optimizing fish sampling for fish - mercury bioaccumulation factors
Scudder Eikenberry, Barbara C.; Riva-Murray, Karen; Knightes, Christopher D.; Journey, Celeste A.; Chasar, Lia C.; Brigham, Mark E.; Bradley, Paul M.
2015-01-01
Fish Bioaccumulation Factors (BAFs; ratios of mercury (Hg) in fish (Hgfish) and water (Hgwater)) are used to develop Total Maximum Daily Load and water quality criteria for Hg-impaired waters. Both applications require representative Hgfish estimates and, thus, are sensitive to sampling and data-treatment methods. Data collected by fixed protocol from 11 streams in 5 states distributed across the US were used to assess the effects of Hgfish normalization/standardization methods and fish sample numbers on BAF estimates. Fish length, followed by weight, was most correlated to adult top-predator Hgfish. Site-specific BAFs based on length-normalized and standardized Hgfish estimates demonstrated up to 50% less variability than those based on non-normalized Hgfish. Permutation analysis indicated that length-normalized and standardized Hgfish estimates based on at least 8 trout or 5 bass resulted in mean Hgfish coefficients of variation less than 20%. These results are intended to support regulatory mercury monitoring and load-reduction program improvements.
Pareto-optimal clustering scheme using data aggregation for wireless sensor networks
NASA Astrophysics Data System (ADS)
Azad, Puneet; Sharma, Vidushi
2015-07-01
The presence of cluster heads (CHs) in a clustered wireless sensor network (WSN) leads to improved data aggregation and enhanced network lifetime. Thus, the selection of appropriate CHs in WSNs is a challenging task, which needs to be addressed. A multicriterion decision-making approach for the selection of CHs is presented using Pareto-optimal theory and technique for order preference by similarity to ideal solution (TOPSIS) methods. CHs are selected using three criteria including energy, cluster density and distance from the sink. The overall network lifetime in this method with 50% data aggregation after simulations is 81% higher than that of distributed hierarchical agglomerative clustering in similar environment and with same set of parameters. Optimum number of clusters is estimated using TOPSIS technique and found to be 9-11 for effective energy usage in WSNs.
A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions
Pan, Guang; Ye, Pengcheng; Yang, Zhidong
2014-01-01
Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is strongly affected by the sampling methods. In this paper, a new sequential optimization sampling method is proposed. Based on the new sampling method, metamodels can be constructed repeatedly through the addition of sampling points, namely, extrema points of metamodels and minimum points of density function. Afterwards, the more accurate metamodels would be constructed by the procedure above. The validity and effectiveness of proposed sampling method are examined by studying typical numerical examples. PMID:25133206
Optimal Sampling of a Reaction Coordinate in Molecular Dynamics
NASA Technical Reports Server (NTRS)
Pohorille, Andrew
2005-01-01
Estimating how free energy changes with the state of a system is a central goal in applications of statistical mechanics to problems of chemical or biological interest. From these free energy changes it is possible, for example, to establish which states of the system are stable, what are their probabilities and how the equilibria between these states are influenced by external conditions. Free energies are also of great utility in determining kinetics of transitions between different states. A variety of methods have been developed to compute free energies of condensed phase systems. Here, I will focus on one class of methods - those that allow for calculating free energy changes along one or several generalized coordinates in the system, often called reaction coordinates or order parameters . Considering that in almost all cases of practical interest a significant computational effort is required to determine free energy changes along such coordinates it is hardly surprising that efficiencies of different methods are of great concern. In most cases, the main difficulty is associated with its shape along the reaction coordinate. If the free energy changes markedly along this coordinate Boltzmann sampling of its different values becomes highly non-uniform. This, in turn, may have considerable, detrimental effect on the performance of many methods for calculating free energies.
A test of an optimal stomatal conductance scheme within the CABLE land surface model
NASA Astrophysics Data System (ADS)
De Kauwe, M. G.; Kala, J.; Lin, Y.-S.; Pitman, A. J.; Medlyn, B. E.; Duursma, R. A.; Abramowitz, G.; Wang, Y.-P.; Miralles, D. G.
2015-02-01
Stomatal conductance (gs) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We constrained the key model parameter "g1", which represents plant water use strategy, by PFT, based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960-1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal model, in conjunction with PFT parameterisations, resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance against upscaled data products was not degraded, but did not noticeably reduce existing model-data biases. We identified assumptions relating to the coupling of the vegetation to the atmosphere and the parameterisation of the minimum stomatal conductance as areas requiring further investigation in both CABLE and potentially other LSMs. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.
NASA Astrophysics Data System (ADS)
Maity, Arnab; Padhi, Radhakant; Mallaram, Sanjeev; Mallikarjuna Rao, G.; Manickavasagam, M.
2016-10-01
A new nonlinear optimal and explicit guidance law is presented in this paper for launch vehicles propelled by solid motors. It can ensure very high terminal precision despite not having the exact knowledge of the thrust-time curve apriori. This was motivated from using it for a carrier launch vehicle in a hypersonic mission, which demands an extremely narrow terminal accuracy window for the launch vehicle for successful initiation of operation of the hypersonic vehicle. The proposed explicit guidance scheme, which computes the optimal guidance command online, ensures the required stringent final conditions with high precision at the injection point. A key feature of the proposed guidance law is an innovative extension of the recently developed model predictive static programming guidance with flexible final time. A penalty function approach is also followed to meet the input and output inequality constraints throughout the vehicle trajectory. In this paper, the guidance law has been successfully validated from nonlinear six degree-of-freedom simulation studies by designing an inner-loop autopilot as well, which enhances confidence of its usefulness significantly. In addition to excellent nominal results, the proposed guidance has been found to have good robustness for perturbed cases as well.
De la Sen, Manuel
2007-01-01
The design of fractional order-holds (FROH) of correcting gains β ∈[−1,1] (potentially and possibly including zero-order-holds, ZOH with β=0, and first-order-holds, FROH with β=1) is discussed related to achieving output deviations being close with respect to its sampled values. A squared error time- integral between the current output and its sampled values is minimized to yield the appropriate correcting gain of the FROH in an analytic way.
Teoh, Wei Lin; Khoo, Michael B C; Teh, Sin Yin
2013-01-01
Designs of the double sampling (DS) X chart are traditionally based on the average run length (ARL) criterion. However, the shape of the run length distribution changes with the process mean shifts, ranging from highly skewed when the process is in-control to almost symmetric when the mean shift is large. Therefore, we show that the ARL is a complicated performance measure and that the median run length (MRL) is a more meaningful measure to depend on. This is because the MRL provides an intuitive and a fair representation of the central tendency, especially for the rightly skewed run length distribution. Since the DS X chart can effectively reduce the sample size without reducing the statistical efficiency, this paper proposes two optimal designs of the MRL-based DS X chart, for minimizing (i) the in-control average sample size (ASS) and (ii) both the in-control and out-of-control ASSs. Comparisons with the optimal MRL-based EWMA X and Shewhart X charts demonstrate the superiority of the proposed optimal MRL-based DS X chart, as the latter requires a smaller sample size on the average while maintaining the same detection speed as the two former charts. An example involving the added potassium sorbate in a yoghurt manufacturing process is used to illustrate the effectiveness of the proposed MRL-based DS X chart in reducing the sample size needed. PMID:23935873
Teoh, Wei Lin; Khoo, Michael B. C.; Teh, Sin Yin
2013-01-01
Designs of the double sampling (DS) chart are traditionally based on the average run length (ARL) criterion. However, the shape of the run length distribution changes with the process mean shifts, ranging from highly skewed when the process is in-control to almost symmetric when the mean shift is large. Therefore, we show that the ARL is a complicated performance measure and that the median run length (MRL) is a more meaningful measure to depend on. This is because the MRL provides an intuitive and a fair representation of the central tendency, especially for the rightly skewed run length distribution. Since the DS chart can effectively reduce the sample size without reducing the statistical efficiency, this paper proposes two optimal designs of the MRL-based DS chart, for minimizing (i) the in-control average sample size (ASS) and (ii) both the in-control and out-of-control ASSs. Comparisons with the optimal MRL-based EWMA and Shewhart charts demonstrate the superiority of the proposed optimal MRL-based DS chart, as the latter requires a smaller sample size on the average while maintaining the same detection speed as the two former charts. An example involving the added potassium sorbate in a yoghurt manufacturing process is used to illustrate the effectiveness of the proposed MRL-based DS chart in reducing the sample size needed. PMID:23935873
Gutiérrez-Cacciabue, Dolores; Teich, Ingrid; Poma, Hugo Ramiro; Cruz, Mercedes Cecilia; Balzarini, Mónica; Rajal, Verónica Beatriz
2014-01-01
Several recreational surface waters in Salta, Argentina, were selected to assess their quality. Seventy percent of the measurements exceeded at least one of the limits established by international legislation becoming unsuitable for their use. To interpret results of complex data, multivariate techniques were applied. Arenales River, due to the variability observed in the data, was divided in two: upstream and downstream representing low and high pollution sites, respectively; and Cluster Analysis supported that differentiation. Arenales River downstream and Campo Alegre Reservoir were the most different environments and Vaqueros and La Caldera Rivers were the most similar. Canonical Correlation Analysis allowed exploration of correlations between physicochemical and microbiological variables except in both parts of Arenales River, and Principal Component Analysis allowed finding relationships among the 9 measured variables in all aquatic environments. Variable’s loadings showed that Arenales River downstream was impacted by industrial and domestic activities, Arenales River upstream was affected by agricultural activities, Campo Alegre Reservoir was disturbed by anthropogenic and ecological effects, and La Caldera and Vaqueros Rivers were influenced by recreational activities. Discriminant Analysis allowed identification of subgroup of variables responsible for seasonal and spatial variations. Enterococcus, dissolved oxygen, conductivity, E. coli, pH, and fecal coliforms are sufficient to spatially describe the quality of the aquatic environments. Regarding seasonal variations, dissolved oxygen, conductivity, fecal coliforms, and pH can be used to describe water quality during dry season, while dissolved oxygen, conductivity, total coliforms, E. coli, and Enterococcus during wet season. Thus, the use of multivariate techniques allowed optimizing monitoring tasks and minimizing costs involved. PMID:25190636
Lonsinger, Robert C; Gese, Eric M; Dempsey, Steven J; Kluever, Bryan M; Johnson, Timothy R; Waits, Lisette P
2015-07-01
Noninvasive genetic sampling, or noninvasive DNA sampling (NDS), can be an effective monitoring approach for elusive, wide-ranging species at low densities. However, few studies have attempted to maximize sampling efficiency. We present a model for combining sample accumulation and DNA degradation to identify the most efficient (i.e. minimal cost per successful sample) NDS temporal design for capture-recapture analyses. We use scat accumulation and faecal DNA degradation rates for two sympatric carnivores, kit fox (Vulpes macrotis) and coyote (Canis latrans) across two seasons (summer and winter) in Utah, USA, to demonstrate implementation of this approach. We estimated scat accumulation rates by clearing and surveying transects for scats. We evaluated mitochondrial (mtDNA) and nuclear (nDNA) DNA amplification success for faecal DNA samples under natural field conditions for 20 fresh scats/species/season from <1-112 days. Mean accumulation rates were nearly three times greater for coyotes (0.076 scats/km/day) than foxes (0.029 scats/km/day) across seasons. Across species and seasons, mtDNA amplification success was ≥95% through day 21. Fox nDNA amplification success was ≥70% through day 21 across seasons. Coyote nDNA success was ≥70% through day 21 in winter, but declined to <50% by day 7 in summer. We identified a common temporal sampling frame of approximately 14 days that allowed species to be monitored simultaneously, further reducing time, survey effort and costs. Our results suggest that when conducting repeated surveys for capture-recapture analyses, overall cost-efficiency for NDS may be improved with a temporal design that balances field and laboratory costs along with deposition and degradation rates.
Lonsinger, Robert C; Gese, Eric M; Dempsey, Steven J; Kluever, Bryan M; Johnson, Timothy R; Waits, Lisette P
2015-07-01
Noninvasive genetic sampling, or noninvasive DNA sampling (NDS), can be an effective monitoring approach for elusive, wide-ranging species at low densities. However, few studies have attempted to maximize sampling efficiency. We present a model for combining sample accumulation and DNA degradation to identify the most efficient (i.e. minimal cost per successful sample) NDS temporal design for capture-recapture analyses. We use scat accumulation and faecal DNA degradation rates for two sympatric carnivores, kit fox (Vulpes macrotis) and coyote (Canis latrans) across two seasons (summer and winter) in Utah, USA, to demonstrate implementation of this approach. We estimated scat accumulation rates by clearing and surveying transects for scats. We evaluated mitochondrial (mtDNA) and nuclear (nDNA) DNA amplification success for faecal DNA samples under natural field conditions for 20 fresh scats/species/season from <1-112 days. Mean accumulation rates were nearly three times greater for coyotes (0.076 scats/km/day) than foxes (0.029 scats/km/day) across seasons. Across species and seasons, mtDNA amplification success was ≥95% through day 21. Fox nDNA amplification success was ≥70% through day 21 across seasons. Coyote nDNA success was ≥70% through day 21 in winter, but declined to <50% by day 7 in summer. We identified a common temporal sampling frame of approximately 14 days that allowed species to be monitored simultaneously, further reducing time, survey effort and costs. Our results suggest that when conducting repeated surveys for capture-recapture analyses, overall cost-efficiency for NDS may be improved with a temporal design that balances field and laboratory costs along with deposition and degradation rates. PMID:25454561
NASA Astrophysics Data System (ADS)
Back, Pär-Erik
2007-04-01
A model is presented for estimating the value of information of sampling programs for contaminated soil. The purpose is to calculate the optimal number of samples when the objective is to estimate the mean concentration. A Bayesian risk-cost-benefit decision analysis framework is applied and the approach is design-based. The model explicitly includes sample uncertainty at a complexity level that can be applied to practical contaminated land problems with limited amount of data. Prior information about the contamination level is modelled by probability density functions. The value of information is expressed in monetary terms. The most cost-effective sampling program is the one with the highest expected net value. The model was applied to a contaminated scrap yard in Göteborg, Sweden, contaminated by metals. The optimal number of samples was determined to be in the range of 16-18 for a remediation unit of 100 m2. Sensitivity analysis indicates that the perspective of the decision-maker is important, and that the cost of failure and the future land use are the most important factors to consider. The model can also be applied for other sampling problems, for example, sampling and testing of wastes to meet landfill waste acceptance procedures.
Piao, Xinglin; Hu, Yongli; Sun, Yanfeng; Yin, Baocai; Gao, Junbin
2014-01-01
The emerging low rank matrix approximation (LRMA) method provides an energy efficient scheme for data collection in wireless sensor networks (WSNs) by randomly sampling a subset of sensor nodes for data sensing. However, the existing LRMA based methods generally underutilize the spatial or temporal correlation of the sensing data, resulting in uneven energy consumption and thus shortening the network lifetime. In this paper, we propose a correlated spatio-temporal data collection method for WSNs based on LRMA. In the proposed method, both the temporal consistence and the spatial correlation of the sensing data are simultaneously integrated under a new LRMA model. Moreover, the network energy consumption issue is considered in the node sampling procedure. We use Gini index to measure both the spatial distribution of the selected nodes and the evenness of the network energy status, then formulate and resolve an optimization problem to achieve optimized node sampling. The proposed method is evaluated on both the simulated and real wireless networks and compared with state-of-the-art methods. The experimental results show the proposed method efficiently reduces the energy consumption of network and prolongs the network lifetime with high data recovery accuracy and good stability. PMID:25490583
Bai, Fang; Liao, Sha; Gu, Junfeng; Jiang, Hualiang; Wang, Xicheng; Li, Honglin
2015-04-27
Metalloproteins, particularly zinc metalloproteins, are promising therapeutic targets, and recent efforts have focused on the identification of potent and selective inhibitors of these proteins. However, the ability of current drug discovery and design technologies, such as molecular docking and molecular dynamics simulations, to probe metal-ligand interactions remains limited because of their complicated coordination geometries and rough treatment in current force fields. Herein we introduce a robust, multiobjective optimization algorithm-driven metalloprotein-specific docking program named MpSDock, which runs on a scheme similar to consensus scoring consisting of a force-field-based scoring function and a knowledge-based scoring function. For this purpose, in this study, an effective knowledge-based zinc metalloprotein-specific scoring function based on the inverse Boltzmann law was designed and optimized using a dynamic sampling and iteration optimization strategy. This optimization strategy can dynamically sample and regenerate decoy poses used in each iteration step of refining the scoring function, thus dramatically improving both the effectiveness of the exploration of the binding conformational space and the sensitivity of the ranking of the native binding poses. To validate the zinc metalloprotein-specific scoring function and its special built-in docking program, denoted MpSDockZn, an extensive comparison was performed against six universal, popular docking programs: Glide XP mode, Glide SP mode, Gold, AutoDock, AutoDock4Zn, and EADock DSS. The zinc metalloprotein-specific knowledge-based scoring function exhibited prominent performance in accurately describing the geometries and interactions of the coordination bonds between the zinc ions and chelating agents of the ligands. In addition, MpSDockZn had a competitive ability to sample and identify native binding poses with a higher success rate than the other six docking programs.
NASA Astrophysics Data System (ADS)
Han, Mancheon; Lee, Choong-Ki; Choi, Hyoung Joon
Hybridization-expansion continuous-time quantum Monte Carlo (CT-HYB) is a popular approach in real material researches because it allows to deal with non-density-density-type interaction. In the conventional CT-HYB, we measure Green's function and find the self energy from the Dyson equation. Because one needs to compute the inverse of the statistical data in this approach, obtained self energy is very sensitive to statistical noise. For that reason, the measurement is not reliable except for low frequencies. Such an error can be suppressed by measuring a special type of higher-order correlation function and is implemented for density-density-type interaction. With the help of the recently reported worm-sampling measurement, we developed an improved self energy measurement scheme which can be applied to any type of interactions. As an illustration, we calculated the self energy for the 3-orbital Hubbard-Kanamori-type Hamiltonian with our newly developed method. This work was supported by NRF of Korea (Grant No. 2011-0018306) and KISTI supercomputing center (Project No. KSC-2015-C3-039)
NASA Astrophysics Data System (ADS)
Utschick, C.; Skoulatos, M.; Schneidewind, A.; Böni, P.
2016-11-01
The cold-neutron triple-axis spectrometer PANDA at the neutron source FRM II has been serving an international user community studying condensed matter physics problems. We report on a new setup, improving the signal-to-noise ratio for small samples and pressure cell setups. Analytical and numerical Monte Carlo methods are used for the optimization of elliptic and parabolic focusing guides. They are placed between the monochromator and sample positions, and the flux at the sample is compared to the one achieved by standard monochromator focusing techniques. A 25 times smaller spot size is achieved, associated with a factor of 2 increased intensity, within the same divergence limits, ± 2 ° . This optional neutron focusing guide shall establish a top-class spectrometer for studying novel exotic properties of matter in combination with more stringent sample environment conditions such as extreme pressures associated with small sample sizes.
Optimal sampling efficiency in Monte Carlo sampling with an approximate potential
Coe, Joshua D; Shaw, M Sam; Sewell, Thomas D
2009-01-01
Building on the work of Iftimie et al., Boltzmann sampling of an approximate potential (the 'reference' system) is used to build a Markov chain in the isothermal-isobaric ensemble. At the endpoints of the chain, the energy is evaluated at a higher level of approximation (the 'full' system) and a composite move encompassing all of the intervening steps is accepted on the basis of a modified Metropolis criterion. For reference system chains of sufficient length, consecutive full energies are statistically decorrelated and thus far fewer are required to build ensemble averages with a given variance. Without modifying the original algorithm, however, the maximum reference chain length is too short to decorrelate full configurations without dramatically lowering the acceptance probability of the composite move. This difficulty stems from the fact that the reference and full potentials sample different statistical distributions. By manipulating the thermodynamic variables characterizing the reference system (pressure and temperature, in this case), we maximize the average acceptance probability of composite moves, lengthening significantly the random walk between consecutive full energy evaluations. In this manner, the number of full energy evaluations needed to precisely characterize equilibrium properties is dramatically reduced. The method is applied to a model fluid, but implications for sampling high-dimensional systems with ab initio or density functional theory (DFT) potentials are discussed.
NASA Astrophysics Data System (ADS)
Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad; Janssen, Hans
2015-02-01
The majority of literature regarding optimized Latin hypercube sampling (OLHS) is devoted to increasing the efficiency of these sampling strategies through the development of new algorithms based on the combination of innovative space-filling criteria and specialized optimization schemes. However, little attention has been given to the impact of the initial design that is fed into the optimization algorithm, on the efficiency of OLHS strategies. Previous studies, as well as codes developed for OLHS, have relied on one of the following two approaches for the selection of the initial design in OLHS: (1) the use of random points in the hypercube intervals (random LHS), and (2) the use of midpoints in the hypercube intervals (midpoint LHS). Both approaches have been extensively used, but no attempt has been previously made to compare the efficiency and robustness of their resulting sample designs. In this study we compare the two approaches and show that the space-filling characteristics of OLHS designs are sensitive to the initial design that is fed into the optimization algorithm. It is also illustrated that the space-filling characteristics of OLHS designs based on midpoint LHS are significantly better those based on random LHS. The two approaches are compared by incorporating their resulting sample designs in Monte Carlo simulation (MCS) for uncertainty propagation analysis, and then, by employing the sample designs in the selection of the training set for constructing non-intrusive polynomial chaos expansion (NIPCE) meta-models which subsequently replace the original full model in MCSs. The analysis is based on two case studies involving numerical simulation of density dependent flow and solute transport in porous media within the context of seawater intrusion in coastal aquifers. We show that the use of midpoint LHS as the initial design increases the efficiency and robustness of the resulting MCSs and NIPCE meta-models. The study also illustrates that this
Zarepisheh, M; Li, R; Xing, L; Ye, Y; Boyd, S
2014-06-01
Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves
NASA Astrophysics Data System (ADS)
Morrison, J. F.; Tsai, H. M.; Bradshaw, P.
1988-12-01
The variable-interval time-averaging (“VITA”) algorithm has been tested in a variety of turbulent boundary layers for its ability to detect shear-stress-producing motions from hot-wire signals. A “VITA + LEVEL” scheme (which uses criteria for both short-time variance and short-time average, i.e.“level”) has been devised, and used in several different boundary layers. This scheme yields length-scale statistics that are acceptably independent of the conditioning criteria, which the VITA scheme does not.
NASA Astrophysics Data System (ADS)
Morrison, J. F.; Tsai, H. M.; Bradshaw, P.
The variable-interval time-averaging ('VITA') algorithm has been tested in a variety of turbulent boundary layers for its ability to detect shear-stress-producing motions from hot-wire signals. A 'VITA+LEVEL' scheme (which uses criteria for both short-time variance and short-time average, i.e., 'level') has been devised, and used in several different boundary layers. This scheme yields length-scale statistics that are acceptably independent of the conditioning criteria, which the VITA scheme does not.
NASA Technical Reports Server (NTRS)
Rao, R. G. S.; Ulaby, F. T.
1977-01-01
The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.
Optimal and maximin sample sizes for multicentre cost-effectiveness trials.
Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F
2015-10-01
This paper deals with the optimal sample sizes for a multicentre trial in which the cost-effectiveness of two treatments in terms of net monetary benefit is studied. A bivariate random-effects model, with the treatment-by-centre interaction effect being random and the main effect of centres fixed or random, is assumed to describe both costs and effects. The optimal sample sizes concern the number of centres and the number of individuals per centre in each of the treatment conditions. These numbers maximize the efficiency or power for given research costs or minimize the research costs at a desired level of efficiency or power. Information on model parameters and sampling costs are required to calculate these optimal sample sizes. In case of limited information on relevant model parameters, sample size formulas are derived for so-called maximin sample sizes which guarantee a power level at the lowest study costs. Four different maximin sample sizes are derived based on the signs of the lower bounds of two model parameters, with one case being worst compared to others. We numerically evaluate the efficiency of the worst case instead of using others. Finally, an expression is derived for calculating optimal and maximin sample sizes that yield sufficient power to test the cost-effectiveness of two treatments. PMID:25656551
Optimization of low-background alpha spectrometers for analysis of thick samples.
Misiaszek, M; Pelczar, K; Wójcik, M; Zuzel, G; Laubenstein, M
2013-11-01
Results of alpha spectrometric measurements performed deep underground and above ground with and without active veto show that the underground measurement of thick samples is the most sensitive method due to significant reduction of the muon-induced background. In addition, the polonium diffusion requires for some samples an appropriate selection of an energy region in the registered spectrum. On the basis of computer simulations the best counting conditions are selected for a thick lead sample in order to optimize the detection limit.
Confronting the ironies of optimal design: Nonoptimal sampling designs with desirable properties
NASA Astrophysics Data System (ADS)
Casman, Elizabeth A.; Naiman, Daniel Q.; Chamberlin, Charles E.
1988-03-01
Two sampling designs are developed for the improvement of parameter estimate precision in nonlinear regression, one for when there is uncertainty in the parameter values, and the other for when the correct model formulation is unknown. Although based on concepts of optimal design theory, the design criteria emphasize efficiency rather than optimality. The development is illustrated using a Streeter-Phelps dissolved oxygen-biochemical oxygen demand model.
Wang, Junxiao; Wang, Xiaorui; Zhou, Shenglu; Wu, Shaohua; Zhu, Yan; Lu, Chunfeng
2016-01-01
With China’s rapid economic development, the reduction in arable land has emerged as one of the most prominent problems in the nation. The long-term dynamic monitoring of arable land quality is important for protecting arable land resources. An efficient practice is to select optimal sample points while obtaining accurate predictions. To this end, the selection of effective points from a dense set of soil sample points is an urgent problem. In this study, data were collected from Donghai County, Jiangsu Province, China. The number and layout of soil sample points are optimized by considering the spatial variations in soil properties and by using an improved simulated annealing (SA) algorithm. The conclusions are as follows: (1) Optimization results in the retention of more sample points in the moderate- and high-variation partitions of the study area; (2) The number of optimal sample points obtained with the improved SA algorithm is markedly reduced, while the accuracy of the predicted soil properties is improved by approximately 5% compared with the raw data; (3) With regard to the monitoring of arable land quality, a dense distribution of sample points is needed to monitor the granularity. PMID:27706051
Protocol for Optimal Quality and Quantity Pollen DNA Isolation from Honey Samples
Lalhmangaihi, Ralte; Ghatak, Souvik; Laha, Ramachandra; Gurusubramanian, Guruswami; Kumar, Nachimuthu Senthil
2014-01-01
The present study illustrates an optimized sample preparation method for an efficient DNA isolation from low quantities of honey samples. A conventional PCR-based method was validated, which potentially enables characterization of plant species from as low as 3 ml bee-honey samples. In the present study, an anionic detergent was used to lyse the hard outer pollen shell, and DTT was used for isolation of thiolated DNA, as it might facilitate protein digestion and assists in releasing the DNA into solution, as well as reduce cross-links between DNA and other biomolecules. Optimization of both the quantity of honey sample and time duration for DNA isolation was done during development of this method. With the use of this method, chloroplast DNA was successfully PCR amplified and sequenced from honey DNA samples. PMID:25365793
Zhang, Huaguang; Wei, Qinglai; Luo, Yanhong
2008-08-01
In this paper, we aim to solve the infinite-time optimal tracking control problem for a class of discrete-time nonlinear systems using the greedy heuristic dynamic programming (HDP) iteration algorithm. A new type of performance index is defined because the existing performance indexes are very difficult in solving this kind of tracking problem, if not impossible. Via system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then, the greedy HDP iteration algorithm is introduced to deal with the regulation problem with rigorous convergence analysis. Three neural networks are used to approximate the performance index, compute the optimal control policy, and model the nonlinear system for facilitating the implementation of the greedy HDP iteration algorithm. An example is given to demonstrate the validity of the proposed optimal tracking control scheme.
Vandermeulen, Eva; De Sadeleer, Carlos; Piepsz, Amy; Ham, Hamphrey R; Dobbeleir, André A; Vermeire, Simon T; Van Hoek, Ingrid M; Daminet, Sylvie; Slegers, Guido; Peremans, Kathelijne Y
2010-08-01
Estimation of the glomerular filtration rate (GFR) is a useful tool in the evaluation of kidney function in feline medicine. GFR can be determined by measuring the rate of tracer disappearance from the blood, and although these measurements are generally performed by multi-sampling techniques, simplified methods are more convenient in clinical practice. The optimal times for a simplified sampling strategy with two blood samples (2BS) for GFR measurement in cats using plasma (51)chromium ethylene diamine tetra-acetic acid ((51)Cr-EDTA) clearance were investigated. After intravenous administration of (51)Cr-EDTA, seven blood samples were obtained in 46 cats (19 euthyroid and 27 hyperthyroid cats, none with previously diagnosed chronic kidney disease (CKD)). The plasma clearance was then calculated from the seven point blood kinetics (7BS) and used for comparison to define the optimal sampling strategy by correlating different pairs of time points to the reference method. Mean GFR estimation for the reference method was 3.7+/-2.5 ml/min/kg (mean+/-standard deviation (SD)). Several pairs of sampling times were highly correlated with this reference method (r(2) > or = 0.980), with the best results when the first sample was taken 30 min after tracer injection and the second sample between 198 and 222 min after injection; or with the first sample at 36 min and the second at 234 or 240 min (r(2) for both combinations=0.984). Because of the similarity of GFR values obtained with the 2BS method in comparison to the values obtained with the 7BS reference method, the simplified method may offer an alternative for GFR estimation. Although a wide range of GFR values was found in the included group of cats, the applicability should be confirmed in cats suspected of renal disease and with confirmed CKD. Furthermore, although no indications of age-related effect were found in this study, a possible influence of age should be included in future studies. PMID:20452793
Mottaz-Brewer, Heather M; Norbeck, Angela D; Adkins, Joshua N; Manes, Nathan P; Ansong, Charles; Shi, Liang; Rikihisa, Yasuko; Kikuchi, Takane; Wong, Scott W; Estep, Ryan D; Heffron, Fred; Pasa-Tolic, Ljiljana; Smith, Richard D
2008-12-01
Mass spectrometry-based proteomics is a powerful analytical tool for investigating pathogens and their interactions within a host. The sensitivity of such analyses provides broad proteome characterization, but the sample-handling procedures must first be optimized to ensure compatibility with the technique and to maximize the dynamic range of detection. The decision-making process for determining optimal growth conditions, preparation methods, sample analysis methods, and data analysis techniques in our laboratory is discussed herein with consideration of the balance in sensitivity, specificity, and biomass losses during analysis of host-pathogen systems.
Nakai, Yoshikatsu; Nin, Kazuko; Teramukai, Satoshi; Taniguchi, Ataru; Fukushima, Mitsuo; Wonderlich, Stephen A
2013-08-01
The purposes of this study were to compare DSM-IV diagnostic criteria and the Broad Categories for the Diagnosis of Eating Disorders (BCD-ED) scheme in terms of the number of cases of Eating Disorder Not Otherwise Specified (EDNOS) and to test which diagnostic tool better captures the variance of psychiatric symptoms in a Japanese sample. One thousand and twenty-nine women with an eating disorder (ED) participated in this study. Assessment methods included structured clinical interviews and administration of the Eating Attitudes Test and the Eating Disorder Inventory. The BCD-ED scheme dramatically decreased the proportion of DSM-IV EDNOS from 45.1% to 1.5%. However, the categorization of patients with the BCD-ED scheme was less able to capture the variance in psychopathology scales than the DSM-IV, suggesting that the BCD-ED scheme may differentiate ED groups less effectively than the DSM-IV. These results suggest that the BCD-ED scheme may have the potential to eliminate the use of DSM-IV EDNOS, but it may have problems capturing the variance of psychiatric symptoms.
XAFSmass: a program for calculating the optimal mass of XAFS samples
NASA Astrophysics Data System (ADS)
Klementiev, K.; Chernikov, R.
2016-05-01
We present a new implementation of the XAFSmass program that calculates the optimal mass of XAFS samples. It has several improvements as compared to the old Windows based program XAFSmass: 1) it is truly platform independent, as provided by Python language, 2) it has an improved parser of chemical formulas that enables parentheses and nested inclusion-to-matrix weight percentages. The program calculates the absorption edge height given the total optical thickness, operates with differently determined sample amounts (mass, pressure, density or sample area) depending on the aggregate state of the sample and solves the inverse problem of finding the elemental composition given the experimental absorption edge jump and the chemical formula.
Spatial Prediction and Optimized Sampling Design for Sodium Concentration in Groundwater
Shabbir, Javid; M. AbdEl-Salam, Nasser; Hussain, Tajammal
2016-01-01
Sodium is an integral part of water, and its excessive amount in drinking water causes high blood pressure and hypertension. In the present paper, spatial distribution of sodium concentration in drinking water is modeled and optimized sampling designs for selecting sampling locations is calculated for three divisions in Punjab, Pakistan. Universal kriging and Bayesian universal kriging are used to predict the sodium concentrations. Spatial simulated annealing is used to generate optimized sampling designs. Different estimation methods (i.e., maximum likelihood, restricted maximum likelihood, ordinary least squares, and weighted least squares) are used to estimate the parameters of the variogram model (i.e, exponential, Gaussian, spherical and cubic). It is concluded that Bayesian universal kriging fits better than universal kriging. It is also observed that the universal kriging predictor provides minimum mean universal kriging variance for both adding and deleting locations during sampling design. PMID:27683016
NASA Astrophysics Data System (ADS)
Bisceglia, E.; Cubizolles, M.; Mallard, F.; Pineda, F.; Francais, O.; Le Pioufle, B.
2013-05-01
Sample preparation is a key issue of modern analytical methods for in vitro diagnostics of diseases with microbiological origins: methods to separate bacteria from other elements of the complex biological samples are of great importance. In the present study, we investigated the DEP force as a way to perform such a de-complexification of the sample by extracting micro-organisms from a complex biological sample under a highly non-uniform electric field in a micro-system based on an interdigitated electrodes array. Different parameters were investigated to optimize the capture efficiency, such as the size of the gap between the electrodes and the height of the capture channel. These parameters are decisive for the distribution of the electric field inside the separation chamber. To optimize these relevant parameters, we performed numerical simulations using COMSOL Multiphysics and correlated them with experimental results. The optimization of the capture efficiency of the device has first been tested on micro-organisms solution but was also investigated on human blood samples spiked with micro-organisms, thereby mimicking real biological samples.
Optimization of sampling effort for a fishery-independent survey with multiple goals.
Xu, Binduo; Zhang, Chongliang; Xue, Ying; Ren, Yiping; Chen, Yong
2015-05-01
Fishery-independent surveys are essential for collecting high quality data to support fisheries management. For fish populations with low abundance and aggregated distribution in a coastal ecosystem, high intensity bottom trawl surveys may result in extra mortality and disturbance to benthic community, imposing unnecessarily large negative impacts on the populations and ecosystem. Optimization of sampling design is necessary to acquire cost-effective sampling efforts, which, however, may not be straightforward for a survey with multiple goals. We developed a simulation approach to evaluate and optimize sampling efforts for a stratified random survey with multiple goals including estimation of abundance indices of individual species and fish groups and species diversity indices. We compared the performances of different sampling efforts when the target estimation indices had different spatial variability over different survey seasons. This study suggests that sampling efforts in a stratified random survey can be reduced while still achieving relatively high precision and accuracy for most indices measuring abundance and biodiversity, which can reduce survey mortality. This study also shows that optimal sampling efforts for a stratified random design may vary with survey objectives. A postsurvey analysis, such as this study, can improve survey designs to achieve the most important survey goals.
Ejnik, J W; Hamilton, M M; Adams, P R; Carmichael, A J
2000-12-15
Kinetic phosphorescence analysis (KPA) is a proven technique for rapid, precise, and accurate determination of uranium in aqueous solutions. Uranium analysis of biological samples require dry-ashing in a muffle furnace between 400 and 600 degrees C followed by wet-ashing with concentrated nitric acid and hydrogen peroxide to digest the organic component in the sample that interferes with uranium determination by KPA. The optimal dry-ashing temperature was determined to be 450 degrees C. At dry-ashing temperatures greater than 450 degrees C, uranium loss was attributed to vaporization. High temperatures also caused increased background values that were attributed to uranium leaching from the glass vials. Dry-ashing temperatures less than 450 degrees C result in the samples needing additional wet-ashing steps. The recovery of uranium in urine samples was 99.2+/-4.02% between spiked concentrations of 1.98-1980 ng (0.198-198 microg l(-1)) uranium, whereas the recovery in whole blood was 89.9+/-7.33% between the same spiked concentrations. The limit of quantification in which uranium in urine and blood could be accurately measured above the background was determined to be 0.05 and 0.6 microg l(-1), respectively. PMID:11130202
Validation of genetic algorithm-based optimal sampling for ocean data assimilation
NASA Astrophysics Data System (ADS)
Heaney, Kevin D.; Lermusiaux, Pierre F. J.; Duda, Timothy F.; Haley, Patrick J.
2016-08-01
Regional ocean models are capable of forecasting conditions for usefully long intervals of time (days) provided that initial and ongoing conditions can be measured. In resource-limited circumstances, the placement of sensors in optimal locations is essential. Here, a nonlinear optimization approach to determine optimal adaptive sampling that uses the genetic algorithm (GA) method is presented. The method determines sampling strategies that minimize a user-defined physics-based cost function. The method is evaluated using identical twin experiments, comparing hindcasts from an ensemble of simulations that assimilate data selected using the GA adaptive sampling and other methods. For skill metrics, we employ the reduction of the ensemble root mean square error (RMSE) between the "true" data-assimilative ocean simulation and the different ensembles of data-assimilative hindcasts. A five-glider optimal sampling study is set up for a 400 km × 400 km domain in the Middle Atlantic Bight region, along the New Jersey shelf-break. Results are compared for several ocean and atmospheric forcing conditions.
