A proposal of optimal sampling design using a modularity strategy

NASA Astrophysics Data System (ADS)

Simone, A.; Giustolisi, O.; Laucelli, D. B.

2016-08-01

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.

Optimal updating magnitude in adaptive flat-distribution sampling

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Drake, Justin A.; Ma, Jianpeng; Pettitt, B. Montgomery

2017-11-01

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

Optimal updating magnitude in adaptive flat-distribution sampling.

PubMed

Zhang, Cheng; Drake, Justin A; Ma, Jianpeng; Pettitt, B Montgomery

2017-11-07

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

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

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

Ridolfi, E.; Napolitano, F., E-mail: francesco.napolitano@uniroma1.it; Alfonso, L.

2016-06-08

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

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

Ranked set sampling: cost and optimal set size.

PubMed

Nahhas, Ramzi W; Wolfe, Douglas A; Chen, Haiying

2002-12-01

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.

Optimal cut-off levels to define obesity: body mass index and waist circumference, and their relationship to cardiovascular disease, dyslipidaemia, hypertension and diabetes in Malaysia.

PubMed

Zaher, Zaki Morad Mohd; Zambari, Robayaah; Pheng, Chan Siew; Muruga, Vadivale; Ng, Bernard; Appannah, Geeta; Onn, Lim Teck

2009-01-01

Many studies in Asia have demonstrated that Asian populations may require lower cut-off levels for body mass index (BMI) and waist circumference to define obesity and abdominal obesity respectively, compared to western populations. Optimal cut-off levels for body mass index and waist circumference were determined to assess the relationship between the two anthropometric- and cardiovascular indices. Receiver operating characteristics analysis was used to determine the optimal cut-off levels. The study sample included 1833 subjects (mean age of 44+/-14 years) from 93 primary care clinics in Malaysia. Eight hundred and seventy two of the subjects were men and 960 were women. The optimal body mass index cut-off values predicting dyslipidaemia, hypertension, diabetes mellitus, or at least one cardiovascular risk factor varied from 23.5 to 25.5 kg/m2 in men and 24.9 to 27.4 kg/m2 in women. As for waist circumference, the optimal cut-off values varied from 83 to 92 cm in men and from 83 to 88 cm in women. The optimal cut-off values from our study showed that body mass index of 23.5 kg/m2 in men and 24.9 kg/m2 in women and waist circumference of 83 cm in men and women may be more suitable for defining the criteria for overweight or obesity among adults in Malaysia. Waist circumference may be a better indicator for the prediction of obesity-related cardiovascular risk factors in men and women compared to BMI. Further investigation using a bigger sample size in Asia needs to be done to confirm our findings.

Optimal sampling and quantization of synthetic aperture radar signals

NASA Technical Reports Server (NTRS)

Wu, C.

1978-01-01

Some theoretical and experimental results on optimal sampling and quantization of synthetic aperture radar (SAR) signals are presented. It includes a description of a derived theoretical relationship between the pixel signal to noise ratio of processed SAR images and the number of quantization bits per sampled signal, assuming homogeneous extended targets. With this relationship known, a solution may be realized for the problem of optimal allocation of a fixed data bit-volume (for specified surface area and resolution criterion) between the number of samples and the number of bits per sample. The results indicate that to achieve the best possible image quality for a fixed bit rate and a given resolution criterion, one should quantize individual samples coarsely and thereby maximize the number of multiple looks. The theoretical results are then compared with simulation results obtained by processing aircraft SAR data.

OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging

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

de Raad, Markus; de Rond, Tristan; Rübel, Oliver

Mass spectrometry imaging (MSI) has primarily been applied in localizing biomolecules within biological matrices. Although well-suited, the application of MSI for comparing thousands of spatially defined spotted samples has been limited. One reason for this is a lack of suitable and accessible data processing tools for the analysis of large arrayed MSI sample sets. In this paper, the OpenMSI Arrayed Analysis Toolkit (OMAAT) is a software package that addresses the challenges of analyzing spatially defined samples in MSI data sets. OMAAT is written in Python and is integrated with OpenMSI (http://openmsi.nersc.gov), a platform for storing, sharing, and analyzing MSI data.more » By using a web-based python notebook (Jupyter), OMAAT is accessible to anyone without programming experience yet allows experienced users to leverage all features. OMAAT was evaluated by analyzing an MSI data set of a high-throughput glycoside hydrolase activity screen comprising 384 samples arrayed onto a NIMS surface at a 450 μm spacing, decreasing analysis time >100-fold while maintaining robust spot-finding. The utility of OMAAT was demonstrated for screening metabolic activities of different sized soil particles, including hydrolysis of sugars, revealing a pattern of size dependent activities. Finally, these results introduce OMAAT as an effective toolkit for analyzing spatially defined samples in MSI. OMAAT runs on all major operating systems, and the source code can be obtained from the following GitHub repository: https://github.com/biorack/omaat.« less

Defining Optimal Brain Health in Adults: A Presidential Advisory From the American Heart Association/American Stroke Association.

PubMed

Gorelick, Philip B; Furie, Karen L; Iadecola, Costantino; Smith, Eric E; Waddy, Salina P; Lloyd-Jones, Donald M; Bae, Hee-Joon; Bauman, Mary Ann; Dichgans, Martin; Duncan, Pamela W; Girgus, Meighan; Howard, Virginia J; Lazar, Ronald M; Seshadri, Sudha; Testai, Fernando D; van Gaal, Stephen; Yaffe, Kristine; Wasiak, Hank; Zerna, Charlotte

2017-10-01

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA's Life's Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index <25 kg/m 2 ) and 3 ideal health factors (untreated blood pressure <120/<80 mm Hg, untreated total cholesterol <200 mg/dL, and fasting blood glucose <100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer's Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA's Life's Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to

Classifier-Guided Sampling for Complex Energy System Optimization

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

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 omore » 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.« less

Realization theory and quadratic optimal controllers for systems defined over Banach and Frechet algebras

NASA Technical Reports Server (NTRS)

Byrnes, C. I.

1980-01-01

It is noted that recent work by Kamen (1979) on the stability of half-plane digital filters shows that the problem of the existence of a feedback law also arises for other Banach algebras in applications. This situation calls for a realization theory and stabilizability criteria for systems defined over Banach for Frechet algebra A. Such a theory is developed here, with special emphasis placed on the construction of finitely generated realizations, the existence of coprime factorizations for T(s) defined over A, and the solvability of the quadratic optimal control problem and the associated algebraic Riccati equation over A.

A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.

PubMed

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.

A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks

PubMed Central

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 Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions

PubMed Central

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

Optimism is universal: exploring the presence and benefits of optimism in a representative sample of the world.

PubMed

Gallagher, Matthew W; Lopez, Shane J; Pressman, Sarah D

2013-10-01

Current theories of optimism suggest that the tendency to maintain positive expectations for the future is an adaptive psychological resource associated with improved well-being and physical health, but the majority of previous optimism research has been conducted in industrialized nations. The present study examined (a) whether optimism is universal, (b) what demographic factors predict optimism, and (c) whether optimism is consistently associated with improved subjective well-being and perceived health worldwide. The present study used representative samples of 142 countries that together represent 95% of the world's population. The total sample of 150,048 individuals had a mean age of 38.28 (SD = 16.85) and approximately equal sex distribution (51.2% female). The relationships between optimism, subjective well-being, and perceived health were examined using hierarchical linear modeling. Results indicated that most individuals and most countries worldwide are optimistic and that higher levels of optimism are associated with improved subjective well-being and perceived health worldwide. The present study provides compelling evidence that optimism is a universal phenomenon and that the associations between optimism and improved psychological functioning are not limited to industrialized nations. © 2012 Wiley Periodicals, Inc.

Optimal sampling with prior information of the image geometry in microfluidic MRI.

PubMed

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. Copyright © 2015 Elsevier Inc. All rights reserved.

Optimal two-phase sampling design for comparing accuracies of two binary classification rules.

PubMed

Xu, Huiping; Hui, Siu L; Grannis, Shaun

2014-02-10

In this paper, we consider the design for comparing the performance of two binary classification rules, for example, two record linkage algorithms or two screening tests. Statistical methods are well developed for comparing these accuracy measures when the gold standard is available for every unit in the sample, or in a two-phase study when the gold standard is ascertained only in the second phase in a subsample using a fixed sampling scheme. However, these methods do not attempt to optimize the sampling scheme to minimize the variance of the estimators of interest. In comparing the performance of two classification rules, the parameters of primary interest are the difference in sensitivities, specificities, and positive predictive values. We derived the analytic variance formulas for these parameter estimates and used them to obtain the optimal sampling design. The efficiency of the optimal sampling design is evaluated through an empirical investigation that compares the optimal sampling with simple random sampling and with proportional allocation. Results of the empirical study show that the optimal sampling design is similar for estimating the difference in sensitivities and in specificities, and both achieve a substantial amount of variance reduction with an over-sample of subjects with discordant results and under-sample of subjects with concordant results. A heuristic rule is recommended when there is no prior knowledge of individual sensitivities and specificities, or the prevalence of the true positive findings in the study population. The optimal sampling is applied to a real-world example in record linkage to evaluate the difference in classification accuracy of two matching algorithms. Copyright © 2013 John Wiley & Sons, Ltd.

An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning

PubMed Central

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

Deep brain stimulation for Parkinson's disease: defining the optimal location within the subthalamic nucleus.

PubMed

Bot, Maarten; Schuurman, P Richard; Odekerken, Vincent J J; Verhagen, Rens; Contarino, Fiorella Maria; De Bie, Rob M A; van den Munckhof, Pepijn

2018-05-01

Individual motor improvement after deep brain stimulation (DBS) of the subthalamic nucleus (STN) for Parkinson's disease (PD) varies considerably. Stereotactic targeting of the dorsolateral sensorimotor part of the STN is considered paramount for maximising effectiveness, but studies employing the midcommissural point (MCP) as anatomical reference failed to show correlation between DBS location and motor improvement. The medial border of the STN as reference may provide better insight in the relationship between DBS location and clinical outcome. Motor improvement after 12 months of 65 STN DBS electrodes was categorised into non-responding, responding and optimally responding body-sides. Stereotactic coordinates of optimal electrode contacts relative to both medial STN border and MCP served to define theoretic DBS 'hotspots'. Using the medial STN border as reference, significant negative correlation (Pearson's correlation -0.52, P<0.01) was found between the Euclidean distance from the centre of stimulation to this DBS hotspot and motor improvement. This hotspot was located at 2.8 mm lateral, 1.7 mm anterior and 2.5 mm superior relative to the medial STN border. Using MCP as reference, no correlation was found. The medial STN border proved superior compared with MCP as anatomical reference for correlation of DBS location and motor improvement, and enabled defining an optimal DBS location within the nucleus. We therefore propose the medial STN border as a better individual reference point than the currently used MCP on preoperative stereotactic imaging, in order to obtain optimal and thus less variable motor improvement for individual patients with PD following STN DBS. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Sample size calculation in cost-effectiveness cluster randomized trials: optimal and maximin approaches.

PubMed

Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F

2014-07-10

In this paper, the optimal sample sizes at the cluster and person levels for each of two treatment arms are obtained for cluster randomized trials where the cost-effectiveness of treatments on a continuous scale is studied. The optimal sample sizes maximize the efficiency or power for a given budget or minimize the budget for a given efficiency or power. Optimal sample sizes require information on the intra-cluster correlations (ICCs) for effects and costs, the correlations between costs and effects at individual and cluster levels, the ratio of the variance of effects translated into costs to the variance of the costs (the variance ratio), sampling and measuring costs, and the budget. When planning, a study information on the model parameters usually is not available. To overcome this local optimality problem, the current paper also presents maximin sample sizes. The maximin sample sizes turn out to be rather robust against misspecifying the correlation between costs and effects at the cluster and individual levels but may lose much efficiency when misspecifying the variance ratio. The robustness of the maximin sample sizes against misspecifying the ICCs depends on the variance ratio. The maximin sample sizes are robust under misspecification of the ICC for costs for realistic values of the variance ratio greater than one but not robust under misspecification of the ICC for effects. Finally, we show how to calculate optimal or maximin sample sizes that yield sufficient power for a test on the cost-effectiveness of an intervention.

Optimal tumor sampling for immunostaining of biomarkers in breast carcinoma

PubMed Central

2011-01-01

Introduction Biomarkers, such as Estrogen Receptor, are used to determine therapy and prognosis in breast carcinoma. Immunostaining assays of biomarker expression have a high rate of inaccuracy; for example, estimates are as high as 20% for Estrogen Receptor. Biomarkers have been shown to be heterogeneously expressed in breast tumors and this heterogeneity may contribute to the inaccuracy of immunostaining assays. Currently, no evidence-based standards exist for the amount of tumor that must be sampled in order to correct for biomarker heterogeneity. The aim of this study was to determine the optimal number of 20X fields that are necessary to estimate a representative measurement of expression in a whole tissue section for selected biomarkers: ER, HER-2, AKT, ERK, S6K1, GAPDH, Cytokeratin, and MAP-Tau. Methods Two collections of whole tissue sections of breast carcinoma were immunostained for biomarkers. Expression was quantified using the Automated Quantitative Analysis (AQUA) method of quantitative immunofluorescence. Simulated sampling of various numbers of fields (ranging from one to thirty five) was performed for each marker. The optimal number was selected for each marker via resampling techniques and minimization of prediction error over an independent test set. Results The optimal number of 20X fields varied by biomarker, ranging between three to fourteen fields. More heterogeneous markers, such as MAP-Tau protein, required a larger sample of 20X fields to produce representative measurement. Conclusions The optimal number of 20X fields that must be sampled to produce a representative measurement of biomarker expression varies by marker with more heterogeneous markers requiring a larger number. The clinical implication of these findings is that breast biopsies consisting of a small number of fields may be inadequate to represent whole tumor biomarker expression for many markers. Additionally, for biomarkers newly introduced into clinical use, especially if

Sample treatment optimization for fish stool metabolomics.

PubMed

Hano, Takeshi; Ito, Mana; Ito, Katsutoshi; Uchida, Motoharu

2018-06-07

Gut microbiota play an essential role in an organism's health. The fecal metabolite profiling content reflects these microbiota-mediated physiological changes in various organisms, including fish. Therefore, metabolomics analysis of fish feces should provide insight into the dynamics linking physiology and gut microbiota. However, metabolites are often unstable in aquatic environments, making fecal metabolites difficult to examine in fish. In this study, a novel method using gas chromatography-mass spectrometry (GC-MS) was developed and optimized for the preparation of metabolomics samples from the feces of the marine fish, red sea bream (Pagrus major). The preparation methodology was optimized, focusing on rinsing frequency and rinsing solvent. Feces (collected within 4 h of excretion) were rinsed three times with sterilized 2.5% NaCl solution or 3.0% artificial seawater (ASW). Among the 86 metabolites identified in the NaCl-rinsed samples, 57 showed superior recovery to that in ASW-rinsed samples, indicating that NaCl is a better rinsing solvent, particularly for amino acids, organic acids, and fatty acids. To evaluate rinsing frequency, fecal samples were rinsed with NaCl solution 0, 1, 3, or 5 times. The results indicate that three or more rinses enabled robust and stable detection of metabolites encapsulated within the solid fecal residue. Furthermore, these data suggest that rinsing is unnecessary when studying sugars, amino acids, and sterols, again highlighting the need for appropriate rinsing solvent and frequency. This study provides further insight into the use of fecal samples to evaluate and promote fish health during farming and supports the application of this and similar analyses to study the effects of environmental fluctuations and/or contamination. Copyright © 2018 Elsevier B.V. All rights reserved.

A General Investigation of Optimized Atmospheric Sample Duration

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

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 radionuclidesmore » (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.« less

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

Defining Tiger Parenting in Chinese Americans.