Validation of genetic algorithm-based optimal sampling for ocean data assimilation
NASA Astrophysics Data System (ADS)
Heaney, Kevin D.; Lermusiaux, Pierre F. J.; Duda, Timothy F.; Haley, Patrick J.
2016-10-01
Regional ocean models are capable of forecasting conditions for usefully long intervals of time (days) provided that initial and ongoing conditions can be measured. In resource-limited circumstances, the placement of sensors in optimal locations is essential. Here, a nonlinear optimization approach to determine optimal adaptive sampling that uses the genetic algorithm (GA) method is presented. The method determines sampling strategies that minimize a user-defined physics-based cost function. The method is evaluated using identical twin experiments, comparing hindcasts from an ensemble of simulations that assimilate data selected using the GA adaptive sampling and other methods. For skill metrics, we employ the reduction of the ensemble root mean square error (RMSE) between the "true" data-assimilative ocean simulation and the different ensembles of data-assimilative hindcasts. A five-glider optimal sampling study is set up for a 400 km × 400 km domain in the Middle Atlantic Bight region, along the New Jersey shelf-break. Results are compared for several ocean and atmospheric forcing conditions.
Shen, Xiong; Zong, Chao; Zhang, Guoqiang
2012-01-01
Finding out the optimal sampling positions for measurement of ventilation rates in a naturally ventilated building using tracer gas is a challenge. Affected by the wind and the opening status, the representative positions inside the building may change dynamically at any time. An optimization procedure using the Response Surface Methodology (RSM) was conducted. In this method, the concentration field inside the building was estimated by a three-order RSM polynomial model. The experimental sampling positions to develop the model were chosen from the cross-section area of a pitched-roof building. The Optimal Design method which can decrease the bias of the model was adopted to select these sampling positions. Experiments with a scale model building were conducted in a wind tunnel to achieve observed values of those positions. Finally, the models in different cases of opening states and wind conditions were established and the optimum sampling position was obtained with a desirability level up to 92% inside the model building. The optimization was further confirmed by another round of experiments.
A Novel Method of Failure Sample Selection for Electrical Systems Using Ant Colony Optimization
Tian, Shulin; Yang, Chenglin; Liu, Cheng
2016-01-01
The influence of failure propagation is ignored in failure sample selection based on traditional testability demonstration experiment method. Traditional failure sample selection generally causes the omission of some failures during the selection and this phenomenon could lead to some fearful risks of usage because these failures will lead to serious propagation failures. This paper proposes a new failure sample selection method to solve the problem. First, the method uses a directed graph and ant colony optimization (ACO) to obtain a subsequent failure propagation set (SFPS) based on failure propagation model and then we propose a new failure sample selection method on the basis of the number of SFPS. Compared with traditional sampling plan, this method is able to improve the coverage of testing failure samples, increase the capacity of diagnosis, and decrease the risk of using. PMID:27738424
NASA Astrophysics Data System (ADS)
Qu, Mengmeng; Jiang, Dazhi; Lu, Lucy X.
2016-11-01
To address the multiscale deformation and fabric development in Earth's ductile lithosphere, micromechanics-based self-consistent homogenization is commonly used to obtain macroscale rheological properties from properties of constituent elements. The homogenization is heavily based on the solution of an Eshelby viscous inclusion in a linear viscous medium and the extension of the solution to nonlinear viscous materials. The homogenization requires repeated numerical evaluation of Eshelby tensors for constituent elements and becomes ever more computationally challenging as the elements are deformed to more elongate or flattened shapes. In this paper, we develop an optimal scheme for evaluating Eshelby tensors, using a combination of a product Gaussian quadrature and the Lebedev quadrature. We first establish, through numerical experiments, an empirical relationship between the inclusion shape and the computational time it takes to evaluate its Eshelby tensors. We then use the relationship to develop an optimal scheme for selecting the most efficient quadrature to obtain the Eshelby tensors. The optimal scheme is applicable to general homogenizations. In this paper, it is implemented in a MATLAB package for investigating the evolution of solitary rigid or deformable inclusions and the development of shape preferred orientations in multi-inclusion systems during deformation. The MATLAB package, upgrading an earlier effort written in MathCad, can be downloaded online.
Optimal Sampling-Based Motion Planning under Differential Constraints: the Driftless Case
Schmerling, Edward; Janson, Lucas; Pavone, Marco
2015-01-01
Motion planning under differential constraints is a classic problem in robotics. To date, the state of the art is represented by sampling-based techniques, with the Rapidly-exploring Random Tree algorithm as a leading example. Yet, the problem is still open in many aspects, including guarantees on the quality of the obtained solution. In this paper we provide a thorough theoretical framework to assess optimality guarantees of sampling-based algorithms for planning under differential constraints. We exploit this framework to design and analyze two novel sampling-based algorithms that are guaranteed to converge, as the number of samples increases, to an optimal solution (namely, the Differential Probabilistic RoadMap algorithm and the Differential Fast Marching Tree algorithm). Our focus is on driftless control-affine dynamical models, which accurately model a large class of robotic systems. In this paper we use the notion of convergence in probability (as opposed to convergence almost surely): the extra mathematical flexibility of this approach yields convergence rate bounds — a first in the field of optimal sampling-based motion planning under differential constraints. Numerical experiments corroborating our theoretical results are presented and discussed. PMID:26618041
Optimization of low-level LS counter Quantulus 1220 for tritium determination in water samples
NASA Astrophysics Data System (ADS)
Jakonić, Ivana; Todorović, Natasa; Nikolov, Jovana; Bronić, Ines Krajcar; Tenjović, Branislava; Vesković, Miroslav
2014-05-01
Liquid scintillation counting (LSC) is the most commonly used technique for measuring tritium. To optimize tritium analysis in waters by ultra-low background liquid scintillation spectrometer Quantulus 1220 the optimization of sample/scintillant ratio, choice of appropriate scintillation cocktail and comparison of their efficiency, background and minimal detectable activity (MDA), the effect of chemi- and photoluminescence and combination of scintillant/vial were performed. ASTM D4107-08 (2006) method had been successfully applied in our laboratory for two years. During our last preparation of samples a serious quench effect in count rates of samples that could be consequence of possible contamination by DMSO was noticed. The goal of this paper is to demonstrate development of new direct method in our laboratory proposed by Pujol and Sanchez-Cabeza (1999), which turned out to be faster and simpler than ASTM method while we are dealing with problem of neutralization of DMSO in apparatus. The minimum detectable activity achieved was 2.0 Bq l-1 for a total counting time of 300 min. In order to test the optimization of system for this method tritium level was determined in Danube river samples and also for several samples within intercomparison with Ruđer Bošković Institute (IRB).
NASA Astrophysics Data System (ADS)
Chapon, Arnaud; Pigrée, Gilbert; Putmans, Valérie; Rogel, Gwendal
Search for low-energy β contaminations in industrial environments requires using Liquid Scintillation Counting. This indirect measurement method supposes a fine control from sampling to measurement itself. Thus, in this paper, we focus on the definition of a measurement method, as generic as possible, for both smears and aqueous samples' characterization. That includes choice of consumables, sampling methods, optimization of counting parameters and definition of energy windows, using the maximization of a Figure of Merit. Detection limits are then calculated considering these optimized parameters. For this purpose, we used PerkinElmer Tri-Carb counters. Nevertheless, except those relative to some parameters specific to PerkinElmer, most of the results presented here can be extended to other counters.
Sampling design optimization for multivariate soil mapping, case study from Hungary
NASA Astrophysics Data System (ADS)
Szatmári, Gábor; Pásztor, László; Barta, Károly
2014-05-01
Direct observations of the soil are important for two main reasons in Digital Soil Mapping (DSM). First, they are used to characterize the relationship between the soil property of interest and the auxiliary information. Second, they are used to improve the predictions based on the auxiliary information. Hence there is a strong necessity to elaborate a well-established soil sampling strategy based on geostatistical tools, prior knowledge and available resources before the samples are actually collected from the area of interest. Fieldwork and laboratory analyses are the most expensive and labor-intensive part of DSM, meanwhile the collected samples and the measured data have a remarkable influence on the spatial predictions and their uncertainty. Numerous sampling strategy optimization techniques developed in the past decades. One of these optimization techniques is Spatial Simulated Annealing (SSA) that has been frequently used in soil surveys to minimize the average universal kriging variance. The benefit of the technique is, that the surveyor can optimize the sampling design for fixed number of observations taking auxiliary information, previously collected samples and inaccessible areas into account. The requirements are the known form of the regression model and the spatial structure of the residuals of the model. Another restriction is, that the technique is able to optimize the sampling design for just one target soil variable. However, in practice a soil survey usually aims to describe the spatial distribution of not just one but several pedological variables. In the recent paper we present a procedure developed in R-code to simultaneously optimize the sampling design by SSA for two soil variables using spatially averaged universal kriging variance as optimization criterion. Soil Organic Matter (SOM) content and rooting depth were chosen for this purpose. The methodology is illustrated with a legacy data set from a study area in Central Hungary. Legacy soil
A stochastic optimization method to estimate the spatial distribution of a pathogen from a sample.
Parnell, S; Gottwald, T R; Irey, M S; Luo, W; van den Bosch, F
2011-10-01
Information on the spatial distribution of plant disease can be utilized to implement efficient and spatially targeted disease management interventions. We present a pathogen-generic method to estimate the spatial distribution of a plant pathogen using a stochastic optimization process which is epidemiologically motivated. Based on an initial sample, the method simulates the individual spread processes of a pathogen between patches of host to generate optimized spatial distribution maps. The method was tested on data sets of Huanglongbing of citrus and was compared with a kriging method from the field of geostatistics using the well-established kappa statistic to quantify map accuracy. Our method produced accurate maps of disease distribution with kappa values as high as 0.46 and was able to outperform the kriging method across a range of sample sizes based on the kappa statistic. As expected, map accuracy improved with sample size but there was a high amount of variation between different random sample placements (i.e., the spatial distribution of samples). This highlights the importance of sample placement on the ability to estimate the spatial distribution of a plant pathogen and we thus conclude that further research into sampling design and its effect on the ability to estimate disease distribution is necessary. PMID:21916625
An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning
Starek, Joseph A.; Gomez, Javier V.; Schmerling, Edward; Janson, Lucas; Moreno, Luis; Pavone, Marco
2015-01-01
Bi-directional search is a widely used strategy to increase the success and convergence rates of sampling-based motion planning algorithms. Yet, few results are available that merge both bi-directional search and asymptotic optimality into existing optimal planners, such as PRM*, RRT*, and FMT*. The objective of this paper is to fill this gap. Specifically, this paper presents a bi-directional, sampling-based, asymptotically-optimal algorithm named Bi-directional FMT* (BFMT*) that extends the Fast Marching Tree (FMT*) algorithm to bidirectional search while preserving its key properties, chiefly lazy search and asymptotic optimality through convergence in probability. BFMT* performs a two-source, lazy dynamic programming recursion over a set of randomly-drawn samples, correspondingly generating two search trees: one in cost-to-come space from the initial configuration and another in cost-to-go space from the goal configuration. Numerical experiments illustrate the advantages of BFMT* over its unidirectional counterpart, as well as a number of other state-of-the-art planners. PMID:27004130
A method to optimize sampling locations for measuring indoor air distributions
NASA Astrophysics Data System (ADS)
Huang, Yan; Shen, Xiong; Li, Jianmin; Li, Bingye; Duan, Ran; Lin, Chao-Hsin; Liu, Junjie; Chen, Qingyan
2015-02-01
Indoor air distributions, such as the distributions of air temperature, air velocity, and contaminant concentrations, are very important to occupants' health and comfort in enclosed spaces. When point data is collected for interpolation to form field distributions, the sampling locations (the locations of the point sensors) have a significant effect on time invested, labor costs and measuring accuracy on field interpolation. This investigation compared two different sampling methods: the grid method and the gradient-based method, for determining sampling locations. The two methods were applied to obtain point air parameter data in an office room and in a section of an economy-class aircraft cabin. The point data obtained was then interpolated to form field distributions by the ordinary Kriging method. Our error analysis shows that the gradient-based sampling method has 32.6% smaller error of interpolation than the grid sampling method. We acquired the function between the interpolation errors and the sampling size (the number of sampling points). According to the function, the sampling size has an optimal value and the maximum sampling size can be determined by the sensor and system errors. This study recommends the gradient-based sampling method for measuring indoor air distributions.
Kashuba, A D; Ballow, C H; Forrest, A
1996-01-01
Data were gathered during an activity-controlled trial in which seriously ill, elderly patients were randomized to receive intravenous ceftazidime or ciprofloxacin and for which adaptive feedback control of drug concentrations in plasma and activity profiles was prospectively performed. The adaptive feedback control algorithm for ceftazidime used an initial population model, a maximum a posteriori (MAP)-Bayesian pharmacokinetic parameter value estimator, and an optimal, sparse sampling strategy for ceftazidime that had been derived from data in the literature obtained from volunteers. Iterative two-stage population pharmacokinetic analysis was performed to develop an unbiased MAP-Bayesian estimator and updated optimal, sparse sampling strategies. The final median values of the population parameters were follows: the volume of distribution of the central compartment was equal to 0.249 liter/kg, the volume of distribution of the peripheral compartment was equal to 0.173 liter/kg, the distributional clearance between the central and peripheral compartments was equal to 0.2251 liter/h/kg, the slope of the total clearance (CL) versus the creatinine clearance (CLCR) was equal to 0.000736 liter/h/kg of CL/1 ml/min/1.73 m2 of CLCR, and nonrenal clearance was equal to + 0.00527 liter/h/kg. Optimal sampling times were dependent on CLCR; for CLCR of > or = 30 ml/min/1.73 m2, the optimal sampling times were 0.583, 3.0, 7.0, and 16.0 h and, for CLCR of < 30 ml/min/1.73 m2, optimal sampling times were 0.583, 4.15, 11.5, and 24.0 h. The study demonstrates that because pharmacokinetic information from volunteers may often not be reflective of specialty populations such as critically ill elderly individuals, iterative two-stage population pharmacokinetic analysis, MAP-Bayesian parameter estimation, and optimal, sparse sampling strategy can be important tools in characterizing their pharmacokinetics. PMID:8843294
Holmgren, Stina; Tovedal, Annika; Björnham, Oscar; Ramebäck, Henrik
2016-04-01
The aim of this paper is to contribute to a more rapid determination of a series of samples containing (90)Sr by making the Cherenkov measurement of the daughter nuclide (90)Y more time efficient. There are many instances when an optimization of the measurement method might be favorable, such as; situations requiring rapid results in order to make urgent decisions or, on the other hand, to maximize the throughput of samples in a limited available time span. In order to minimize the total analysis time, a mathematical model was developed which calculates the time of ingrowth as well as individual measurement times for n samples in a series. This work is focused on the measurement of (90)Y during ingrowth, after an initial chemical separation of strontium, in which it is assumed that no other radioactive strontium isotopes are present. By using a fixed minimum detectable activity (MDA) and iterating the measurement time for each consecutive sample the total analysis time will be less, compared to using the same measurement time for all samples. It was found that by optimization, the total analysis time for 10 samples can be decreased greatly, from 21h to 6.5h, when assuming a MDA of 1Bq/L and at a background count rate of approximately 0.8cpm.
NASA Astrophysics Data System (ADS)
Rapaglia, John; Koukoulas, Sotirios; Zaggia, Luca; Lichter, Michal; Manfé, Giorgia; Vafeidis, Athanasios T.
2012-03-01
Performing a mass balance of radium isotopes is a commonly employed method for quantifying the flux of groundwater into the sea. However, the spatial variability of 224Ra can compromise the results of mass balances in environmental studies. We address this uncertainty by optimizing the distribution of Ra samples within a surface survey of 224Ra activity in the Lesina Lagoon, Italy. After checking for spatial dependence, location-allocation modeling (LAM) was utilized to determine optimal distribution of samples for thinning the sampling design. Trend surface analysis (TSA) was employed to interpolate the Ra activity throughout the lagoon. No significant change was found when using all 41 samples or only 25 randomly distributed samples. Results from the TSA showed a linear trend and bi-modal distribution in surface 224Ra. This information was utilized to perform mass balances in two separate basins (east and west). SGD was found to be significantly higher in the western basin (4.8 vs. 0.7 cm d - 1 ). Additionally, mass balances were performed using the average 224Ra activity from the trend surface analysis calculated with 41 and 25 samples respectively and total lagoon SGD was found to be 10.4-10.5 m 3 s - 1 . Results show that SGD is significant in the Lesina Lagoon.
Sample volume optimization for radon-in-water detection by liquid scintillation counting.
Schubert, Michael; Kopitz, Juergen; Chałupnik, Stanisław
2014-08-01
Radon is used as environmental tracer in a wide range of applications particularly in aquatic environments. If liquid scintillation counting (LSC) is used as detection method the radon has to be transferred from the water sample into a scintillation cocktail. Whereas the volume of the cocktail is generally given by the size of standard LSC vials (20 ml) the water sample volume is not specified. Aim of the study was an optimization of the water sample volume, i.e. its minimization without risking a significant decrease in LSC count-rate and hence in counting statistics. An equation is introduced, which allows calculating the ²²²Rn concentration that was initially present in a water sample as function of the volumes of water sample, sample flask headspace and scintillation cocktail, the applicable radon partition coefficient, and the detected count-rate value. It was shown that water sample volumes exceeding about 900 ml do not result in a significant increase in count-rate and hence counting statistics. On the other hand, sample volumes that are considerably smaller than about 500 ml lead to noticeably lower count-rates (and poorer counting statistics). Thus water sample volumes of about 500-900 ml should be chosen for LSC radon-in-water detection, if 20 ml vials are applied.
Determining Optimal Location and Numbers of Sample Transects for Characterization of UXO Sites
BILISOLY, ROGER L.; MCKENNA, SEAN A.
2003-01-01
Previous work on sample design has been focused on constructing designs for samples taken at point locations. Significantly less work has been done on sample design for data collected along transects. A review of approaches to point and transect sampling design shows that transects can be considered as a sequential set of point samples. Any two sampling designs can be compared through using each one to predict the value of the quantity being measured on a fixed reference grid. The quality of a design is quantified in two ways: computing either the sum or the product of the eigenvalues of the variance matrix of the prediction error. An important aspect of this analysis is that the reduction of the mean prediction error variance (MPEV) can be calculated for any proposed sample design, including one with straight and/or meandering transects, prior to taking those samples. This reduction in variance can be used as a ''stopping rule'' to determine when enough transect sampling has been completed on the site. Two approaches for the optimization of the transect locations are presented. The first minimizes the sum of the eigenvalues of the predictive error, and the second minimizes the product of these eigenvalues. Simulated annealing is used to identify transect locations that meet either of these objectives. This algorithm is applied to a hypothetical site to determine the optimal locations of two iterations of meandering transects given a previously existing straight transect. The MPEV calculation is also used on both a hypothetical site and on data collected at the Isleta Pueblo to evaluate its potential as a stopping rule. Results show that three or four rounds of systematic sampling with straight parallel transects covering 30 percent or less of the site, can reduce the initial MPEV by as much as 90 percent. The amount of reduction in MPEV can be used as a stopping rule, but the relationship between MPEV and the results of excavation versus no
Smith, F A; Kroft, S H
1996-01-01
The idea of using patient samples as the basis for control procedures elicits a continuing fascination among laboratorians, particularly in the current environment of cost restriction. Average of normals (AON) procedures, although little used, have been carefully investigated at the theoretical level. The performance characteristics of Bull's algorithm have not been thoroughly delineated, however, despite its widespread use. The authors have generalized Bull's algorithm to use variably sized batches of patient samples and a range of exponential factors. For any given batch size, there is an optimal exponential factor to maximize the overall power of error detection. The optimized exponentially adjusted moving mean (EAMM) procedure, a variant of AON and Bull's algorithm, outperforms both parent procedures. As with any AON procedure, EAMM is most useful when the ratio of population variability to analytical variability (standard deviation ratio, SDR) is low.
Cache-Aware Asymptotically-Optimal Sampling-Based Motion Planning.
Ichnowski, Jeffrey; Prins, Jan F; Alterovitz, Ron
2014-05-01
We present CARRT* (Cache-Aware Rapidly Exploring Random Tree*), an asymptotically optimal sampling-based motion planner that significantly reduces motion planning computation time by effectively utilizing the cache memory hierarchy of modern central processing units (CPUs). CARRT* can account for the CPU's cache size in a manner that keeps its working dataset in the cache. The motion planner progressively subdivides the robot's configuration space into smaller regions as the number of configuration samples rises. By focusing configuration exploration in a region for periods of time, nearest neighbor searching is accelerated since the working dataset is small enough to fit in the cache. CARRT* also rewires the motion planning graph in a manner that complements the cache-aware subdivision strategy to more quickly refine the motion planning graph toward optimality. We demonstrate the performance benefit of our cache-aware motion planning approach for scenarios involving a point robot as well as the Rethink Robotics Baxter robot. PMID:25419474
An Optimized Method for Quantification of Pathogenic Leptospira in Environmental Water Samples.
Riediger, Irina N; Hoffmaster, Alex R; Casanovas-Massana, Arnau; Biondo, Alexander W; Ko, Albert I; Stoddard, Robyn A
2016-01-01
Leptospirosis is a zoonotic disease usually acquired by contact with water contaminated with urine of infected animals. However, few molecular methods have been used to monitor or quantify pathogenic Leptospira in environmental water samples. Here we optimized a DNA extraction method for the quantification of leptospires using a previously described Taqman-based qPCR method targeting lipL32, a gene unique to and highly conserved in pathogenic Leptospira. QIAamp DNA mini, MO BIO PowerWater DNA and PowerSoil DNA Isolation kits were evaluated to extract DNA from sewage, pond, river and ultrapure water samples spiked with leptospires. Performance of each kit varied with sample type. Sample processing methods were further evaluated and optimized using the PowerSoil DNA kit due to its performance on turbid water samples and reproducibility. Centrifugation speeds, water volumes and use of Escherichia coli as a carrier were compared to improve DNA recovery. All matrices showed a strong linearity in a range of concentrations from 106 to 10° leptospires/mL and lower limits of detection ranging from <1 cell /ml for river water to 36 cells/mL for ultrapure water with E. coli as a carrier. In conclusion, we optimized a method to quantify pathogenic Leptospira in environmental waters (river, pond and sewage) which consists of the concentration of 40 mL samples by centrifugation at 15,000×g for 20 minutes at 4°C, followed by DNA extraction with the PowerSoil DNA Isolation kit. Although the method described herein needs to be validated in environmental studies, it potentially provides the opportunity for effective, timely and sensitive assessment of environmental leptospiral burden. PMID:27487084
An Optimized Method for Quantification of Pathogenic Leptospira in Environmental Water Samples
Riediger, Irina N.; Hoffmaster, Alex R.; Biondo, Alexander W.; Ko, Albert I.; Stoddard, Robyn A.
2016-01-01
Leptospirosis is a zoonotic disease usually acquired by contact with water contaminated with urine of infected animals. However, few molecular methods have been used to monitor or quantify pathogenic Leptospira in environmental water samples. Here we optimized a DNA extraction method for the quantification of leptospires using a previously described Taqman-based qPCR method targeting lipL32, a gene unique to and highly conserved in pathogenic Leptospira. QIAamp DNA mini, MO BIO PowerWater DNA and PowerSoil DNA Isolation kits were evaluated to extract DNA from sewage, pond, river and ultrapure water samples spiked with leptospires. Performance of each kit varied with sample type. Sample processing methods were further evaluated and optimized using the PowerSoil DNA kit due to its performance on turbid water samples and reproducibility. Centrifugation speeds, water volumes and use of Escherichia coli as a carrier were compared to improve DNA recovery. All matrices showed a strong linearity in a range of concentrations from 106 to 10° leptospires/mL and lower limits of detection ranging from <1 cell /ml for river water to 36 cells/mL for ultrapure water with E. coli as a carrier. In conclusion, we optimized a method to quantify pathogenic Leptospira in environmental waters (river, pond and sewage) which consists of the concentration of 40 mL samples by centrifugation at 15,000×g for 20 minutes at 4°C, followed by DNA extraction with the PowerSoil DNA Isolation kit. Although the method described herein needs to be validated in environmental studies, it potentially provides the opportunity for effective, timely and sensitive assessment of environmental leptospiral burden. PMID:27487084
Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao
2014-10-01
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/.
Toward 3D-guided prostate biopsy target optimization: an estimation of tumor sampling probabilities
NASA Astrophysics Data System (ADS)
Martin, Peter R.; Cool, Derek W.; Romagnoli, Cesare; Fenster, Aaron; Ward, Aaron D.
2014-03-01
Magnetic resonance imaging (MRI)-targeted, 3D transrectal ultrasound (TRUS)-guided "fusion" prostate biopsy aims to reduce the ~23% false negative rate of clinical 2D TRUS-guided sextant biopsy. Although it has been reported to double the positive yield, MRI-targeted biopsy still yields false negatives. Therefore, we propose optimization of biopsy targeting to meet the clinician's desired tumor sampling probability, optimizing needle targets within each tumor and accounting for uncertainties due to guidance system errors, image registration errors, and irregular tumor shapes. We obtained multiparametric MRI and 3D TRUS images from 49 patients. A radiologist and radiology resident contoured 81 suspicious regions, yielding 3D surfaces that were registered to 3D TRUS. We estimated the probability, P, of obtaining a tumor sample with a single biopsy. Given an RMS needle delivery error of 3.5 mm for a contemporary fusion biopsy system, P >= 95% for 21 out of 81 tumors when the point of optimal sampling probability was targeted. Therefore, more than one biopsy core must be taken from 74% of the tumors to achieve P >= 95% for a biopsy system with an error of 3.5 mm. Our experiments indicated that the effect of error along the needle axis on the percentage of core involvement (and thus the measured tumor burden) was mitigated by the 18 mm core length.
Damage identification in beams using speckle shearography and an optimal spatial sampling
NASA Astrophysics Data System (ADS)
Mininni, M.; Gabriele, S.; Lopes, H.; Araújo dos Santos, J. V.
2016-10-01
Over the years, the derivatives of modal displacement and rotation fields have been used to localize damage in beams. Usually, the derivatives are computed by applying finite differences. The finite differences propagate and amplify the errors that exist in real measurements, and thus, it is necessary to minimize this problem in order to get reliable damage localizations. A way to decrease the propagation and amplification of the errors is to select an optimal spatial sampling. This paper presents a technique where an optimal spatial sampling of modal rotation fields is computed and used to obtain the modal curvatures. Experimental measurements of modal rotation fields of a beam with single and multiple damages are obtained with shearography, which is an optical technique allowing the measurement of full-fields. These measurements are used to test the validity of the optimal sampling technique for the improvement of damage localization in real structures. An investigation on the ability of a model updating technique to quantify the damage is also reported. The model updating technique is defined by the variations of measured natural frequencies and measured modal rotations and aims at calibrating the values of the second moment of area in the damaged areas, which were previously localized.
Spectral gap optimization of order parameters for sampling complex molecular systems.
Tiwary, Pratyush; Berne, B J
2016-03-15
In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs.
Spectral gap optimization of order parameters for sampling complex molecular systems
Tiwary, Pratyush; Berne, B. J.
2016-01-01
In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs. PMID:26929365
ERIC Educational Resources Information Center
Foster, Geraldine R. K.; Tickle, Martin
2013-01-01
Background and objective: Some districts in the United Kingdom (UK), where the level of child dental caries is high and water fluoridation has not been possible, implement school-based fluoridated milk (FM) schemes. However, process variables, such as consent to drink FM and loss of children as they mature, impede the effectiveness of these…
NASA Astrophysics Data System (ADS)
Tavakoli, Rouhollah
2016-01-01
An unconditionally energy stable time stepping scheme is introduced to solve Cahn-Morral-like equations in the present study. It is constructed based on the combination of David Eyre's time stepping scheme and Schur complement approach. Although the presented method is general and independent of the choice of homogeneous free energy density function term, logarithmic and polynomial energy functions are specifically considered in this paper. The method is applied to study the spinodal decomposition in multi-component systems and optimal space tiling problems. A penalization strategy is developed, in the case of later problem, to avoid trivial solutions. Extensive numerical experiments demonstrate the success and performance of the presented method. According to the numerical results, the method is convergent and energy stable, independent of the choice of time stepsize. Its MATLAB implementation is included in the appendix for the numerical evaluation of algorithm and reproduction of the presented results.
Tiwari, P; Xie, Y; Chen, Y; Deasy, J
2014-06-01
Purpose: The IMRT optimization problem requires substantial computer time to find optimal dose distributions because of the large number of variables and constraints. Voxel sampling reduces the number of constraints and accelerates the optimization process, but usually deteriorates the quality of the dose distributions to the organs. We propose a novel sampling algorithm that accelerates the IMRT optimization process without significantly deteriorating the quality of the dose distribution. Methods: We included all boundary voxels, as well as a sampled fraction of interior voxels of organs in the optimization. We selected a fraction of interior voxels using a clustering algorithm, that creates clusters of voxels that have similar influence matrix signatures. A few voxels are selected from each cluster based on the pre-set sampling rate. Results: We ran sampling and no-sampling IMRT plans for de-identified head and neck treatment plans. Testing with the different sampling rates, we found that including 10% of inner voxels produced the good dose distributions. For this optimal sampling rate, the algorithm accelerated IMRT optimization by a factor of 2–3 times with a negligible loss of accuracy that was, on average, 0.3% for common dosimetric planning criteria. Conclusion: We demonstrated that a sampling could be developed that reduces optimization time by more than a factor of 2, without significantly degrading the dose quality.
A Two-Stage Method to Determine Optimal Product Sampling considering Dynamic Potential Market
Hu, Zhineng; Lu, Wei; Han, Bing
2015-01-01
This paper develops an optimization model for the diffusion effects of free samples under dynamic changes in potential market based on the characteristics of independent product and presents a two-stage method to figure out the sampling level. The impact analysis of the key factors on the sampling level shows that the increase of the external coefficient or internal coefficient has a negative influence on the sampling level. And the changing rate of the potential market has no significant influence on the sampling level whereas the repeat purchase has a positive one. Using logistic analysis and regression analysis, the global sensitivity analysis gives a whole analysis of the interaction of all parameters, which provides a two-stage method to estimate the impact of the relevant parameters in the case of inaccuracy of the parameters and to be able to construct a 95% confidence interval for the predicted sampling level. Finally, the paper provides the operational steps to improve the accuracy of the parameter estimation and an innovational way to estimate the sampling level. PMID:25821847
A two-stage method to determine optimal product sampling considering dynamic potential market.
Hu, Zhineng; Lu, Wei; Han, Bing
2015-01-01
This paper develops an optimization model for the diffusion effects of free samples under dynamic changes in potential market based on the characteristics of independent product and presents a two-stage method to figure out the sampling level. The impact analysis of the key factors on the sampling level shows that the increase of the external coefficient or internal coefficient has a negative influence on the sampling level. And the changing rate of the potential market has no significant influence on the sampling level whereas the repeat purchase has a positive one. Using logistic analysis and regression analysis, the global sensitivity analysis gives a whole analysis of the interaction of all parameters, which provides a two-stage method to estimate the impact of the relevant parameters in the case of inaccuracy of the parameters and to be able to construct a 95% confidence interval for the predicted sampling level. Finally, the paper provides the operational steps to improve the accuracy of the parameter estimation and an innovational way to estimate the sampling level.
JR Bontha; GR Golcar; N Hannigan
2000-08-29
The BNFL Inc. flowsheet for the pretreatment and vitrification of the Hanford High Level Tank waste includes the use of several hundred Reverse Flow Diverters (RFDs) for sampling and transferring the radioactive slurries and Pulsed Jet mixers to homogenize or suspend the tank contents. The Pulsed Jet mixing and the RFD sampling devices represent very simple and efficient methods to mix and sample slurries, respectively, using compressed air to achieve the desired operation. The equipment has no moving parts, which makes them very suitable for mixing and sampling highly radioactive wastes. However, the effectiveness of the mixing and sampling systems are yet to be demonstrated when dealing with Hanford slurries, which exhibit a wide range of physical and theological properties. This report describes the results of the testing of BNFL's Pulsed Jet mixing and RFD sampling systems in a 13-ft ID and 15-ft height dish-bottomed tank at Battelle's 336 building high-bay facility using AZ-101/102 simulants containing up to 36-wt% insoluble solids. The specific objectives of the work were to: Demonstrate the effectiveness of the Pulsed Jet mixing system to thoroughly homogenize Hanford-type slurries over a range of solids loading; Minimize/optimize air usage by changing sequencing of the Pulsed Jet mixers or by altering cycle times; and Demonstrate that the RFD sampler can obtain representative samples of the slurry up to the maximum RPP-WTP baseline concentration of 25-wt%.
Ferrer-Paris, José Rafael; Sánchez-Mercado, Ada; Rodríguez, Jon Paul
2013-03-01
The development of efficient sampling protocols is an essential prerequisite to evaluate and identify priority conservation areas. There are f ew protocols for fauna inventory and monitoring in wide geographical scales for the tropics, where the complexity of communities and high biodiversity levels, make the implementation of efficient protocols more difficult. We proposed here a simple strategy to optimize the capture of dung beetles, applied to sampling with baited traps and generalizable to other sampling methods. We analyzed data from eight transects sampled between 2006-2008 withthe aim to develop an uniform sampling design, that allows to confidently estimate species richness, abundance and composition at wide geographical scales. We examined four characteristics of any sampling design that affect the effectiveness of the sampling effort: the number of traps, sampling duration, type and proportion of bait, and spatial arrangement of the traps along transects. We used species accumulation curves, rank-abundance plots, indicator species analysis, and multivariate correlograms. We captured 40 337 individuals (115 species/morphospecies of 23 genera). Most species were attracted by both dung and carrion, but two thirds had greater relative abundance in traps baited with human dung. Different aspects of the sampling design influenced each diversity attribute in different ways. To obtain reliable richness estimates, the number of traps was the most important aspect. Accurate abundance estimates were obtained when the sampling period was increased, while the spatial arrangement of traps was determinant to capture the species composition pattern. An optimum sampling strategy for accurate estimates of richness, abundance and diversity should: (1) set 50-70 traps to maximize the number of species detected, (2) get samples during 48-72 hours and set trap groups along the transect to reliably estimate species abundance, (3) set traps in groups of at least 10 traps to
Morley, Shannon M.; Seiner, Brienne N.; Finn, Erin C.; Greenwood, Lawrence R.; Smith, Steven C.; Gregory, Stephanie J.; Haney, Morgan M.; Lucas, Dawn D.; Arrigo, Leah M.; Beacham, Tere A.; Swearingen, Kevin J.; Friese, Judah I.; Douglas, Matthew; Metz, Lori A.
2015-05-01
Mixed fission and activation materials resulting from various nuclear processes and events contain a wide range of isotopes for analysis spanning almost the entire periodic table. In some applications such as environmental monitoring, nuclear waste management, and national security a very limited amount of material is available for analysis and characterization so an integrated analysis scheme is needed to measure multiple radionuclides from one sample. This work describes the production of a complex synthetic sample containing fission products, activation products, and irradiated soil and determines the percent recovery of select isotopes through the integrated chemical separation scheme. Results were determined using gamma energy analysis of separated fractions and demonstrate high yields of Ag (76 ± 6%), Au (94 ± 7%), Cd (59 ± 2%), Co (93 ± 5%), Cs (88 ± 3%), Fe (62 ± 1%), Mn (70 ± 7%), Np (65 ± 5%), Sr (73 ± 2%) and Zn (72 ± 3%). Lower yields (< 25%) were measured for Ga, Ir, Sc, and W. Based on the results of this experiment, a complex synthetic sample can be prepared with low atom/fission ratios and isotopes of interest accurately and precisely measured following an integrated chemical separation method.
NASA Astrophysics Data System (ADS)
Zhou, Rurui; Li, Yu; Lu, Di; Liu, Haixing; Zhou, Huicheng
2016-09-01
This paper investigates the use of an epsilon-dominance non-dominated sorted genetic algorithm II (ɛ-NSGAII) as a sampling approach with an aim to improving sampling efficiency for multiple metrics uncertainty analysis using Generalized Likelihood Uncertainty Estimation (GLUE). The effectiveness of ɛ-NSGAII based sampling is demonstrated compared with Latin hypercube sampling (LHS) through analyzing sampling efficiency, multiple metrics performance, parameter uncertainty and flood forecasting uncertainty with a case study of flood forecasting uncertainty evaluation based on Xinanjiang model (XAJ) for Qing River reservoir, China. Results obtained demonstrate the following advantages of the ɛ-NSGAII based sampling approach in comparison to LHS: (1) The former performs more effective and efficient than LHS, for example the simulation time required to generate 1000 behavioral parameter sets is shorter by 9 times; (2) The Pareto tradeoffs between metrics are demonstrated clearly with the solutions from ɛ-NSGAII based sampling, also their Pareto optimal values are better than those of LHS, which means better forecasting accuracy of ɛ-NSGAII parameter sets; (3) The parameter posterior distributions from ɛ-NSGAII based sampling are concentrated in the appropriate ranges rather than uniform, which accords with their physical significance, also parameter uncertainties are reduced significantly; (4) The forecasted floods are close to the observations as evaluated by three measures: the normalized total flow outside the uncertainty intervals (FOUI), average relative band-width (RB) and average deviation amplitude (D). The flood forecasting uncertainty is also reduced a lot with ɛ-NSGAII based sampling. This study provides a new sampling approach to improve multiple metrics uncertainty analysis under the framework of GLUE, and could be used to reveal the underlying mechanisms of parameter sets under multiple conflicting metrics in the uncertainty analysis process.
Sugano, Yasutaka; Mizuta, Masahiro; Takao, Seishin; Shirato, Hiroki; Sutherland, Kenneth L.; Date, Hiroyuki
2015-11-15
Purpose: Radiotherapy of solid tumors has been performed with various fractionation regimens such as multi- and hypofractionations. However, the ability to optimize the fractionation regimen considering the physical dose distribution remains insufficient. This study aims to optimize the fractionation regimen, in which the authors propose a graphical method for selecting the optimal number of fractions (n) and dose per fraction (d) based on dose–volume histograms for tumor and normal tissues of organs around the tumor. Methods: Modified linear-quadratic models were employed to estimate the radiation effects on the tumor and an organ at risk (OAR), where the repopulation of the tumor cells and the linearity of the dose-response curve in the high dose range of the surviving fraction were considered. The minimization problem for the damage effect on the OAR was solved under the constraint that the radiation effect on the tumor is fixed by a graphical method. Here, the damage effect on the OAR was estimated based on the dose–volume histogram. Results: It was found that the optimization of fractionation scheme incorporating the dose–volume histogram is possible by employing appropriate cell surviving models. The graphical method considering the repopulation of tumor cells and a rectilinear response in the high dose range enables them to derive the optimal number of fractions and dose per fraction. For example, in the treatment of prostate cancer, the optimal fractionation was suggested to lie in the range of 8–32 fractions with a daily dose of 2.2–6.3 Gy. Conclusions: It is possible to optimize the number of fractions and dose per fraction based on the physical dose distribution (i.e., dose–volume histogram) by the graphical method considering the effects on tumor and OARs around the tumor. This method may stipulate a new guideline to optimize the fractionation regimen for physics-guided fractionation.
Dynamics of hepatitis C under optimal therapy and sampling based analysis
NASA Astrophysics Data System (ADS)
Pachpute, Gaurav; Chakrabarty, Siddhartha P.
2013-08-01
We examine two models for hepatitis C viral (HCV) dynamics, one for monotherapy with interferon (IFN) and the other for combination therapy with IFN and ribavirin. Optimal therapy for both the models is determined using the steepest gradient method, by defining an objective functional which minimizes infected hepatocyte levels, virion population and side-effects of the drug(s). The optimal therapies for both the models show an initial period of high efficacy, followed by a gradual decline. The period of high efficacy coincides with a significant decrease in the viral load, whereas the efficacy drops after hepatocyte levels are restored. We use the Latin hypercube sampling technique to randomly generate a large number of patient scenarios and study the dynamics of each set under the optimal therapy already determined. Results show an increase in the percentage of responders (indicated by drop in viral load below detection levels) in case of combination therapy (72%) as compared to monotherapy (57%). Statistical tests performed to study correlations between sample parameters and time required for the viral load to fall below detection level, show a strong monotonic correlation with the death rate of infected hepatocytes, identifying it to be an important factor in deciding individual drug regimens.
Optimization of a sample processing protocol for recovery of Bacillus anthracis spores from soil
Silvestri, Erin E.; Feldhake, David; Griffin, Dale; Lisle, John T.; Nichols, Tonya L.; Shah, Sanjiv; Pemberton, A; Schaefer III, Frank W
2016-01-01
Following a release of Bacillus anthracis spores into the environment, there is a potential for lasting environmental contamination in soils. There is a need for detection protocols for B. anthracis in environmental matrices. However, identification of B. anthracis within a soil is a difficult task. Processing soil samples helps to remove debris, chemical components, and biological impurities that can interfere with microbiological detection. This study aimed to optimize a previously used indirect processing protocol, which included a series of washing and centrifugation steps. Optimization of the protocol included: identifying an ideal extraction diluent, variation in the number of wash steps, variation in the initial centrifugation speed, sonication and shaking mechanisms. The optimized protocol was demonstrated at two laboratories in order to evaluate the recovery of spores from loamy and sandy soils. The new protocol demonstrated an improved limit of detection for loamy and sandy soils over the non-optimized protocol with an approximate matrix limit of detection at 14 spores/g of soil. There were no significant differences overall between the two laboratories for either soil type, suggesting that the processing protocol will be robust enough to use at multiple laboratories while achieving comparable recoveries.
Chenel, Marylore; Ogungbenro, Kayode; Duval, Vincent; Laveille, Christian; Jochemsen, Roeline; Aarons, Leon
2005-12-01
The objective of this paper is to determine optimal blood sampling time windows for the estimation of pharmacokinetic (PK) parameters by a population approach within the clinical constraints. A population PK model was developed to describe a reference phase II PK dataset. Using this model and the parameter estimates, D-optimal sampling times were determined by optimising the determinant of the population Fisher information matrix (PFIM) using PFIM_ _M 1.2 and the modified Fedorov exchange algorithm. Optimal sampling time windows were then determined by allowing the D-optimal windows design to result in a specified level of efficiency when compared to the fixed-times D-optimal design. The best results were obtained when K(a) and IIV on K(a) were fixed. Windows were determined using this approach assuming 90% level of efficiency and uniform sample distribution. Four optimal sampling time windows were determined as follow: at trough between 22 h and new drug administration; between 2 and 4 h after dose for all patients; and for 1/3 of the patients only 2 sampling time windows between 4 and 10 h after dose, equal to [4 h-5 h 05] and [9 h 10-10 h]. This work permitted the determination of an optimal design, with suitable sampling time windows which was then evaluated by simulations. The sampling time windows will be used to define the sampling schedule in a prospective phase II study.
Model reduction algorithms for optimal control and importance sampling of diffusions
NASA Astrophysics Data System (ADS)
Hartmann, Carsten; Schütte, Christof; Zhang, Wei
2016-08-01
We propose numerical algorithms for solving optimal control and importance sampling problems based on simplified models. The algorithms combine model reduction techniques for multiscale diffusions and stochastic optimization tools, with the aim of reducing the original, possibly high-dimensional problem to a lower dimensional representation of the dynamics, in which only a few relevant degrees of freedom are controlled or biased. Specifically, we study situations in which either a reaction coordinate onto which the dynamics can be projected is known, or situations in which the dynamics shows strongly localized behavior in the small noise regime. No explicit assumptions about small parameters or scale separation have to be made. We illustrate the approach with simple, but paradigmatic numerical examples.
NASA Astrophysics Data System (ADS)
Ridolfi, E.; Alfonso, L.; Di Baldassarre, G.; Napolitano, F.
2016-06-01
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.
Ayad, G.; Barriere, T.; Gelin, J. C.; Liu, B.
2007-05-17
The paper is concerned with optimization and parametric identification of Powder Injection Molding process that consists first in injection of powder mixture with polymer binder and then to the sintering of the resulting powders parts by solid state diffusion. In the first part, one describes an original methodology to optimize the injection stage based on the combination of Design Of Experiments and an adaptive Response Surface Modeling. Then the second part of the paper describes the identification strategy that one proposes for the sintering stage, using the identification of sintering parameters from dilatometer curves followed by the optimization of the sintering process. The proposed approaches are applied to the optimization for manufacturing of a ceramic femoral implant. One demonstrates that the proposed approach give satisfactory results.
NASA Astrophysics Data System (ADS)
Agarwal, R. K.; Zhang, Z.; Zhu, C.
2013-12-01
For optimization of CO2 storage and reduced CO2 plume migration in saline aquifers, a genetic algorithm (GA) based optimizer has been developed which is combined with the DOE multi-phase flow and heat transfer numerical simulation code TOUGH2. Designated as GA-TOUGH2, this combined solver/optimizer has been verified by performing optimization studies on a number of model problems and comparing the results with brute-force optimization which requires a large number of simulations. Using GA-TOUGH2, an innovative reservoir engineering technique known as water-alternating-gas (WAG) injection has been investigated to determine the optimal WAG operation for enhanced CO2 storage capacity. The topmost layer (layer # 9) of Utsira formation at Sleipner Project, Norway is considered as a case study. A cylindrical domain, which possesses identical characteristics of the detailed 3D Utsira Layer #9 model except for the absence of 3D topography, was used. Topographical details are known to be important in determining the CO2 migration at Sleipner, and are considered in our companion model for history match of the CO2 plume migration at Sleipner. However, simplification on topography here, without compromising accuracy, is necessary to analyze the effectiveness of WAG operation on CO2 migration without incurring excessive computational cost. Selected WAG operation then can be simulated with full topography details later. We consider a cylindrical domain with thickness of 35 m with horizontal flat caprock. All hydrogeological properties are retained from the detailed 3D Utsira Layer #9 model, the most important being the horizontal-to-vertical permeability ratio of 10. Constant Gas Injection (CGI) operation with nine-year average CO2 injection rate of 2.7 kg/s is considered as the baseline case for comparison. The 30-day, 15-day, and 5-day WAG cycle durations are considered for the WAG optimization design. Our computations show that for the simplified Utsira Layer #9 model, the
Stemkens, Bjorn; Tijssen, Rob H.N.; Senneville, Baudouin D. de
2015-03-01
Purpose: To determine the optimum sampling strategy for retrospective reconstruction of 4-dimensional (4D) MR data for nonrigid motion characterization of tumor and organs at risk for radiation therapy purposes. Methods and Materials: For optimization, we compared 2 surrogate signals (external respiratory bellows and internal MRI navigators) and 2 MR sampling strategies (Cartesian and radial) in terms of image quality and robustness. Using the optimized protocol, 6 pancreatic cancer patients were scanned to calculate the 4D motion. Region of interest analysis was performed to characterize the respiratory-induced motion of the tumor and organs at risk simultaneously. Results: The MRI navigator was found to be a more reliable surrogate for pancreatic motion than the respiratory bellows signal. Radial sampling is most benign for undersampling artifacts and intraview motion. Motion characterization revealed interorgan and interpatient variation, as well as heterogeneity within the tumor. Conclusions: A robust 4D-MRI method, based on clinically available protocols, is presented and successfully applied to characterize the abdominal motion in a small number of pancreatic cancer patients.
An S/H circuit with parasitics optimized for IF-sampling
NASA Astrophysics Data System (ADS)
Xuqiang, Zheng; Fule, Li; Zhijun, Wang; Weitao, Li; Wen, Jia; Zhihua, Wang; Shigang, Yue
2016-06-01
An IF-sampling S/H is presented, which adopts a flip-around structure, bottom-plate sampling technique and improved input bootstrapped switches. To achieve high sampling linearity over a wide input frequency range, the floating well technique is utilized to optimize the input switches. Besides, techniques of transistor load linearization and layout improvement are proposed to further reduce and linearize the parasitic capacitance. The S/H circuit has been fabricated in 0.18-μm CMOS process as the front-end of a 14 bit, 250 MS/s pipeline ADC. For 30 MHz input, the measured SFDR/SNDR of the ADC is 94.7 dB/68. 5dB, which can remain over 84.3 dB/65.4 dB for input frequency up to 400 MHz. The ADC presents excellent dynamic performance at high input frequency, which is mainly attributed to the parasitics optimized S/H circuit. Poject supported by the Shenzhen Project (No. JSGG20150512162029307).
Optimization of Sample Site Selection Imaging for OSIRIS-REx Using Asteroid Surface Analog Images
NASA Astrophysics Data System (ADS)
Tanquary, Hannah E.; Sahr, Eric; Habib, Namrah; Hawley, Christopher; Weber, Nathan; Boynton, William V.; Kinney-Spano, Ellyne; Lauretta, Dante
2014-11-01
OSIRIS-REx will return a sample of regolith from the surface of asteroid 101955 Bennu. The mission will obtain high resolution images of the asteroid in order to create detailed maps which will satisfy multiple mission objectives. To select a site, we must (i) identify hazards to the spacecraft and (ii) characterize a number of candidate sites to determine the optimal location for sampling. To further characterize the site, a long-term science campaign will be undertaken to constrain the geologic properties. To satisfy these objectives, the distribution and size of blocks at the sample site and backup sample site must be determined. This will be accomplished through the creation of rock size frequency distribution maps. The primary goal of this study is to optimize the creation of these map products by assessing techniques for counting blocks on small bodies, and assessing the methods of analysis of the resulting data. We have produced a series of simulated surfaces of Bennu which have been imaged, and the images processed to simulate Polycam images during the Reconnaissance phase. These surface analog images allow us to explore a wide range of imaging conditions, both ideal and non-ideal. The images have been “degraded”, and are displayed as thumbnails representing the limits of Polycam resolution from an altitude of 225 meters. Specifically, this study addresses the mission requirement that the rock size frequency distribution of regolith grains < 2cm in longest dimension must be determined for the sample sites during Reconnaissance. To address this requirement, we focus on the range of available lighting angles. Varying illumination and phase angles in the simulated images, we can compare the size-frequency distributions calculated from the degraded images with the known size frequency distributions of the Bennu simulant material, and thus determine the optimum lighting conditions for satisfying the 2 cm requirement.
Easton, D.F.; Goldgar, D.E.
1994-09-01
As genes underlying susceptibility to human disease are identified through linkage analysis, it is becoming increasingly clear that genetic heterogeneity is the rule rather than the exception. The focus of the present work is to examine the power and optimal sampling design for localizing a second disease gene when one disease gene has previously been identified. In particular, we examined the case when the unknown locus had lower penetrance, but higher frequency, than the known locus. Three scenarios regarding knowledge about locus 1 were examined: no linkage information (i.e. standard heterogeneity analysis), tight linkage with a known highly polymorphic marker locus, and mutation testing. Exact expected LOD scores (ELODs) were calculated for a number of two-locus genetic models under the 3 scenarios of heterogeneity for nuclear families containing 2, 3 or 4 affected children, with 0 or 1 affected parents. A cost function based upon the cost of ascertaining and genotyping sufficient samples to achieve an ELOD of 3.0 was used to evaluate the designs. As expected, the power and the optimal pedigree sampling strategy was dependent on the underlying model and the heterogeneity testing status. When the known locus had higher penetrance than the unknown locus, three affected siblings with unaffected parents proved to be optimal for all levels of heterogeneity. In general, mutation testing at the first locus provided substantially more power for detecting the second locus than linkage evidence alone. However, when both loci had relatively low penetrance, mutation testing provided little improvement in power since most families could be expected to be segregating the high risk allele at both loci.
Madisch, Ijad; Wölfel, Roman; Harste, Gabi; Pommer, Heidi; Heim, Albert
2006-09-01
Precise typing of human adenoviruses (HAdV) is fundamental for epidemiology and the detection of infection chains. As only few of the 51 adenovirus types are associated with life- threatening disseminated diseases in immunodeficient patients, detection of one of these types may have prognostic value and lead to immediate therapeutic intervention. A recently published molecular typing scheme consisting of two steps (sequencing of a generic PCR product closely adjacent to loop 1 of the main neutralization determinant epsilon, and for species HAdV-B, -C, and -D the sequencing of loop 2 [Madisch et al., 2005]) was applied to 119 clinical samples. HAdV DNA was typed unequivocally even in cases of culture negative samples, for example in immunodeficient patients before HAdV causes high virus loads and disseminated disease. Direct typing results demonstrated the predominance of HAdV-1, -2, -5, and -31 in immunodeficient patients suggesting the significance of the persistence of these viruses for the pathogenesis of disseminated disease. In contrast, HAdV-3 predominated in immunocompetent patients and cocirculation of four subtypes was demonstrated. Typing of samples from a conjunctivitis outbreak in multiple military barracks demonstrated various HAdV types (2, 4, 8, 19) and not the suspected unique adenovirus etiology. This suggests that our molecular typing scheme will be also useful for epidemiological investigations. In conclusion, our two-step molecular typing system will permit the precise and rapid typing of clinical HAdV isolates and even of HAdV DNA in clinical samples without the need of time-consuming virus isolation prior to typing.
Optimizing the Operating Temperature for an array of MOX Sensors on an Open Sampling System
NASA Astrophysics Data System (ADS)
Trincavelli, M.; Vergara, A.; Rulkov, N.; Murguia, J. S.; Lilienthal, A.; Huerta, R.
2011-09-01
Chemo-resistive transduction is essential for capturing the spatio-temporal structure of chemical compounds dispersed in different environments. Due to gas dispersion mechanisms, namely diffusion, turbulence and advection, the sensors in an open sampling system, i.e. directly exposed to the environment to be monitored, are exposed to low concentrations of gases with many fluctuations making, as a consequence, the identification and monitoring of the gases even more complicated and challenging than in a controlled laboratory setting. Therefore, tuning the value of the operating temperature becomes crucial for successfully identifying and monitoring the pollutant gases, particularly in applications such as exploration of hazardous areas, air pollution monitoring, and search and rescue1. In this study we demonstrate the benefit of optimizing the sensor's operating temperature when the sensors are deployed in an open sampling system, i.e. directly exposed to the environment to be monitored.
AMORE-HX: a multidimensional optimization of radial enhanced NMR-sampled hydrogen exchange.
Gledhill, John M; Walters, Benjamin T; Wand, A Joshua
2009-09-01
The Cartesian sampled three-dimensional HNCO experiment is inherently limited in time resolution and sensitivity for the real time measurement of protein hydrogen exchange. This is largely overcome by use of the radial HNCO experiment that employs the use of optimized sampling angles. The significant practical limitation presented by use of three-dimensional data is the large data storage and processing requirements necessary and is largely overcome by taking advantage of the inherent capabilities of the 2D-FT to process selective frequency space without artifact or limitation. Decomposition of angle spectra into positive and negative ridge components provides increased resolution and allows statistical averaging of intensity and therefore increased precision. Strategies for averaging ridge cross sections within and between angle spectra are developed to allow further statistical approaches for increasing the precision of measured hydrogen occupancy. Intensity artifacts potentially introduced by over-pulsing are effectively eliminated by use of the BEST approach. PMID:19633974
Tuomas, V.; Jaakko, L.
2013-07-01
This article discusses the optimization of the target motion sampling (TMS) temperature treatment method, previously implemented in the Monte Carlo reactor physics code Serpent 2. The TMS method was introduced in [1] and first practical results were presented at the PHYSOR 2012 conference [2]. The method is a stochastic method for taking the effect of thermal motion into account on-the-fly in a Monte Carlo neutron transport calculation. It is based on sampling the target velocities at collision sites and then utilizing the 0 K cross sections at target-at-rest frame for reaction sampling. The fact that the total cross section becomes a distributed quantity is handled using rejection sampling techniques. The original implementation of the TMS requires 2.0 times more CPU time in a PWR pin-cell case than a conventional Monte Carlo calculation relying on pre-broadened effective cross sections. In a HTGR case examined in this paper the overhead factor is as high as 3.6. By first changing from a multi-group to a continuous-energy implementation and then fine-tuning a parameter affecting the conservativity of the majorant cross section, it is possible to decrease the overhead factors to 1.4 and 2.3, respectively. Preliminary calculations are also made using a new and yet incomplete optimization method in which the temperature of the basis cross section is increased above 0 K. It seems that with the new approach it may be possible to decrease the factors even as low as 1.06 and 1.33, respectively, but its functionality has not yet been proven. Therefore, these performance measures should be considered preliminary. (authors)
NASA Astrophysics Data System (ADS)
Wang, Yan; Li, Xianguo; Peng, Xuewei; Tang, Xuli; Deng, Xiaoyan
2012-06-01
This study examined levels of polycyclic aromatic hydrocarbons (PAHs) in estuarine sediments in Licun (Qingdao, China) by gas chromatography under optimized conditions for sample pretreatment via ultrasonic extraction, column chromatography, and thin layer chromatography. Methanol and dichloromethane (DCM)/methanol (2:1, v/v) were used in ultrasonic extraction, and DCM was used as eluate for column chromatography. The developing system consisted of n-hexane and DCM at a ratio of 9:1 (v/v), with DCM as the extraction solvent for PAHs-containing silica gel scraped off the plate. When the spiking level is 100 ng, total recoveries of spiked matrices for four target PAHs (phenanthrene, anthracene, pyrene and chrysene) were 83.7%, 76.4%, 85.8%, and 88.7%, respectively, with relative standard deviation (RSD) between 5.0% and 6.5% ( n = 4). When the spiking level is 1000 ng, associated total recoveries were 78.6%, 72.7%, 82.7% and 85.3%, respectively, with RSD between 4.4% and 5.3% ( n = 4). The optimized method was advantageous for determination of PAHs in complex matrix due to its effective sample purification.
Ma, Li; Wang, Lin; Tang, Jie; Yang, Zhaoguang
2016-08-01
Statistical experimental designs were employed to optimize the extraction condition of arsenic species (As(III), As(V), monomethylarsonic acid (MMA) and dimethylarsonic acid (DMA)) in paddy rice by a simple solvent extraction using water as an extraction reagent. The effect of variables were estimated by a two-level Plackett-Burman factorial design. A five-level central composite design was subsequently employed to optimize the significant factors. The desirability parameters of the significant factors were confirmed to 60min of shaking time and 85°C of extraction temperature by compromising the experimental period and extraction efficiency. The analytical performances, such as linearity, method detection limits, relative standard deviation and recovery were examined, and these data exhibited broad linear range, high sensitivity and good precision. The proposed method was applied for real rice samples. The species of As(III), As(V) and DMA were detected in all the rice samples mostly in the order As(III)>As(V)>DMA. PMID:26988503
Optimization of multi-channel neutron focusing guides for extreme sample environments
NASA Astrophysics Data System (ADS)
Di Julio, D. D.; Lelièvre-Berna, E.; Courtois, P.; Andersen, K. H.; Bentley, P. M.
2014-07-01
In this work, we present and discuss simulation results for the design of multichannel neutron focusing guides for extreme sample environments. A single focusing guide consists of any number of supermirror-coated curved outer channels surrounding a central channel. Furthermore, a guide is separated into two sections in order to allow for extension into a sample environment. The performance of a guide is evaluated through a Monte-Carlo ray tracing simulation which is further coupled to an optimization algorithm in order to find the best possible guide for a given situation. A number of population-based algorithms have been investigated for this purpose. These include particle-swarm optimization, artificial bee colony, and differential evolution. The performance of each algorithm and preliminary results of the design of a multi-channel neutron focusing guide using these methods are described. We found that a three-channel focusing guide offered the best performance, with a gain factor of 2.4 compared to no focusing guide, for the design scenario investigated in this work.
Optimization of b-Value Sampling for Diffusion-Weighted Imaging of the Kidney
Zhang, Jeff L.; Sigmund, Eric E.; Rusinek, Henry; Chandarana, Hersh; Storey, Pippa; Chen, Qun; Lee, Vivian S.
2016-01-01
Diffusion-weighted imaging (DWI) involves data acquisitions at multiple b values. In this paper, we presented a method of selecting the b values that maximize estimation precision of the biexponential analysis of renal DWI data. We developed an error propagation factor for the biexponential model, and proposed to optimize the b-value samplings by minimizing the error propagation factor. A prospective study of four healthy human subjects (eight kidneys) was done to verify the feasibility of the proposed protocol and to assess the validity of predicted precision for DWI measures, followed by Monte Carlo simulations of DWI signals based on acquired data from renal lesions of 16 subjects. In healthy subjects, the proposed methods improved precision (P = 0.003) and accuracy (P < 0.001) significantly in region-of-interest based biexponential analysis. In Monte Carlo simulation of renal lesions, the b-sampling optimization lowered estimation error by at least 20–30% compared with uniformly distributed b values, and improved the differentiation between malignant and benign lesions significantly. In conclusion, the proposed method has the potential of maximizing the precision and accuracy of the biexponential analysis of renal DWI. PMID:21702062
Optimization of a pre-MEKC separation SPE procedure for steroid molecules in human urine samples.
Olędzka, Ilona; Kowalski, Piotr; Dziomba, Szymon; Szmudanowski, Piotr; Bączek, Tomasz
2013-01-01
Many steroid hormones can be considered as potential biomarkers and their determination in body fluids can create opportunities for the rapid diagnosis of many diseases and disorders of the human body. Most existing methods for the determination of steroids are usually time- and labor-consuming and quite costly. Therefore, the aim of analytical laboratories is to develop a new, relatively low-cost and rapid implementation methodology for their determination in biological samples. Due to the fact that there is little literature data on concentrations of steroid hormones in urine samples, we have made attempts at the electrophoretic determination of these compounds. For this purpose, an extraction procedure for the optimized separation and simultaneous determination of seven steroid hormones in urine samples has been investigated. The isolation of analytes from biological samples was performed by liquid-liquid extraction (LLE) with dichloromethane and compared to solid phase extraction (SPE) with C18 and hydrophilic-lipophilic balance (HLB) columns. To separate all the analytes a micellar electrokinetic capillary chromatography (MECK) technique was employed. For full separation of all the analytes a running buffer (pH 9.2), composed of 10 mM sodium tetraborate decahydrate (borax), 50 mM sodium dodecyl sulfate (SDS), and 10% methanol was selected. The methodology developed in this work for the determination of steroid hormones meets all the requirements of analytical methods. The applicability of the method has been confirmed for the analysis of urine samples collected from volunteers--both men and women (students, amateur bodybuilders, using and not applying steroid doping). The data obtained during this work can be successfully used for further research on the determination of steroid hormones in urine samples. PMID:24232737
Optimized measurement of radium-226 concentration in liquid samples with radon-222 emanation.
Perrier, Frédéric; Aupiais, Jean; Girault, Frédéric; Przylibski, Tadeusz A; Bouquerel, Hélène
2016-06-01
Measuring radium-226 concentration in liquid samples using radon-222 emanation remains competitive with techniques such as liquid scintillation, alpha or mass spectrometry. Indeed, we show that high-precision can be obtained without air circulation, using an optimal air to liquid volume ratio and moderate heating. Cost-effective and efficient measurement of radon concentration is achieved by scintillation flasks and sufficiently long counting times for signal and background. More than 400 such measurements were performed, including 39 dilution experiments, a successful blind measurement of six reference test solutions, and more than 110 repeated measurements. Under optimal conditions, uncertainties reach 5% for an activity concentration of 100 mBq L(-1) and 10% for 10 mBq L(-1). While the theoretical detection limit predicted by Monte Carlo simulation is around 3 mBq L(-1), a conservative experimental estimate is rather 5 mBq L(-1), corresponding to 0.14 fg g(-1). The method was applied to 47 natural waters, 51 commercial waters, and 17 wine samples, illustrating that it could be an option for liquids that cannot be easily measured by other methods. Counting of scintillation flasks can be done in remote locations in absence of electricity supply, using a solar panel. Thus, this portable method, which has demonstrated sufficient accuracy for numerous natural liquids, could be useful in geological and environmental problems, with the additional benefit that it can be applied in isolated locations and in circumstances when samples cannot be transported. PMID:26998570
Optimized measurement of radium-226 concentration in liquid samples with radon-222 emanation.
Perrier, Frédéric; Aupiais, Jean; Girault, Frédéric; Przylibski, Tadeusz A; Bouquerel, Hélène
2016-06-01
Measuring radium-226 concentration in liquid samples using radon-222 emanation remains competitive with techniques such as liquid scintillation, alpha or mass spectrometry. Indeed, we show that high-precision can be obtained without air circulation, using an optimal air to liquid volume ratio and moderate heating. Cost-effective and efficient measurement of radon concentration is achieved by scintillation flasks and sufficiently long counting times for signal and background. More than 400 such measurements were performed, including 39 dilution experiments, a successful blind measurement of six reference test solutions, and more than 110 repeated measurements. Under optimal conditions, uncertainties reach 5% for an activity concentration of 100 mBq L(-1) and 10% for 10 mBq L(-1). While the theoretical detection limit predicted by Monte Carlo simulation is around 3 mBq L(-1), a conservative experimental estimate is rather 5 mBq L(-1), corresponding to 0.14 fg g(-1). The method was applied to 47 natural waters, 51 commercial waters, and 17 wine samples, illustrating that it could be an option for liquids that cannot be easily measured by other methods. Counting of scintillation flasks can be done in remote locations in absence of electricity supply, using a solar panel. Thus, this portable method, which has demonstrated sufficient accuracy for numerous natural liquids, could be useful in geological and environmental problems, with the additional benefit that it can be applied in isolated locations and in circumstances when samples cannot be transported.
Optimizing Oriented Planar-Supported Lipid Samples for Solid-State Protein NMR
Rainey, Jan K.; Sykes, Brian D.
2005-01-01
Sample orientation relative to the static magnetic field of an NMR spectrometer allows study of membrane proteins in the lipid bilayer setting. The straightforward preparation and handling of extremely thin mica substrates with consistent surface properties has prompted us to examine oriented phospholipid bilayer and hexagonal phases on mica. The spectral characteristics of oriented lipid samples formed on mica are as good as or better than those on glass. Nine solvents with varying dielectric constants were used to cast lipid films or for vesicle spreading; film characteristics were then compared, and static solid-state 31P-NMR was used to characterize the degree of orientation of the hydrated lipid species. Lipids with four headgroup chemistries were tested: 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG), 1,2-dioleoyl-sn-glycero-3-phosphate (DOPA), and 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE). Solvent affected orientation of POPG, DOPA, and DOPE, but not POPC. Film characteristics varied with solvent, with ramifications for producing homogeneous oriented lipid samples. POPC was used to optimize the amount of lipid per substrate and compare hydration methods. POPG did not orient reproducibly, whereas POPG-POPC mixtures did. DOPA showed 1–2 oriented states depending upon hydration level and deposition method. DOPE formed an oriented hexagonal phase that underwent a reversible temperature-induced phase transition to the oriented bilayer phase. PMID:16085766
Sparse Recovery Optimization in Wireless Sensor Networks with a Sub-Nyquist Sampling Rate.
Brunelli, Davide; Caione, Carlo
2015-07-10
Compressive sensing (CS) is a new technology in digital signal processing capable of high-resolution capture of physical signals from few measurements, which promises impressive improvements in the field of wireless sensor networks (WSNs). In this work, we extensively investigate the effectiveness of compressive sensing (CS) when real COTSresource-constrained sensor nodes are used for compression, evaluating how the different parameters can affect the energy consumption and the lifetime of the device. Using data from a real dataset, we compare an implementation of CS using dense encoding matrices, where samples are gathered at a Nyquist rate, with the reconstruction of signals sampled at a sub-Nyquist rate. The quality of recovery is addressed, and several algorithms are used for reconstruction exploiting the intra- and inter-signal correlation structures. We finally define an optimal under-sampling ratio and reconstruction algorithm capable of achieving the best reconstruction at the minimum energy spent for the compression. The results are verified against a set of different kinds of sensors on several nodes used for environmental monitoring.
Sparse Recovery Optimization in Wireless Sensor Networks with a Sub-Nyquist Sampling Rate
Brunelli, Davide; Caione, Carlo
2015-01-01
Compressive sensing (CS) is a new technology in digital signal processing capable of high-resolution capture of physical signals from few measurements, which promises impressive improvements in the field of wireless sensor networks (WSNs). In this work, we extensively investigate the effectiveness of compressive sensing (CS) when real COTSresource-constrained sensor nodes are used for compression, evaluating how the different parameters can affect the energy consumption and the lifetime of the device. Using data from a real dataset, we compare an implementation of CS using dense encoding matrices, where samples are gathered at a Nyquist rate, with the reconstruction of signals sampled at a sub-Nyquist rate. The quality of recovery is addressed, and several algorithms are used for reconstruction exploiting the intra- and inter-signal correlation structures. We finally define an optimal under-sampling ratio and reconstruction algorithm capable of achieving the best reconstruction at the minimum energy spent for the compression. The results are verified against a set of different kinds of sensors on several nodes used for environmental monitoring. PMID:26184203
Severtson, Dustin; Flower, Ken; Nansen, Christian
2016-08-01
The cabbage aphid is a significant pest worldwide in brassica crops, including canola. This pest has shown considerable ability to develop resistance to insecticides, so these should only be applied on a "when and where needed" basis. Thus, optimized sampling plans to accurately assess cabbage aphid densities are critically important to determine the potential need for pesticide applications. In this study, we developed a spatially optimized binomial sequential sampling plan for cabbage aphids in canola fields. Based on five sampled canola fields, sampling plans were developed using 0.1, 0.2, and 0.3 proportions of plants infested as action thresholds. Average sample numbers required to make a decision ranged from 10 to 25 plants. Decreasing acceptable error from 10 to 5% was not considered practically feasible, as it substantially increased the number of samples required to reach a decision. We determined the relationship between the proportions of canola plants infested and cabbage aphid densities per plant, and proposed a spatially optimized sequential sampling plan for cabbage aphids in canola fields, in which spatial features (i.e., edge effects) and optimization of sampling effort (i.e., sequential sampling) are combined. Two forms of stratification were performed to reduce spatial variability caused by edge effects and large field sizes. Spatially optimized sampling, starting at the edge of fields, reduced spatial variability and therefore increased the accuracy of infested plant density estimates. The proposed spatially optimized sampling plan may be used to spatially target insecticide applications, resulting in cost savings, insecticide resistance mitigation, conservation of natural enemies, and reduced environmental impact.
Severtson, Dustin; Flower, Ken; Nansen, Christian
2016-08-01
The cabbage aphid is a significant pest worldwide in brassica crops, including canola. This pest has shown considerable ability to develop resistance to insecticides, so these should only be applied on a "when and where needed" basis. Thus, optimized sampling plans to accurately assess cabbage aphid densities are critically important to determine the potential need for pesticide applications. In this study, we developed a spatially optimized binomial sequential sampling plan for cabbage aphids in canola fields. Based on five sampled canola fields, sampling plans were developed using 0.1, 0.2, and 0.3 proportions of plants infested as action thresholds. Average sample numbers required to make a decision ranged from 10 to 25 plants. Decreasing acceptable error from 10 to 5% was not considered practically feasible, as it substantially increased the number of samples required to reach a decision. We determined the relationship between the proportions of canola plants infested and cabbage aphid densities per plant, and proposed a spatially optimized sequential sampling plan for cabbage aphids in canola fields, in which spatial features (i.e., edge effects) and optimization of sampling effort (i.e., sequential sampling) are combined. Two forms of stratification were performed to reduce spatial variability caused by edge effects and large field sizes. Spatially optimized sampling, starting at the edge of fields, reduced spatial variability and therefore increased the accuracy of infested plant density estimates. The proposed spatially optimized sampling plan may be used to spatially target insecticide applications, resulting in cost savings, insecticide resistance mitigation, conservation of natural enemies, and reduced environmental impact. PMID:27371709
Don't Fear Optimality: Sampling for Probabilistic-Logic Sequence Models
NASA Astrophysics Data System (ADS)
Thon, Ingo
One of the current challenges in artificial intelligence is modeling dynamic environments that change due to the actions or activities undertaken by people or agents. The task of inferring hidden states, e.g. the activities or intentions of people, based on observations is called filtering. Standard probabilistic models such as Dynamic Bayesian Networks are able to solve this task efficiently using approximative methods such as particle filters. However, these models do not support logical or relational representations. The key contribution of this paper is the upgrade of a particle filter algorithm for use with a probabilistic logical representation through the definition of a proposal distribution. The performance of the algorithm depends largely on how well this distribution fits the target distribution. We adopt the idea of logical compilation into Binary Decision Diagrams for sampling. This allows us to use the optimal proposal distribution which is normally prohibitively slow.
Optimizing Peirce-Smith Converters Using Thermodynamic Modeling and Plant Sampling
NASA Astrophysics Data System (ADS)
Cardona, N.; Mackey, P. J.; Coursol, P.; Parada, R.; Parra, R.
2012-05-01
The performance of pyrometallurgical slag cleaning furnaces at many primary copper smelters is dependent in part on the quality of the converter slag, commonly produced in the batch-wise Peirce Smith converter (PSC). In order to understand the impact of converter slag chemistry and at the same time help optimize the converter operation, thermodynamic modeling of molten slag (including any contained slag solid fractions) was carried out on slag produced at the Chagres smelter in Chile. Phase characterization studies on actual plant slag samples were also carried out. The results are provided in the present paper. This work is also considered as a case study example to illustrate the type of work that can be performed to fairly quickly diagnose the quality of converter slag and assess the overall condition of the converter operation.
A Procedure to Determine the Optimal Sensor Positions for Locating AE Sources in Rock Samples
NASA Astrophysics Data System (ADS)
Duca, S.; Occhiena, C.; Sambuelli, L.
2015-03-01
Within a research work aimed to better understand frost weathering mechanisms of rocks, laboratory tests have been designed to specifically assess a theoretical model of crack propagation due to ice segregation process in water-saturated and thermally microcracked cubic samples of Arolla gneiss. As the formation and growth of microcracks during freezing tests on rock material is accompanied by a sudden release of stored elastic energy, the propagation of elastic waves can be detected, at the laboratory scale, by acoustic emission (AE) sensors. The AE receiver array geometry is a sensitive factor influencing source location errors, for it can greatly amplify the effect of small measurement errors. Despite the large literature on the AE source location, little attention, to our knowledge, has been paid to the description of the experimental design phase. As a consequence, the criteria for sensor positioning are often not declared and not related to location accuracy. In the present paper, a tool for the identification of the optimal sensor position on a cubic shape rock specimen is presented. The optimal receiver configuration is chosen by studying the condition numbers of each of the kernel matrices, used for inverting the arrival time and finding the source location, and obtained for properly selected combinations between sensors and sources positions.