PubMed

Kim, Su Yeong

2013-09-01

"Tiger" parenting, as described by Amy Chua [2011], has instigated scholarly discourse on this phenomenon and its possible effects on families. Our eight-year longitudinal study, published in the Asian American Journal of Psychology [Kim, Wang, Orozco-Lapray, Shen, & Murtuza, 2013b], demonstrates that tiger parenting is not a common parenting profile in a sample of 444 Chinese American families. Tiger parenting also does not relate to superior academic performance in children. In fact, the best developmental outcomes were found among children of supportive parents. We examine the complexities around defining tiger parenting by reviewing classical literature on parenting styles and scholarship on Asian American parenting, along with Amy Chua's own description of her parenting method, to develop, define, and categorize variability in parenting in a sample of Chinese American families. We also provide evidence that supportive parenting is important for the optimal development of Chinese American adolescents.

Cache-Aware Asymptotically-Optimal Sampling-Based Motion Planning

PubMed Central

Ichnowski, Jeffrey; Prins, Jan F.; Alterovitz, Ron

2014-01-01

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

Cache-Aware Asymptotically-Optimal Sampling-Based Motion Planning.

PubMed

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.

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.

Logical definability and asymptotic growth in optimization and counting problems

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

Compton, K.

1994-12-31

There has recently been a great deal of interest in the relationship between logical definability and NP-optimization problems. Let MS{sub n} (resp. MP{sub n}) be the class of problems to compute, for given a finite structure A, the maximum number of tuples {bar x} in A satisfying a {Sigma}{sub n} (resp. II{sub n}) formula {psi}({bar x}, {bar S}) as {bar S} ranges over predicates on A. Kolaitis and Thakur showed that the classes MS{sub n} and MP{sub n} collapse to a hierarchy of four levels. Papadimitriou and Yannakakis previously showed that problems in the two lowest levels MS{sub 0} andmore » MS{sub 1} (which they called Max Snp and Max Np) are approximable to within a contrast factor in polynomial time. Similarly, Saluja, Subrahmanyam, and Thakur defined SS{sub n} (resp. SP{sub n}) to be the class of problems to compute, for given a finite structure A, the number of tuples ({bar T}, {bar S}) satisfying a given {Sigma}{sub n} (resp. II{sub n}) formula {psi}({bar T}, {bar c}) in A. They showed that the classes SS{sub n} and SP{sub n} collapse to a hierarchy of five levels and that problems in the two lowest levels SS{sub 0} and SS{sub 1} have a fully polynomial time randomized approximation scheme. We define extended classes MSF{sub n}, MPF{sub n} SSF{sub n}, and SPF{sub n} by allowing formulae to contain predicates definable in a logic known as least fixpoint logic. The resulting hierarchies classes collapse to the same number of levels and problems in the bottom levels can be approximated as before, but now some problems descend from the highest levels in the original hierarchies to the lowest levels in the new hierarchies. We introduce a method characterizing rates of growth of average solution sizes thereby showing a number of important problems do not belong MSF{sub 1} and SSF{sub 1}. This method is related to limit laws for logics and the probabilistic method from combinatorics.« less

Defining Tiger Parenting in Chinese Americans

PubMed Central

Kim, Su Yeong

2016-01-01

“Tiger” parenting, as described by Amy Chua [2011], has instigated scholarly discourse on this phenomenon and its possible effects on families. Our eight-year longitudinal study, published in the Asian American Journal of Psychology [Kim, Wang, Orozco-Lapray, Shen, & Murtuza, 2013b], demonstrates that tiger parenting is not a common parenting profile in a sample of 444 Chinese American families. Tiger parenting also does not relate to superior academic performance in children. In fact, the best developmental outcomes were found among children of supportive parents. We examine the complexities around defining tiger parenting by reviewing classical literature on parenting styles and scholarship on Asian American parenting, along with Amy Chua’s own description of her parenting method, to develop, define, and categorize variability in parenting in a sample of Chinese American families. We also provide evidence that supportive parenting is important for the optimal development of Chinese American adolescents. PMID:27182075

Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes.

PubMed

Binns, Michael; de Atauri, Pedro; Vlysidis, Anestis; Cascante, Marta; Theodoropoulos, Constantinos

2015-02-18

Flux balance analysis is traditionally implemented to identify the maximum theoretical flux for some specified reaction and a single distribution of flux values for all the reactions present which achieve this maximum value. However it is well known that the uncertainty in reaction networks due to branches, cycles and experimental errors results in a large number of combinations of internal reaction fluxes which can achieve the same optimal flux value. In this work, we have modified the applied linear objective of flux balance analysis to include a poling penalty function, which pushes each new set of reaction fluxes away from previous solutions generated. Repeated poling-based flux balance analysis generates a sample of different solutions (a characteristic set), which represents all the possible functionality of the reaction network. Compared to existing sampling methods, for the purpose of generating a relatively "small" characteristic set, our new method is shown to obtain a higher coverage than competing methods under most conditions. The influence of the linear objective function on the sampling (the linear bias) constrains optimisation results to a subspace of optimal solutions all producing the same maximal fluxes. Visualisation of reaction fluxes plotted against each other in 2 dimensions with and without the linear bias indicates the existence of correlations between fluxes. This method of sampling is applied to the organism Actinobacillus succinogenes for the production of succinic acid from glycerol. A new method of sampling for the generation of different flux distributions (sets of individual fluxes satisfying constraints on the steady-state mass balances of intermediates) has been developed using a relatively simple modification of flux balance analysis to include a poling penalty function inside the resulting optimisation objective function. This new methodology can achieve a high coverage of the possible flux space and can be used with and without

Optimal combination of illusory and luminance-defined 3-D surfaces: A role for ambiguity.

PubMed

Hartle, Brittney; Wilcox, Laurie M; Murray, Richard F

2018-04-01

The shape of the illusory surface in stereoscopic Kanizsa figures is determined by the interpolation of depth from the luminance edges of adjacent inducing elements. Despite ambiguity in the position of illusory boundaries, observers reliably perceive a coherent three-dimensional (3-D) surface. However, this ambiguity may contribute additional uncertainty to the depth percept beyond what is expected from measurement noise alone. We evaluated the intrinsic ambiguity of illusory boundaries by using a cue-combination paradigm to measure the reliability of depth percepts elicited by stereoscopic illusory surfaces. We assessed the accuracy and precision of depth percepts using 3-D Kanizsa figures relative to luminance-defined surfaces. The location of the surface peak was defined by illusory boundaries, luminance-defined edges, or both. Accuracy and precision were assessed using a depth-discrimination paradigm. A maximum likelihood linear cue combination model was used to evaluate the relative contribution of illusory and luminance-defined signals to the perceived depth of the combined surface. Our analysis showed that the standard deviation of depth estimates was consistent with an optimal cue combination model, but the points of subjective equality indicated that observers consistently underweighted the contribution of illusory boundaries. This systematic underweighting may reflect a combination rule that attributes additional intrinsic ambiguity to the location of the illusory boundary. Although previous studies show that illusory and luminance-defined contours share many perceptual similarities, our model suggests that ambiguity plays a larger role in the perceptual representation of illusory contours than of luminance-defined contours.

Spatial Prediction and Optimized Sampling Design for Sodium Concentration in Groundwater

PubMed Central

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

Optimal design in pediatric pharmacokinetic and pharmacodynamic clinical studies.

PubMed

Roberts, Jessica K; Stockmann, Chris; Balch, Alfred; Yu, Tian; Ward, Robert M; Spigarelli, Michael G; Sherwin, Catherine M T

2015-03-01

It is not trivial to conduct clinical trials with pediatric participants. Ethical, logistical, and financial considerations add to the complexity of pediatric studies. Optimal design theory allows investigators the opportunity to apply mathematical optimization algorithms to define how to structure their data collection to answer focused research questions. These techniques can be used to determine an optimal sample size, optimal sample times, and the number of samples required for pharmacokinetic and pharmacodynamic studies. The aim of this review is to demonstrate how to determine optimal sample size, optimal sample times, and the number of samples required from each patient by presenting specific examples using optimal design tools. Additionally, this review aims to discuss the relative usefulness of sparse vs rich data. This review is intended to educate the clinician, as well as the basic research scientist, whom plan on conducting a pharmacokinetic/pharmacodynamic clinical trial in pediatric patients. © 2015 John Wiley & Sons Ltd.