Clague, D; Weisgraber, T; Rockway, J; McBride, K
2006-02-12
The focus of research effort described here is to develop novel simulation tools to address design and optimization needs in the general class of problems that involve species and fluid (liquid and gas phases) transport through sieving media. This was primarily motivated by the heightened attention on Chem/Bio early detection systems, which among other needs, have a need for high efficiency filtration, collection and sample preparation systems. Hence, the said goal was to develop the computational analysis tools necessary to optimize these critical operations. This new capability is designed to characterize system efficiencies based on the details of the microstructure and environmental effects. To accomplish this, new lattice Boltzmann simulation capabilities where developed to include detailed microstructure descriptions, the relevant surface forces that mediate species capture and release, and temperature effects for both liquid and gas phase systems. While developing the capability, actual demonstration and model systems (and subsystems) of national and programmatic interest were targeted to demonstrate the capability. As a result, where possible, experimental verification of the computational capability was performed either directly using Digital Particle Image Velocimetry or published results.
NASA Technical Reports Server (NTRS)
Emmitt, G. D.; Seze, G.
1991-01-01
Simulated cloud/hole fields as well as Landsat imagery are used in a computer model to evaluate several proposed sampling patterns and shot management schemes for pulsed space-based Doppler lidars. Emphasis is placed on two proposed sampling strategies - one obtained from a conically scanned single telescope and the other from four fixed telescopes that are sequentially used by one laser. The question of whether there are any sampling patterns that maximize the number of resolution areas with vertical soundings to the PBL is addressed.
Fünfstück, Tillmann; Arandjelovic, Mimi; Morgan, David B.; Sanz, Crickette; Reed, Patricia; Olson, Sarah H.; Cameron, Ken; Ondzie, Alain; Peeters, Martine; Vigilant, Linda
2015-01-01
Populations of an organism living in marked geographical or evolutionary isolation from other populations of the same species are often termed subspecies and expected to show some degree of genetic distinctiveness. The common chimpanzee (Pan troglodytes) is currently described as four geographically delimited subspecies: the western (P. t. verus), the nigerian-cameroonian (P. t. ellioti), the central (P. t. troglodytes) and the eastern (P. t. schweinfurthii) chimpanzees. Although these taxa would be expected to be reciprocally monophyletic, studies have not always consistently resolved the central and eastern chimpanzee taxa. Most studies, however, used data from individuals of unknown or approximate geographic provenance. Thus, genetic data from samples of known origin may shed light on the evolutionary relationship of these subspecies. We generated microsatellite genotypes from noninvasively collected fecal samples of 185 central chimpanzees that were sampled across large parts of their range and analyzed them together with 283 published eastern chimpanzee genotypes from known localities. We observed a clear signal of isolation by distance across both subspecies. Further, we found that a large proportion of comparisons between groups taken from the same subspecies showed higher genetic differentiation than the least differentiated between-subspecies comparison. This proportion decreased substantially when we simulated a more clumped sampling scheme by including fewer groups. Our results support the general concept that the distribution of the sampled individuals can dramatically affect the inference of genetic population structure. With regard to chimpanzees, our results emphasize the close relationship of equatorial chimpanzees from central and eastern equatorial Africa and the difficult nature of subspecies definitions. PMID:25330245
Fünfstück, Tillmann; Arandjelovic, Mimi; Morgan, David B; Sanz, Crickette; Reed, Patricia; Olson, Sarah H; Cameron, Ken; Ondzie, Alain; Peeters, Martine; Vigilant, Linda
2015-02-01
Populations of an organism living in marked geographical or evolutionary isolation from other populations of the same species are often termed subspecies and expected to show some degree of genetic distinctiveness. The common chimpanzee (Pan troglodytes) is currently described as four geographically delimited subspecies: the western (P. t. verus), the nigerian-cameroonian (P. t. ellioti), the central (P. t. troglodytes) and the eastern (P. t. schweinfurthii) chimpanzees. Although these taxa would be expected to be reciprocally monophyletic, studies have not always consistently resolved the central and eastern chimpanzee taxa. Most studies, however, used data from individuals of unknown or approximate geographic provenance. Thus, genetic data from samples of known origin may shed light on the evolutionary relationship of these subspecies. We generated microsatellite genotypes from noninvasively collected fecal samples of 185 central chimpanzees that were sampled across large parts of their range and analyzed them together with 283 published eastern chimpanzee genotypes from known localities. We observed a clear signal of isolation by distance across both subspecies. Further, we found that a large proportion of comparisons between groups taken from the same subspecies showed higher genetic differentiation than the least differentiated between-subspecies comparison. This proportion decreased substantially when we simulated a more clumped sampling scheme by including fewer groups. Our results support the general concept that the distribution of the sampled individuals can dramatically affect the inference of genetic population structure. With regard to chimpanzees, our results emphasize the close relationship of equatorial chimpanzees from central and eastern equatorial Africa and the difficult nature of subspecies definitions.
Hong, R.M.; Chiu, H.K.
1999-11-01
Performance comparisons of a DIII-D neutral beam ion source operated with two different schemes of supplying neutral gas to the arc chamber were performed. Superior performance was achieved when gas was puffed into both the arc chamber and the neutralizer with the gas flows optimized as compared to supplying gas through the neutralizer alone. To form a neutral beam, ions extracted from the arc chamber and accelerated are passed through a neutralizing cell of gas. Neutral gas is commonly puffed into the neutralizing cell to supplement the residual neutral gas from the arc chamber to obtain maximum neutralization efficiency. However, maximizing neutralization efficiency does not necessarily provide the maximum available neutral beam power, since high levels of neutral gas can increase beam loss through collisions and cause larger beam divergence. Excessive gas diffused from the neutralizer into the accelerator region also increases the number of energetic particles (ions and secondary electrons from the accelerator grid surfaces) deposited on the accelerator grids, increasing the possibility of overheating. We have operated an ion source with a constant optimal gas flow directly into the arc chamber while gas flow into the neutralizer was varied. Neutral beam power available for injecting into plasmas was obtained based on the measured data of beam energy, beam current, beam transmission, beam divergence, and neutralization efficiency for various neutralizer gas flow rates. We will present the results of performance comparison with the two gas puffing schemes, and show steps of obtaining the maximum available beam power and determining the optimum neutralizer gas flow rate.
Whelan, Donna R.; Bell, Toby D. M.
2015-01-01
Single molecule localization microscopy (SMLM) techniques allow for sub-diffraction imaging with spatial resolutions better than 10 nm reported. Much has been discussed relating to different variations of SMLM and all-inclusive microscopes can now be purchased, removing the need for in-house software or hardware development. However, little discussion has occurred examining the reliability and quality of the images being produced, as well as the potential for overlooked preparative artifacts. As a result of the up to an order-of-magnitude improvement in spatial resolution, substantially more detail is observed, including changes in distribution and ultrastructure caused by the many steps required to fix, permeabilize, and stain a sample. Here we systematically investigate many of these steps including different fixatives, fixative concentration, permeabilization concentration and timing, antibody concentration, and buffering. We present three well-optimized fixation protocols for staining microtubules, mitochondria and actin in a mammalian cell line and then discuss various artifacts in relation to images obtained from samples prepared using the protocols. The potential for such errors to go undetected in SMLM images and the complications in defining a ‘good’ image using previous parameters applied to confocal microscopy are also discussed. PMID:25603780
A simple optimized microwave digestion method for multielement monitoring in mussel samples
NASA Astrophysics Data System (ADS)
Saavedra, Y.; González, A.; Fernández, P.; Blanco, J.
2004-04-01
With the aim of obtaining a set of common decomposition conditions allowing the determination of several metals in mussel tissue (Hg by cold vapour atomic absorption spectrometry; Cu and Zn by flame atomic absorption spectrometry; and Cd, PbCr, Ni, As and Ag by electrothermal atomic absorption spectrometry), a factorial experiment was carried out using as factors the sample weight, digestion time and acid addition. It was found that the optimal conditions were 0.5 g of freeze-dried and triturated samples with 6 ml of nitric acid and subjected to microwave heating for 20 min at 180 psi. This pre-treatment, using only one step and one oxidative reagent, was suitable to determine the nine metals studied with no subsequent handling of the digest. It was possible to carry out the determination of atomic absorption using calibrations with aqueous standards and matrix modifiers for cadmium, lead, chromium, arsenic and silver. The accuracy of the procedure was checked using oyster tissue (SRM 1566b) and mussel tissue (CRM 278R) certified reference materials. The method is now used routinely to monitor these metals in wild and cultivated mussels, and found to be good.
Whelan, Donna R; Bell, Toby D M
2015-01-21
Single molecule localization microscopy (SMLM) techniques allow for sub-diffraction imaging with spatial resolutions better than 10 nm reported. Much has been discussed relating to different variations of SMLM and all-inclusive microscopes can now be purchased, removing the need for in-house software or hardware development. However, little discussion has occurred examining the reliability and quality of the images being produced, as well as the potential for overlooked preparative artifacts. As a result of the up to an order-of-magnitude improvement in spatial resolution, substantially more detail is observed, including changes in distribution and ultrastructure caused by the many steps required to fix, permeabilize, and stain a sample. Here we systematically investigate many of these steps including different fixatives, fixative concentration, permeabilization concentration and timing, antibody concentration, and buffering. We present three well-optimized fixation protocols for staining microtubules, mitochondria and actin in a mammalian cell line and then discuss various artifacts in relation to images obtained from samples prepared using the protocols. The potential for such errors to go undetected in SMLM images and the complications in defining a 'good' image using previous parameters applied to confocal microscopy are also discussed.
NASA Astrophysics Data System (ADS)
Mindrup, Frank M.; Friend, Mark A.; Bauer, Kenneth W.
2012-01-01
There are numerous anomaly detection algorithms proposed for hyperspectral imagery. Robust parameter design (RPD) techniques provide an avenue to select robust settings capable of operating consistently across a large variety of image scenes. Many researchers in this area are faced with a paucity of data. Unfortunately, there are no data splitting methods for model validation of datasets with small sample sizes. Typically, training and test sets of hyperspectral images are chosen randomly. Previous research has developed a framework for optimizing anomaly detection in HSI by considering specific image characteristics as noise variables within the context of RPD; these characteristics include the Fisher's score, ratio of target pixels and number of clusters. We have developed method for selecting hyperspectral image training and test subsets that yields consistent RPD results based on these noise features. These subsets are not necessarily orthogonal, but still provide improvements over random training and test subset assignments by maximizing the volume and average distance between image noise characteristics. The small sample training and test selection method is contrasted with randomly selected training sets as well as training sets chosen from the CADEX and DUPLEX algorithms for the well known Reed-Xiaoli anomaly detector.
NASA Technical Reports Server (NTRS)
Leyland, Jane Anne
2001-01-01
A closed-loop optimal neural-network controller technique was developed to optimize rotorcraft aeromechanical behaviour. This technique utilities a neural-network scheme to provide a general non-linear model of the rotorcraft. A modem constrained optimisation method is used to determine and update the constants in the neural-network plant model as well as to determine the optimal control vector. Current data is read, weighted, and added to a sliding data window. When the specified maximum number of data sets allowed in the data window is exceeded, the oldest data set is and the remaining data sets are re-weighted. This procedure provides at least four additional degrees-of-freedom in addition to the size and geometry of the neural-network itself with which to optimize the overall operation of the controller. These additional degrees-of-freedom are: 1. the maximum length of the sliding data window, 2. the frequency of neural-network updates, 3. the weighting of the individual data sets within the sliding window, and 4. the maximum number of optimisation iterations used for the neural-network updates.
Gostic, T; Klemenc, S; Stefane, B
2009-05-30
The pyrolysis behaviour of pure cocaine base as well as the influence of various additives was studied using conditions that are relevant to the smoking of illicit cocaine by humans. For this purpose an aerobic pyrolysis device was developed and the experimental conditions were optimized. In the first part of our study the optimization of some basic experimental parameters of the pyrolysis was performed, i.e., the furnace temperature, the sampling start time, the heating period, the sampling time, and the air-flow rate through the system. The second part of the investigation focused on the volatile products formed during the pyrolysis of a pure cocaine free base and mixtures of cocaine base and adulterants. The anaesthetics lidocaine, benzocaine, procaine, the analgesics phenacetine and paracetamol, and the stimulant caffeine were used as the adulterants. Under the applied experimental conditions complete volatilization of the samples was achieved, i.e., the residuals of the studied compounds were not detected in the pyrolysis cell. Volatilization of the pure cocaine base showed that the cocaine recovery available for inhalation (adsorbed on traps) was approximately 76%. GC-MS and NMR analyses of the smoke condensate revealed the presence of some additional cocaine pyrolytic products, such as anhydroecgonine methyl ester (AEME), benzoic acid (BA) and carbomethoxycycloheptatrienes (CMCHTs). Experiments with different cocaine-adulterant mixtures showed that the addition of the adulterants changed the thermal behaviour of the cocaine. The most significant of these was the effect of paracetamol. The total recovery of the cocaine (adsorbed on traps and in a glass tube) from the 1:1 cocaine-paracetamol mixture was found to be only 3.0+/-0.8%, versus 81.4+/-2.9% for the pure cocaine base. The other adulterants showed less-extensive effects on the recovery of cocaine, but the pyrolysis of the cocaine-procaine mixture led to the formation of some unique pyrolytic products
Kim, Hojin; Li Ruijiang; Lee, Rena; Goldstein, Thomas; Boyd, Stephen; Candes, Emmanuel; Xing Lei
2012-07-15
Purpose: A new treatment scheme coined as dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT) has recently been proposed to bridge the gap between IMRT and VMAT. By increasing the angular sampling of radiation beams while eliminating dispensable segments of the incident fields, DASSIM-RT is capable of providing improved conformity in dose distributions while maintaining high delivery efficiency. The fact that DASSIM-RT utilizes a large number of incident beams represents a major computational challenge for the clinical applications of this powerful treatment scheme. The purpose of this work is to provide a practical solution to the DASSIM-RT inverse planning problem. Methods: The inverse planning problem is formulated as a fluence-map optimization problem with total-variation (TV) minimization. A newly released L1-solver, template for first-order conic solver (TFOCS), was adopted in this work. TFOCS achieves faster convergence with less memory usage as compared with conventional quadratic programming (QP) for the TV form through the effective use of conic forms, dual-variable updates, and optimal first-order approaches. As such, it is tailored to specifically address the computational challenges of large-scale optimization in DASSIM-RT inverse planning. Two clinical cases (a prostate and a head and neck case) are used to evaluate the effectiveness and efficiency of the proposed planning technique. DASSIM-RT plans with 15 and 30 beams are compared with conventional IMRT plans with 7 beams in terms of plan quality and delivery efficiency, which are quantified by conformation number (CN), the total number of segments and modulation index, respectively. For optimization efficiency, the QP-based approach was compared with the proposed algorithm for the DASSIM-RT plans with 15 beams for both cases. Results: Plan quality improves with an increasing number of incident beams, while the total number of segments is maintained to be about the
Ncube, Somandla; Poliwoda, Anna; Tutu, Hlanganani; Wieczorek, Piotr; Chimuka, Luke
2016-10-15
A liquid phase microextraction based on hollow fibre followed by liquid chromatographic determination was developed for the extraction and quantitation of the hallucinogenic muscimol from urine samples. Method applicability on polar hallucinogens was also tested on two alkaloids, a psychedelic hallucinogen, tryptamine and a polar amino acid, tryptophan which exists in its charged state in the entire pH range. A multivariate design of experiments was used in which a half fractional factorial approach was applied to screen six factors (donor phase pH, acceptor phase HCl concentration, carrier composition, stirring rate, extraction time and salt content) for their extent of vitality in carrier mediated liquid microextractions. Four factors were deemed essential for the effective extraction of each analyte. The vital factors were further optimized for the extraction of single-spiked analyte solutions using a central composite design. When the simultaneous extraction of analytes was performed under universal factor conditions biased towards maximizing the enrichment of muscimol, a good composite desirability value of 0.687 was obtained. The method was finally applied on spiked urine samples with acceptable enrichments of 4.1, 19.7 and 24.1 obtained for muscimol, tryptophan and tryptamine respectively. Matrix-based calibration curves were used to address matrix effects. The r(2) values of the matrix-based linear regression prediction models ranged from 0.9933 to 0.9986. The linearity of the regression line of the matrix-based calibration curves for each analyte was directly linked to the analyte enrichment repeatability which ranged from an RSD value of 8.3-13.1%. Limits of detection for the developed method were 5.12, 3.10 and 0.21ngmL(-1) for muscimol, tryptophan and tryptamine respectively. The developed method has proven to offer a viable alternative for the quantitation of muscimol in human urine samples.
Optimizing stream water mercury sampling for calculation of fish bioaccumulation factors
Riva-Murray, Karen; Bradley, Paul M.; Journey, Celeste A.; Brigham, Mark E.; Scudder Eikenberry, Barbara C.; Knightes, Christopher; Button, Daniel T.
2013-01-01
Mercury (Hg) bioaccumulation factors (BAFs) for game fishes are widely employed for monitoring, assessment, and regulatory purposes. Mercury BAFs are calculated as the fish Hg concentration (Hgfish) divided by the water Hg concentration (Hgwater) and, consequently, are sensitive to sampling and analysis artifacts for fish and water. We evaluated the influence of water sample timing, filtration, and mercury species on the modeled relation between game fish and water mercury concentrations across 11 streams and rivers in five states in order to identify optimum Hgwater sampling approaches. Each model included fish trophic position, to account for a wide range of species collected among sites, and flow-weighted Hgwater estimates. Models were evaluated for parsimony, using Akaike’s Information Criterion. Better models included filtered water methylmercury (FMeHg) or unfiltered water methylmercury (UMeHg), whereas filtered total mercury did not meet parsimony requirements. Models including mean annual FMeHg were superior to those with mean FMeHg calculated over shorter time periods throughout the year. FMeHg models including metrics of high concentrations (80th percentile and above) observed during the year performed better, in general. These higher concentrations occurred most often during the growing season at all sites. Streamflow was significantly related to the probability of achieving higher concentrations during the growing season at six sites, but the direction of influence varied among sites. These findings indicate that streamwater Hg collection can be optimized by evaluating site-specific FMeHg - UMeHg relations, intra-annual temporal variation in their concentrations, and streamflow-Hg dynamics.
Nie Xiaobo; Liang Jian; Yan Di
2012-12-15
Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h
NASA Astrophysics Data System (ADS)
Oh, Eunsong; Kim, Sug-Whan; Cho, Seongick; Ryu, Joo-Hyung
2011-10-01
In our earlier study[12], we suggested a new alignment algorithm called Multiple Design Configuration Optimization (MDCO hereafter) method combining the merit function regression (MFR) computation with the differential wavefront sampling method (DWS). In this study, we report alignment state estimation performances of the method for three target optical systems (i.e. i) a two-mirror Cassegrain telescope of 58mm in diameter for deep space earth observation, ii) a three-mirror anastigmat of 210mm in aperture for ocean monitoring from the geostationary orbit, and iii) on-axis/off-axis pairs of a extremely large telescope of 27.4m in aperture). First we introduced known amounts of alignment state disturbances to the target optical system elements. Example alignment parameter ranges may include, but not limited to, from 800microns to 10mm in decenter, and from 0.1 to 1.0 degree in tilt. We then ran alignment state estimation simulation using MDCO, MFR and DWS. The simulation results show that MDCO yields much better estimation performance than MFR and DWS over the alignment disturbance level of up to 150 times larger than the required tolerances. In particular, with its simple single field measurement, MDCO exhibits greater practicality and application potentials for shop floor optical testing environment than MFR and DWS.
Huang, Bao-Tian; Lu, Jia-Yang; Lin, Pei-Xian; Chen, Jian-Zhou; Li, De-Rui; Chen, Chuang-Zhen
2015-01-01
This study aimed to determine the optimal fraction scheme (FS) in patients with small peripheral non-small cell lung cancer (NSCLC) undergoing stereotactic body radiotherapy (SBRT) with the 4 × 12 Gy scheme as the reference. CT simulation data for sixteen patients diagnosed with primary NSCLC or metastatic tumor with a single peripheral lesion ≤3 cm were used in this study. Volumetric modulated arc therapy (VMAT) plans were designed based on ten different FS of 1 × 25 Gy, 1 × 30 Gy, 1 × 34 Gy, 3 × 15 Gy, 3 × 18 Gy, 3 × 20 Gy, 4 × 12 Gy, 5 × 12 Gy, 6 × 10 Gy and 10 × 7 Gy. Five different radiobiological models were employed to predict the tumor control probability (TCP) value. Three other models were utilized to estimate the normal tissue complication probability (NTCP) value to the lung and the modified equivalent uniform dose (mEUD) value to the chest wall (CW). The 1 × 30 Gy regimen is recommended to achieve 4.2% higher TCP and slightly higher NTCP and mEUD values to the lung and CW compared with the 4 × 12 Gy schedule, respectively. This regimen also greatly shortens the treatment duration. However, the 3 × 15 Gy schedule is suggested in patients where the lung-to-tumor volume ratio is small or where the tumor is adjacent to the CW. PMID:26657569
NASA Astrophysics Data System (ADS)
Leube, Philipp; Geiges, Andreas; Nowak, Wolfgang
2010-05-01
Incorporating hydrogeological data, such as head and tracer data, into stochastic models of subsurface flow and transport helps to reduce prediction uncertainty. Considering limited financial resources available for the data acquisition campaign, information needs towards the prediction goal should be satisfied in a efficient and task-specific manner. For finding the best one among a set of design candidates, an objective function is commonly evaluated, which measures the expected impact of data on prediction confidence, prior to their collection. An appropriate approach to this task should be stochastically rigorous, master non-linear dependencies between data, parameters and model predictions, and allow for a wide variety of different data types. Existing methods fail to fulfill all these requirements simultaneously. For this reason, we introduce a new method, denoted as CLUE (Cross-bred Likelihood Uncertainty Estimator), that derives the essential distributions and measures of data utility within a generalized, flexible and accurate framework. The method makes use of Bayesian GLUE (Generalized Likelihood Uncertainty Estimator) and extends it to an optimal design method by marginalizing over the yet unknown data values. Operating in a purely Bayesian Monte-Carlo framework, CLUE is a strictly formal information processing scheme free of linearizations. It provides full flexibility associated with the type of measurements (linear, non-linear, direct, indirect) and accounts for almost arbitrary sources of uncertainty (e.g. heterogeneity, geostatistical assumptions, boundary conditions, model concepts) via stochastic simulation and Bayesian model averaging. This helps to minimize the strength and impact of possible subjective prior assumptions, that would be hard to defend prior to data collection. Our study focuses on evaluating two different uncertainty measures: (i) expected conditional variance and (ii) expected relative entropy of a given prediction goal. The
Pietrzyńska, Monika; Voelkel, Adam
2014-11-01
In-needle extraction was applied for preparation of aqueous samples. This technique was used for direct isolation of analytes from liquid samples which was achieved by forcing the flow of the sample through the sorbent layer: silica or polymer (styrene/divinylbenzene). Specially designed needle was packed with three different sorbents on which the analytes (phenol, p-benzoquinone, 4-chlorophenol, thymol and caffeine) were retained. Acceptable sampling conditions for direct analysis of liquid sample were selected. Experimental data collected from the series of liquid samples analysis made with use of in-needle device showed that the effectiveness of the system depends on various parameters such as breakthrough volume and the sorption capacity, effect of sampling flow rate, solvent effect on elution step, required volume of solvent for elution step. The optimal sampling flow rate was in range of 0.5-2 mL/min, the minimum volume of solvent was at 400 µL level. PMID:25127610
Tan, Maxine; Pu, Jiantao; Zheng, Bin
2014-01-01
In the field of computer-aided mammographic mass detection, many different features and classifiers have been tested. Frequently, the relevant features and optimal topology for the artificial neural network (ANN)-based approaches at the classification stage are unknown, and thus determined by trial-and-error experiments. In this study, we analyzed a classifier that evolves ANNs using genetic algorithms (GAs), which combines feature selection with the learning task. The classifier named “Phased Searching with NEAT in a Time-Scaled Framework” was analyzed using a dataset with 800 malignant and 800 normal tissue regions in a 10-fold cross-validation framework. The classification performance measured by the area under a receiver operating characteristic (ROC) curve was 0.856 ± 0.029. The result was also compared with four other well-established classifiers that include fixed-topology ANNs, support vector machines (SVMs), linear discriminant analysis (LDA), and bagged decision trees. The results show that Phased Searching outperformed the LDA and bagged decision tree classifiers, and was only significantly outperformed by SVM. Furthermore, the Phased Searching method required fewer features and discarded superfluous structure or topology, thus incurring a lower feature computational and training and validation time requirement. Analyses performed on the network complexities evolved by Phased Searching indicate that it can evolve optimal network topologies based on its complexification and simplification parameter selection process. From the results, the study also concluded that the three classifiers – SVM, fixed-topology ANN, and Phased Searching with NeuroEvolution of Augmenting Topologies (NEAT) in a Time-Scaled Framework – are performing comparably well in our mammographic mass detection scheme. PMID:25392680
Yilmaz, Banu Coskun; Yilmaz, Cengiz; Yilmaz, Necat S; Balli, Ebru; Tasdelen, Bahar
2010-01-01
For autologous chondrocyte implantation, the chondral tissue obtained is transferred from the operating room to the laboratory using specialized carrier systems within 24 hours. Similar expenses are used for the transport of cultured chondrocytes. The purpose of this study was to find the optimal temperature, size of tissue, and time that the chondrocytes can stand without losing viability and proliferative capacity. Fresh calf cartilage was harvested and divided into 24 groups. Half of the samples were diced into 1- to 2-mm(3) pieces. All 12 groups were kept at either 4 degrees C, 25 degrees C, or 37 degrees C for 1, 3, 5, or 7 days and were seeded for cell culture. Times to reach confluence values were compared. Produced cell suspensions were grouped similarly and tested similarly. Neither the temperature nor the waiting days caused any difference in the proliferative capacity of the cells. Diced tissues yielded a shorter time to reach confluence values. Chondral tissue obtained from the patient can be transferred to the laboratory at temperatures ranging from 4 degrees C to 37 degrees C in up to 7 days. These conditions did not affect the proliferative capacity or the viability of the chondrocytes. Dicing the tissue prior to transport will shorten total culturing time. The expanded cell suspensions should be transferred at temperatures from 4 degrees C to 25 degrees C within 3 days. Specialized carrier systems to get the chondral tissue from the operating room to the laboratory and to take the expanded chondrocytes back to the operating room within hours may not be necessary.
Lundin, Jessica I; Dills, Russell L; Ylitalo, Gina M; Hanson, M Bradley; Emmons, Candice K; Schorr, Gregory S; Ahmad, Jacqui; Hempelmann, Jennifer A; Parsons, Kim M; Wasser, Samuel K
2016-01-01
Biologic sample collection in wild cetacean populations is challenging. Most information on toxicant levels is obtained from blubber biopsy samples; however, sample collection is invasive and strictly regulated under permit, thus limiting sample numbers. Methods are needed to monitor toxicant levels that increase temporal and repeat sampling of individuals for population health and recovery models. The objective of this study was to optimize measuring trace levels (parts per billion) of persistent organic pollutants (POPs), namely polychlorinated-biphenyls (PCBs), polybrominated-diphenyl-ethers (PBDEs), dichlorodiphenyltrichloroethanes (DDTs), and hexachlorocyclobenzene, in killer whale scat (fecal) samples. Archival scat samples, initially collected, lyophilized, and extracted with 70 % ethanol for hormone analyses, were used to analyze POP concentrations. The residual pellet was extracted and analyzed using gas chromatography coupled with mass spectrometry. Method detection limits ranged from 11 to 125 ng/g dry weight. The described method is suitable for p,p'-DDE, PCBs-138, 153, 180, and 187, and PBDEs-47 and 100; other POPs were below the limit of detection. We applied this method to 126 scat samples collected from Southern Resident killer whales. Scat samples from 22 adult whales also had known POP concentrations in blubber and demonstrated significant correlations (p < 0.01) between matrices across target analytes. Overall, the scat toxicant measures matched previously reported patterns from blubber samples of decreased levels in reproductive-age females and a decreased p,p'-DDE/∑PCB ratio in J-pod. Measuring toxicants in scat samples provides an unprecedented opportunity to noninvasively evaluate contaminant levels in wild cetacean populations; these data have the prospect to provide meaningful information for vital management decisions. PMID:26298464
Lundin, Jessica I; Dills, Russell L; Ylitalo, Gina M; Hanson, M Bradley; Emmons, Candice K; Schorr, Gregory S; Ahmad, Jacqui; Hempelmann, Jennifer A; Parsons, Kim M; Wasser, Samuel K
2016-01-01
Biologic sample collection in wild cetacean populations is challenging. Most information on toxicant levels is obtained from blubber biopsy samples; however, sample collection is invasive and strictly regulated under permit, thus limiting sample numbers. Methods are needed to monitor toxicant levels that increase temporal and repeat sampling of individuals for population health and recovery models. The objective of this study was to optimize measuring trace levels (parts per billion) of persistent organic pollutants (POPs), namely polychlorinated-biphenyls (PCBs), polybrominated-diphenyl-ethers (PBDEs), dichlorodiphenyltrichloroethanes (DDTs), and hexachlorocyclobenzene, in killer whale scat (fecal) samples. Archival scat samples, initially collected, lyophilized, and extracted with 70 % ethanol for hormone analyses, were used to analyze POP concentrations. The residual pellet was extracted and analyzed using gas chromatography coupled with mass spectrometry. Method detection limits ranged from 11 to 125 ng/g dry weight. The described method is suitable for p,p'-DDE, PCBs-138, 153, 180, and 187, and PBDEs-47 and 100; other POPs were below the limit of detection. We applied this method to 126 scat samples collected from Southern Resident killer whales. Scat samples from 22 adult whales also had known POP concentrations in blubber and demonstrated significant correlations (p < 0.01) between matrices across target analytes. Overall, the scat toxicant measures matched previously reported patterns from blubber samples of decreased levels in reproductive-age females and a decreased p,p'-DDE/∑PCB ratio in J-pod. Measuring toxicants in scat samples provides an unprecedented opportunity to noninvasively evaluate contaminant levels in wild cetacean populations; these data have the prospect to provide meaningful information for vital management decisions.
Interplanetary program to optimize simulated trajectories (IPOST). Volume 4: Sample cases
NASA Technical Reports Server (NTRS)
Hong, P. E.; Kent, P. D; Olson, D. W.; Vallado, C. A.
1992-01-01
The Interplanetary Program to Optimize Simulated Trajectories (IPOST) is intended to support many analysis phases, from early interplanetary feasibility studies through spacecraft development and operations. The IPOST output provides information for sizing and understanding mission impacts related to propulsion, guidance, communications, sensor/actuators, payload, and other dynamic and geometric environments. IPOST models three degree of freedom trajectory events, such as launch/ascent, orbital coast, propulsive maneuvering (impulsive and finite burn), gravity assist, and atmospheric entry. Trajectory propagation is performed using a choice of Cowell, Encke, Multiconic, Onestep, or Conic methods. The user identifies a desired sequence of trajectory events, and selects which parameters are independent (controls) and dependent (targets), as well as other constraints and the cost function. Targeting and optimization are performed using the Standard NPSOL algorithm. The IPOST structure allows sub-problems within a master optimization problem to aid in the general constrained parameter optimization solution. An alternate optimization method uses implicit simulation and collocation techniques.
Parametric optimization of selective laser melting for forming Ti6Al4V samples by Taguchi method
NASA Astrophysics Data System (ADS)
Sun, Jianfeng; Yang, Yongqiang; Wang, Di
2013-07-01
In this study, a selective laser melting experiment was carried out with Ti6Al4V alloy powders. To produce samples with maximum density, selective laser melting parameters of laser power, scanning speed, powder thickness, hatching space and scanning strategy were carefully selected. As a statistical design of experimental technique, the Taguchi method was used to optimize the selected parameters. The results were analyzed using analyses of variance (ANOVA) and the signal-to-noise (S/N) ratios by design-expert software for the optimal parameters, and a regression model was established. The regression equation revealed a linear relationship among the density, laser power, scanning speed, powder thickness and scanning strategy. From the experiments, sample with density higher than 95% was obtained. The microstructure of obtained sample was mainly composed of acicular martensite, α phase and β phase. The micro-hardness was 492 HV0.2.
Chaudhary, Neha; Tøndel, Kristin; Bhatnagar, Rakesh; dos Santos, Vítor A P Martins; Puchałka, Jacek
2016-03-01
Genome-Scale Metabolic Reconstructions (GSMRs), along with optimization-based methods, predominantly Flux Balance Analysis (FBA) and its derivatives, are widely applied for assessing and predicting the behavior of metabolic networks upon perturbation, thereby enabling identification of potential novel drug targets and biotechnologically relevant pathways. The abundance of alternate flux profiles has led to the evolution of methods to explore the complete solution space aiming to increase the accuracy of predictions. Herein we present a novel, generic algorithm to characterize the entire flux space of GSMR upon application of FBA, leading to the optimal value of the objective (the optimal flux space). Our method employs Modified Latin-Hypercube Sampling (LHS) to effectively border the optimal space, followed by Principal Component Analysis (PCA) to identify and explain the major sources of variability within it. The approach was validated with the elementary mode analysis of a smaller network of Saccharomyces cerevisiae and applied to the GSMR of Pseudomonas aeruginosa PAO1 (iMO1086). It is shown to surpass the commonly used Monte Carlo Sampling (MCS) in providing a more uniform coverage for a much larger network in less number of samples. Results show that although many fluxes are identified as variable upon fixing the objective value, majority of the variability can be reduced to several main patterns arising from a few alternative pathways. In iMO1086, initial variability of 211 reactions could almost entirely be explained by 7 alternative pathway groups. These findings imply that the possibilities to reroute greater portions of flux may be limited within metabolic networks of bacteria. Furthermore, the optimal flux space is subject to change with environmental conditions. Our method may be a useful device to validate the predictions made by FBA-based tools, by describing the optimal flux space associated with these predictions, thus to improve them.
Chaudhary, Neha; Tøndel, Kristin; Bhatnagar, Rakesh; dos Santos, Vítor A P Martins; Puchałka, Jacek
2016-03-01
Genome-Scale Metabolic Reconstructions (GSMRs), along with optimization-based methods, predominantly Flux Balance Analysis (FBA) and its derivatives, are widely applied for assessing and predicting the behavior of metabolic networks upon perturbation, thereby enabling identification of potential novel drug targets and biotechnologically relevant pathways. The abundance of alternate flux profiles has led to the evolution of methods to explore the complete solution space aiming to increase the accuracy of predictions. Herein we present a novel, generic algorithm to characterize the entire flux space of GSMR upon application of FBA, leading to the optimal value of the objective (the optimal flux space). Our method employs Modified Latin-Hypercube Sampling (LHS) to effectively border the optimal space, followed by Principal Component Analysis (PCA) to identify and explain the major sources of variability within it. The approach was validated with the elementary mode analysis of a smaller network of Saccharomyces cerevisiae and applied to the GSMR of Pseudomonas aeruginosa PAO1 (iMO1086). It is shown to surpass the commonly used Monte Carlo Sampling (MCS) in providing a more uniform coverage for a much larger network in less number of samples. Results show that although many fluxes are identified as variable upon fixing the objective value, majority of the variability can be reduced to several main patterns arising from a few alternative pathways. In iMO1086, initial variability of 211 reactions could almost entirely be explained by 7 alternative pathway groups. These findings imply that the possibilities to reroute greater portions of flux may be limited within metabolic networks of bacteria. Furthermore, the optimal flux space is subject to change with environmental conditions. Our method may be a useful device to validate the predictions made by FBA-based tools, by describing the optimal flux space associated with these predictions, thus to improve them. PMID
Sampling is the act of selecting items from a specified population in order to estimate the parameters of that population (e.g., selecting soil samples to characterize the properties at an environmental site). Sampling occurs at various levels and times throughout an environmenta...
Harju, Kirsi; Rapinoja, Marja-Leena; Avondet, Marc-André; Arnold, Werner; Schär, Martin; Burrell, Stephen; Luginbühl, Werner; Vanninen, Paula
2015-11-25
Saxitoxin (STX) and some selected paralytic shellfish poisoning (PSP) analogues in mussel samples were identified and quantified with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Sample extraction and purification methods of mussel sample were optimized for LC-MS/MS analysis. The developed method was applied to the analysis of the homogenized mussel samples in the proficiency test (PT) within the EQuATox project (Establishment of Quality Assurance for the Detection of Biological Toxins of Potential Bioterrorism Risk). Ten laboratories from eight countries participated in the STX PT. Identification of PSP toxins in naturally contaminated mussel samples was performed by comparison of product ion spectra and retention times with those of reference standards. The quantitative results were obtained with LC-MS/MS by spiking reference standards in toxic mussel extracts. The results were within the z-score of ±1 when compared to the results measured with the official AOAC (Association of Official Analytical Chemists) method 2005.06, pre-column oxidation high-performance liquid chromatography with fluorescence detection (HPLC-FLD).
NASA Astrophysics Data System (ADS)
Martin, Peter R.; Cool, Derek W.; Romagnoli, Cesare; Fenster, Aaron; Ward, Aaron D.
2015-03-01
Magnetic resonance imaging (MRI)-targeted, 3D transrectal ultrasound (TRUS)-guided "fusion" prostate biopsy aims to reduce the 21-47% false negative rate of clinical 2D TRUS-guided sextant biopsy. Although it has been reported to double the positive yield, MRI-targeted biopsy still has a substantial false negative rate. Therefore, we propose optimization of biopsy targeting to meet the clinician's desired tumor sampling probability, optimizing needle targets within each tumor and accounting for uncertainties due to guidance system errors, image registration errors, and irregular tumor shapes. As a step toward this optimization, we obtained multiparametric MRI (mpMRI) and 3D TRUS images from 49 patients. A radiologist and radiology resident contoured 81 suspicious regions, yielding 3D surfaces that were registered to 3D TRUS. We estimated the probability, P, of obtaining a tumor sample with a single biopsy, and investigated the effects of systematic errors and anisotropy on P. Our experiments indicated that a biopsy system's lateral and elevational errors have a much greater effect on sampling probabilities, relative to its axial error. We have also determined that for a system with RMS error of 3.5 mm, tumors of volume 1.9 cm3 and smaller may require more than one biopsy core to ensure 95% probability of a sample with 50% core involvement, and tumors 1.0 cm3 and smaller may require more than two cores.
Pooler, P.S.; Smith, D.R.
2005-01-01
We compared the ability of simple random sampling (SRS) and a variety of systematic sampling (SYS) designs to estimate abundance, quantify spatial clustering, and predict spatial distribution of freshwater mussels. Sampling simulations were conducted using data obtained from a census of freshwater mussels in a 40 X 33 m section of the Cacapon River near Capon Bridge, West Virginia, and from a simulated spatially random population generated to have the same abundance as the real population. Sampling units that were 0.25 m 2 gave more accurate and precise abundance estimates and generally better spatial predictions than 1-m2 sampling units. Systematic sampling with ???2 random starts was more efficient than SRS. Estimates of abundance based on SYS were more accurate when the distance between sampling units across the stream was less than or equal to the distance between sampling units along the stream. Three measures for quantifying spatial clustering were examined: Hopkins Statistic, the Clumping Index, and Morisita's Index. Morisita's Index was the most reliable, and the Hopkins Statistic was prone to false rejection of complete spatial randomness. SYS designs with units spaced equally across and up stream provided the most accurate predictions when estimating the spatial distribution by kriging. Our research indicates that SYS designs with sampling units equally spaced both across and along the stream would be appropriate for sampling freshwater mussels even if no information about the true underlying spatial distribution of the population were available to guide the design choice. ?? 2005 by The North American Benthological Society.
Weber, Scott; Puskar, Kathryn Rose; Ren, Dianxu
2010-09-01
Stress, developmental changes and social adjustment problems can be significant in rural teens. Screening for psychosocial problems by teachers and other school personnel is infrequent but can be a useful health promotion strategy. We used a cross-sectional survey descriptive design to examine the inter-relationships between depressive symptoms and perceived social support, self-esteem, and optimism in a sample of rural school-based adolescents. Depressive symptoms were negatively correlated with peer social support, family social support, self-esteem, and optimism. Findings underscore the importance for teachers and other school staff to provide health education. Results can be used as the basis for education to improve optimism, self-esteem, social supports and, thus, depression symptoms of teens.
Peevor, R; Jones, J; Fiander, A N; Hibbitts, S
2011-05-01
Incorporation of HPV testing into cervical screening is anticipated and robust methods for DNA extraction from liquid based cytology (LBC) samples are required. This study compared QIAamp extraction with Proteinase K digestion and developed methods to address DNA extraction failure (β-globin PCR negative) from clinical specimens. Proteinase K and QIAamp extraction methods in paired LBC samples were comparable with adequate DNA retrieved from 93.3% of clinical specimens. An HPV prevalence cohort (n=10,000) found 7% (n=676) LBC samples tested negative for β-globin, and were classified as inadequate. This 'failure' rate is unsuitable for population screening, particularly as the sampling method is intrusive. 379/676 samples were assessed to determine the cause of test failure. Re-testing confirmed adequate DNA in 21.6% of the original extracts; re-extraction from stored material identified 56.2% samples contained adequate material; dilution to overcome sample inhibition (1:10) resolved 51.7% cases in original extracts and 28% in new extracts. A standardised approach to HPV testing with an optimal DNA concentration input rather than standard volume input is recommended. Samples failing initial DNA extraction should be repeat extracted and assessed for sample inhibition to reduce the 7% of HPV tests being reported as inadequate and reduce the need for retesting of those women to <1%.
Tan, A A; Azman, S N; Abdul Rani, N R; Kua, B C; Sasidharan, S; Kiew, L V; Othman, N; Noordin, R; Chen, Y
2011-12-01
There is a great diversity of protein samples types and origins, therefore the optimal procedure for each sample type must be determined empirically. In order to obtain a reproducible and complete sample presentation which view as many proteins as possible on the desired 2DE gel, it is critical to perform additional sample preparation steps to improve the quality of the final results, yet without selectively losing the proteins. To address this, we developed a general method that is suitable for diverse sample types based on phenolchloroform extraction method (represented by TRI reagent). This method was found to yield good results when used to analyze human breast cancer cell line (MCF-7), Vibrio cholerae, Cryptocaryon irritans cyst and liver abscess fat tissue. These types represent cell line, bacteria, parasite cyst and pus respectively. For each type of samples, several attempts were made to methodically compare protein isolation methods using TRI-reagent Kit, EasyBlue Kit, PRO-PREP™ Protein Extraction Solution and lysis buffer. The most useful protocol allows the extraction and separation of a wide diversity of protein samples that is reproducible among repeated experiments. Our results demonstrated that the modified TRI-reagent Kit had the highest protein yield as well as the greatest number of total proteins spots count for all type of samples. Distinctive differences in spot patterns were also observed in the 2DE gel of different extraction methods used for each type of sample. PMID:22433892
Technology Transfer Automated Retrieval System (TEKTRAN)
The primary advantage of Dynamically Dimensioned Search algorithm (DDS) is that it outperforms many other optimization techniques in both convergence speed and the ability in searching for parameter sets that satisfy statistical guidelines while requiring only one algorithm parameter (perturbation f...
Reynolds, Kaycee N; Loecke, Terrance D; Burgin, Amy J; Davis, Caroline A; Riveros-Iregui, Diego; Thomas, Steven A; St Clair, Martin A; Ward, Adam S
2016-06-21
Understanding linked hydrologic and biogeochemical processes such as nitrate loading to agricultural streams requires that the sampling bias and precision of monitoring strategies be known. An existing spatially distributed, high-frequency nitrate monitoring network covering ∼40% of Iowa provided direct observations of in situ nitrate concentrations at a temporal resolution of 15 min. Systematic subsampling of nitrate records allowed for quantification of uncertainties (bias and precision) associated with estimates of various nitrate parameters, including: mean nitrate concentration, proportion of samples exceeding the nitrate drinking water standard (DWS), peak (>90th quantile) nitrate concentration, and nitrate flux. We subsampled continuous records for 47 site-year combinations mimicking common, but labor-intensive, water-sampling regimes (e.g., time-interval, stage-triggered, and dynamic-discharge storm sampling). Our results suggest that time-interval sampling most efficiently characterized all nitrate parameters, except at coarse frequencies for nitrate flux. Stage-triggered storm sampling most precisely captured nitrate flux when less than 0.19% of possible 15 min observations for a site-year were used. The time-interval strategy had the greatest return on sampling investment by most precisely and accurately quantifying nitrate parameters per sampling effort. These uncertainty estimates can aid in designing sampling strategies focused on nitrate monitoring in the tile-drained Midwest or similar agricultural regions.
NASA Astrophysics Data System (ADS)
Kirkham, R.; Olsen, K.; Hayes, J. C.; Emer, D. F.
2013-12-01
Underground nuclear tests may be first detected by seismic or air samplers operated by the CTBTO (Comprehensive Nuclear-Test-Ban Treaty Organization). After initial detection of a suspicious event, member nations may call for an On-Site Inspection (OSI) that in part, will sample for localized releases of radioactive noble gases and particles. Although much of the commercially available equipment and methods used for surface and subsurface environmental sampling of gases can be used for an OSI scenario, on-site sampling conditions, required sampling volumes and establishment of background concentrations of noble gases require development of specialized methodologies. To facilitate development of sampling equipment and methodologies that address OSI sampling volume and detection objectives, and to collect information required for model development, a field test site was created at a former underground nuclear explosion site located in welded volcanic tuff. A mixture of SF-6, Xe127 and Ar37 was metered into 4400 m3 of air as it was injected into the top region of the UNE cavity. These tracers were expected to move towards the surface primarily in response to barometric pumping or through delayed cavity pressurization (accelerated transport to minimize source decay time). Sampling approaches compared during the field exercise included sampling at the soil surface, inside surface fractures, and at soil vapor extraction points at depths down to 2 m. Effectiveness of various sampling approaches and the results of tracer gas measurements will be presented.
Shaw, Milton Sam; Coe, Joshua D; Sewell, Thomas D
2009-01-01
An optimized version of the Nested Markov Chain Monte Carlo sampling method is applied to the calculation of the Hugoniot for liquid nitrogen. The 'full' system of interest is calculated using density functional theory (DFT) with a 6-31 G* basis set for the configurational energies. The 'reference' system is given by a model potential fit to the anisotropic pair interaction of two nitrogen molecules from DFT calculations. The EOS is sampled in the isobaric-isothermal (NPT) ensemble with a trial move constructed from many Monte Carlo steps in the reference system. The trial move is then accepted with a probability chosen to give the full system distribution. The P's and T's of the reference and full systems are chosen separately to optimize the computational time required to produce the full system EOS. The method is numerically very efficient and predicts a Hugoniot in excellent agreement with experimental data.
Yi, Xinzhu; Bayen, Stéphane; Kelly, Barry C; Li, Xu; Zhou, Zhi
2015-12-01
A solid-phase extraction/liquid chromatography/electrospray ionization/multi-stage mass spectrometry (SPE-LC-ESI-MS/MS) method was optimized in this study for sensitive and simultaneous detection of multiple antibiotics in urban surface waters and soils. Among the seven classes of tested antibiotics, extraction efficiencies of macrolides, lincosamide, chloramphenicol, and polyether antibiotics were significantly improved under optimized sample extraction pH. Instead of only using acidic extraction in many existing studies, the results indicated that antibiotics with low pK a values (<7) were extracted more efficiently under acidic conditions and antibiotics with high pK a values (>7) were extracted more efficiently under neutral conditions. The effects of pH were more obvious on polar compounds than those on non-polar compounds. Optimization of extraction pH resulted in significantly improved sample recovery and better detection limits. Compared with reported values in the literature, the average reduction of minimal detection limits obtained in this study was 87.6% in surface waters (0.06-2.28 ng/L) and 67.1% in soils (0.01-18.16 ng/g dry wt). This method was subsequently applied to detect antibiotics in environmental samples in a heavily populated urban city, and macrolides, sulfonamides, and lincomycin were frequently detected. Antibiotics with highest detected concentrations were sulfamethazine (82.5 ng/L) in surface waters and erythromycin (6.6 ng/g dry wt) in soils. The optimized sample extraction strategy can be used to improve the detection of a variety of antibiotics in environmental surface waters and soils.
Cardellicchio, Nicola; Di Leo, Antonella; Giandomenico, Santina; Santoro, Stefania
2006-01-01
Optimization of acid digestion method for mercury determination in marine biological samples (dolphin liver, fish and mussel tissues) using a closed vessel microwave sample preparation is presented. Five digestion procedures with different acid mixtures were investigated: the best results were obtained when the microwave-assisted digestion was based on sample dissolution with HNO3-H2SO4-K2Cr2O7 mixture. A comparison between microwave digestion and conventional reflux digestion shows there are considerable losses of mercury in the open digestion system. The microwave digestion method has been tested satisfactorily using two certified reference materials. Analytical results show a good agreement with certified values. The microwave digestion proved to be a reliable and rapid method for decomposition of biological samples in mercury determination.
Delgado, J; Moure, J C; Vives-Gilabert, Y; Delfino, M; Espinosa, A; Gómez-Ansón, B
2014-07-01
A scheme to significantly speed up the processing of MRI with FreeSurfer (FS) is presented. The scheme is aimed at maximizing the productivity (number of subjects processed per unit time) for the use case of research projects with datasets involving many acquisitions. The scheme combines the already existing GPU-accelerated version of the FS workflow with a task-level parallel scheme supervised by a resource scheduler. This allows for an optimum utilization of the computational power of a given hardware platform while avoiding problems with shortages of platform resources. The scheme can be executed on a wide variety of platforms, as its implementation only involves the script that orchestrates the execution of the workflow components and the FS code itself requires no modifications. The scheme has been implemented and tested on a commodity platform within the reach of most research groups (a personal computer with four cores and an NVIDIA GeForce 480 GTX graphics card). Using the scheduled task-level parallel scheme, a productivity above 0.6 subjects per hour is achieved on the test platform, corresponding to a speedup of over six times compared to the default CPU-only serial FS workflow.
Delgado, J; Moure, J C; Vives-Gilabert, Y; Delfino, M; Espinosa, A; Gómez-Ansón, B
2014-07-01
A scheme to significantly speed up the processing of MRI with FreeSurfer (FS) is presented. The scheme is aimed at maximizing the productivity (number of subjects processed per unit time) for the use case of research projects with datasets involving many acquisitions. The scheme combines the already existing GPU-accelerated version of the FS workflow with a task-level parallel scheme supervised by a resource scheduler. This allows for an optimum utilization of the computational power of a given hardware platform while avoiding problems with shortages of platform resources. The scheme can be executed on a wide variety of platforms, as its implementation only involves the script that orchestrates the execution of the workflow components and the FS code itself requires no modifications. The scheme has been implemented and tested on a commodity platform within the reach of most research groups (a personal computer with four cores and an NVIDIA GeForce 480 GTX graphics card). Using the scheduled task-level parallel scheme, a productivity above 0.6 subjects per hour is achieved on the test platform, corresponding to a speedup of over six times compared to the default CPU-only serial FS workflow. PMID:24430512
Yang, Yuanzhong; Boysen, Reinhard I; Hearn, Milton T W
2006-07-15
A versatile experimental approach is described to achieve very high sensitivity analysis of peptides by capillary electrophoresis-mass spectrometry with sheath flow configuration based on optimization of field-amplified sample injection. Compared to traditional hydrodynamic injection methods, signal enhancement in terms of detection sensitivity of the bioanalytes by more than 3000-fold can be achieved. The effects of injection conditions, composition of the acid and organic solvent in the sample solution, length of the water plug, sample injection time, and voltage on the efficiency of the sample stacking have been systematically investigated, with peptides in the low-nanomolar (10(-9) M) range readily detected under the optimized conditions. Linearity of the established stacking method was found to be excellent over 2 orders of magnitude of concentration. The method was further evaluated for the analysis of low concentration bioactive peptide mixtures and tryptic digests of proteins. A distinguishing feature of the described approach is that it can be employed directly for the analysis of low-abundance protein fragments generated by enzymatic digestion and a reversed-phase-based sample-desalting procedure. Thus, rapid identification of protein fragments as low-abundance analytes can be achieved with this new approach by comparison of the actual tandem mass spectra of selected peptides with the predicted fragmentation patterns using online database searching algorithms. PMID:16841892
Aubier, Thomas G; Sherratt, Thomas N
2015-11-01
The convergent evolution of warning signals in unpalatable species, known as Müllerian mimicry, has been observed in a wide variety of taxonomic groups. This form of mimicry is generally thought to have arisen as a consequence of local frequency-dependent selection imposed by sampling predators. However, despite clear evidence for local selection against rare warning signals, there appears an almost embarrassing amount of polymorphism in natural warning colors, both within and among populations. Because the model of predator cognition widely invoked to explain Müllerian mimicry (Müller's "fixed n(k)" model) is highly simplified and has not been empirically supported; here, we explore the dynamical consequences of the optimal strategy for sampling unfamiliar prey. This strategy, based on a classical exploration-exploitation trade-off, not only allows for a variable number of prey sampled, but also accounts for predator neophobia under some conditions. In contrast to Müller's "fixed n(k)" sampling rule, the optimal sampling strategy is capable of generating a variety of dynamical outcomes, including mimicry but also regional and local polymorphism. Moreover, the heterogeneity of predator behavior across space and time that a more nuanced foraging strategy allows, can even further facilitate the emergence of both local and regional polymorphism in prey warning color.
NASA Astrophysics Data System (ADS)
Yao, Qiang; Takahashi, Keita; Fujii, Toshiaki
2013-03-01
In recent years, ray space (or light field in other literatures) photography has gained a great popularity in the area of computer vision and image processing, and an efficient acquisition of a ray space is of great significance in the practical application. In order to handle the huge data problem in the acquisition process, in this paper, we propose a method of compressively sampling and reconstructing one ray space. In our method, one weighted matrix which reflects the amplitude structure of non-zero coefficients in 2D-DCT domain is designed and generated by using statistics from available data set. The weighted matrix is integrated in ι1 norm optimization to reconstruct the ray space, and we name this method as statistically-weighted ι1 norm optimization. Experimental result shows that the proposed method achieves better reconstruction result at both low (0.1 of original sampling rate) and high (0.5 of original sampling rate) subsampling rates. In addition, the reconstruction time is also reduced by 25% compared to the reconstruction time by plain ι1 norm optimization.
Kraut, Alexandra; Marcellin, Marlène; Adrait, Annie; Kuhn, Lauriane; Louwagie, Mathilde; Kieffer-Jaquinod, Sylvie; Lebert, Dorothée; Masselon, Christophe D; Dupuis, Alain; Bruley, Christophe; Jaquinod, Michel; Garin, Jérôme; Gallagher-Gambarelli, Maighread
2009-07-01
To comply with current proteomics guidelines, it is often necessary to analyze the same peptide samples several times. Between analyses, the sample must be stored in such a way as to conserve its intrinsic properties, without losing either peptides or signal intensity. This article describes two studies designed to define the optimal storage conditions for peptide samples between analyses. With the use of a label-free strategy, peptide conservation was compared over a 28-day period in three different recipients: standard plastic tubes, glass tubes, and low-adsorption plastic tubes. The results of this study showed that standard plastic tubes are unsuitable for peptide storage over the period studied. Glass tubes were found to perform better than standard plastic, but optimal peptide recovery was achieved using low-adsorption plastic tubes. The peptides showing poor recovery following storage were mainly hydrophobic in nature. The differences in peptide recovery between glass and low-adsorption plastic tubes were further studied using isotopically labeled proteins. This study allowed accurate comparison of peptide recovery between the two tube types within the same LC-MS run. The results of the label-free study were confirmed. Further, it was possible to demonstrate that peptide recovery in low-adsorption plastic tubes was optimal whatever the peptide concentration stored.
Improved estimates of forest vegetation structure and biomass with a LiDAR-optimized sampling design
NASA Astrophysics Data System (ADS)
Hawbaker, Todd J.; Keuler, Nicholas S.; Lesak, Adrian A.; Gobakken, Terje; Contrucci, Kirk; Radeloff, Volker C.
2009-06-01
LiDAR data are increasingly available from both airborne and spaceborne missions to map elevation and vegetation structure. Additionally, global coverage may soon become available with NASA's planned DESDynI sensor. However, substantial challenges remain to using the growing body of LiDAR data. First, the large volumes of data generated by LiDAR sensors require efficient processing methods. Second, efficient sampling methods are needed to collect the field data used to relate LiDAR data with vegetation structure. In this paper, we used low-density LiDAR data, summarized within pixels of a regular grid, to estimate forest structure and biomass across a 53,600 ha study area in northeastern Wisconsin. Additionally, we compared the predictive ability of models constructed from a random sample to a sample stratified using mean and standard deviation of LiDAR heights. Our models explained between 65 to 88% of the variability in DBH, basal area, tree height, and biomass. Prediction errors from models constructed using a random sample were up to 68% larger than those from the models built with a stratified sample. The stratified sample included a greater range of variability than the random sample. Thus, applying the random sample model to the entire population violated a tenet of regression analysis; namely, that models should not be used to extrapolate beyond the range of data from which they were constructed. Our results highlight that LiDAR data integrated with field data sampling designs can provide broad-scale assessments of vegetation structure and biomass, i.e., information crucial for carbon and biodiversity science.
O’Connell, Steven G.; McCartney, Melissa A.; Paulik, L. Blair; Allan, Sarah E.; Tidwell, Lane G.; Wilson, Glenn; Anderson, Kim A.
2014-01-01
Sequestering semi-polar compounds can be difficult with low-density polyethylene (LDPE), but those pollutants may be more efficiently absorbed using silicone. In this work, optimized methods for cleaning, infusing reference standards, and polymer extraction are reported along with field comparisons of several silicone materials for polycyclic aromatic hydrocarbons (PAHs) and pesticides. In a final field demonstration, the most optimal silicone material is coupled with LDPE in a large-scale study to examine PAHs in addition to oxygenated-PAHs (OPAHs) at a Superfund site. OPAHs exemplify a sensitive range of chemical properties to compare polymers (log Kow 0.2–5.3), and transformation products of commonly studied parent PAHs. On average, while polymer concentrations differed nearly 7-fold, water-calculated values were more similar (about 3.5-fold or less) for both PAHs (17) and OPAHs (7). Individual water concentrations of OPAHs differed dramatically between silicone and LDPE, highlighting the advantages of choosing appropriate polymers and optimized methods for pollutant monitoring. PMID:25009960
Optimization of the Sampling Periods and the Quantization Bit Lengths for Networked Estimation
Suh, Young Soo; Ro, Young Sik; Kang, Hee Jun
2010-01-01
This paper is concerned with networked estimation, where sensor data are transmitted over a network of limited transmission rate. The transmission rate depends on the sampling periods and the quantization bit lengths. To investigate how the sampling periods and the quantization bit lengths affect the estimation performance, an equation to compute the estimation performance is provided. An algorithm is proposed to find sampling periods and quantization bit lengths combination, which gives good estimation performance while satisfying the transmission rate constraint. Through the numerical example, the proposed algorithm is verified. PMID:22163557
Siqueira, Glécio Machado; Dafonte, Jorge Dafonte; Bueno Lema, Javier; Valcárcel Armesto, Montserrat; Silva, Ênio Farias França e
2014-01-01
This study presents a combined application of an EM38DD for assessing soil apparent electrical conductivity (ECa) and a dual-sensor vertical penetrometer Veris-3000 for measuring soil electrical conductivity (ECveris) and soil resistance to penetration (PR). The measurements were made at a 6 ha field cropped with forage maize under no-tillage after sowing and located in Northwestern Spain. The objective was to use data from ECa for improving the estimation of soil PR. First, data of ECa were used to determine the optimized sampling scheme of the soil PR in 40 points. Then, correlation analysis showed a significant negative relationship between soil PR and ECa, ranging from −0.36 to −0.70 for the studied soil layers. The spatial dependence of soil PR was best described by spherical models in most soil layers. However, below 0.50 m the spatial pattern of soil PR showed pure nugget effect, which could be due to the limited number of PR data used in these layers as the values of this parameter often were above the range measured by our equipment (5.5 MPa). The use of ECa as secondary variable slightly improved the estimation of PR by universal cokriging, when compared with kriging. PMID:25610899
Machado Siqueira, Glécio; Dafonte Dafonte, Jorge; Bueno Lema, Javier; Valcárcel Armesto, Montserrat; França e Silva, Ênio Farias
2014-01-01
This study presents a combined application of an EM38DD for assessing soil apparent electrical conductivity (ECa) and a dual-sensor vertical penetrometer Veris-3000 for measuring soil electrical conductivity (ECveris) and soil resistance to penetration (PR). The measurements were made at a 6 ha field cropped with forage maize under no-tillage after sowing and located in Northwestern Spain. The objective was to use data from ECa for improving the estimation of soil PR. First, data of ECa were used to determine the optimized sampling scheme of the soil PR in 40 points. Then, correlation analysis showed a significant negative relationship between soil PR and ECa, ranging from -0.36 to -0.70 for the studied soil layers. The spatial dependence of soil PR was best described by spherical models in most soil layers. However, below 0.50 m the spatial pattern of soil PR showed pure nugget effect, which could be due to the limited number of PR data used in these layers as the values of this parameter often were above the range measured by our equipment (5.5 MPa). The use of ECa as secondary variable slightly improved the estimation of PR by universal cokriging, when compared with kriging.
OPTIMIZING MINIRHIZOTRON SAMPLE FREQUENCY FOR ESTIMATING FINE ROOT PRODUCTION AND TURNOVER
The most frequent reason for using minirhizotrons in natural ecosystems is the determination of fine root production and turnover. Our objective is to determine the optimum sampling frequency for estimating fine root production and turnover using data from evergreen (Pseudotsuga ...
Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks
Stohlgren, Thomas J.; Kumar, Sunil; Barnett, David T.; Evangelista, Paul H.
2011-01-01
Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.
Optimal design of near-Earth asteroid sample-return trajectories in the Sun-Earth-Moon system
NASA Astrophysics Data System (ADS)
He, Shengmao; Zhu, Zhengfan; Peng, Chao; Ma, Jian; Zhu, Xiaolong; Gao, Yang
2016-08-01
In the 6th edition of the Chinese Space Trajectory Design Competition held in 2014, a near-Earth asteroid sample-return trajectory design problem was released, in which the motion of the spacecraft is modeled in multi-body dynamics, considering the gravitational forces of the Sun, Earth, and Moon. It is proposed that an electric-propulsion spacecraft initially parking in a circular 200-km-altitude low Earth orbit is expected to rendezvous with an asteroid and carry as much sample as possible back to the Earth in a 10-year time frame. The team from the Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences has reported a solution with an asteroid sample mass of 328 tons, which is ranked first in the competition. In this article, we will present our design and optimization methods, primarily including overall analysis, target selection, escape from and capture by the Earth-Moon system, and optimization of impulsive and low-thrust trajectories that are modeled in multi-body dynamics. The orbital resonance concept and lunar gravity assists are considered key techniques employed for trajectory design. The reported solution, preliminarily revealing the feasibility of returning a hundreds-of-tons asteroid or asteroid sample, envisions future space missions relating to near-Earth asteroid exploration.
Wiegmann, Daniel D; Seubert, Steven M; Wade, Gordon A
2010-02-21
The behavior of a female in search of a mate determines the likelihood that she encounters a high-quality male in the search process. The fixed sample (best-of-n) search strategy and the sequential search (fixed threshold) strategy are two prominent models of search behavior. The sequential search strategy dominates the former strategy--yields an equal or higher expected net fitness return to searchers--when search costs are nontrivial and the distribution of quality among prospective mates is uniform or truncated normal. In this paper our objective is to determine whether there are any search costs or distributions of male quality for which the sequential search strategy is inferior to the fixed sample search strategy. The two search strategies are derived under general conditions in which females evaluate encountered males by inspection of an indicator character that has some functional relationship to male quality. The solutions are identical to the original models when the inspected male attribute is itself male quality. The sequential search strategy is shown to dominate the fixed sample search strategy for all search costs and distributions of male quality. Low search costs have been implicated to explain empirical observations that are consistent with the use of a fixed sample search strategy, but under conditions in which the original models were derived there is no search cost or distribution of male quality that favors the fixed sample search strategy. Plausible alternative explanations for the apparent use of this search strategy are discussed.
Optimizing sampling design to deal with mist-net avoidance in Amazonian birds and bats.
Marques, João Tiago; Ramos Pereira, Maria J; Marques, Tiago A; Santos, Carlos David; Santana, Joana; Beja, Pedro; Palmeirim, Jorge M
2013-01-01
Mist netting is a widely used technique to sample bird and bat assemblages. However, captures often decline with time because animals learn and avoid the locations of nets. This avoidance or net shyness can substantially decrease sampling efficiency. We quantified the day-to-day decline in captures of Amazonian birds and bats with mist nets set at the same location for four consecutive days. We also evaluated how net avoidance influences the efficiency of surveys under different logistic scenarios using re-sampling techniques. Net avoidance caused substantial declines in bird and bat captures, although more accentuated in the latter. Most of the decline occurred between the first and second days of netting: 28% in birds and 47% in bats. Captures of commoner species were more affected. The numbers of species detected also declined. Moving nets daily to minimize the avoidance effect increased captures by 30% in birds and 70% in bats. However, moving the location of nets may cause a reduction in netting time and captures. When moving the nets caused the loss of one netting day it was no longer advantageous to move the nets frequently. In bird surveys that could even decrease the number of individuals captured and species detected. Net avoidance can greatly affect sampling efficiency but adjustments in survey design can minimize this. Whenever nets can be moved without losing netting time and the objective is to capture many individuals, they should be moved daily. If the main objective is to survey species present then nets should still be moved for bats, but not for birds. However, if relocating nets causes a significant loss of netting time, moving them to reduce effects of shyness will not improve sampling efficiency in either group. Overall, our findings can improve the design of mist netting sampling strategies in other tropical areas.
Trojanowski, S.; Ciszek, M.
2009-10-15
In the paper we present an analytical calculation method for determination of the sensitivity of a pulse field magnetometer working with a first order gradiometer. Our considerations here are especially focused on a case of magnetic moment measurements of very small samples. Derived in the work analytical equations allow for a quick estimation of the magnetometer's sensitivity and give also the way to its calibration using the sample simulation coil method. On the base of the given in the paper calculations we designed and constructed a simple homemade magnetometer and performed its sensitivity calibration.
Kilambi, Himabindu V; Manda, Kalyani; Sanivarapu, Hemalatha; Maurya, Vineet K; Sharma, Rameshwar; Sreelakshmi, Yellamaraju
2016-01-01
An optimized protocol was developed for shotgun proteomics of tomato fruit, which is a recalcitrant tissue due to a high percentage of sugars and secondary metabolites. A number of protein extraction and fractionation techniques were examined for optimal protein extraction from tomato fruits followed by peptide separation on nanoLCMS. Of all evaluated extraction agents, buffer saturated phenol was the most efficient. In-gel digestion [SDS-PAGE followed by separation on LCMS (GeLCMS)] of phenol-extracted sample yielded a maximal number of proteins. For in-solution digested samples, fractionation by strong anion exchange chromatography (SAX) also gave similar high proteome coverage. For shotgun proteomic profiling, optimization of mass spectrometry parameters such as automatic gain control targets (5E+05 for MS, 1E+04 for MS/MS); ion injection times (500 ms for MS, 100 ms for MS/MS); resolution of 30,000; signal threshold of 500; top N-value of 20 and fragmentation by collision-induced dissociation yielded the highest number of proteins. Validation of the above protocol in two tomato cultivars demonstrated its reproducibility, consistency, and robustness with a CV of < 10%. The protocol facilitated the detection of five-fold higher number of proteins compared to published reports in tomato fruits. The protocol outlined would be useful for high-throughput proteome analysis from tomato fruits and can be applied to other recalcitrant tissues. PMID:27446192
NASA Astrophysics Data System (ADS)
Zawadowicz, M. A.; Del Negro, L. A.
2010-12-01
Hazardous air pollutants (HAPs) are usually present in the atmosphere at pptv-level, requiring measurements with high sensitivity and minimal contamination. Commonly used evacuated canister methods require an overhead in space, money and time that often is prohibitive to primarily-undergraduate institutions. This study optimized an analytical method based on solid-phase microextraction (SPME) of ambient gaseous matrix, which is a cost-effective technique of selective VOC extraction, accessible to an unskilled undergraduate. Several approaches to SPME extraction and sample analysis were characterized and several extraction parameters optimized. Extraction time, temperature and laminar air flow velocity around the fiber were optimized to give highest signal and efficiency. Direct, dynamic extraction of benzene from a moving air stream produced better precision (±10%) than sampling of stagnant air collected in a polymeric bag (±24%). Using a low-polarity chromatographic column in place of a standard (5%-Phenyl)-methylpolysiloxane phase decreased the benzene detection limit from 2 ppbv to 100 pptv. The developed method is simple and fast, requiring 15-20 minutes per extraction and analysis. It will be field-validated and used as a field laboratory component of various undergraduate Chemistry and Environmental Studies courses.
Kilambi, Himabindu V.; Manda, Kalyani; Sanivarapu, Hemalatha; Maurya, Vineet K.; Sharma, Rameshwar; Sreelakshmi, Yellamaraju
2016-01-01
An optimized protocol was developed for shotgun proteomics of tomato fruit, which is a recalcitrant tissue due to a high percentage of sugars and secondary metabolites. A number of protein extraction and fractionation techniques were examined for optimal protein extraction from tomato fruits followed by peptide separation on nanoLCMS. Of all evaluated extraction agents, buffer saturated phenol was the most efficient. In-gel digestion [SDS-PAGE followed by separation on LCMS (GeLCMS)] of phenol-extracted sample yielded a maximal number of proteins. For in-solution digested samples, fractionation by strong anion exchange chromatography (SAX) also gave similar high proteome coverage. For shotgun proteomic profiling, optimization of mass spectrometry parameters such as automatic gain control targets (5E+05 for MS, 1E+04 for MS/MS); ion injection times (500 ms for MS, 100 ms for MS/MS); resolution of 30,000; signal threshold of 500; top N-value of 20 and fragmentation by collision-induced dissociation yielded the highest number of proteins. Validation of the above protocol in two tomato cultivars demonstrated its reproducibility, consistency, and robustness with a CV of < 10%. The protocol facilitated the detection of five-fold higher number of proteins compared to published reports in tomato fruits. The protocol outlined would be useful for high-throughput proteome analysis from tomato fruits and can be applied to other recalcitrant tissues. PMID:27446192
Superposition Enhanced Nested Sampling
NASA Astrophysics Data System (ADS)
Martiniani, Stefano; Stevenson, Jacob D.; Wales, David J.; Frenkel, Daan
2014-07-01
The theoretical analysis of many problems in physics, astronomy, and applied mathematics requires an efficient numerical exploration of multimodal parameter spaces that exhibit broken ergodicity. Monte Carlo methods are widely used to deal with these classes of problems, but such simulations suffer from a ubiquitous sampling problem: The probability of sampling a particular state is proportional to its entropic weight. Devising an algorithm capable of sampling efficiently the full phase space is a long-standing problem. Here, we report a new hybrid method for the exploration of multimodal parameter spaces exhibiting broken ergodicity. Superposition enhanced nested sampling combines the strengths of global optimization with the unbiased or athermal sampling of nested sampling, greatly enhancing its efficiency with no additional parameters. We report extensive tests of this new approach for atomic clusters that are known to have energy landscapes for which conventional sampling schemes suffer from broken ergodicity. We also introduce a novel parallelization algorithm for nested sampling.
Optimal Sampling of Units in Three-Level Cluster Randomized Designs: An Ancova Framework
ERIC Educational Resources Information Center
Konstantopoulos, Spyros
2011-01-01
Field experiments with nested structures assign entire groups such as schools to treatment and control conditions. Key aspects of such cluster randomized experiments include knowledge of the intraclass correlation structure and the sample sizes necessary to achieve adequate power to detect the treatment effect. The units at each level of the…
Carver, Charles S.; Scheier, Michael F.; Segerstrom, Suzanne C.
2010-01-01
Optimism is an individual difference variable that reflects the extent to which people hold generalized favorable expectancies for their future. Higher levels of optimism have been related prospectively to better subjective well-being in times of adversity or difficulty (i.e., controlling for previous well-being). Consistent with such findings, optimism has been linked to higher levels of engagement coping and lower levels of avoidance, or disengagement, coping. There is evidence that optimism is associated with taking proactive steps to protect one's health, whereas pessimism is associated with health-damaging behaviors. Consistent with such findings, optimism is also related to indicators of better physical health. The energetic, task-focused approach that optimists take to goals also relates to benefits in the socioeconomic world. Some evidence suggests that optimism relates to more persistence in educational efforts and to higher later income. Optimists also appear to fare better than pessimists in relationships. Although there are instances in which optimism fails to convey an advantage, and instances in which it may convey a disadvantage, those instances are relatively rare. In sum, the behavioral patterns of optimists appear to provide models of living for others to learn from. PMID:20170998
Janson, Lucas; Schmerling, Edward; Clark, Ashley; Pavone, Marco
2015-01-01
In this paper we present a novel probabilistic sampling-based motion planning algorithm called the Fast Marching Tree algorithm (FMT*). The algorithm is specifically aimed at solving complex motion planning problems in high-dimensional configuration spaces. This algorithm is proven to be asymptotically optimal and is shown to converge to an optimal solution faster than its state-of-the-art counterparts, chiefly PRM* and RRT*. The FMT* algorithm performs a “lazy” dynamic programming recursion on a predetermined number of probabilistically-drawn samples to grow a tree of paths, which moves steadily outward in cost-to-arrive space. As such, this algorithm combines features of both single-query algorithms (chiefly RRT) and multiple-query algorithms (chiefly PRM), and is reminiscent of the Fast Marching Method for the solution of Eikonal equations. As a departure from previous analysis approaches that are based on the notion of almost sure convergence, the FMT* algorithm is analyzed under the notion of convergence in probability: the extra mathematical flexibility of this approach allows for convergence rate bounds—the first in the field of optimal sampling-based motion planning. Specifically, for a certain selection of tuning parameters and configuration spaces, we obtain a convergence rate bound of order O(n−1/d+ρ), where n is the number of sampled points, d is the dimension of the configuration space, and ρ is an arbitrarily small constant. We go on to demonstrate asymptotic optimality for a number of variations on FMT*, namely when the configuration space is sampled non-uniformly, when the cost is not arc length, and when connections are made based on the number of nearest neighbors instead of a fixed connection radius. Numerical experiments over a range of dimensions and obstacle configurations confirm our the-oretical and heuristic arguments by showing that FMT*, for a given execution time, returns substantially better solutions than either PRM* or RRT
Optimized methods for extracting circulating small RNAs from long-term stored equine samples.