Defining the optimal cut-off values for liver enzymes in diagnosing blunt liver injury.

PubMed

Koyama, Tomohide; Hamada, Hirohisa; Nishida, Masamichi; Naess, Paal A; Gaarder, Christine; Sakamoto, Tetsuya

2016-01-25

Patients with blunt trauma to the liver have elevated levels of liver enzymes within a short time post injury, potentially useful in screening patients for computed tomography (CT). This study was performed to define the optimal cut-off values for serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in patients with blunt liver injury diagnosed with contrast enhanced multi detector-row CT (CE-MDCT). All patients admitted from May 2006 to July 2013 to Teikyo University Hospital Trauma and Critical Care Center, and who underwent abdominal CE-MDCT within 3 h after blunt trauma, were retrospectively enrolled. Using receiver operating characteristic (ROC) curve analysis, the optimal cut-off values for AST and ALT were defined, and sensitivity and specificity were calculated. Of a total of 676 blunt trauma patients 64 patients were diagnosed with liver injury (Group LI+) and 612 patients without liver injury (Group LI-). Group LI+ and LI- were comparable for age, Revised Trauma Score, and Probability of survival. The groups differed in Injury Severity Score [median 21 (interquartile range 9-33) vs. 17 (9-26) (p < 0.01)]. Group LI+ had higher AST than LI- [276 (48-503) vs. 44 (16-73); p < 0.001] and higher ALT [240 (92-388) vs. 32 (16-49); p < 0.001]. Using ROC curve analysis, the optimal cut-off values for AST and ALT were set at 109 U/l and 97 U/l, respectively. Based on these values, AST ≥ 109 U/l had a sensitivity of 81%, a specificity of 82%, a positive predictive value of 32%, and a negative predictive value of 98%. The corresponding values for ALT ≥ 97 U/l were 78, 88, 41 and 98%, respectively, and for the combination of AST ≥ 109 U/l and/or ALT ≥ 97 U/l were 84, 81, 32, 98%, respectively. We have identified AST ≥ 109 U/l and ALT ≥ 97 U/l as optimal cut-off values in predicting the presence of liver injury, potentially useful as a screening tool for CT scan in patients otherwise eligible for observation only or as a transfer

Sampling scales define occupancy and underlying occupancy-abundance relationships in animals.

PubMed

Steenweg, Robin; Hebblewhite, Mark; Whittington, Jesse; Lukacs, Paul; McKelvey, Kevin

2018-01-01

also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship. © 2017 by the Ecological Society of America.

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.

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

PubMed Central

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

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

Spectral gap optimization of order parameters for sampling complex molecular systems

PubMed Central

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

Evaluation of optimized bronchoalveolar lavage sampling designs for characterization of pulmonary drug distribution.

PubMed

Clewe, Oskar; Karlsson, Mats O; Simonsson, Ulrika S H

2015-12-01

Bronchoalveolar lavage (BAL) is a pulmonary sampling technique for characterization of drug concentrations in epithelial lining fluid and alveolar cells. Two hypothetical drugs with different pulmonary distribution rates (fast and slow) were considered. An optimized BAL sampling design was generated assuming no previous information regarding the pulmonary distribution (rate and extent) and with a maximum of two samples per subject. Simulations were performed to evaluate the impact of the number of samples per subject (1 or 2) and the sample size on the relative bias and relative root mean square error of the parameter estimates (rate and extent of pulmonary distribution). The optimized BAL sampling design depends on a characterized plasma concentration time profile, a population plasma pharmacokinetic model, the limit of quantification (LOQ) of the BAL method and involves only two BAL sample time points, one early and one late. The early sample should be taken as early as possible, where concentrations in the BAL fluid ≥ LOQ. The second sample should be taken at a time point in the declining part of the plasma curve, where the plasma concentration is equivalent to the plasma concentration in the early sample. Using a previously described general pulmonary distribution model linked to a plasma population pharmacokinetic model, simulated data using the final BAL sampling design enabled characterization of both the rate and extent of pulmonary distribution. The optimized BAL sampling design enables characterization of both the rate and extent of the pulmonary distribution for both fast and slowly equilibrating drugs.

Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli.

PubMed

Westfall, Jacob; Kenny, David A; Judd, Charles M

2014-10-01

Researchers designing experiments in which a sample of participants responds to a sample of stimuli are faced with difficult questions about optimal study design. The conventional procedures of statistical power analysis fail to provide appropriate answers to these questions because they are based on statistical models in which stimuli are not assumed to be a source of random variation in the data, models that are inappropriate for experiments involving crossed random factors of participants and stimuli. In this article, we present new methods of power analysis for designs with crossed random factors, and we give detailed, practical guidance to psychology researchers planning experiments in which a sample of participants responds to a sample of stimuli. We extensively examine 5 commonly used experimental designs, describe how to estimate statistical power in each, and provide power analysis results based on a reasonable set of default parameter values. We then develop general conclusions and formulate rules of thumb concerning the optimal design of experiments in which a sample of participants responds to a sample of stimuli. We show that in crossed designs, statistical power typically does not approach unity as the number of participants goes to infinity but instead approaches a maximum attainable power value that is possibly small, depending on the stimulus sample. We also consider the statistical merits of designs involving multiple stimulus blocks. Finally, we provide a simple and flexible Web-based power application to aid researchers in planning studies with samples of stimuli.

Optimization of the two-sample rank Neyman-Pearson detector

NASA Astrophysics Data System (ADS)

Akimov, P. S.; Barashkov, V. M.

1984-10-01

The development of optimal algorithms concerned with rank considerations in the case of finite sample sizes involves considerable mathematical difficulties. The present investigation provides results related to the design and the analysis of an optimal rank detector based on a utilization of the Neyman-Pearson criteria. The detection of a signal in the presence of background noise is considered, taking into account n observations (readings) x1, x2, ... xn in the experimental communications channel. The computation of the value of the rank of an observation is calculated on the basis of relations between x and the variable y, representing interference. Attention is given to conditions in the absence of a signal, the probability of the detection of an arriving signal, details regarding the utilization of the Neyman-Pearson criteria, the scheme of an optimal rank, multichannel, incoherent detector, and an analysis of the detector.

Optimization of techniques for multiple platform testing in small, precious samples such as human chorionic villus sampling.

PubMed

Pisarska, Margareta D; Akhlaghpour, Marzieh; Lee, Bora; Barlow, Gillian M; Xu, Ning; Wang, Erica T; Mackey, Aaron J; Farber, Charles R; Rich, Stephen S; Rotter, Jerome I; Chen, Yii-der I; Goodarzi, Mark O; Guller, Seth; Williams, John

2016-11-01

Multiple testing to understand global changes in gene expression based on genetic and epigenetic modifications is evolving. Chorionic villi, obtained for prenatal testing, is limited, but can be used to understand ongoing human pregnancies. However, optimal storage, processing and utilization of CVS for multiple platform testing have not been established. Leftover CVS samples were flash-frozen or preserved in RNAlater. Modifications to standard isolation kits were performed to isolate quality DNA and RNA from samples as small as 2-5 mg. RNAlater samples had significantly higher RNA yields and quality and were successfully used in microarray and RNA-sequencing (RNA-seq). RNA-seq libraries generated using 200 versus 800-ng RNA showed similar biological coefficients of variation. RNAlater samples had lower DNA yields and quality, which improved by heating the elution buffer to 70 °C. Purification of DNA was not necessary for bisulfite-conversion and genome-wide methylation profiling. CVS cells were propagated and continue to express genes found in freshly isolated chorionic villi. CVS samples preserved in RNAlater are superior. Our optimized techniques provide specimens for genetic, epigenetic and gene expression studies from a single small sample which can be used to develop diagnostics and treatments using a systems biology approach in the prenatal period. © 2016 John Wiley & Sons, Ltd. © 2016 John Wiley & Sons, Ltd.