Unger, Lucia; Fouché, Nathalie; Leeb, Tosso; Gerber, Vincent; Pacholewska, Alicja
2016-01-01
Circulating miRNAs in body fluids, particularly serum, are promising candidates for future routine biomarker profiling in various pathologic conditions in human and veterinary medicine. However, reliable standardized methods for miRNA extraction from equine serum and fresh or archived whole blood are sorely lacking. We systematically compared various miRNA extraction methods from serum and whole blood after short and long-term storage without addition of RNA stabilizing additives prior to freezing. Time of storage at room temperature prior to freezing did not affect miRNA quality in serum. Furthermore, we showed that miRNA of NGS-sufficient quality can be recovered from blood samples after >10 years of storage at -80 °C. This allows retrospective analyses of miRNAs from archived samples. PMID:27356979
Brewer, Heather M.; Norbeck, Angela D.; Adkins, Joshua N.; Manes, Nathan P.; Ansong, Charles; Shi, Liang; Rikihisa, Yasuko; Kikuchi, Takane; Wong, Scott; Estep, Ryan D.; Heffron, Fred; Pasa-Tolic, Ljiljana; Smith, Richard D.
2008-12-19
The elucidation of critical functional pathways employed by pathogens and hosts during an infectious cycle is both challenging and central to our understanding of infectious diseases. In recent years, mass spectrometry-based proteomics has been used as a powerful tool to identify key pathogenesis-related proteins and pathways. Despite the analytical power of mass spectrometry-based technologies, samples must be appropriately prepared to characterize the functions of interest (e.g. host-response to a pathogen or a pathogen-response to a host). The preparation of these protein samples requires multiple decisions about what aspect of infection is being studied, and it may require the isolation of either host and/or pathogen cellular material.
NASA Technical Reports Server (NTRS)
Hague, D. S.; Merz, A. W.
1976-01-01
Atmospheric sampling has been carried out by flights using an available high-performance supersonic aircraft. Altitude potential of an off-the-shelf F-15 aircraft is examined. It is shown that the standard F-15 has a maximum altitude capability in excess of 100,000 feet for routine flight operation by NASA personnel. This altitude is well in excess of the minimum altitudes which must be achieved for monitoring the possible growth of suspected aerosol contaminants.
Van den Broeck, F; Geldof, S; Polman, K; Volckaert, F A M; Huyse, T
2011-08-01
Genotyping individual larval stages and eggs of natural parasite populations is complicated by the difficulty of obtaining reliable genotypes from low quantity DNA template. A suitable storage and extraction protocol, together with a thorough quantification of genotyping errors are therefore crucial for molecular epidemiological studies. Here we test the robustness, handling time, ease of use, cost effectiveness and success rate of various fixation (Whatman FTA(®) Classic and Elute Cards, 70% EtOH and RNAlater(®)) and subsequent DNA extraction methods (commercial kits and proteinase K protocol). None of these methods require a cooling chain and are therefore suitable for field collection. Based on a multiplex microsatellite PCR with nine loci the success and reliability of each technique is evaluated by the proportion of samples with at least eight scored loci and the proportion of genotyping errors. If only the former is taken into account, FTA(®) Elute is recommended (83% success; 44% genotyping error; 0.2 €/sample; 1h 20 m handling time). However, when also considering the genotyping errors, handling time and ease of use, we opt for 70% EtOH with the 96-well plate technology followed by a simple proteinase K extraction (73% success; 0% genotyping error; 0.2 €/sample; 15m handling time). For eggs we suggest (1) to pool all eggs per person in 1.5 ml tubes filled with 70% EtOH for transport and (2) to identify each egg to species level prior to genotyping. To this end we extended the Rapid diagnostic PCR developed by Webster et al. (2010) with a S. mansoni-specific primer to discriminate between S. mansoni, S. haematobium and S. bovis in a single PCR reaction. The success rate of genotyping eggs was 75% (0% genotyping error). This is the first study to incorporate genotyping errors through re-amplification for the evaluation of schistosome sampling protocols and the identification of error-prone loci.
NASA Astrophysics Data System (ADS)
Pawcenis, Dominika; Koperska, Monika A.; Milczarek, Jakub M.; Łojewski, Tomasz; Łojewska, Joanna
2014-02-01
A direct goal of this paper was to improve the methods of sample preparation and separation for analyses of fibroin polypeptide with the use of size exclusion chromatography (SEC). The motivation for the study arises from our interest in natural polymers included in historic textile and paper artifacts, and is a logical response to the urgent need for developing rationale-based methods for materials conservation. The first step is to develop a reliable analytical tool which would give insight into fibroin structure and its changes caused by both natural and artificial ageing. To investigate the influence of preparation conditions, two sets of artificially aged samples were prepared (with and without NaCl in sample solution) and measured by the means of SEC with multi angle laser light scattering detector. It was shown that dialysis of fibroin dissolved in LiBr solution allows removal of the salt which destroys stacks chromatographic columns and prevents reproducible analyses. Salt rich (NaCl) water solutions of fibroin improved the quality of chromatograms.
Cook, Kimberly L; Britt, Jenks S
2007-04-01
Detection of Johne's disease, an enteric infection of cattle caused by Mycobacterium avium subsp. paratuberculosis (M. paratuberculosis), has been impeded by the lack of rapid, reliable detection methods. The goal of this study was to optimize methodologies for detecting M. paratuberculosis in manure from an infected dairy cow or in contaminated soil samples using a quantitative, real-time PCR (QRT-PCR) based analysis. Three different nucleic acid extraction techniques, the efficiency of direct versus indirect sample extraction, and sample pooling were assessed. The limit of detection was investigated by adding dilutions of M. paratuberculosis to soil. Results show that the highest yield (19.4+/-2.3 microg(-1) DNA extract) and the highest copy number of the targeted M. paratuberculosis IS900 sequence (1.3+/-0.2x10(8) copies g(-1) manure) were obtained with DNA extracted from manure using Qbiogene's Fast DNA Spin kit for soil. Pooling ten samples of M. paratuberculosis-contaminated soil improved the limit of detection ten fold (between 20 and 115 M. paratuberculosis cells g(-1) soil). Detection was between 65% and 95% higher when samples were extracted directly using bead-beating than when using pre-treatment with cell extraction buffers. The final soil-sampling and extraction regime was applied for detection of M. paratuberculosis in pasture soil after the removal of a M. paratuberculosis culture positive dairy cow. M. paratuberculosis remained in the pasture soil for more than 200 days. Results from these studies suggest that DNA extraction method, sampling protocol and PCR conditions each critically influence the outcome and validity of the QRT-PCR analysis of M. paratuberculosis concentrations in environmental samples.
Soil moisture optimal sampling strategy for Sentinel 1 validation super-sites in Poland
NASA Astrophysics Data System (ADS)
Usowicz, Boguslaw; Lukowski, Mateusz; Marczewski, Wojciech; Lipiec, Jerzy; Usowicz, Jerzy; Rojek, Edyta; Slominska, Ewa; Slominski, Jan
2014-05-01
Soil moisture (SM) exhibits a high temporal and spatial variability that is dependent not only on the rainfall distribution, but also on the topography of the area, physical properties of soil and vegetation characteristics. Large variability does not allow on certain estimation of SM in the surface layer based on ground point measurements, especially in large spatial scales. Remote sensing measurements allow estimating the spatial distribution of SM in the surface layer on the Earth, better than point measurements, however they require validation. This study attempts to characterize the SM distribution by determining its spatial variability in relation to the number and location of ground point measurements. The strategy takes into account the gravimetric and TDR measurements with different sampling steps, abundance and distribution of measuring points on scales of arable field, wetland and commune (areas: 0.01, 1 and 140 km2 respectively), taking into account the different status of SM. Mean values of SM were lowly sensitive on changes in the number and arrangement of sampling, however parameters describing the dispersion responded in a more significant manner. Spatial analysis showed autocorrelations of the SM, which lengths depended on the number and the distribution of points within the adopted grids. Directional analysis revealed a differentiated anisotropy of SM for different grids and numbers of measuring points. It can therefore be concluded that both the number of samples, as well as their layout on the experimental area, were reflected in the parameters characterizing the SM distribution. This suggests the need of using at least two variants of sampling, differing in the number and positioning of the measurement points, wherein the number of them must be at least 20. This is due to the value of the standard error and range of spatial variability, which show little change with the increase in the number of samples above this figure. Gravimetric method
Csikai, J; Dóczi, R
2009-01-01
The advantages and limitations of epithermal neutrons in qualification of hydrocarbons via their H contents and C/H atomic ratios have been investigated systematically. Sensitivity of this method and the dimensions of the interrogated regions were determined for various types of hydrogenous samples. Results clearly demonstrate the advantages of direct neutron detection, e.g. by BF(3) counters as compared to the foil activation method in addition to using the hardness of the spectral shape of Pu-Be neutrons to that from a (252)Cf source.
Design Of A Sorbent/desorbent Unit For Sample Pre-treatment Optimized For QMB Gas Sensors
Pennazza, G.; Cristina, S.; Santonico, M.; Martinelli, E.; Di Natale, C.; D'Amico, A.; Paolesse, R.
2009-05-23
Sample pre-treatment is a typical procedure in analytical chemistry aimed at improving the performance of analytical systems. In case of gas sensors sample pre-treatment systems are devised to overcome sensors limitations in terms of selectivity and sensitivity. For this purpose, systems based on adsorption and desorption processes driven by temperature conditioning have been illustrated. The involvement of large temperature ranges may pose problems when QMB gas sensors are used. In this work a study of such influences on the overall sensing properties of QMB sensors are illustrated. The results allowed the design of a pre-treatment unit coupled with a QMB gas sensors array optimized to operate in a suitable temperatures range. The performance of the system are illustrated by the partially separation of water vapor in a gas mixture, and by substantial improvement of the signal to noise ratio.
Baden, Tom; Schubert, Timm; Chang, Le; Wei, Tao; Zaichuk, Mariana; Wissinger, Bernd; Euler, Thomas
2013-12-01
For efficient coding, sensory systems need to adapt to the distribution of signals to which they are exposed. In vision, natural scenes above and below the horizon differ in the distribution of chromatic and achromatic features. Consequently, many species differentially sample light in the sky and on the ground using an asymmetric retinal arrangement of short- (S, "blue") and medium- (M, "green") wavelength-sensitive photoreceptor types. Here, we show that in mice this photoreceptor arrangement provides for near-optimal sampling of natural achromatic contrasts. Two-photon population imaging of light-driven calcium signals in the synaptic terminals of cone-photoreceptors expressing a calcium biosensor revealed that S, but not M cones, preferred dark over bright stimuli, in agreement with the predominance of dark contrasts in the sky but not on the ground. Therefore, the different cone types do not only form the basis of "color vision," but in addition represent distinct (achromatic) contrast-selective channels.
Design Of A Sorbent/desorbent Unit For Sample Pre-treatment Optimized For QMB Gas Sensors
NASA Astrophysics Data System (ADS)
Pennazza, G.; Santonico, M.; Martinelli, E.; Paolesse, R.; Di Natale, C.; Cristina, S.; D'Amico, A.
2009-05-01
Sample pre-treatment is a typical procedure in analytical chemistry aimed at improving the performance of analytical systems. In case of gas sensors sample pre-treatment systems are devised to overcome sensors limitations in terms of selectivity and sensitivity. For this purpose, systems based on adsorption and desorption processes driven by temperature conditioning have been illustrated. The involvement of large temperature ranges may pose problems when QMB gas sensors are used. In this work a study of such influences on the overall sensing properties of QMB sensors are illustrated. The results allowed the design of a pret-reatment unit coupled with a QMB gas sensors array optimized to operate in a suitable temperatures range. The performance of the system are illustrated by the partially separation of water vapor in a gas mixture, and by substantial improvement of the signal to noise ratio.
AlMasoud, Najla; Correa, Elon; Trivedi, Drupad K; Goodacre, Royston
2016-06-21
Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has successfully been used for the analysis of high molecular weight compounds, such as proteins and nucleic acids. By contrast, analysis of low molecular weight compounds with this technique has been less successful due to interference from matrix peaks which have a similar mass to the target analyte(s). Recently, a variety of modified matrices and matrix additives have been used to overcome these limitations. An increased interest in lipid analysis arose from the feasibility of correlating these components with many diseases, e.g. atherosclerosis and metabolic dysfunctions. Lipids have a wide range of chemical properties making their analysis difficult with traditional methods. MALDI-TOF-MS shows excellent potential for sensitive and rapid analysis of lipids, and therefore this study focuses on computational-analytical optimization of the analysis of five lipids (4 phospholipids and 1 acylglycerol) in complex mixtures using MALDI-TOF-MS with fractional factorial design (FFD) and Pareto optimality. Five different experimental factors were investigated using FFD which reduced the number of experiments performed by identifying 720 key experiments from a total of 8064 possible analyses. Factors investigated included the following: matrices, matrix preparations, matrix additives, additive concentrations, and deposition methods. This led to a significant reduction in time and cost of sample analysis with near optimal conditions. We discovered that the key factors used to produce high quality spectra were the matrix and use of appropriate matrix additives. PMID:27228355
Fajar, N M; Carro, A M; Lorenzo, R A; Fernandez, F; Cela, R
2008-08-01
The efficiency of microwave-assisted extraction with saponification (MAES) for the determination of seven polybrominated flame retardants (polybrominated biphenyls, PBBs; and polybrominated diphenyl ethers, PBDEs) in aquaculture samples is described and compared with microwave-assisted extraction (MAE). Chemometric techniques based on experimental designs and desirability functions were used for simultaneous optimization of the operational parameters used in both MAES and MAE processes. Application of MAES to this group of contaminants in aquaculture samples, which had not been previously applied to this type of analytes, was shown to be superior to MAE in terms of extraction efficiency, extraction time and lipid content extracted from complex matrices (0.7% as against 18.0% for MAE extracts). PBBs and PBDEs were determined by gas chromatography with micro-electron capture detection (GC-muECD). The quantification limits for the analytes were 40-750 pg g(-1) (except for BB-15, which was 1.43 ng g(-1)). Precision for MAES-GC-muECD (%RSD < 11%) was significantly better than for MAE-GC-muECD (%RSD < 20%). The accuracy of both optimized methods was satisfactorily demonstrated by analysis of appropriate certified reference material (CRM), WMF-01.
Fajar, N M; Carro, A M; Lorenzo, R A; Fernandez, F; Cela, R
2008-08-01
The efficiency of microwave-assisted extraction with saponification (MAES) for the determination of seven polybrominated flame retardants (polybrominated biphenyls, PBBs; and polybrominated diphenyl ethers, PBDEs) in aquaculture samples is described and compared with microwave-assisted extraction (MAE). Chemometric techniques based on experimental designs and desirability functions were used for simultaneous optimization of the operational parameters used in both MAES and MAE processes. Application of MAES to this group of contaminants in aquaculture samples, which had not been previously applied to this type of analytes, was shown to be superior to MAE in terms of extraction efficiency, extraction time and lipid content extracted from complex matrices (0.7% as against 18.0% for MAE extracts). PBBs and PBDEs were determined by gas chromatography with micro-electron capture detection (GC-muECD). The quantification limits for the analytes were 40-750 pg g(-1) (except for BB-15, which was 1.43 ng g(-1)). Precision for MAES-GC-muECD (%RSD < 11%) was significantly better than for MAE-GC-muECD (%RSD < 20%). The accuracy of both optimized methods was satisfactorily demonstrated by analysis of appropriate certified reference material (CRM), WMF-01. PMID:18608498
Chen, DI-WEN
2001-11-21
Airborne hazardous plumes inadvertently released during nuclear/chemical/biological incidents are mostly of unknown composition and concentration until measurements are taken of post-accident ground concentrations from plume-ground deposition of constituents. Unfortunately, measurements often are days post-incident and rely on hazardous manned air-vehicle measurements. Before this happens, computational plume migration models are the only source of information on the plume characteristics, constituents, concentrations, directions of travel, ground deposition, etc. A mobile ''lighter than air'' (LTA) system is being developed at Oak Ridge National Laboratory that will be part of the first response in emergency conditions. These interactive and remote unmanned air vehicles will carry light-weight detectors and weather instrumentation to measure the conditions during and after plume release. This requires a cooperative computationally organized, GPS-controlled set of LTA's that self-coordinate around the objectives in an emergency situation in restricted time frames. A critical step before an optimum and cost-effective field sampling and monitoring program proceeds is the collection of data that provides statistically significant information, collected in a reliable and expeditious manner. Efficient aerial arrangements of the detectors taking the data (for active airborne release conditions) are necessary for plume identification, computational 3-dimensional reconstruction, and source distribution functions. This report describes the application of stochastic or geostatistical simulations to delineate the plume for guiding subsequent sampling and monitoring designs. A case study is presented of building digital plume images, based on existing ''hard'' experimental data and ''soft'' preliminary transport modeling results of Prairie Grass Trials Site. Markov Bayes Simulation, a coupled Bayesian/geostatistical methodology, quantitatively combines soft information
Zhang, Zulin; Troldborg, Mads; Yates, Kyari; Osprey, Mark; Kerr, Christine; Hallett, Paul D; Baggaley, Nikki; Rhind, Stewart M; Dawson, Julian J C; Hough, Rupert L
2016-11-01
In many agricultural catchments of Europe and North America, pesticides occur at generally low concentrations with significant temporal variation. This poses several challenges for both monitoring and understanding ecological risks/impacts of these chemicals. This study aimed to compare the performance of passive and spot sampling strategies given the constraints of typical regulatory monitoring. Nine pesticides were investigated in a river currently undergoing regulatory monitoring (River Ugie, Scotland). Within this regulatory framework, spot and passive sampling were undertaken to understand spatiotemporal occurrence, mass loads and ecological risks. All the target pesticides were detected in water by both sampling strategies. Chlorotoluron was observed to be the dominant pesticide by both spot (maximum: 111.8ng/l, mean: 9.35ng/l) and passive sampling (maximum: 39.24ng/l, mean: 4.76ng/l). The annual pesticide loads were estimated to be 2735g and 1837g based on the spot and passive sampling data, respectively. The spatiotemporal trend suggested that agricultural activities were the primary source of the compounds with variability in loads explained in large by timing of pesticide applications and rainfall. The risk assessment showed chlorotoluron and chlorpyrifos posed the highest ecological risks with 23% of the chlorotoluron spot samples and 36% of the chlorpyrifos passive samples resulting in a Risk Quotient greater than 0.1. This suggests that mitigation measures might need to be taken to reduce the input of pesticides into the river. The overall comparison of the two sampling strategies supported the hypothesis that passive sampling tends to integrate the contaminants over a period of exposure and allows quantification of contamination at low concentration. The results suggested that within a regulatory monitoring context passive sampling was more suitable for flux estimation and risk assessment of trace contaminants which cannot be diagnosed by spot
Zhang, Zulin; Troldborg, Mads; Yates, Kyari; Osprey, Mark; Kerr, Christine; Hallett, Paul D; Baggaley, Nikki; Rhind, Stewart M; Dawson, Julian J C; Hough, Rupert L
2016-11-01
In many agricultural catchments of Europe and North America, pesticides occur at generally low concentrations with significant temporal variation. This poses several challenges for both monitoring and understanding ecological risks/impacts of these chemicals. This study aimed to compare the performance of passive and spot sampling strategies given the constraints of typical regulatory monitoring. Nine pesticides were investigated in a river currently undergoing regulatory monitoring (River Ugie, Scotland). Within this regulatory framework, spot and passive sampling were undertaken to understand spatiotemporal occurrence, mass loads and ecological risks. All the target pesticides were detected in water by both sampling strategies. Chlorotoluron was observed to be the dominant pesticide by both spot (maximum: 111.8ng/l, mean: 9.35ng/l) and passive sampling (maximum: 39.24ng/l, mean: 4.76ng/l). The annual pesticide loads were estimated to be 2735g and 1837g based on the spot and passive sampling data, respectively. The spatiotemporal trend suggested that agricultural activities were the primary source of the compounds with variability in loads explained in large by timing of pesticide applications and rainfall. The risk assessment showed chlorotoluron and chlorpyrifos posed the highest ecological risks with 23% of the chlorotoluron spot samples and 36% of the chlorpyrifos passive samples resulting in a Risk Quotient greater than 0.1. This suggests that mitigation measures might need to be taken to reduce the input of pesticides into the river. The overall comparison of the two sampling strategies supported the hypothesis that passive sampling tends to integrate the contaminants over a period of exposure and allows quantification of contamination at low concentration. The results suggested that within a regulatory monitoring context passive sampling was more suitable for flux estimation and risk assessment of trace contaminants which cannot be diagnosed by spot
Smiley Evans, Tierra; Barry, Peter A.; Gilardi, Kirsten V.; Goldstein, Tracey; Deere, Jesse D.; Fike, Joseph; Yee, JoAnn; Ssebide, Benard J; Karmacharya, Dibesh; Cranfield, Michael R.; Wolking, David; Smith, Brett; Mazet, Jonna A. K.; Johnson, Christine K.
2015-01-01
Free-ranging nonhuman primates are frequent sources of zoonotic pathogens due to their physiologic similarity and in many tropical regions, close contact with humans. Many high-risk disease transmission interfaces have not been monitored for zoonotic pathogens due to difficulties inherent to invasive sampling of free-ranging wildlife. Non-invasive surveillance of nonhuman primates for pathogens with high potential for spillover into humans is therefore critical for understanding disease ecology of existing zoonotic pathogen burdens and identifying communities where zoonotic diseases are likely to emerge in the future. We developed a non-invasive oral sampling technique using ropes distributed to nonhuman primates to target viruses shed in the oral cavity, which through bite wounds and discarded food, could be transmitted to people. Optimization was performed by testing paired rope and oral swabs from laboratory colony rhesus macaques for rhesus cytomegalovirus (RhCMV) and simian foamy virus (SFV) and implementing the technique with free-ranging terrestrial and arboreal nonhuman primate species in Uganda and Nepal. Both ubiquitous DNA and RNA viruses, RhCMV and SFV, were detected in oral samples collected from ropes distributed to laboratory colony macaques and SFV was detected in free-ranging macaques and olive baboons. Our study describes a technique that can be used for disease surveillance in free-ranging nonhuman primates and, potentially, other wildlife species when invasive sampling techniques may not be feasible. PMID:26046911
Pena, Ma Teresa; Vecino-Bello, X; Casais, Ma Carmen; Mejuto, Ma Carmen; Cela, Rafael
2012-02-01
A simple and rapid dispersive liquid-liquid microextraction method has been developed for the determination of 11 benzotriazoles and benzothiazoles in water samples. Tri-n-butylphosphate (TBP) was used as extractant, thus avoiding the use of toxic water-immiscible chlorinated solvents. The influence of several variables (e.g., type and volume of dispersant and extraction solvents, sample pH, ionic strength, etc.) on the performance of the sample preparation step was systematically evaluated. Analytical determinations were carried out by high-performance liquid chromatography with fluorescence and UV detection and liquid chromatography-electrospray ionization-tandem mass spectrometry. The optimized method exhibited a good precision level with relative standard deviation values between 3.7% and 8.4%. Extraction yields ranging from 67% to 97% were obtained for all of these considered compounds. Finally, the proposed method was successfully applied to the analysis of benzotriazoles and benzothiazoles in real water samples (tap, river, industrial waters, and treated and raw wastewaters). PMID:22134495
NASA Astrophysics Data System (ADS)
Taniai, G.; Oda, H.; Kurihara, M.; Hashimoto, S.
2010-12-01
Halogenated volatile organic compounds (HVOCs) produced in the marine environment are thought to play a key role in atmospheric reactions, particularly those involved in the global radiation budget and the depression of tropospheric and stratospheric ozone. To evaluate HVOCs concentrations in the various natural samples, we developed an automated dynamic headspace extraction method for the determination of 15 HVOCs, such as chloromethane, bromomethane, bromoethane, iodomethane, iodoethane, bromochloromethane, 1-iodopropane, 2-iodopropane, dibromomethane, bromodichloromethane, chloroiodomethane, chlorodibromomethane, bromoiodomethane, tribromomethane, and diiodomethane. Dynamic headspace system (GERSTEL DHS) was used to purge the gas phase above samples and to trap HVOCs on the adsorbent column from the purge gas. We measured the HVOCs concentrations in the adsorbent column with gas chromatograph (Agilent 6890N)- mass spectrometer (Agilent 5975C). In dynamic headspace system, an glass tube containing Tenax TA or Tenax GR was used as adsorbent column for the collection of 15 HVOCs. The parameters for purge and trap extraction, such as purge flow rate (ml/min), purge volume (ml), incubation time (min), and agitator speed (rpm), were optimized. The detection limits of HVOCs in water samples were 1270 pM (chloromethane), 103 pM (bromomethane), 42.1 pM (iodomethane), and 1.4 to 10.2 pM (other HVOCs). The repeatability (relative standard deviation) for 15 HVOCs were < 9 % except chloromethane (16.2 %) and bromomethane (11.0 %). On the basis of the measurements for various samples, we concluded that this analytical method is useful for the determination of wide range of HVOCs with boiling points between - 24°C (chloromethane) and 181°C (diiodomethane) for the liquid or viscous samples.
Sanchez, Gaëtan; Lecaignard, Françoise; Otman, Anatole; Maby, Emmanuel; Mattout, Jérémie
2016-01-01
The relatively young field of Brain-Computer Interfaces has promoted the use of electrophysiology and neuroimaging in real-time. In the meantime, cognitive neuroscience studies, which make extensive use of functional exploration techniques, have evolved toward model-based experiments and fine hypothesis testing protocols. Although these two developments are mostly unrelated, we argue that, brought together, they may trigger an important shift in the way experimental paradigms are being designed, which should prove fruitful to both endeavors. This change simply consists in using real-time neuroimaging in order to optimize advanced neurocognitive hypothesis testing. We refer to this new approach as the instantiation of an Active SAmpling Protocol (ASAP). As opposed to classical (static) experimental protocols, ASAP implements online model comparison, enabling the optimization of design parameters (e.g., stimuli) during the course of data acquisition. This follows the well-known principle of sequential hypothesis testing. What is radically new, however, is our ability to perform online processing of the huge amount of complex data that brain imaging techniques provide. This is all the more relevant at a time when physiological and psychological processes are beginning to be approached using more realistic, generative models which may be difficult to tease apart empirically. Based upon Bayesian inference, ASAP proposes a generic and principled way to optimize experimental design adaptively. In this perspective paper, we summarize the main steps in ASAP. Using synthetic data we illustrate its superiority in selecting the right perceptual model compared to a classical design. Finally, we briefly discuss its future potential for basic and clinical neuroscience as well as some remaining challenges. PMID:27458364
Jauzein, Cécile; Fricke, Anna; Mangialajo, Luisa; Lemée, Rodolphe
2016-06-15
In the framework of monitoring of benthic harmful algal blooms (BHABs), the most commonly reported sampling strategy is based on the collection of macrophytes. However, this methodology has some inherent problems. A potential alternative method uses artificial substrates that collect resuspended benthic cells. The current study defines main improvements in this technique, through the use of fiberglass screens during a bloom of Ostreopsis cf. ovata. A novel set-up for the deployment of artificial substrates in the field was tested, using an easy clip-in system that helped restrain substrates perpendicular to the water flow. An experiment was run in order to compare the cell collection efficiency of different mesh sizes of fiberglass screens and results suggested an optimal porosity of 1-3mm. The present study goes further on showing artificial substrates, such as fiberglass screens, as efficient tools for the monitoring and mitigation of BHABs. PMID:27048690
Yu, Yuqi; Wang, Jinan; Shao, Qiang E-mail: Jiye.Shi@ucb.com Zhu, Weiliang E-mail: Jiye.Shi@ucb.com; Shi, Jiye E-mail: Jiye.Shi@ucb.com
2015-03-28
The application of temperature replica exchange molecular dynamics (REMD) simulation on protein motion is limited by its huge requirement of computational resource, particularly when explicit solvent model is implemented. In the previous study, we developed a velocity-scaling optimized hybrid explicit/implicit solvent REMD method with the hope to reduce the temperature (replica) number on the premise of maintaining high sampling efficiency. In this study, we utilized this method to characterize and energetically identify the conformational transition pathway of a protein model, the N-terminal domain of calmodulin. In comparison to the standard explicit solvent REMD simulation, the hybrid REMD is much less computationally expensive but, meanwhile, gives accurate evaluation of the structural and thermodynamic properties of the conformational transition which are in well agreement with the standard REMD simulation. Therefore, the hybrid REMD could highly increase the computational efficiency and thus expand the application of REMD simulation to larger-size protein systems.
Jauzein, Cécile; Fricke, Anna; Mangialajo, Luisa; Lemée, Rodolphe
2016-06-15
In the framework of monitoring of benthic harmful algal blooms (BHABs), the most commonly reported sampling strategy is based on the collection of macrophytes. However, this methodology has some inherent problems. A potential alternative method uses artificial substrates that collect resuspended benthic cells. The current study defines main improvements in this technique, through the use of fiberglass screens during a bloom of Ostreopsis cf. ovata. A novel set-up for the deployment of artificial substrates in the field was tested, using an easy clip-in system that helped restrain substrates perpendicular to the water flow. An experiment was run in order to compare the cell collection efficiency of different mesh sizes of fiberglass screens and results suggested an optimal porosity of 1-3mm. The present study goes further on showing artificial substrates, such as fiberglass screens, as efficient tools for the monitoring and mitigation of BHABs.
Lee, Jae Hwan; Jia, Chunrong; Kim, Yong Doo; Kim, Hong Hyun; Pham, Tien Thang; Choi, Young Seok; Seo, Young Un; Lee, Ike Woo
2012-01-01
Trimethylsilanol (TMSOH) can cause damage to surfaces of scanner lenses in the semiconductor industry, and there is a critical need to measure and control airborne TMSOH concentrations. This study develops a thermal desorption (TD)-gas chromatography (GC)-mass spectrometry (MS) method for measuring trace-level TMSOH in occupational indoor air. Laboratory method optimization obtained best performance when using dual-bed tube configuration (100 mg of Tenax TA followed by 100 mg of Carboxen 569), n-decane as a solvent, and a TD temperature of 300°C. The optimized method demonstrated high recovery (87%), satisfactory precision (<15% for spiked amounts exceeding 1 ng), good linearity (R2 = 0.9999), a wide dynamic mass range (up to 500 ng), low method detection limit (2.8 ng m−3 for a 20-L sample), and negligible losses for 3-4-day storage. The field study showed performance comparable to that in laboratory and yielded first measurements of TMSOH, ranging from 1.02 to 27.30 μg/m3, in the semiconductor industry. We suggested future development of real-time monitoring techniques for TMSOH and other siloxanes for better maintenance and control of scanner lens in semiconductor wafer manufacturing. PMID:22966229
NASA Astrophysics Data System (ADS)
Oroza, C.; Zheng, Z.; Zhang, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.
2015-12-01
Recent advancements in wireless sensing technologies are enabling real-time application of spatially representative point-scale measurements to model hydrologic processes at the basin scale. A major impediment to the large-scale deployment of these networks is the difficulty of finding representative sensor locations and resilient wireless network topologies in complex terrain. Currently, observatories are structured manually in the field, which provides no metric for the number of sensors required for extrapolation, does not guarantee that point measurements are representative of the basin as a whole, and often produces unreliable wireless networks. We present a methodology that combines LiDAR data, pattern recognition, and stochastic optimization to simultaneously identify representative sampling locations, optimal sensor number, and resilient network topologies prior to field deployment. We compare the results of the algorithm to an existing 55-node wireless snow and soil network at the Southern Sierra Critical Zone Observatory. Existing data show that the algorithm is able to capture a broader range of key attributes affecting snow and soil moisture, defined by a combination of terrain, vegetation and soil attributes, and thus is better suited to basin-wide monitoring. We believe that adopting this structured, analytical approach could improve data quality, increase reliability, and decrease the cost of deployment for future networks.
Design and Sampling Plan Optimization for RT-qPCR Experiments in Plants: A Case Study in Blueberry.
Die, Jose V; Roman, Belen; Flores, Fernando; Rowland, Lisa J
2016-01-01
The qPCR assay has become a routine technology in plant biotechnology and agricultural research. It is unlikely to be technically improved, but there are still challenges which center around minimizing the variability in results and transparency when reporting technical data in support of the conclusions of a study. There are a number of aspects of the pre- and post-assay workflow that contribute to variability of results. Here, through the study of the introduction of error in qPCR measurements at different stages of the workflow, we describe the most important causes of technical variability in a case study using blueberry. In this study, we found that the stage for which increasing the number of replicates would be the most beneficial depends on the tissue used. For example, we would recommend the use of more RT replicates when working with leaf tissue, while the use of more sampling (RNA extraction) replicates would be recommended when working with stems or fruits to obtain the most optimal results. The use of more qPCR replicates provides the least benefit as it is the most reproducible step. By knowing the distribution of error over an entire experiment and the costs at each step, we have developed a script to identify the optimal sampling plan within the limits of a given budget. These findings should help plant scientists improve the design of qPCR experiments and refine their laboratory practices in order to conduct qPCR assays in a more reliable-manner to produce more consistent and reproducible data. PMID:27014296
Design and Sampling Plan Optimization for RT-qPCR Experiments in Plants: A Case Study in Blueberry.
Die, Jose V; Roman, Belen; Flores, Fernando; Rowland, Lisa J
2016-01-01
The qPCR assay has become a routine technology in plant biotechnology and agricultural research. It is unlikely to be technically improved, but there are still challenges which center around minimizing the variability in results and transparency when reporting technical data in support of the conclusions of a study. There are a number of aspects of the pre- and post-assay workflow that contribute to variability of results. Here, through the study of the introduction of error in qPCR measurements at different stages of the workflow, we describe the most important causes of technical variability in a case study using blueberry. In this study, we found that the stage for which increasing the number of replicates would be the most beneficial depends on the tissue used. For example, we would recommend the use of more RT replicates when working with leaf tissue, while the use of more sampling (RNA extraction) replicates would be recommended when working with stems or fruits to obtain the most optimal results. The use of more qPCR replicates provides the least benefit as it is the most reproducible step. By knowing the distribution of error over an entire experiment and the costs at each step, we have developed a script to identify the optimal sampling plan within the limits of a given budget. These findings should help plant scientists improve the design of qPCR experiments and refine their laboratory practices in order to conduct qPCR assays in a more reliable-manner to produce more consistent and reproducible data.
Design and Sampling Plan Optimization for RT-qPCR Experiments in Plants: A Case Study in Blueberry
Die, Jose V.; Roman, Belen; Flores, Fernando; Rowland, Lisa J.
2016-01-01
The qPCR assay has become a routine technology in plant biotechnology and agricultural research. It is unlikely to be technically improved, but there are still challenges which center around minimizing the variability in results and transparency when reporting technical data in support of the conclusions of a study. There are a number of aspects of the pre- and post-assay workflow that contribute to variability of results. Here, through the study of the introduction of error in qPCR measurements at different stages of the workflow, we describe the most important causes of technical variability in a case study using blueberry. In this study, we found that the stage for which increasing the number of replicates would be the most beneficial depends on the tissue used. For example, we would recommend the use of more RT replicates when working with leaf tissue, while the use of more sampling (RNA extraction) replicates would be recommended when working with stems or fruits to obtain the most optimal results. The use of more qPCR replicates provides the least benefit as it is the most reproducible step. By knowing the distribution of error over an entire experiment and the costs at each step, we have developed a script to identify the optimal sampling plan within the limits of a given budget. These findings should help plant scientists improve the design of qPCR experiments and refine their laboratory practices in order to conduct qPCR assays in a more reliable-manner to produce more consistent and reproducible data. PMID:27014296
Fakanya, Wellington M.; Tothill, Ibtisam E.
2014-01-01
The development of an electrochemical immunosensor for the biomarker, C-reactive protein (CRP), is reported in this work. CRP has been used to assess inflammation and is also used in a multi-biomarker system as a predictive biomarker for cardiovascular disease risk. A gold-based working electrode sensor was developed, and the types of electrode printing inks and ink curing techniques were then optimized. The electrodes with the best performance parameters were then employed for the construction of an immunosensor for CRP by immobilizing anti-human CRP antibody on the working electrode surface. A sandwich enzyme-linked immunosorbent assay (ELISA) was then constructed after sample addition by using anti-human CRP antibody labelled with horseradish peroxidase (HRP). The signal was generated by the addition of a mediator/substrate system comprised of 3,3,5',5'-Tetramethylbenzidine dihydrochloride (TMB) and hydrogen peroxide (H2O2). Measurements were conducted using chronoamperometry at −200 mV against an integrated Ag/AgCl reference electrode. A CRP limit of detection (LOD) of 2.2 ng·mL−1 was achieved in spiked serum samples, and performance agreement was obtained with reference to a commercial ELISA kit. The developed CRP immunosensor was able to detect a diagnostically relevant range of the biomarker in serum without the need for signal amplification using nanoparticles, paving the way for future development on a cardiac panel electrochemical point-of-care diagnostic device. PMID:25587427
NASA Astrophysics Data System (ADS)
Zhu, R.; Lin, Y.-S.; Lipp, J. S.; Meador, T. B.; Hinrichs, K.-U.
2014-09-01
Amino sugars are quantitatively significant constituents of soil and marine sediment, but their sources and turnover in environmental samples remain poorly understood. The stable carbon isotopic composition of amino sugars can provide information on the lifestyles of their source organisms and can be monitored during incubations with labeled substrates to estimate the turnover rates of microbial populations. However, until now, such investigation has been carried out only with soil samples, partly because of the much lower abundance of amino sugars in marine environments. We therefore optimized a procedure for compound-specific isotopic analysis of amino sugars in marine sediment, employing gas chromatography-isotope ratio mass spectrometry. The whole procedure consisted of hydrolysis, neutralization, enrichment, and derivatization of amino sugars. Except for the derivatization step, the protocol introduced negligible isotopic fractionation, and the minimum requirement of amino sugar for isotopic analysis was 20 ng, i.e., equivalent to ~8 ng of amino sugar carbon. Compound-specific stable carbon isotopic analysis of amino sugars obtained from marine sediment extracts indicated that glucosamine and galactosamine were mainly derived from organic detritus, whereas muramic acid showed isotopic imprints from indigenous bacterial activities. The δ13C analysis of amino sugars provides a valuable addition to the biomarker-based characterization of microbial metabolism in the deep marine biosphere, which so far has been lipid oriented and biased towards the detection of archaeal signals.
Heidarizadi, Elham; Tabaraki, Reza
2016-01-01
A sensitive cloud point extraction method for simultaneous determination of trace amounts of sunset yellow (SY), allura red (AR) and brilliant blue (BB) by spectrophotometry was developed. Experimental parameters such as Triton X-100 concentration, KCl concentration and initial pH on extraction efficiency of dyes were optimized using response surface methodology (RSM) with a Doehlert design. Experimental data were evaluated by applying RSM integrating a desirability function approach. The optimum condition for extraction efficiency of SY, AR and BB simultaneously were: Triton X-100 concentration 0.0635 mol L(-1), KCl concentration 0.11 mol L(-1) and pH 4 with maximum overall desirability D of 0.95. Correspondingly, the maximum extraction efficiency of SY, AR and BB were 100%, 92.23% and 95.69%, respectively. At optimal conditions, extraction efficiencies were 99.8%, 92.48% and 95.96% for SY, AR and BB, respectively. These values were only 0.2%, 0.25% and 0.27% different from the predicted values, suggesting that the desirability function approach with RSM was a useful technique for simultaneously dye extraction. Linear calibration curves were obtained in the range of 0.02-4 for SY, 0.025-2.5 for AR and 0.02-4 μg mL(-1) for BB under optimum condition. Detection limit based on three times the standard deviation of the blank (3Sb) was 0.009, 0.01 and 0.007 μg mL(-1) (n=10) for SY, AR and BB, respectively. The method was successfully used for the simultaneous determination of the dyes in different food samples. PMID:26653445
Heidarizadi, Elham; Tabaraki, Reza
2016-01-01
A sensitive cloud point extraction method for simultaneous determination of trace amounts of sunset yellow (SY), allura red (AR) and brilliant blue (BB) by spectrophotometry was developed. Experimental parameters such as Triton X-100 concentration, KCl concentration and initial pH on extraction efficiency of dyes were optimized using response surface methodology (RSM) with a Doehlert design. Experimental data were evaluated by applying RSM integrating a desirability function approach. The optimum condition for extraction efficiency of SY, AR and BB simultaneously were: Triton X-100 concentration 0.0635 mol L(-1), KCl concentration 0.11 mol L(-1) and pH 4 with maximum overall desirability D of 0.95. Correspondingly, the maximum extraction efficiency of SY, AR and BB were 100%, 92.23% and 95.69%, respectively. At optimal conditions, extraction efficiencies were 99.8%, 92.48% and 95.96% for SY, AR and BB, respectively. These values were only 0.2%, 0.25% and 0.27% different from the predicted values, suggesting that the desirability function approach with RSM was a useful technique for simultaneously dye extraction. Linear calibration curves were obtained in the range of 0.02-4 for SY, 0.025-2.5 for AR and 0.02-4 μg mL(-1) for BB under optimum condition. Detection limit based on three times the standard deviation of the blank (3Sb) was 0.009, 0.01 and 0.007 μg mL(-1) (n=10) for SY, AR and BB, respectively. The method was successfully used for the simultaneous determination of the dyes in different food samples.
Shao, Qiang; Yang, Lijiang; Gao, Yi Qin
2011-12-21
Our previous study showed that for the tested polypeptides which have similar β-hairpin structures but different sequences, their folding free energy pathways are dominantly determined by the turn conformational propensity. In this study, we study how the turn conformational propensity affects the structure of hairpins. The folding of two mutants of GB1p peptide (GB1m2 and GB1m3), which have the optimized turn sequence ((6)DDATK(11)T → (6)NPATG(11)K) with native structures unsolved, were simulated using integrated tempering sampling molecular dynamics simulations and the predicted stable structures were compared to wild-type GB1p. It was observed that the turn optimization of GB1p generates a more favored 5-residue type I(') turn in addition to the 6-residue type I turn in wild-type GB1p. As a result two distinctly different hairpin structures are formed corresponding to the "misfolded" (M) and the "folded" (F) states. M state is a one-residue-shifted asymmetric β-hairpin structure whereas F state has the similar symmetric hairpin structure as wild-type GB1p. The formation of the favored type I(') turn has a small free energy barrier and leads to the shifted β-hairpin structure, following the modified "zipping" model. The presence of disfavored type I turn structure makes the folding of a β-hairpin consistent with the "hydrophobic-core-centric" model. On the other hand, the folding simulations on other two GB1p mutants (GB1r1 and GBr2), which have the position of the hydrophobic core cluster further away from the turn compared to wild-type GB1p, showed that moving the hydrophobic core cluster away from the turn region destabilizes but does not change the hairpin structure. Therefore, the present study showed that the turn conformational propensity is a key factor in affecting not only the folding pathways but also the stable structure of β-hairpins, and the turn conformational change induced by the turn optimization leads to significant changes of
Sharma, M; Todor, D; Fields, E
2014-06-01
Purpose: To present a novel method allowing fast, true volumetric optimization of T and O HDR treatments and to quantify its benefits. Materials and Methods: 27 CT planning datasets and treatment plans from six consecutive cervical cancer patients treated with 4–5 intracavitary T and O insertions were used. Initial treatment plans were created with a goal of covering high risk (HR)-CTV with D90 > 90% and minimizing D2cc to rectum, bladder and sigmoid with manual optimization, approved and delivered. For the second step, each case was re-planned adding a new structure, created from the 100% prescription isodose line of the manually optimized plan to the existent physician delineated HR-CTV, rectum, bladder and sigmoid. New, more rigorous DVH constraints for the critical OARs were used for the optimization. D90 for the HR-CTV and D2cc for OARs were evaluated in both plans. Results: Two-step optimized plans had consistently smaller D2cc's for all three OARs while preserving good D90s for HR-CTV. On plans with “excellent” CTV coverage, average D90 of 96% (range 91–102), sigmoid D2cc was reduced on average by 37% (range 16–73), bladder by 28% (range 20–47) and rectum by 27% (range 15–45). Similar reductions were obtained on plans with “good” coverage, with an average D90 of 93% (range 90–99). For plans with inferior coverage, average D90 of 81%, an increase in coverage to 87% was achieved concurrently with D2cc reductions of 31%, 18% and 11% for sigmoid, bladder and rectum. Conclusions: A two-step DVH-based optimization can be added with minimal planning time increase, but with the potential of dramatic and systematic reductions of D2cc for OARs and in some cases with concurrent increases in target dose coverage. These single-fraction modifications would be magnified over the course of 4–5 intracavitary insertions and may have real clinical implications in terms of decreasing both acute and late toxicity.
Abdulra'uf, Lukman Bola; Sirhan, Ala Yahya; Tan, Guan Huat
2015-01-01
Sample preparation has been identified as the most important step in analytical chemistry and has been tagged as the bottleneck of analytical methodology. The current trend is aimed at developing cost-effective, miniaturized, simplified, and environmentally friendly sample preparation techniques. The fundamentals and applications of multivariate statistical techniques for the optimization of microextraction sample preparation and chromatographic analysis of pesticide residues are described in this review. The use of Placket-Burman, Doehlert matrix, and Box-Behnken designs are discussed. As observed in this review, a number of analytical chemists have combined chemometrics and microextraction techniques, which has helped to streamline sample preparation and improve sample throughput. PMID:26525235
NASA Astrophysics Data System (ADS)
Guarieiro, Lílian Lefol Nani; Pereira, Pedro Afonso de Paula; Torres, Ednildo Andrade; da Rocha, Gisele Olimpio; de Andrade, Jailson B.
Biodiesel is emerging as a renewable fuel, hence becoming a promising alternative to fossil fuels. Biodiesel can form blends with diesel in any ratio, and thus could replace partially, or even totally, diesel fuel in diesel engines what would bring a number of environmental, economical and social advantages. Although a number of studies are available on regulated substances, there is a gap of studies on unregulated substances, such as carbonyl compounds, emitted during the combustion of biodiesel, biodiesel-diesel and/or ethanol-biodiesel-diesel blends. CC is a class of hazardous pollutants known to be participating in photochemical smog formation. In this work a comparison was carried out between the two most widely used CC collection methods: C18 cartridges coated with an acid solution of 2,4-dinitrophenylhydrazine (2,4-DNPH) and impinger bottles filled in 2,4-DNPH solution. Sampling optimization was performed using a 2 2 factorial design tool. Samples were collected from the exhaust emissions of a diesel engine with biodiesel and operated by a steady-state dynamometer. In the central body of factorial design, the average of the sum of CC concentrations collected using impingers was 33.2 ppmV but it was only 6.5 ppmV for C18 cartridges. In addition, the relative standard deviation (RSD) was 4% for impingers and 37% for C18 cartridges. Clearly, the impinger system is able to collect CC more efficiently, with lower error than the C18 cartridge system. Furthermore, propionaldehyde was nearly not sampled by C18 system at all. For these reasons, the impinger system was chosen in our study. The optimized sampling conditions applied throughout this study were: two serially connected impingers each containing 10 mL of 2,4-DNPH solution at a flow rate of 0.2 L min -1 during 5 min. A profile study of the C1-C4 vapor-phase carbonyl compound emissions was obtained from exhaust of pure diesel (B0), pure biodiesel (B100) and biodiesel-diesel mixtures (B2, B5, B10, B20, B50, B
Golubeva, Yelena G; Smith, Roberta M; Sternberg, Lawrence R
2013-01-01
Laser microdissection is an invaluable tool in medical research that facilitates collecting specific cell populations for molecular analysis. Diversity of research targets (e.g., cancerous and precancerous lesions in clinical and animal research, cell pellets, rodent embryos, etc.) and varied scientific objectives, however, present challenges toward establishing standard laser microdissection protocols. Sample preparation is crucial for quality RNA, DNA and protein retrieval, where it often determines the feasibility of a laser microdissection project. The majority of microdissection studies in clinical and animal model research are conducted on frozen tissues containing native nucleic acids, unmodified by fixation. However, the variable morphological quality of frozen sections from tissues containing fat, collagen or delicate cell structures can limit or prevent successful harvest of the desired cell population via laser dissection. The CryoJane Tape-Transfer System®, a commercial device that improves cryosectioning outcomes on glass slides has been reported superior for slide preparation and isolation of high quality osteocyte RNA (frozen bone) during laser dissection. Considering the reported advantages of CryoJane for laser dissection on glass slides, we asked whether the system could also work with the plastic membrane slides used by UV laser based microdissection instruments, as these are better suited for collection of larger target areas. In an attempt to optimize laser microdissection slide preparation for tissues of different RNA stability and cryosectioning difficulty, we evaluated the CryoJane system for use with both glass (laser capture microdissection) and membrane (laser cutting microdissection) slides. We have established a sample preparation protocol for glass and membrane slides including manual coating of membrane slides with CryoJane solutions, cryosectioning, slide staining and dissection procedure, lysis and RNA extraction that facilitated
Vollmer, Tanja; Schottstedt, Volkmar; Bux, Juergen; Walther-Wenke, Gabriele; Knabbe, Cornelius; Dreier, Jens
2014-01-01
Background There is growing concern on the residual risk of bacterial contamination of platelet concentrates in Germany, despite the reduction of the shelf-life of these concentrates and the introduction of bacterial screening. In this study, the applicability of the BactiFlow flow cytometric assay for bacterial screening of platelet concentrates on day 2 or 3 of their shelf-life was assessed in two German blood services. The results were used to evaluate currently implemented or newly discussed screening strategies. Materials and methods Two thousand and ten apheresis platelet concentrates were tested on day 2 or day 3 after donation using BactiFlow flow cytometry. Reactive samples were confirmed by the BacT/Alert culture system. Results Twenty-four of the 2,100 platelet concentrates tested were reactive in the first test by BactiFlow. Of these 24 platelet concentrates, 12 were false-positive and the other 12 were initially reactive. None of the microbiological cultures of the initially reactive samples was positive. Parallel examination of 1,026 platelet concentrates by culture revealed three positive platelet concentrates with bacteria detected only in the anaerobic culture bottle and identified as Staphylococcus species. Two platelet concentrates were confirmed positive for Staphylcoccus epidermidis by culture. Retrospective analysis of the growth kinetics of the bacteria indicated that the bacterial titres were most likely below the diagnostic sensitivity of the BactiFlow assay (<300 CFU/mL) and probably had no transfusion relevance. Conclusions The BactiFlow assay is very convenient for bacterial screening of platelet concentrates independently of the testing day and the screening strategy. Although the optimal screening strategy could not be defined, this study provides further data to help achieve this goal. PMID:24887230
Sun, Phillip Zhe; Wang, Enfeng; Cheung, Jerry S.; Zhang, Xiaoan; Benner, Thomas; Sorensen, A Gregory
2011-01-01
Chemical exchange saturation transfer (CEST) MRI is capable of measuring dilute labile protons and microenvironment properties; however, the CEST contrast is also dependent upon experimental conditions, particularly, the RF irradiation scheme. Although continuous-wave (CW) RF irradiation has been conventionally utilized, the RF pulse duration or duty cycle are limited on most clinical systems, for which pulsed RF irradiation must be chosen. Here, conventional numerical simulation was extended to describe pulsed-CEST MRI contrast as a function of RF pulse parameters (i.e., RF pulse duration and flip angle) and labile proton properties (i.e., exchange rate and chemical shift). For diamagnetic CEST agents undergoing slow/intermediate chemical exchange, our simulation showed a linear regression relationship between the optimal mean RF power for pulsed-CEST MRI and that of CW-CEST MRI. Worth noting, the optimized pulsed-CEST contrast was approximately equal to that of CW-CEST MRI for exchange rates below 50 s−1, as confirmed experimentally using a multi-compartment pH phantom. Moreover, acute stroke animals were imaged with both pulsed- and CW- amide protons CEST MRI, which showed similar contrast. In summary, our study elucidated the RF irradiation dependence of pulsed-CEST MRI contrast, providing useful insights to guide its experimental optimization and quantification. PMID:21437977
Dolan, C V; Boomsma, D I
1998-05-01
Percentages of extremely concordant and extremely discordant sib pairs are calculated that maximize the power to detect a quantitative trait locus (QTL) under a variety of circumstances using the EDAC test. We assume a large fixed number of randomly sampled sib pairs, such as one would hope to find in the large twin registries, and limited resources to genotype a certain number of selected sib pairs. Our aim is to investigate whether optimal selection can be achieved when prior knowledge concerning the QTL gene action, QTL allele frequency, QTL effect size, and background (residual) sib correlation is limited or absent. To this end we calculate the best selection percentages for a large number of models, which differ in QTL gene action allele frequency, background correlation, and QTL effect size. By averaging these percentages over gene action, over allele frequency, over gene action, and over allele frequencies, we arrive at general recommendations concerning selection percentages. The soundness of these recommendations is subsequently in a number of test cases. PMID:9670595
Masson, Perrine; Alves, Alexessander Couto; Ebbels, Timothy M D; Nicholson, Jeremy K; Want, Elizabeth J
2010-09-15
A series of six protocols were evaluated for UPLC-MS based untargeted metabolic profiling of liver extracts in terms of reproducibility and number of metabolite features obtained. These protocols, designed to extract both polar and nonpolar metabolites, were based on (i) a two stage extraction approach or (ii) a simultaneous extraction in a biphasic mixture, employing different volumes and combinations of extraction and resuspension solvents. A multivariate statistical strategy was developed to allow comparison of the multidimensional variation between the methods. The optimal protocol for profiling both polar and nonpolar metabolites was found to be an aqueous extraction with methanol/water followed by an organic extraction with dichloromethane/methanol, with resuspension of the dried extracts in methanol/water before UPLC-MS analysis. This protocol resulted in a median CV of feature intensities among experimental replicates of <20% for aqueous extracts and <30% for organic extracts. These data demonstrate the robustness of the proposed protocol for extracting metabolites from liver samples and make it well suited for untargeted liver profiling in studies exploring xenobiotic hepatotoxicity and clinical investigations of liver disease. The generic nature of this protocol facilitates its application to other tissues, for example, brain or lung, enhancing its utility in clinical and toxicological studies. PMID:20715759
Khajeh, Mostafa; Golzary, Ali Reza
2014-10-15
In this work, zinc nanoparticles-chitosan based solid phase extraction has been developed for separation and preconcentration of trace amount of methyl orange from water samples. Artificial neural network-cuckoo optimization algorithm has been employed to develop the model for simulation and optimization of this method. The pH, volume of elution solvent, mass of zinc oxide nanoparticles-chitosan, flow rate of sample and elution solvent were the input variables, while recovery of methyl orange was the output. The optimum conditions were obtained by cuckoo optimization algorithm. At the optimum conditions, the limit of detections of 0.7μgL(-1)was obtained for the methyl orange. The developed procedure was then applied to the separation and preconcentration of methyl orange from water samples. PMID:24835725
Khajeh, Mostafa; Golzary, Ali Reza
2014-10-15
In this work, zinc nanoparticles-chitosan based solid phase extraction has been developed for separation and preconcentration of trace amount of methyl orange from water samples. Artificial neural network-cuckoo optimization algorithm has been employed to develop the model for simulation and optimization of this method. The pH, volume of elution solvent, mass of zinc oxide nanoparticles-chitosan, flow rate of sample and elution solvent were the input variables, while recovery of methyl orange was the output. The optimum conditions were obtained by cuckoo optimization algorithm. At the optimum conditions, the limit of detections of 0.7μgL(-1)was obtained for the methyl orange. The developed procedure was then applied to the separation and preconcentration of methyl orange from water samples.
NASA Astrophysics Data System (ADS)
Khajeh, Mostafa; Golzary, Ali Reza
2014-10-01
In this work, zinc nanoparticles-chitosan based solid phase extraction has been developed for separation and preconcentration of trace amount of methyl orange from water samples. Artificial neural network-cuckoo optimization algorithm has been employed to develop the model for simulation and optimization of this method. The pH, volume of elution solvent, mass of zinc oxide nanoparticles-chitosan, flow rate of sample and elution solvent were the input variables, while recovery of methyl orange was the output. The optimum conditions were obtained by cuckoo optimization algorithm. At the optimum conditions, the limit of detections of 0.7 μg L-1was obtained for the methyl orange. The developed procedure was then applied to the separation and preconcentration of methyl orange from water samples.
NASA Astrophysics Data System (ADS)
Peng, J.; Liu, Q.; Wen, J.; Fan, W.; Dou, B.
2015-12-01
Coarse-resolution satellite albedo products are increasingly applied in geographical researches because of their capability to characterize the spatio-temporal patterns of land surface parameters. In the long-term validation of coarse-resolution satellite products with ground measurements, the scale effect, i.e., the mismatch between point measurement and pixel observation becomes the main challenge, particularly over heterogeneous land surfaces. Recent advances in Wireless Sensor Networks (WSN) technologies offer an opportunity for validation using multi-point observations instead of single-point observation. The difficulty is to ensure the representativeness of the WSN in heterogeneous areas with limited nodes. In this study, the objective is to develop a ground-based spatial sampling strategy through consideration of the historical prior knowledge and avoidance of the information redundancy between different sensor nodes. Taking albedo as an example. First, we derive monthly local maps of albedo from 30-m HJ CCD images a 3-year period. Second, we pick out candidate points from the areas with higher temporal stability which helps to avoid the transition or boundary areas. Then, the representativeness (r) of each candidate point is evaluated through the correlational analysis between the point-specific and area-average time sequence albedo vector. The point with the highest r was noted as the new sensor point. Before electing a new point, the vector component of the selected points should be taken out from the vectors in the following correlational analysis. The selection procedure would be ceased once if the integral representativeness (R) meets the accuracy requirement. Here, the sampling method is adapted to both single-parameter and multi-parameter situations. Finally, it is shown that this sampling method has been effectively worked in the optimized layout of Huailai remote sensing station in China. The coarse resolution pixel covering this station could be
Multidimensional explicit difference schemes for hyperbolic conservation laws
NASA Technical Reports Server (NTRS)
Vanleer, B.
1983-01-01
First and second order explicit difference schemes are derived for a three dimensional hyperbolic system of conservation laws, without recourse to dimensional factorization. All schemes are upwind (backward) biased and optimally stable.
Multidimensional explicit difference schemes for hyperbolic conservation laws
NASA Technical Reports Server (NTRS)
Van Leer, B.
1984-01-01
First- and second-order explicit difference schemes are derived for a three-dimensional hyperbolic system of conservation laws, without recourse to dimensional factorization. All schemes are upwind biased and optimally stable.
Wan, Xinlong; Kim, Min Jee; Kim, Iksoo
2013-11-01
We newly sequenced mitochondrial genomes of Spodoptera litura and Cnaphalocrocis medinalis belonging to Lepidoptera to obtain further insight into mitochondrial genome evolution in this group and investigated the influence of optimal strategies on phylogenetic reconstruction of Lepidoptera. Estimation of p-distances of each mitochondrial gene for available taxonomic levels has shown the highest value in ND6, whereas the lowest values in COI and COII at the nucleotide level, suggesting different utility of each gene for different hierarchical group when individual genes are utilized for phylogenetic analysis. Phylogenetic analyses mainly yielded the relationships (((((Bombycoidea + Geometroidea) + Noctuoidea) + Pyraloidea) + Papilionoidea) + Tortricoidea), evidencing the polyphyly of Macrolepidoptera. The Noctuoidea concordantly recovered the familial relationships (((Arctiidae + Lymantriidae) + Noctuidae) + Notodontidae). The tests of optimality strategies, such as exclusion of third codon positions, inclusion of rRNA and tRNA genes, data partitioning, RY recoding approach, and recoding nucleotides into amino acids suggested that the majority of the strategies did not substantially alter phylogenetic topologies or nodal supports, except for the sister relationship between Lycaenidae and Pieridae only in the amino acid dataset, which was in contrast to the sister relationship between Lycaenidae and Nymphalidae in Papilionoidea in the remaining datasets.
NASA Astrophysics Data System (ADS)
Aspinall, M. D.; Joyce, M. J.; Mackin, R. O.; Jarrah, Z.; Boston, A. J.; Nolan, P. J.; Peyton, A. J.; Hawkes, N. P.
2009-01-01
A unique, digital time pick-off method, known as sample-interpolation timing (SIT) is described. This method demonstrates the possibility of improved timing resolution for the digital measurement of time of flight compared with digital replica-analogue time pick-off methods for signals sampled at relatively low rates. Three analogue timing methods have been replicated in the digital domain (leading-edge, crossover and constant-fraction timing) for pulse data sampled at 8 GSa s-1. Events arising from the 7Li(p, n)7Be reaction have been detected with an EJ-301 organic liquid scintillator and recorded with a fast digital sampling oscilloscope. Sample-interpolation timing was developed solely for the digital domain and thus performs more efficiently on digital signals compared with analogue time pick-off methods replicated digitally, especially for fast signals that are sampled at rates that current affordable and portable devices can achieve. Sample interpolation can be applied to any analogue timing method replicated digitally and thus also has the potential to exploit the generic capabilities of analogue techniques with the benefits of operating in the digital domain. A threshold in sampling rate with respect to the signal pulse width is observed beyond which further improvements in timing resolution are not attained. This advance is relevant to many applications in which time-of-flight measurement is essential.
NASA Technical Reports Server (NTRS)
Drusano, George L.
1991-01-01
The optimal sampling theory is evaluated in applications to studies related to the distribution and elimination of several drugs (including ceftazidime, piperacillin, and ciprofloxacin), using the SAMPLE module of the ADAPT II package of programs developed by D'Argenio and Schumitzky (1979, 1988) and comparing the pharmacokinetic parameter values with results obtained by traditional ten-sample design. The impact of the use of optimal sampling was demonstrated in conjunction with NONMEM (Sheiner et al., 1977) approach, in which the population is taken as the unit of analysis, allowing even fragmentary patient data sets to contribute to population parameter estimates. It is shown that this technique is applicable in both the single-dose and the multiple-dose environments. The ability to study real patients made it possible to show that there was a bimodal distribution in ciprofloxacin nonrenal clearance.
NASA Astrophysics Data System (ADS)
Fridjine, S.; Amlouk, M.
In this study, we define a synthetic parameter: optothermal expansivity as a quantitative guide to evaluating and optimizing both the thermal and the optical performance of PV-T functional materials. The definition of this parameter, ψAB (Amlouk-Boubaker parameter), takes into account the thermal diffusivity and the optical effective absorptivity of the material. The values of this parameter, which seems to be a characteristic one, correspond to the total volume that contains a fixed amount of heat per unit time (m3 s-1) and can be considered as a 3D velocity of the transmitted heat inside the material. As the PV-T combined devices need to have simultaneous optical and thermal efficiency, we try to investigate some recently proposed materials (β-SnS2, In2S3, ZnS1-xSex|0 ≤x<0.5 and Zn-doped thioindate compounds) using the newly established ψAB/Eg abacus.
ERIC Educational Resources Information Center
Geldhof, G. John; Gestsdottir, Steinunn; Stefansson, Kristjan; Johnson, Sara K.; Bowers, Edmond P.; Lerner, Richard M.
2015-01-01
Intentional self-regulation (ISR) undergoes significant development across the life span. However, our understanding of ISR's development and function remains incomplete, in part because the field's conceptualization and measurement of ISR vary greatly. A key sample case involves how Baltes and colleagues' Selection, Optimization,…
Liu Yu; Guo Qiuquan; Nie Hengyong; Lau, W. M.; Yang Jun
2009-12-15
The mechanism of dynamic force modes has been successfully applied to many atomic force microscopy (AFM) applications, such as tapping mode and phase imaging. The high-order flexural vibration modes are recent advancement of AFM dynamic force modes. AFM optical lever detection sensitivity plays a major role in dynamic force modes because it determines the accuracy in mapping surface morphology, distinguishing various tip-surface interactions, and measuring the strength of the tip-surface interactions. In this work, we have analyzed optimization and calibration of the optical lever detection sensitivity for an AFM cantilever-tip ensemble vibrating in high-order flexural modes and simultaneously experiencing a wide range and variety of tip-sample interactions. It is found that the optimal detection sensitivity depends on the vibration mode, the ratio of the force constant of tip-sample interactions to the cantilever stiffness, as well as the incident laser spot size and its location on the cantilever. It is also found that the optimal detection sensitivity is less dependent on the strength of tip-sample interactions for high-order flexural modes relative to the fundamental mode, i.e., tapping mode. When the force constant of tip-sample interactions significantly exceeds the cantilever stiffness, the optimal detection sensitivity occurs only when the laser spot locates at a certain distance from the cantilever-tip end. Thus, in addition to the 'globally optimized detection sensitivity', the 'tip optimized detection sensitivity' is also determined. Finally, we have proposed a calibration method to determine the actual AFM detection sensitivity in high-order flexural vibration modes against the static end-load sensitivity that is obtained traditionally by measuring a force-distance curve on a hard substrate in the contact mode.
Kwak, Minjung; Jung, Sin-Ho
2014-01-01
Summary Phase II clinical trials are often conducted to determine whether a new treatment is sufficiently promising to warrant a major controlled clinical evaluation against a standard therapy. We consider single-arm phase II clinical trials with right censored survival time responses where the ordinary one-sample logrank test is commonly used for testing the treatment efficacy. For planning such clinical trials this paper presents two-stage designs that are optimal in the sense that the expected sample size is minimized if the new regimen has low efficacy subject to constraints of the type I and type II errors. Two-stage designs which minimize the maximal sample size are also determined. Optimal and minimax designs for a range of design parameters are tabulated along with examples. PMID:24338995
NASA Astrophysics Data System (ADS)
Dyck, Tobias; Haas, Stefan
2016-04-01
We present a novel approach to obtaining a quick prediction of a sample's topography after the treatment with direct laser interference patterning (DLIP) . The underlying model uses the parameters of the experimental setup as input, calculates the laser intensity distribution in the interference volume and determines the corresponding heat intake into the material as well as the subsequent heat diffusion within the material. The resulting heat distribution is used to determine the topography of the sample after the DLIP treatment . This output topography is in good agreement with corresponding experiments. The model can be applied in optimization algorithms in which a sample topography needs to be engineered in order to suit the needs of a given device. A prominent example for such an application is the optimization of the light scattering properties of the textured interfaces in a solar cell.
Establishing a Proficiency Testing Scheme for Drinking Water Radiochemistry
Brookman, Brian
2008-08-14
As part of its international water proficiency testing (PT) scheme, 'Aquacheck', the LGC Proficiency Testing Group has established a new water radiochemistry PT scheme. The PT scheme is aimed at laboratories who undertake radiochemical analysis on drinking water samples as part of an environmental monitoring programme. Following a scheme design and feasibility study, the new scheme was established to monitor the laboratory performance of participants undertaking the determination of gross alpha, gross beta and tritium activity. Three rounds of the new water radiochemistry PT scheme are now complete. This paper explains the process of establishing such a scheme, reviews the results so far, and addresses future development of the scheme.
Pay scheme preferences and health policy objectives.
Abelsen, Birgit
2011-04-01
This paper studies the preferences among healthcare workers towards pay schemes involving different levels of risk. It identifies which pay scheme individuals would prefer for themselves, and which they think is best in furthering health policy objectives. The paper adds, methodologically, a way of defining pay schemes that include different levels of risk. A questionnaire was mailed to a random sample of 1111 dentists. Respondents provided information about their current and preferred pay schemes, and indicated which pay scheme, in their opinion, would best further overall health policy objectives. A total of 504 dentists (45%) returned the questionnaire, and there was no indication of systematic non-response bias. All public dentists had a current pay scheme based on a fixed salary and the majority of individuals preferred a pay scheme with more income risk. Their preferred pay schemes coincided with the ones believed to further stabilise healthcare personnel. The predominant current pay scheme among private dentists was based solely on individual output, and the majority of respondents preferred this pay scheme. In addition, their preferred pay schemes coincided with the ones believed to further efficiency objectives. Both public and private dentists believed that pay schemes, furthering efficiency objectives, had to include more performance-related pay than the ones believed to further stability and quality objectives. PMID:20565995
Risticevic, Sanja; DeEll, Jennifer R; Pawliszyn, Janusz
2012-08-17
Metabolomics currently represents one of the fastest growing high-throughput molecular analysis platforms that refer to the simultaneous and unbiased analysis of metabolite pools constituting a particular biological system under investigation. In response to the ever increasing interest in development of reliable methods competent with obtaining a complete and accurate metabolomic snapshot for subsequent identification, quantification and profiling studies, the purpose of the current investigation is to test the feasibility of solid phase microextraction for advanced fingerprinting of volatile and semivolatile metabolites in complex samples. In particular, the current study is focussed on the development and optimization of solid phase microextraction (SPME) - comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-ToFMS) methodology for metabolite profiling of apples (Malus × domestica Borkh.). For the first time, GC × GC attributes in terms of molecular structure-retention relationships and utilization of two-dimensional separation space on orthogonal GC × GC setup were exploited in the field of SPME method optimization for complex sample analysis. Analytical performance data were assessed in terms of method precision when commercial coatings are employed in spiked metabolite aqueous sample analysis. The optimized method consisted of the implementation of direct immersion SPME (DI-SPME) extraction mode and its application to metabolite profiling of apples, and resulted in a tentative identification of 399 metabolites and the composition of a metabolite database far more comprehensive than those obtainable with classical one-dimensional GC approaches. Considering that specific metabolome constituents were for the first time reported in the current study, a valuable approach for future advanced fingerprinting studies in the field of fruit biology is proposed. The current study also intensifies the understanding of SPME
NASA Astrophysics Data System (ADS)
Brum, Daniel M.; Lima, Claudio F.; Robaina, Nicolle F.; Fonseca, Teresa Cristina O.; Cassella, Ricardo J.
2011-05-01
The present paper reports the optimization for Cu, Fe and Pb determination in naphtha by graphite furnace atomic absorption spectrometry (GF AAS) employing a strategy based on the injection of the samples as detergent emulsions. The method was optimized in relation to the experimental conditions for the emulsion formation and taking into account that the three analytes (Cu, Fe and Pb) should be measured in the same emulsion. The optimization was performed in a multivariate way by employing a three-variable Doehlert design and a multiple response strategy. For this purpose, the individual responses of the three analytes were combined, yielding a global response that was employed as a dependent variable. The three factors related to the optimization process were: the concentration of HNO 3, the concentration of the emulsifier agent (Triton X-100 or Triton X-114) in aqueous solution used to emulsify the sample and the volume of solution. At optimum conditions, it was possible to obtain satisfactory results with an emulsion formed by mixing 4 mL of the samples with 1 mL of a 4.7% w/v Triton X-100 solution prepared in 10% v/v HNO 3 medium. The resulting emulsion was stable for 250 min, at least, and provided enough sensitivity to determine the three analytes in the five samples tested. A recovery test was performed to evaluate the accuracy of the optimized procedure and recovery rates, in the range of 88-105%; 94-118% and 95-120%, were verified for Cu, Fe and Pb, respectively.
Lamiable, A; Thevenet, P; Tufféry, P
2016-08-01
Hidden Markov Model derived structural alphabets are a probabilistic framework in which the complete conformational space of a peptidic chain is described in terms of probability distributions that can be sampled to identify conformations of largest probabilities. Here, we assess how three strategies to sample sub-optimal conformations-Viterbi k-best, forward backtrack and a taboo sampling approach-can lead to the efficient generation of peptide conformations. We show that the diversity of sampling is essential to compensate biases introduced in the estimates of the probabilities, and we find that only the forward backtrack and a taboo sampling strategies can efficiently generate native or near-native models. Finally, we also find such approaches are as efficient as former protocols, while being one order of magnitude faster, opening the door to the large scale de novo modeling of peptides and mini-proteins. © 2016 Wiley Periodicals, Inc. PMID:27317417
Lee, Seunggeun; Emond, Mary J.; Bamshad, Michael J.; Barnes, Kathleen C.; Rieder, Mark J.; Nickerson, Deborah A.; Christiani, David C.; Wurfel, Mark M.; Lin, Xihong
2012-01-01
We propose in this paper a unified approach for testing the association between rare variants and phenotypes in sequencing association studies. This approach maximizes power by adaptively using the data to optimally combine the burden test and the nonburden sequence kernel association test (SKAT). Burden tests are more powerful when most variants in a region are causal and the effects are in the same direction, whereas SKAT is more powerful when a large fraction of the variants in a region are noncausal or the effects of causal variants are in different directions. The proposed unified test maintains the power in both scenarios. We show that the unified test corresponds to the optimal test in an extended family of SKAT tests, which we refer to as SKAT-O. The second goal of this paper is to develop a small-sample adjustment procedure for the proposed methods for the correction of conservative type I error rates of SKAT family tests when the trait of interest is dichotomous and the sample size is small. Both small-sample-adjusted SKAT and the optimal unified test (SKAT-O) are computationally efficient and can easily be applied to genome-wide sequencing association studies. We evaluate the finite sample performance of the proposed methods using extensive simulation studies and illustrate their application using the acute-lung-injury exome-sequencing data of the National Heart, Lung, and Blood Institute Exome Sequencing Project. PMID:22863193
The use of Thompson sampling to increase estimation precision.
Kaptein, Maurits
2015-06-01
In this article, we consider a sequential sampling scheme for efficient estimation of the difference between the means of two independent treatments when the population variances are unequal across groups. The sampling scheme proposed is based on a solution to bandit problems called Thompson sampling. While this approach is most often used to maximize the cumulative payoff over competing treatments, we show that the same method can also be used to balance exploration and exploitation when the aim of the experimenter is to efficiently increase estimation precision. We introduce this novel design optimization method and, by simulation, show its effectiveness.
Dorn-In, Samart; Bassitta, Rupert; Schwaiger, Karin; Bauer, Johann; Hölzel, Christina S
2015-06-01
Universal primers targeting the bacterial 16S-rRNA-gene allow quantification of the total bacterial load in variable sample types by qPCR. However, many universal primer pairs also amplify DNA of plants or even of archaea and other eukaryotic cells. By using these primers, the total bacterial load might be misevaluated, whenever samples contain high amounts of non-target DNA. Thus, this study aimed to provide primer pairs which are suitable for quantification and identification of bacterial DNA in samples such as feed, spices and sample material from digesters. For 42 primers, mismatches to the sequence of chloroplasts and mitochondria of plants were evaluated. Six primer pairs were further analyzed with regard to the question whether they anneal to DNA of archaea, animal tissue and fungi. Subsequently they were tested with sample matrix such as plants, feed, feces, soil and environmental samples. To this purpose, the target DNA in the samples was quantified by qPCR. The PCR products of plant and feed samples were further processed for the Single Strand Conformation Polymorphism method followed by sequence analysis. The sequencing results revealed that primer pair 335F/769R amplified only bacterial DNA in samples such as plants and animal feed, in which the DNA of plants prevailed.