Defining And Characterizing Sample Representativeness For DWPF Melter Feed Samples

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

Shine, E. P.; Poirier, M. R.

2013-10-29

Representative sampling is important throughout the Defense Waste Processing Facility (DWPF) process, and the demonstrated success of the DWPF process to achieve glass product quality over the past two decades is a direct result of the quality of information obtained from the process. The objective of this report was to present sampling methods that the Savannah River Site (SRS) used to qualify waste being dispositioned at the DWPF. The goal was to emphasize the methodology, not a list of outcomes from those studies. This methodology includes proven methods for taking representative samples, the use of controlled analytical methods, and datamore » interpretation and reporting that considers the uncertainty of all error sources. Numerous sampling studies were conducted during the development of the DWPF process and still continue to be performed in order to evaluate options for process improvement. Study designs were based on use of statistical tools applicable to the determination of uncertainties associated with the data needs. Successful designs are apt to be repeated, so this report chose only to include prototypic case studies that typify the characteristics of frequently used designs. Case studies have been presented for studying in-tank homogeneity, evaluating the suitability of sampler systems, determining factors that affect mixing and sampling, comparing the final waste glass product chemical composition and durability to that of the glass pour stream sample and other samples from process vessels, and assessing the uniformity of the chemical composition in the waste glass product. Many of these studies efficiently addressed more than one of these areas of concern associated with demonstrating sample representativeness and provide examples of statistical tools in use for DWPF. The time when many of these designs were implemented was in an age when the sampling ideas of Pierre Gy were not as widespread as they are today. Nonetheless, the engineers and

Data-Driven Sampling Matrix Boolean Optimization for Energy-Efficient Biomedical Signal Acquisition by Compressive Sensing.

PubMed

Wang, Yuhao; Li, Xin; Xu, Kai; Ren, Fengbo; Yu, Hao

2017-04-01

Compressive sensing is widely used in biomedical applications, and the sampling matrix plays a critical role on both quality and power consumption of signal acquisition. It projects a high-dimensional vector of data into a low-dimensional subspace by matrix-vector multiplication. An optimal sampling matrix can ensure accurate data reconstruction and/or high compression ratio. Most existing optimization methods can only produce real-valued embedding matrices that result in large energy consumption during data acquisition. In this paper, we propose an efficient method that finds an optimal Boolean sampling matrix in order to reduce the energy consumption. Compared to random Boolean embedding, our data-driven Boolean sampling matrix can improve the image recovery quality by 9 dB. Moreover, in terms of sampling hardware complexity, it reduces the energy consumption by 4.6× and the silicon area by 1.9× over the data-driven real-valued embedding.

Multiple sensitive estimation and optimal sample size allocation in the item sum technique.

PubMed

Perri, Pier Francesco; Rueda García, María Del Mar; Cobo Rodríguez, Beatriz

2018-01-01

For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systematic development and optimization of chemically defined medium supporting high cell density growth of Bacillus coagulans.

PubMed

Chen, Yu; Dong, Fengqing; Wang, Yonghong

2016-09-01

With determined components and experimental reducibility, the chemically defined medium (CDM) and the minimal chemically defined medium (MCDM) are used in many metabolism and regulation studies. This research aimed to develop the chemically defined medium supporting high cell density growth of Bacillus coagulans, which is a promising producer of lactic acid and other bio-chemicals. In this study, a systematic methodology combining the experimental technique with flux balance analysis (FBA) was proposed to design and simplify a CDM. The single omission technique and single addition technique were employed to determine the essential and stimulatory compounds, before the optimization of their concentrations by the statistical method. In addition, to improve the growth rationally, in silico omission and addition were performed by FBA based on the construction of a medium-size metabolic model of B. coagulans 36D1. Thus, CDMs were developed to obtain considerable biomass production of at least five B. coagulans strains, in which two model strains B. coagulans 36D1 and ATCC 7050 were involved.

Optimally Stopped Optimization

NASA Astrophysics Data System (ADS)

Vinci, Walter; Lidar, Daniel

We combine the fields of heuristic optimization and optimal stopping. We propose a strategy for benchmarking randomized optimization algorithms that minimizes the expected total cost for obtaining a good solution with an optimal number of calls to the solver. To do so, rather than letting the objective function alone define a cost to be minimized, we introduce a further cost-per-call of the algorithm. We show that this problem can be formulated using optimal stopping theory. The expected cost is a flexible figure of merit for benchmarking probabilistic solvers that can be computed when the optimal solution is not known, and that avoids the biases and arbitrariness that affect other measures. The optimal stopping formulation of benchmarking directly leads to a real-time, optimal-utilization strategy for probabilistic optimizers with practical impact. We apply our formulation to benchmark the performance of a D-Wave 2X quantum annealer and the HFS solver, a specialized classical heuristic algorithm designed for low tree-width graphs. On a set of frustrated-loop instances with planted solutions defined on up to N = 1098 variables, the D-Wave device is between one to two orders of magnitude faster than the HFS solver.

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

PubMed

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.

Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range.

PubMed

Luo, Dehui; Wan, Xiang; Liu, Jiming; Tong, Tiejun

2018-06-01

The era of big data is coming, and evidence-based medicine is attracting increasing attention to improve decision making in medical practice via integrating evidence from well designed and conducted clinical research. Meta-analysis is a statistical technique widely used in evidence-based medicine for analytically combining the findings from independent clinical trials to provide an overall estimation of a treatment effectiveness. The sample mean and standard deviation are two commonly used statistics in meta-analysis but some trials use the median, the minimum and maximum values, or sometimes the first and third quartiles to report the results. Thus, to pool results in a consistent format, researchers need to transform those information back to the sample mean and standard deviation. In this article, we investigate the optimal estimation of the sample mean for meta-analysis from both theoretical and empirical perspectives. A major drawback in the literature is that the sample size, needless to say its importance, is either ignored or used in a stepwise but somewhat arbitrary manner, e.g. the famous method proposed by Hozo et al. We solve this issue by incorporating the sample size in a smoothly changing weight in the estimators to reach the optimal estimation. Our proposed estimators not only improve the existing ones significantly but also share the same virtue of the simplicity. The real data application indicates that our proposed estimators are capable to serve as "rules of thumb" and will be widely applied in evidence-based medicine.

Optimization of Sample Points for Monitoring Arable Land Quality by Simulated Annealing while Considering Spatial Variations

PubMed Central

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

Generalized Likelihood Uncertainty Estimation (GLUE) Using Multi-Optimization Algorithm as Sampling Method

NASA Astrophysics Data System (ADS)

Wang, Z.

2015-12-01

For decades, distributed and lumped hydrological models have furthered our understanding of hydrological system. The development of hydrological simulation in large scale and high precision elaborated the spatial descriptions and hydrological behaviors. Meanwhile, the new trend is also followed by the increment of model complexity and number of parameters, which brings new challenges of uncertainty quantification. Generalized Likelihood Uncertainty Estimation (GLUE) has been widely used in uncertainty analysis for hydrological models referring to Monte Carlo method coupled with Bayesian estimation. However, the stochastic sampling method of prior parameters adopted by GLUE appears inefficient, especially in high dimensional parameter space. The heuristic optimization algorithms utilizing iterative evolution show better convergence speed and optimality-searching performance. In light of the features of heuristic optimization algorithms, this study adopted genetic algorithm, differential evolution, shuffled complex evolving algorithm to search the parameter space and obtain the parameter sets of large likelihoods. Based on the multi-algorithm sampling, hydrological model uncertainty analysis is conducted by the typical GLUE framework. To demonstrate the superiority of the new method, two hydrological models of different complexity are examined. The results shows the adaptive method tends to be efficient in sampling and effective in uncertainty analysis, providing an alternative path for uncertainty quantilization.

Efficient Round-Trip Time Optimization for Replica-Exchange Enveloping Distribution Sampling (RE-EDS).

PubMed

Sidler, Dominik; Cristòfol-Clough, Michael; Riniker, Sereina

2017-06-13

Replica-exchange enveloping distribution sampling (RE-EDS) allows the efficient estimation of free-energy differences between multiple end-states from a single molecular dynamics (MD) simulation. In EDS, a reference state is sampled, which can be tuned by two types of parameters, i.e., smoothness parameters(s) and energy offsets, such that all end-states are sufficiently sampled. However, the choice of these parameters is not trivial. Replica exchange (RE) or parallel tempering is a widely applied technique to enhance sampling. By combining EDS with the RE technique, the parameter choice problem could be simplified and the challenge shifted toward an optimal distribution of the replicas in the smoothness-parameter space. The choice of a certain replica distribution can alter the sampling efficiency significantly. In this work, global round-trip time optimization (GRTO) algorithms are tested for the use in RE-EDS simulations. In addition, a local round-trip time optimization (LRTO) algorithm is proposed for systems with slowly adapting environments, where a reliable estimate for the round-trip time is challenging to obtain. The optimization algorithms were applied to RE-EDS simulations of a system of nine small-molecule inhibitors of phenylethanolamine N-methyltransferase (PNMT). The energy offsets were determined using our recently proposed parallel energy-offset (PEOE) estimation scheme. While the multistate GRTO algorithm yielded the best replica distribution for the ligands in water, the multistate LRTO algorithm was found to be the method of choice for the ligands in complex with PNMT. With this, the 36 alchemical free-energy differences between the nine ligands were calculated successfully from a single RE-EDS simulation 10 ns in length. Thus, RE-EDS presents an efficient method for the estimation of relative binding free energies.

Simultaneous beam sampling and aperture shape optimization for SPORT.

PubMed

Zarepisheh, Masoud; Li, Ruijiang; Ye, Yinyu; Xing, Lei

2015-02-01

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. 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. 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 neck and a prostate case

Simultaneous beam sampling and aperture shape optimization for SPORT

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

Zarepisheh, Masoud; Li, Ruijiang; Xing, Lei, E-mail: Lei@stanford.edu

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 decisionmore » 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

Enhancing sampling design in mist-net bat surveys by accounting for sample size optimization.

PubMed

Trevelin, Leonardo Carreira; Novaes, Roberto Leonan Morim; Colas-Rosas, Paul François; Benathar, Thayse Cristhina Melo; Peres, Carlos A

2017-01-01

The advantages of mist-netting, the main technique used in Neotropical bat community studies to date, include logistical implementation, standardization and sampling representativeness. Nonetheless, study designs still have to deal with issues of detectability related to how different species behave and use the environment. Yet there is considerable sampling heterogeneity across available studies in the literature. Here, we approach the problem of sample size optimization. We evaluated the common sense hypothesis that the first six hours comprise the period of peak night activity for several species, thereby resulting in a representative sample for the whole night. To this end, we combined re-sampling techniques, species accumulation curves, threshold analysis, and community concordance of species compositional data, and applied them to datasets of three different Neotropical biomes (Amazonia, Atlantic Forest and Cerrado). We show that the strategy of restricting sampling to only six hours of the night frequently results in incomplete sampling representation of the entire bat community investigated. From a quantitative standpoint, results corroborated the existence of a major Sample Area effect in all datasets, although for the Amazonia dataset the six-hour strategy was significantly less species-rich after extrapolation, and for the Cerrado dataset it was more efficient. From the qualitative standpoint, however, results demonstrated that, for all three datasets, the identity of species that are effectively sampled will be inherently impacted by choices of sub-sampling schedule. We also propose an alternative six-hour sampling strategy (at the beginning and the end of a sample night) which performed better when resampling Amazonian and Atlantic Forest datasets on bat assemblages. Given the observed magnitude of our results, we propose that sample representativeness has to be carefully weighed against study objectives, and recommend that the trade-off between

Enhancing sampling design in mist-net bat surveys by accounting for sample size optimization

PubMed Central

Trevelin, Leonardo Carreira; Novaes, Roberto Leonan Morim; Colas-Rosas, Paul François; Benathar, Thayse Cristhina Melo; Peres, Carlos A.

2017-01-01

The advantages of mist-netting, the main technique used in Neotropical bat community studies to date, include logistical implementation, standardization and sampling representativeness. Nonetheless, study designs still have to deal with issues of detectability related to how different species behave and use the environment. Yet there is considerable sampling heterogeneity across available studies in the literature. Here, we approach the problem of sample size optimization. We evaluated the common sense hypothesis that the first six hours comprise the period of peak night activity for several species, thereby resulting in a representative sample for the whole night. To this end, we combined re-sampling techniques, species accumulation curves, threshold analysis, and community concordance of species compositional data, and applied them to datasets of three different Neotropical biomes (Amazonia, Atlantic Forest and Cerrado). We show that the strategy of restricting sampling to only six hours of the night frequently results in incomplete sampling representation of the entire bat community investigated. From a quantitative standpoint, results corroborated the existence of a major Sample Area effect in all datasets, although for the Amazonia dataset the six-hour strategy was significantly less species-rich after extrapolation, and for the Cerrado dataset it was more efficient. From the qualitative standpoint, however, results demonstrated that, for all three datasets, the identity of species that are effectively sampled will be inherently impacted by choices of sub-sampling schedule. We also propose an alternative six-hour sampling strategy (at the beginning and the end of a sample night) which performed better when resampling Amazonian and Atlantic Forest datasets on bat assemblages. Given the observed magnitude of our results, we propose that sample representativeness has to be carefully weighed against study objectives, and recommend that the trade-off between

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

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).

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.

Theory of sampling: four critical success factors before analysis.

PubMed

Wagner, Claas; Esbensen, Kim H

2015-01-01

Food and feed materials characterization, risk assessment, and safety evaluations can only be ensured if QC measures are based on valid analytical data, stemming from representative samples. The Theory of Sampling (TOS) is the only comprehensive theoretical framework that fully defines all requirements to ensure sampling correctness and representativity, and to provide the guiding principles for sampling in practice. TOS also defines the concept of material heterogeneity and its impact on the sampling process, including the effects from all potential sampling errors. TOS's primary task is to eliminate bias-generating errors and to minimize sampling variability. Quantitative measures are provided to characterize material heterogeneity, on which an optimal sampling strategy should be based. Four critical success factors preceding analysis to ensure a representative sampling process are presented here.

Optimization of Sample Preparation and Instrumental Parameters for the Rapid Analysis of Drugs of Abuse in Hair samples by MALDI-MS/MS Imaging

NASA Astrophysics Data System (ADS)

Flinders, Bryn; Beasley, Emma; Verlaan, Ricky M.; Cuypers, Eva; Francese, Simona; Bassindale, Tom; Clench, Malcolm R.; Heeren, Ron M. A.

2017-08-01

Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) has been employed to rapidly screen longitudinally sectioned drug user hair samples for cocaine and its metabolites using continuous raster imaging. Optimization of the spatial resolution and raster speed were performed on intact cocaine contaminated hair samples. The optimized settings (100 × 150 μm at 0.24 mm/s) were subsequently used to examine longitudinally sectioned drug user hair samples. The MALDI-MS/MS images showed the distribution of the most abundant cocaine product ion at m/z 182. Using the optimized settings, multiple hair samples obtained from two users were analyzed in approximately 3 h: six times faster than the standard spot-to-spot acquisition method. Quantitation was achieved using longitudinally sectioned control hair samples sprayed with a cocaine dilution series. A multiple reaction monitoring (MRM) experiment was also performed using the `dynamic pixel' imaging method to screen for cocaine and a range of its metabolites, in order to differentiate between contaminated hairs and drug users. Cocaine, benzoylecgonine, and cocaethylene were detectable, in agreement with analyses carried out using the standard LC-MS/MS method. [Figure not available: see fulltext.