Abarshi, M M; Mohammed, I U; Wasswa, P; Hillocks, R J; Holt, J; Legg, J P; Seal, S E; Maruthi, M N
2010-02-01
Sampling procedures and diagnostic protocols were optimized for accurate diagnosis of Cassava brown streak virus (CBSV) (genus Ipomovirus, family Potyviridae). A cetyl trimethyl ammonium bromide (CTAB) method was optimized for sample preparation from infected cassava plants and compared with the RNeasy plant mini kit (Qiagen) for sensitivity, reproducibility and costs. CBSV was detectable readily in total RNAs extracted using either method. The major difference between the two methods was in the cost of consumables, with the CTAB 10x cheaper (0.53 pounds sterling=US$0.80 per sample) than the RNeasy method (5.91 pounds sterling=US$8.86 per sample). A two-step RT-PCR (1.34 pounds sterling=US$2.01 per sample), although less sensitive, was at least 3-times cheaper than a one-step RT-PCR (4.48 pounds sterling=US$6.72). The two RT-PCR tests revealed consistently the presence of CBSV both in symptomatic and asymptomatic leaves and indicated that asymptomatic leaves can be used reliably for virus diagnosis. Depending on the accuracy required, sampling 100-400 plants per field is an appropriate recommendation for CBSD diagnosis, giving a 99.9% probability of detecting a disease incidence of 6.7-1.7%, respectively. CBSV was detected at 10(-4)-fold dilutions in composite sampling, indicating that the most efficient way to index many samples for CBSV will be to screen pooled samples. The diagnostic protocols described below are reliable and the most cost-effective methods available currently for detecting CBSV.
Dispersion-relation-preserving schemes for computational aeroacoustics
NASA Technical Reports Server (NTRS)
Tam, Christopher K. W.; Webb, Jay C.
1992-01-01
Finite difference schemes that have the same dispersion relations as the original partial differential equations are referred to as dispersion-relation-preserving (DRP) schemes. A method to construct time marching DRP schemes by optimizing the finite difference approximations of the space and time derivatives in the wave number and frequency space is presented. A sequence of numerical simulations is then performed.
Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies
Hampton, Jerrad; Doostan, Alireza
2015-01-01
Sampling orthogonal polynomial bases via Monte Carlo is of interest for uncertainty quantification of models with random inputs, using Polynomial Chaos (PC) expansions. It is known that bounding a probabilistic parameter, referred to as coherence, yields a bound on the number of samples necessary to identify coefficients in a sparse PC expansion via solution to an ℓ{sub 1}-minimization problem. Utilizing results for orthogonal polynomials, we bound the coherence parameter for polynomials of Hermite and Legendre type under their respective natural sampling distribution. In both polynomial bases we identify an importance sampling distribution which yields a bound with weaker dependence on the order of the approximation. For more general orthonormal bases, we propose the coherence-optimal sampling: a Markov Chain Monte Carlo sampling, which directly uses the basis functions under consideration to achieve a statistical optimality among all sampling schemes with identical support. We demonstrate these different sampling strategies numerically in both high-order and high-dimensional, manufactured PC expansions. In addition, the quality of each sampling method is compared in the identification of solutions to two differential equations, one with a high-dimensional random input and the other with a high-order PC expansion. In both cases, the coherence-optimal sampling scheme leads to similar or considerably improved accuracy.
NASA Astrophysics Data System (ADS)
Dou, Tai H.; Min, Yugang; Neylon, John; Thomas, David; Kupelian, Patrick; Santhanam, Anand P.
2016-03-01
Deformable image registration (DIR) is an important step in radiotherapy treatment planning. An optimal input registration parameter set is critical to achieve the best registration performance with the specific algorithm. Methods In this paper, we investigated a parameter optimization strategy for Optical-flow based DIR of the 4DCT lung anatomy. A novel fast simulated annealing with adaptive Monte Carlo sampling algorithm (FSA-AMC) was investigated for solving the complex non-convex parameter optimization problem. The metric for registration error for a given parameter set was computed using landmark-based mean target registration error (mTRE) between a given volumetric image pair. To reduce the computational time in the parameter optimization process, a GPU based 3D dense optical-flow algorithm was employed for registering the lung volumes. Numerical analyses on the parameter optimization for the DIR were performed using 4DCT datasets generated with breathing motion models and open-source 4DCT datasets. Results showed that the proposed method efficiently estimated the optimum parameters for optical-flow and closely matched the best registration parameters obtained using an exhaustive parameter search method.
An adaptive additive inflation scheme for Ensemble Kalman Filters
NASA Astrophysics Data System (ADS)
Sommer, Matthias; Janjic, Tijana
2016-04-01
Data assimilation for atmospheric dynamics requires an accurate estimate for the uncertainty of the forecast in order to obtain an optimal combination with available observations. This uncertainty has two components, firstly the uncertainty which originates in the the initial condition of that forecast itself and secondly the error of the numerical model used. While the former can be approximated quite successfully with an ensemble of forecasts (an additional sampling error will occur), little is known about the latter. For ensemble data assimilation, ad-hoc methods to address model error include multiplicative and additive inflation schemes, possibly also flow-dependent. The additive schemes rely on samples for the model error e.g. from short-term forecast tendencies or differences of forecasts with varying resolutions. However since these methods work in ensemble space (i.e. act directly on the ensemble perturbations) the sampling error is fixed and can be expected to affect the skill substiantially. In this contribution we show how inflation can be generalized to take into account more degrees of freedom and what improvements for future operational ensemble data assimilation can be expected from this, also in comparison with other inflation schemes.
Cardozo, Manuelle C; Cavalcante, Dannuza D; Silva, Daniel L F; Santos, Walter N L Dos; Bezerra, Marcos A
2016-09-01
A method was developed for determination of total antimony in hair samples from patients undergoing chemotherapy against Leishmaniasis based on the administration of pentavalent antimonial drugs. The method is based on microwave assisted digestion of the samples in a pressurized system, reduction of Sb5+ to Sb3+ with KI solution (10% w/v) in ascorbic acid (2%, w/v) and its subsequent determination by hydride generation atomic fluorescence spectrometry (HG-AFS). The proportions of each component (HCl, HNO3 and water) used in the digestion were studied applying a constrained mixtures design. The optimal proportions found were 50% water, 25% HNO3 and 25% HCl. Variables involved in the generation of antimony hydride were optimized using a Doehlert design revealing that good sensitivity is found when using 2.0% w/v NaBH4 and 4.4 mol L-1 HCl. Under the optimum experimental conditions, the method allows the determination of antimony in hair samples with detection and quantification limits of 1.4 and 4.6 ng g-1, respectively, and precision expressed as relative standard deviation (RSD) of 2.8% (n = 10 to 10.0 mg L-1). The developed method was applied in the analysis of hair samples from patients who take medication against Leishmaniasis. PMID:27580363
Lv, Yan; Yuan, Tao; Hu, Jiangyong; Wang, Wenhua
2009-09-01
This study intended to develop a robust and sensitive method for simultaneous determination of polycyclic musks (HHCB and AHTN) and nitro musks (musk xylene (MX) and musk ketone (MK)) in water samples using optimized solid-phase extraction (SPE) by gas chromatography and mass spectrometry (GC-MS). The SPE procedure was optimized in terms of selections of SPE cartridge, sample pH, elution process, etc. The method detection limits (MDLs) were from 0.09 to 0.18 ng L(-1) for the analytes. The recoveries ranged from 88.3 to 104.1% in spiked deionized water and from 86.4 to 106.8% in groundwater samples, respectively. The proposed approach was also validated by detecting real samples. The results revealed that HHCB and AHTN were ubiquitous in the local aquatic matrices. Furthermore, nitro musks were found in some aquatic matrices, which is consistent with the fact that nitro musks are still being produced and applied in China.
Cardozo, Manuelle C; Cavalcante, Dannuza D; Silva, Daniel L F; Santos, Walter N L Dos; Bezerra, Marcos A
2016-09-01
A method was developed for determination of total antimony in hair samples from patients undergoing chemotherapy against Leishmaniasis based on the administration of pentavalent antimonial drugs. The method is based on microwave assisted digestion of the samples in a pressurized system, reduction of Sb5+ to Sb3+ with KI solution (10% w/v) in ascorbic acid (2%, w/v) and its subsequent determination by hydride generation atomic fluorescence spectrometry (HG-AFS). The proportions of each component (HCl, HNO3 and water) used in the digestion were studied applying a constrained mixtures design. The optimal proportions found were 50% water, 25% HNO3 and 25% HCl. Variables involved in the generation of antimony hydride were optimized using a Doehlert design revealing that good sensitivity is found when using 2.0% w/v NaBH4 and 4.4 mol L-1 HCl. Under the optimum experimental conditions, the method allows the determination of antimony in hair samples with detection and quantification limits of 1.4 and 4.6 ng g-1, respectively, and precision expressed as relative standard deviation (RSD) of 2.8% (n = 10 to 10.0 mg L-1). The developed method was applied in the analysis of hair samples from patients who take medication against Leishmaniasis.
Stenholm, Ake; Holmström, Sara; Hjärthag, Sandra; Lind, Ola
2012-01-01
Trace-level analysis of alkylphenol polyethoxylates (APEOs) in wastewater containing sludge requires the prior removal of contaminants and preconcentration. In this study, the effects on optimal work-up procedures of the types of alkylphenols present, their degree of ethoxylation, the biofilm wastewater treatment and the sample matrix were investigated for these purposes. The sampling spot for APEO-containing specimens from an industrial wastewater treatment plant was optimized, including a box that surrounded the tubing outlet carrying the wastewater, to prevent sedimented sludge contaminating the collected samples. Following these changes, the sampling precision (in terms of dry matter content) at a point just under the tubing leading from the biofilm reactors was 0.7% RSD. The findings were applied to develop a work-up procedure for use prior to a high-performance liquid chromatography-fluorescence detection analysis method capable of quantifying nonylphenol polyethoxylates (NPEOs) and poorly investigated dinonylphenol polyethoxylates (DNPEOs) at low microg L(-1) concentrations in effluents from non-activated sludge biofilm reactors. The selected multi-step work-up procedure includes lyophilization and pressurized fluid extraction (PFE) followed by strong ion exchange solid phase extraction (SPE). The yields of the combined procedure, according to tests with NP10EO-spiked effluent from a wastewater treatment plant, were in the 62-78% range. PMID:22519096
Noss, Ilka; Doekes, Gert; Sander, Ingrid; Heederik, Dick J J; Thorne, Peter S; Wouters, Inge M
2010-08-01
We recently introduced a passive dust sampling method for airborne endotoxin and glucan exposure assessment-the electrostatic dustfall collector (EDC). In this study, we assessed the effects of different storage and extraction procedures on measured endotoxin and glucan levels, using 12 parallel EDC samples from 10 low exposed indoor environments. Additionally, we compared 2- and 4-week sampling with the prospect of reaching higher dust yields. Endotoxin concentrations were highest after extraction with pyrogen-free water (pf water) + Tween. Phosphate-buffered saline (PBS)-Tween yielded significantly (44%) lower levels, and practically no endotoxin was detected after extraction in pf water without Tween. Glucan levels were highest after extraction in PBS-Tween at 120 degrees C, whereas extracts made in NaOH at room temperature or 120 degrees C were completely negative. Direct extraction from the EDC cloth or sequential extraction after a preceding endotoxin extraction yielded comparable glucan levels. Sample storage at different temperatures before extraction did not affect endotoxin and glucan concentrations. Doubling the sampling duration yielded similar endotoxin and only 50% higher glucan levels. In conclusion, of the tested variables, the extraction medium was the predominant factor affecting endotoxin and glucan yields.
Błażewicz, Anna; Klatka, Maria; Dolliver, Wojciech; Kocjan, Ryszard
2014-07-01
A fast, accurate and precise ion chromatography method with pulsed amperometric detection was applied to evaluate a variety of parameters affecting the determination of total iodine in serum and urine of 81 subjects, including 56 obese and 25 healthy Polish children. The sample pretreatment methods were carried out in a closed system and with the assistance of microwaves. Both alkaline and acidic digestion procedures were developed and optimized to find the simplest combination of reagents and the appropriate parameters for digestion that would allow for the fastest, least time consuming and most cost-effective way of analysis. A good correlation between the certified and the measured concentrations was achieved. The best recoveries (96.8% for urine and 98.8% for serum samples) were achieved using 1ml of 25% tetramethylammonium hydroxide solution within 6min for 0.1ml of serum/urine samples. Using 0.5ml of 65% nitric acid solution the best recovery (95.3%) was obtained when 7min of effective digestion time was used. Freeze-thaw stability and long-term stability were checked. After 24 weeks 14.7% loss of iodine in urine, and 10.9% in serum samples occurred. For urine samples, better correlation (R(2)=0.9891) of various sample preparation procedures (alkaline digestion and application of OnGuard RP cartidges) was obtained. Significantly lower iodide content was found in samples taken from obese children. Serum iodine content in obese children was markedly variable in comparison with the healthy group, whereas the difference was less evident when urine samples were analyzed. The mean content in serum was 59.12±8.86μg/L, and in urine 98.26±25.93 for obese children when samples were prepared by the use of optimized alkaline digestion reinforced by microwaves. In healthy children the mean content in serum was 82.58±6.01μg/L, and in urine 145.76±31.44μg/L.
Verant, Michelle L; Bohuski, Elizabeth A; Lorch, Jeffery M; Blehert, David S
2016-03-01
The continued spread of white-nose syndrome and its impacts on hibernating bat populations across North America has prompted nationwide surveillance efforts and the need for high-throughput, noninvasive diagnostic tools. Quantitative real-time polymerase chain reaction (qPCR) analysis has been increasingly used for detection of the causative fungus, Pseudogymnoascus destructans, in both bat- and environment-associated samples and provides a tool for quantification of fungal DNA useful for research and monitoring purposes. However, precise quantification of nucleic acid from P. destructans is dependent on effective and standardized methods for extracting nucleic acid from various relevant sample types. We describe optimized methodologies for extracting fungal nucleic acids from sediment, guano, and swab-based samples using commercial kits together with a combination of chemical, enzymatic, and mechanical modifications. Additionally, we define modifications to a previously published intergenic spacer-based qPCR test for P. destructans to refine quantification capabilities of this assay. PMID:26965231
Farooq, Hashim; Courtier-Murias, Denis; Soong, Ronald; Masoom, Hussain; Maas, Werner; Fey, Michael; Kumar, Rajeev; Monette, Martine; Stronks, Henry; Simpson, Myrna J; Simpson, André J
2013-03-01
A method is presented that combines Carr-Purcell-Meiboom-Gill (CPMG) during acquisition with either selective or nonselective excitation to produce a considerable intensity enhancement and a simultaneous loss in chemical shift information. A range of parameters can theoretically be optimized very rapidly on the basis of the signal from the entire sample (hard excitation) or spectral subregion (soft excitation) and should prove useful for biological, environmental, and polymer samples that often exhibit highly dispersed and broad spectral profiles. To demonstrate the concept, we focus on the application of our method to T(1) determination, specifically for the slowest relaxing components in a sample, which ultimately determines the optimal recycle delay in quantitative NMR. The traditional inversion recovery (IR) pulse program is combined with a CPMG sequence during acquisition. The slowest relaxing components are selected with a shaped pulse, and then, low-power CPMG echoes are applied during acquisition with intervals shorter than chemical shift evolution (RCPMG) thus producing a single peak with an SNR commensurate with the sum of the signal integrals in the selected region. A traditional (13)C IR experiment is compared with the selective (13)C IR-RCPMG sequence and yields the same T(1) values for samples of lysozyme and riverine dissolved organic matter within error. For lysozyme, the RCPMG approach is ~70 times faster, and in the case of dissolved organic matter is over 600 times faster. This approach can be adapted for the optimization of a host of parameters where chemical shift information is not necessary, such as cross-polarization/mixing times and pulse lengths.
Duhaime, Melissa B; Deng, Li; Poulos, Bonnie T; Sullivan, Matthew B
2012-01-01
Metagenomics generates and tests hypotheses about dynamics and mechanistic drivers in wild populations, yet commonly suffers from insufficient (< 1 ng) starting genomic material for sequencing. Current solutions for amplifying sufficient DNA for metagenomics analyses include linear amplification for deep sequencing (LADS), which requires more DNA than is normally available, linker-amplified shotgun libraries (LASLs), which is prohibitively low throughput, and whole-genome amplification, which is significantly biased and thus non-quantitative. Here, we adapt the LASL approach to next generation sequencing by offering an alternate polymerase for challenging samples, developing a more efficient sizing step, integrating a ‘reconditioning PCR’ step to increase yield and minimize late-cycle PCR artefacts, and empirically documenting the quantitative capability of the optimized method with both laboratory isolate and wild community viral DNA. Our optimized linker amplification method requires as little as 1 pg of DNA and is the most precise and accurate available, with G + C content amplification biases less than 1.5-fold, even for complex samples as diverse as a wild virus community. While optimized here for 454 sequencing, this linker amplification method can be used to prepare metagenomics libraries for sequencing with next-generation platforms, including Illumina and Ion Torrent, the first of which we tested and present data for here. PMID:22713159
Duhaime, Melissa B; Deng, Li; Poulos, Bonnie T; Sullivan, Matthew B
2012-09-01
Metagenomics generates and tests hypotheses about dynamics and mechanistic drivers in wild populations, yet commonly suffers from insufficient (< 1 ng) starting genomic material for sequencing. Current solutions for amplifying sufficient DNA for metagenomics analyses include linear amplification for deep sequencing (LADS), which requires more DNA than is normally available, linker-amplified shotgun libraries (LASLs), which is prohibitively low throughput, and whole-genome amplification, which is significantly biased and thus non-quantitative. Here, we adapt the LASL approach to next generation sequencing by offering an alternate polymerase for challenging samples, developing a more efficient sizing step, integrating a 'reconditioning PCR' step to increase yield and minimize late-cycle PCR artefacts, and empirically documenting the quantitative capability of the optimized method with both laboratory isolate and wild community viral DNA. Our optimized linker amplification method requires as little as 1 pg of DNA and is the most precise and accurate available, with G + C content amplification biases less than 1.5-fold, even for complex samples as diverse as a wild virus community. While optimized here for 454 sequencing, this linker amplification method can be used to prepare metagenomics libraries for sequencing with next-generation platforms, including Illumina and Ion Torrent, the first of which we tested and present data for here.
NASA Astrophysics Data System (ADS)
Zhang, Zhiming; Huang, Ying; Bridgelall, Raj; Palek, Leonard; Strommen, Robert
2015-06-01
Weigh-in-motion (WIM) measurement has been widely used for weight enforcement, pavement design, freight management, and intelligent transportation systems to monitor traffic in real-time. However, to use such sensors effectively, vehicles must exit the traffic stream and slow down to match their current capabilities. Hence, agencies need devices with higher vehicle passing speed capabilities to enable continuous weight measurements at mainline speeds. The current practices for data acquisition at such high speeds are fragmented. Deployment configurations and settings depend mainly on the experiences of operation engineers. To assure adequate data, most practitioners use very high frequency measurements that result in redundant samples, thereby diminishing the potential for real-time processing. The larger data memory requirements from higher sample rates also increase storage and processing costs. The field lacks a sampling design or standard to guide appropriate data acquisition of high-speed WIM measurements. This study develops the appropriate sample rate requirements as a function of the vehicle speed. Simulations and field experiments validate the methods developed. The results will serve as guidelines for future high-speed WIM measurements using in-pavement strain-based sensors.
Morris, R.D.
1986-01-01
As the task of environmental planning and management becomes increasingly complex and costly, the amount and quality of data it requires grows accordingly. The vast-majority of water-quality sampling networks are designed through a ill-defined, qualitative approach. This dissertation develops the theoretical background for a quantitative approach to the design, testing, and enhancement of water-quality sampling and monitoring networks. The method uses a technique derived from regionalized variable theory known as universal kriging to provide a measure of the uncertainty of estimates at unsampled locations for a particular sampling network. Regionalized variable theory provides a powerful tool for the analysis of spatially auto correlated data. Essentially all aquatic parameters exhibit some degree of autocorrelation due to the nature of hydrodynamic mixing and advection processes. This allows for the adaptation of regionalized variable theory for use in the design of water-quality-sampling networks. By providing a variance for estimates at unsampled locations, kriging gives a measure of uncertainty. A curve depicting the relative severity of water quality in the region of interest is used in conjunction with the kriging variance to develop a function which describes the consequences of the uncertainty of these estimates.
FRESCO: flexible alignment with rectangle scoring schemes.
Dalca, A V; Brudno, M
2008-01-01
While the popular DNA sequence alignment tools incorporate powerful heuristics to allow for fast and accurate alignment of DNA, most of them still optimize the classical Needleman Wunsch scoring scheme. The development of novel scoring schemes is often hampered by the difficulty of finding an optimizing algorithm for each non-trivial scheme. In this paper we define the broad class of rectangle scoring schemes, and describe an algorithm and tool that can align two sequences with an arbitrary rectangle scoring scheme in polynomial time. Rectangle scoring schemes encompass some of the popular alignment scoring metrics currently in use, as well as many other functions. We investigate a novel scoring function based on minimizing the expected number of random diagonals observed with the given scores and show that it rivals the LAGAN and Clustal-W aligners, without using any biological or evolutionary parameters. The FRESCO program, freely available at http://compbio.cs.toronto.edu/fresco, gives bioinformatics researchers the ability to quickly compare the performance of other complex scoring formulas without having to implement new algorithms to optimize them.
Optimal descending, hypersonic turn to heading
NASA Astrophysics Data System (ADS)
Eisler, G. R.; Hull, D. G.
Approximations are made to the point-mass equations of motion for flight within the atmosphere. Optimal controls are formulated for a reentry vehicle to execute a maximum-terminal-velocity turn to a specified heading while executing steep, descent trajectories. A Newton scheme is used repetitively to solve a nonlinear algebraic system for two parameters in the control equations to provide the on-line guidance. Trajectory comparisons from the repetitive solution of the optimal control problem, pure numerical optimization, and simulation of sample-data guidance show good agreement, if the atmospheric model is accurate.
Optimal descending, hypersonic turn to heading
Eisler, G.R.; Hull, D.G.
1986-01-01
Approximations are made to the point-mass equations of motion for flight within the atmosphere. Optimal controls are formulated for a reentry vehicle to execute a maximum-terminal-velocity turn to a specified heading while executing steep, descent trajectories. A Newton scheme is used repetitively to solve a nonlinear algebraic system for two parameters in the control equations to provide the on-line guidance. Trajectory comparisons from the repetitive solution of the optimal control problem, pure numerical optimization, and simulation of sample-data guidance show good agreement, if the atmospheric model is accurate.
NASA Astrophysics Data System (ADS)
Popa, Mihnea; Roth, Mike
2003-06-01
In this paper we study the relationship between two different compactifications of the space of vector bundle quotients of an arbitrary vector bundle on a curve. One is Grothendieck's Quot scheme, while the other is a moduli space of stable maps to the relative Grassmannian. We establish an essentially optimal upper bound on the dimension of the two compactifications. Based on that, we prove that for an arbitrary vector bundle, the Quot schemes of quotients of large degree are irreducible and generically smooth. We precisely describe all the vector bundles for which the same thing holds in the case of the moduli spaces of stable maps. We show that there are in general no natural morphisms between the two compactifications. Finally, as an application, we obtain new cases of a conjecture on effective base point freeness for pluritheta linear series on moduli spaces of vector bundles.
Two-dimensional T2 distribution mapping in rock core plugs with optimal k-space sampling.
Xiao, Dan; Balcom, Bruce J
2012-07-01
Spin-echo single point imaging has been employed for 1D T(2) distribution mapping, but a simple extension to 2D is challenging since the time increase is n fold, where n is the number of pixels in the second dimension. Nevertheless 2D T(2) mapping in fluid saturated rock core plugs is highly desirable because the bedding plane structure in rocks often results in different pore properties within the sample. The acquisition time can be improved by undersampling k-space. The cylindrical shape of rock core plugs yields well defined intensity distributions in k-space that may be efficiently determined by new k-space sampling patterns that are developed in this work. These patterns acquire 22.2% and 11.7% of the k-space data points. Companion density images may be employed, in a keyhole imaging sense, to improve image quality. T(2) weighted images are fit to extract T(2) distributions, pixel by pixel, employing an inverse Laplace transform. Images reconstructed with compressed sensing, with similar acceleration factors, are also presented. The results show that restricted k-space sampling, in this application, provides high quality results.
NASA Astrophysics Data System (ADS)
Mao, Zhiyi; Shan, Ruifeng; Wang, Jiajun; Cai, Wensheng; Shao, Xueguang
2014-07-01
Polyphenols in plant samples have been extensively studied because phenolic compounds are ubiquitous in plants and can be used as antioxidants in promoting human health. A method for rapid determination of three phenolic compounds (chlorogenic acid, scopoletin and rutin) in plant samples using near-infrared diffuse reflectance spectroscopy (NIRDRS) is studied in this work. Partial least squares (PLS) regression was used for building the calibration models, and the effects of spectral preprocessing and variable selection on the models are investigated for optimization of the models. The results show that individual spectral preprocessing and variable selection has no or slight influence on the models, but the combination of the techniques can significantly improve the models. The combination of continuous wavelet transform (CWT) for removing the variant background, multiplicative scatter correction (MSC) for correcting the scattering effect and randomization test (RT) for selecting the informative variables was found to be the best way for building the optimal models. For validation of the models, the polyphenol contents in an independent sample set were predicted. The correlation coefficients between the predicted values and the contents determined by high performance liquid chromatography (HPLC) analysis are as high as 0.964, 0.948 and 0.934 for chlorogenic acid, scopoletin and rutin, respectively.
NASA Astrophysics Data System (ADS)
Moczo, P.; Kristek, J.; Galis, M.; Pazak, P.
2009-12-01
Numerical prediction of earthquake ground motion in sedimentary basins and valleys often has to account for P-wave to S-wave speed ratios (Vp/Vs) as large as 5 and even larger, mainly in sediments below groundwater level. The ratio can attain values larger than 10 in unconsolidated sediments (e.g. in Ciudad de México). In a process of developing 3D optimally-accurate finite-difference schemes we encountered a serious problem with accuracy in media with large Vp/Vs ratio. This led us to investigate the very fundamental reasons for the inaccuracy. In order to identify the very basic inherent aspects of the numerical schemes responsible for their behavior with varying Vp/Vs ratio, we restricted to the most basic 2nd-order 2D numerical schemes on a uniform grid in a homogeneous medium. Although basic in the specified sense, the schemes comprise the decisive features for accuracy of wide class of numerical schemes. We investigated 6 numerical schemes: finite-difference_displacement_conventional grid (FD_D_CG) finite-element_Lobatto integration (FE_L) finite-element_Gauss integration (FE_G) finite-difference_displacement-stress_partly-staggered grid (FD_DS_PSG) finite-difference_displacement-stress_staggered grid (FD_DS_SG) finite-difference_velocity-stress_staggered grid (FD_VS_SG) We defined and calculated local errors of the schemes in amplitude and polarization. Because different schemes use different time steps, they need different numbers of time levels to calculate solution for a desired time window. Therefore, we normalized errors for a unit time. The normalization allowed for a direct comparison of errors of different schemes. Extensive numerical calculations for wide ranges of values of the Vp/Vs ratio, spatial sampling ratio, stability ratio, and entire range of directions of propagation with respect to the spatial grid led to interesting and surprising findings. Accuracy of FD_D_CG, FE_L and FE_G strongly depends on Vp/Vs ratio. The schemes are not
NASA Astrophysics Data System (ADS)
Metzger, Stefan; Burba, George; Burns, Sean P.; Blanken, Peter D.; Li, Jiahong; Luo, Hongyan; Zulueta, Rommel C.
2016-03-01
Several initiatives are currently emerging to observe the exchange of energy and matter between the earth's surface and atmosphere standardized over larger space and time domains. For example, the National Ecological Observatory Network (NEON) and the Integrated Carbon Observing System (ICOS) are set to provide the ability of unbiased ecological inference across ecoclimatic zones and decades by deploying highly scalable and robust instruments and data processing. In the construction of these observatories, enclosed infrared gas analyzers are widely employed for eddy covariance applications. While these sensors represent a substantial improvement compared to their open- and closed-path predecessors, remaining high-frequency attenuation varies with site properties and gas sampling systems, and requires correction. Here, we show that components of the gas sampling system can substantially contribute to such high-frequency attenuation, but their effects can be significantly reduced by careful system design. From laboratory tests we determine the frequency at which signal attenuation reaches 50 % for individual parts of the gas sampling system. For different models of rain caps and particulate filters, this frequency falls into ranges of 2.5-16.5 Hz for CO2, 2.4-14.3 Hz for H2O, and 8.3-21.8 Hz for CO2, 1.4-19.9 Hz for H2O, respectively. A short and thin stainless steel intake tube was found to not limit frequency response, with 50 % attenuation occurring at frequencies well above 10 Hz for both H2O and CO2. From field tests we found that heating the intake tube and particulate filter continuously with 4 W was effective, and reduced the occurrence of problematic relative humidity levels (RH > 60 %) by 50 % in the infrared gas analyzer cell. No further improvement of H2O frequency response was found for heating in excess of 4 W. These laboratory and field tests were reconciled using resistor-capacitor theory, and NEON's final gas sampling system was developed on this
Vaz, Sharmila; Cordier, Reinie; Boyes, Mark; Parsons, Richard; Joosten, Annette; Ciccarelli, Marina; Falkmer, Marita; Falkmer, Torbjorn
2016-01-01
An important characteristic of a screening tool is its discriminant ability or the measure’s accuracy to distinguish between those with and without mental health problems. The current study examined the inter-rater agreement and screening concordance of the parent and teacher versions of SDQ at scale, subscale and item-levels, with the view of identifying the items that have the most informant discrepancies; and determining whether the concordance between parent and teacher reports on some items has the potential to influence decision making. Cross-sectional data from parent and teacher reports of the mental health functioning of a community sample of 299 students with and without disabilities from 75 different primary schools in Perth, Western Australia were analysed. The study found that: a) Intraclass correlations between parent and teacher ratings of children’s mental health using the SDQ at person level was fair on individual child level; b) The SDQ only demonstrated clinical utility when there was agreement between teacher and parent reports using the possible or 90% dichotomisation system; and c) Three individual items had positive likelihood ratio scores indicating clinical utility. Of note was the finding that the negative likelihood ratio or likelihood of disregarding the absence of a condition when both parents and teachers rate the item as absent was not significant. Taken together, these findings suggest that the SDQ is not optimised for use in community samples and that further psychometric evaluation of the SDQ in this context is clearly warranted. PMID:26771673
Vaz, Sharmila; Cordier, Reinie; Boyes, Mark; Parsons, Richard; Joosten, Annette; Ciccarelli, Marina; Falkmer, Marita; Falkmer, Torbjorn
2016-01-01
An important characteristic of a screening tool is its discriminant ability or the measure's accuracy to distinguish between those with and without mental health problems. The current study examined the inter-rater agreement and screening concordance of the parent and teacher versions of SDQ at scale, subscale and item-levels, with the view of identifying the items that have the most informant discrepancies; and determining whether the concordance between parent and teacher reports on some items has the potential to influence decision making. Cross-sectional data from parent and teacher reports of the mental health functioning of a community sample of 299 students with and without disabilities from 75 different primary schools in Perth, Western Australia were analysed. The study found that: a) Intraclass correlations between parent and teacher ratings of children's mental health using the SDQ at person level was fair on individual child level; b) The SDQ only demonstrated clinical utility when there was agreement between teacher and parent reports using the possible or 90% dichotomisation system; and c) Three individual items had positive likelihood ratio scores indicating clinical utility. Of note was the finding that the negative likelihood ratio or likelihood of disregarding the absence of a condition when both parents and teachers rate the item as absent was not significant. Taken together, these findings suggest that the SDQ is not optimised for use in community samples and that further psychometric evaluation of the SDQ in this context is clearly warranted. PMID:26771673
Puscasu, Silvia; Aubin, Simon; Cloutier, Yves; Sarazin, Philippe; Tra, Huu V; Gagné, Sébastien
2015-04-01
4,4-methylene diphenyl diisocyanate (MDI) aerosol exposure evaluation in spray foam insulation application is known as being a challenge because the spray foam application actually involves a fast-curing process. Available techniques are either not user-friendly or are inaccurate or not validated for this application. To address these issues, a new approach using a CIP10M was developed to appropriately collect MDI aerosol in spray foam insulation while being suitable for personal sampling. The CIP10M is a commercially available personal aerosol sampler that has been validated for the collection of microbial spores into a liquid medium. Tributylphosphate with 1-(2-methoxyphenyl)piperazine (MOPIP) was introduced into the CIP10M to collect and stabilize the MDI aerosols. The limit of detection and limit of quantification of the method were 0.007 and 0.024 μg ml(-1), respectively. The dynamic range was from 0.024 to 0.787 μg ml(-1) (with R (2) ≥ 0.990), which corresponds to concentrations in the air from 0.04 to 1.3 µg m(-3), assuming 60 min of sampling at 10 l min(-1). The intraday and interday analytical precisions were <2% for all of the concentration levels tested, and the accuracy was within an appropriate range of 98 ± 1%. No matrix effect was observed, and a total recovery of 99% was obtained. Parallel sampling was performed in a real MDI foam spraying environment with a CIP10M and impingers containing toluene/MOPIP (reference method). The results obtained show that the CIP10M provides levels of MDI monomer in the same range as the impingers, and higher levels of MDI oligomers. The negative bias observed for MDI monomer was between 2 and 26%, whereas the positive bias observed for MDI oligomers was between 76 and 113%, with both biases calculated with a confidence level of 95%. The CIP10M seems to be a promising approach for MDI aerosol exposure evaluation in spray foam applications.
Optimization of a gas sampling system for measuring eddy-covariance fluxes of H2O and CO2
NASA Astrophysics Data System (ADS)
Metzger, S.; Burba, G.; Burns, S. P.; Blanken, P. D.; Li, J.; Luo, H.; Zulueta, R. C.
2015-10-01
Several initiatives are currently emerging to observe the exchange of energy and matter between the earth's surface and atmosphere standardized over larger space and time domains. For example, the National Ecological Observatory Network (NEON) and the Integrated Carbon Observing System (ICOS) will provide the ability of unbiased ecological inference across eco-climatic zones and decades by deploying highly scalable and robust instruments and data processing. In the construction of these observatories, enclosed infrared gas analysers are widely employed for eddy-covariance applications. While these sensors represent a substantial improvement compared to their open- and closed-path predecessors, remaining high-frequency attenuation varies with site properties, and requires correction. Here, we show that the gas sampling system substantially contributes to high-frequency attenuation, which can be minimized by careful design. From laboratory tests we determine the frequency at which signal attenuation reaches 50 % for individual parts of the gas sampling system. For different models of rain caps and particulate filters, this frequency falls into ranges of 2.5-16.5 Hz for CO2, 2.4-14.3 Hz for H2O, and 8.3-21.8 Hz for CO2, 1.4-19.9 Hz for H2O, respectively. A short and thin stainless steel intake tube was found to not limit frequency response, with 50 % attenuation occurring at frequencies well above 10 Hz for both H2O and CO2. From field tests we found that heating the intake tube and particulate filter continuously with 4 W was effective, and reduced the occurrence of problematic relative humidity levels (RH > 60 %) by 50 % in the infrared gas analyser cell. No further improvement of H2O frequency response was found for heating in excess of 4 W. These laboratory and field tests were reconciled using resistor-capacitor theory, and NEON's final gas sampling system was developed on this basis. The design consists of the stainless steel intake tube, a pleated mesh
Nieuwoudt, M K; Holroyd, S E; McGoverin, C M; Simpson, M C; Williams, D E
2016-10-01
We have developed a powerful general spectroscopic method for rapidly screening liquid milk for adulterants by combining reflective focusing wells simply fabricated in aluminum with a small, portable Raman spectrometer with a focusing fiber optic probe. Hemispherical aluminum sample wells were specially designed to optimize internal reflection and sampling volume by matching the focal length of the mirror to the depth of focus of the laser probe. The technique was tested on milk adulterated with 4 different nitrogen-rich compounds (melamine, urea, dicyandiamide, and ammonium sulfate) and sucrose. No sample preparation of the milk was needed, and the total analysis time was 4min. Reliable sample presentation enabled average reproducibility of 8% residual standard deviation. The limit of detection interval measured from partial least squares calibrations ranged between 140 and 520mg/L for the 4 N-rich compounds and between 7,000 and 36,000mg/L (0.7-3.6%) for sucrose. The portability of the system and the reliability and reproducibility of this technique open opportunities for general, reagentless screening of milk for adulterants at the point of collection. PMID:27474982
Geophysical Inversion through Hierarchical Genetic Algorithm Scheme
NASA Astrophysics Data System (ADS)
Furman, Alex; Huisman, Johan A.
2010-05-01
Geophysical investigation is a powerful tool that allows non-invasive and non-destructive mapping of subsurface states and properties. However, non-uniqueness associated with the inversion process halts these methods from becoming of more quantitative use. One major direction researchers are going is constraining the inverse problem by hydrological observations and models. An alternative to the commonly used direct inversion methods are global optimization schemes (such as genetic algorithms and Monte Carlo Markov Chain methods). However, the major limitation here is the desired high resolution of the tomographic image, which leads to a large number of parameters and an unreasonably high computational effort when using global optimization schemes. One way to overcome these problems is to combine the advantages of both direct and global inversion methods through hierarchical inversion. That is, starting the inversion with relatively coarse resolution of parameters, achieving good inversion using one of the two inversion schemes (global or direct), and then refining the resolution and applying a combination of global and direct inversion schemes for the whole domain or locally. In this work we explore through synthetic case studies the option of using a global optimization scheme for inversion of electrical resistivity tomography data through hierarchical refinement of the model resolution.
Wüst, Thomas; Landau, David P
2012-08-14
Coarse-grained (lattice-) models have a long tradition in aiding efforts to decipher the physical or biological complexity of proteins. Despite the simplicity of these models, however, numerical simulations are often computationally very demanding and the quest for efficien