Drying step optimization to obtain large-size transparent magnesium-aluminate spinel samples

NASA Astrophysics Data System (ADS)

Petit, Johan; Lallemant, Lucile

2017-05-01

In the transparent ceramics processing, the green body elaboration step is probably the most critical one. Among the known techniques, wet shaping processes are particularly interesting because they enable the particles to find an optimum position on their own. Nevertheless, the presence of water molecules leads to drying issues. During the water removal, its concentration gradient induces cracks limiting the sample size: laboratory samples are generally less damaged because of their small size but upscaling the samples for industrial applications lead to an increasing cracking probability. Thanks to the drying step optimization, large size spinel samples were obtained.

Optimally Stopped Optimization

NASA Astrophysics Data System (ADS)

Vinci, Walter; Lidar, Daniel A.

2016-11-01

We combine the fields of heuristic optimization and optimal stopping. We propose a strategy for benchmarking randomized optimization algorithms that minimizes the expected total cost for obtaining a good solution with an optimal number of calls to the solver. To do so, rather than letting the objective function alone define a cost to be minimized, we introduce a further cost-per-call of the algorithm. We show that this problem can be formulated using optimal stopping theory. The expected cost is a flexible figure of merit for benchmarking probabilistic solvers that can be computed when the optimal solution is not known and that avoids the biases and arbitrariness that affect other measures. The optimal stopping formulation of benchmarking directly leads to a real-time optimal-utilization strategy for probabilistic optimizers with practical impact. We apply our formulation to benchmark simulated annealing on a class of maximum-2-satisfiability (MAX2SAT) problems. We also compare the performance of a D-Wave 2X quantum annealer to the Hamze-Freitas-Selby (HFS) solver, a specialized classical heuristic algorithm designed for low-tree-width graphs. On a set of frustrated-loop instances with planted solutions defined on up to N =1098 variables, the D-Wave device is 2 orders of magnitude faster than the HFS solver, and, modulo known caveats related to suboptimal annealing times, exhibits identical scaling with problem size.

Optimizing the triple-axis spectrometer PANDA at the MLZ for small samples and complex sample environment conditions

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 spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

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.

Multiple indicator cokriging with application to optimal sampling for environmental monitoring

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Dowd, Peter A.

2005-02-01

A probabilistic solution to the problem of spatial interpolation of a variable at an unsampled location consists of estimating the local cumulative distribution function (cdf) of the variable at that location from values measured at neighbouring locations. As this distribution is conditional to the data available at neighbouring locations it incorporates the uncertainty of the value of the variable at the unsampled location. Geostatistics provides a non-parametric solution to such problems via the various forms of indicator kriging. In a least squares sense indicator cokriging is theoretically the best estimator but in practice its use has been inhibited by problems such as an increased number of violations of order relations constraints when compared with simpler forms of indicator kriging. In this paper, we describe a methodology and an accompanying computer program for estimating a vector of indicators by simple indicator cokriging, i.e. simultaneous estimation of the cdf for K different thresholds, {F(u,zk),k=1,…,K}, by solving a unique cokriging system for each location at which an estimate is required. This approach produces a variance-covariance matrix of the estimated vector of indicators which is used to fit a model to the estimated local cdf by logistic regression. This model is used to correct any violations of order relations and automatically ensures that all order relations are satisfied, i.e. the estimated cumulative distribution function, F^(u,zk), is such that: F^(u,zk)∈[0,1],∀zk,andF^(u,zk)⩽F^(u,z)forzkoptimal spatial sampling strategy is required for environmental monitoring, is used to demonstrate the methodology and the use of the program. The purpose of the sampling is to determine the spatial extent of a specified phase (e.g. areal distribution of a pollutant or contaminant). The sampling is sequential with a new sample being added to an existing network at each step of the procedure. The optimal

Optimization of a Sample Processing Protocol for Recovery of ...

EPA Pesticide Factsheets

Journal Article 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.

Optimal probes for withdrawal of uncontaminated fluid samples

NASA Astrophysics Data System (ADS)

Sherwood, J. D.

2005-08-01

Withdrawal of fluid by a composite probe pushed against the face z =0 of a porous half-space z >0 is modeled assuming incompressible Darcy flow. The probe is circular, of radius a, with an inner sampling section of radius αa and a concentric outer guard probe αa βa is saturated with fluid 2; the two fluids have the same viscosity. It is assumed that the interface between the two fluids is sharp and remains so as it moves through the rock. The pressure in the probe is lower than that of the pore fluid in the rock, so that the fluid interface is convected with the fluids towards the probe. This idealized axisymmetric problem is solved numerically, and it is shown that an analysis based on far-field spherical flow towards a point sink is a good approximation when the nondimensional depth of fluid 1 is large, i.e., β ≫1. The inner sampling probe eventually produces pure fluid 2, and this technique has been proposed for sampling pore fluids in rock surrounding an oil well [A. Hrametz, C. Gardner, M. Wais, and M. Proett, U.S. Patent No. 6,301,959 B1 (16 October 2001)]. Fluid 1 is drilling fluid filtrate, which has displaced the original pore fluid (fluid 2), a pure sample of which is required. The time required to collect an uncontaminated sample of original pore fluid can be minimized by a suitable choice of the probe geometry α [J. Sherwood, J. Fitzgerald and B. Hill, U.S. Patent No. 6,719,049 B2 (13 April 2004)]. It is shown that the optimal choice of α depends on the depth of filtrate invasion β and the volume of sample required.

Statistical aspects of point count sampling

USGS Publications Warehouse

Barker, R.J.; Sauer, J.R.; Ralph, C.J.; Sauer, J.R.; Droege, S.

1995-01-01

The dominant feature of point counts is that they do not census birds, but instead provide incomplete counts of individuals present within a survey plot. Considering a simple model for point count sampling, we demon-strate that use of these incomplete counts can bias estimators and testing procedures, leading to inappropriate conclusions. A large portion of the variability in point counts is caused by the incomplete counting, and this within-count variation can be confounded with ecologically meaningful varia-tion. We recommend caution in the analysis of estimates obtained from point counts. Using; our model, we also consider optimal allocation of sampling effort. The critical step in the optimization process is in determining the goals of the study and methods that will be used to meet these goals. By explicitly defining the constraints on sampling and by estimating the relationship between precision and bias of estimators and time spent counting, we can predict the optimal time at a point for each of several monitoring goals. In general, time spent at a point will differ depending on the goals of the study.

Seismic sample areas defined from incomplete catalogues: an application to the Italian territory

NASA Astrophysics Data System (ADS)

Mulargia, F.; Tinti, S.

1985-11-01

The comprehensive understanding of earthquake source-physics under real conditions requires the study not of single faults as separate entities but rather of a seismically active region as a whole, accounting for the interaction among different structures. We define "seismic sample area" the most convenient region to be used as a natural laboratory for the study of seismic source physics. This coincides with the region where the average large magnitude seismicity is the highest. To this end, time and space future distributions of large earthquakes are to be estimated. Using catalog seismicity as an input, the rate of occurrence is not constant but appears generally biased by incompleteness in some parts of the catalog and possible nonstationarities in seismic activity. We present a statistical procedure which is capable, under a few mild assumptions, of both detecting nonstationarities in seismicity and finding the incomplete parts of a seismic catalog. The procedure is based on Kolmogorov-Smirnov nonparametric statistics, and can be applied without a priori assuming the parent distribution of the events. The efficiency of this procedure allows the analysis of small data sets. An application to the Italian territory is presented, using the most recent version of the ENEL seismic catalog. Seismic activity takes place in six well defined areas but only five of them have a number of events sufficient for analysis. Barring a few exceptions, seismicity is found stationary throughout the whole catalog span 1000-1980. The eastern Alps region stands out as the best "sample area", with the highest average probability of event occurrence per time and area unit. Final objective of this characterization is to stimulate a program of intensified research.

Optimization of Evans blue quantitation in limited rat tissue samples

PubMed Central

Wang, Hwai-Lee; Lai, Ted Weita

2014-01-01

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. PMID:25300427

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.

Optimized probability sampling of study sites to improve generalizability in a multisite intervention trial.

PubMed

Kraschnewski, Jennifer L; Keyserling, Thomas C; Bangdiwala, Shrikant I; Gizlice, Ziya; Garcia, Beverly A; Johnston, Larry F; Gustafson, Alison; Petrovic, Lindsay; Glasgow, Russell E; Samuel-Hodge, Carmen D

2010-01-01

Studies of type 2 translation, the adaption of evidence-based interventions to real-world settings, should include representative study sites and staff to improve external validity. Sites for such studies are, however, often selected by convenience sampling, which limits generalizability. We used an optimized probability sampling protocol to select an unbiased, representative sample of study sites to prepare for a randomized trial of a weight loss intervention. We invited North Carolina health departments within 200 miles of the research center to participate (N = 81). Of the 43 health departments that were eligible, 30 were interested in participating. To select a representative and feasible sample of 6 health departments that met inclusion criteria, we generated all combinations of 6 from the 30 health departments that were eligible and interested. From the subset of combinations that met inclusion criteria, we selected 1 at random. Of 593,775 possible combinations of 6 counties, 15,177 (3%) met inclusion criteria. Sites in the selected subset were similar to all eligible sites in terms of health department characteristics and county demographics. Optimized probability sampling improved generalizability by ensuring an unbiased and representative sample of study sites.

Optimization of liquid scintillation measurements applied to smears and aqueous samples collected in industrial environments

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.

Determination of the optimal sample size for a clinical trial accounting for the population size.

PubMed

Stallard, Nigel; Miller, Frank; Day, Simon; Hee, Siew Wan; Madan, Jason; Zohar, Sarah; Posch, Martin

2017-07-01

The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision-theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two-arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal Time-Resource Allocation for Energy-Efficient Physical Activity Detection

PubMed Central

Thatte, Gautam; Li, Ming; Lee, Sangwon; Emken, B. Adar; Annavaram, Murali; Narayanan, Shrikanth; Spruijt-Metz, Donna; Mitra, Urbashi

2011-01-01

The optimal allocation of samples for physical activity detection in a wireless body area network for health-monitoring is considered. The number of biometric samples collected at the mobile device fusion center, from both device-internal and external Bluetooth heterogeneous sensors, is optimized to minimize the transmission power for a fixed number of samples, and to meet a performance requirement defined using the probability of misclassification between multiple hypotheses. A filter-based feature selection method determines an optimal feature set for classification, and a correlated Gaussian model is considered. Using experimental data from overweight adolescent subjects, it is found that allocating a greater proportion of samples to sensors which better discriminate between certain activity levels can result in either a lower probability of error or energy-savings ranging from 18% to 22%, in comparison to equal allocation of samples. The current activity of the subjects and the performance requirements do not significantly affect the optimal allocation, but employing personalized models results in improved energy-efficiency. As the number of samples is an integer, an exhaustive search to determine the optimal allocation is typical, but computationally expensive. To this end, an alternate, continuous-valued vector optimization is derived which yields approximately optimal allocations and can be implemented on the mobile fusion center due to its significantly lower complexity. PMID:21796237

Liebowitz Social Anxiety Scale (LSAS): Optimal cut points for remission and response in a German sample.

PubMed

von Glischinski, M; Willutzki, U; Stangier, U; Hiller, W; Hoyer, J; Leibing, E; Leichsenring, F; Hirschfeld, G

2018-02-11

The Liebowitz Social Anxiety Scale (LSAS) is the most frequently used instrument to assess social anxiety disorder (SAD) in clinical research and practice. Both a self-reported (LSAS-SR) and a clinician-administered (LSAS-CA) version are available. The aim of the present study was to define optimal cut-off (OC) scores for remission and response to treatment for the LSAS in a German sample. Data of N = 311 patients with SAD were used who had completed psychotherapeutic treatment within a multicentre randomized controlled trial. Diagnosis of SAD and reduction in symptom severity according to the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th edition, served as gold standard. OCs yielding the best balance between sensitivity and specificity were determined using receiver operating characteristics. The variability of the resulting OCs was estimated by nonparametric bootstrapping. Using diagnosis of SAD (present vs. absent) as a criterion, results for remission indicated cut-off values of 35 for the LSAS-SR and 30 for the LSAS-CA, with acceptable sensitivity (LSAS-SR: .83, LSAS-CA: .88) and specificity (LSAS-SR: .82, LSAS-CA: .87). For detection of response to treatment, assessed by a 1-point reduction in the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th edition, rating, a reduction of 28% for the LSAS-SR and 29% for the LSAS-CA yielded the best balance between sensitivity (LSAS-SR: .75, LSAS-CA: .83) and specificity (LSAS-SR: .76, LSAS-CA: .80). To our knowledge, we are the first to define cut points for the LSAS in a German sample. Overall, the cut points for remission and response corroborate previously reported cut points, now building on a broader data basis. Copyright © 2018 John Wiley & Sons, Ltd.

Laboratory sample stability. Is it possible to define a consensus stability function? An example of five blood magnitudes.

PubMed

Gómez Rioja, Rubén; Martínez Espartosa, Débora; Segovia, Marta; Ibarz, Mercedes; Llopis, María Antonia; Bauça, Josep Miquel; Marzana, Itziar; Barba, Nuria; Ventura, Monserrat; García Del Pino, Isabel; Puente, Juan José; Caballero, Andrea; Gómez, Carolina; García Álvarez, Ana; Alsina, María Jesús; Álvarez, Virtudes

2018-05-05

The stability limit of an analyte in a biological sample can be defined as the time required until a measured property acquires a bias higher than a defined specification. Many studies assessing stability and presenting recommendations of stability limits are available, but differences among them are frequent. The aim of this study was to classify and to grade a set of bibliographic studies on the stability of five common blood measurands and subsequently generate a consensus stability function. First, a bibliographic search was made for stability studies for five analytes in blood: alanine aminotransferase (ALT), glucose, phosphorus, potassium and prostate specific antigen (PSA). The quality of every study was evaluated using an in-house grading tool. Second, the different conditions of stability were uniformly defined and the percent deviation (PD%) over time for each analyte and condition were scattered while unifying studies with similar conditions. From the 37 articles considered as valid, up to 130 experiments were evaluated and 629 PD% data were included (106 for ALT, 180 for glucose, 113 for phosphorus, 145 for potassium and 85 for PSA). Consensus stability equations were established for glucose, potassium, phosphorus and PSA, but not for ALT. Time is the main variable affecting stability in medical laboratory samples. Bibliographic studies differ in recommedations of stability limits mainly because of different specifications for maximum allowable error. Definition of a consensus stability function in specific conditions can help laboratories define stability limits using their own quality specifications.

Optimal number of features as a function of sample size for various classification rules.

PubMed

Hua, Jianping; Xiong, Zixiang; Lowey, James; Suh, Edward; Dougherty, Edward R

2005-04-15

Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. For the companion website, please

Optimized methods for total nucleic acid extraction and quantification of the bat white-nose syndrome fungus, Pseudogymnoascus destructans, from swab and environmental samples.

PubMed

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. © 2016 The Author(s).

Optimized methods for total nucleic acid extraction and quantification of the bat white-nose syndrome fungus, Pseudogymnoascus destructans, from swab and environmental samples

USGS Publications Warehouse

Verant, Michelle; Bohuski, Elizabeth A.; Lorch, Jeffrey M.; Blehert, David

2016-01-01

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 fromP. 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.

Characterizing the optimal flux space of genome-scale metabolic reconstructions through modified latin-hypercube sampling.

PubMed

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.

Importance Sampling in the Evaluation and Optimization of Buffered Failure Probability

DTIC Science & Technology

2015-07-01

12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015...Importance Sampling in the Evaluation and Optimization of Buffered Failure Probability Marwan M. Harajli Graduate Student, Dept. of Civil and Environ...criterion is usually the failure probability . In this paper, we examine the buffered failure probability as an attractive alternative to the failure

SU-E-T-295: Simultaneous Beam Sampling and Aperture Shape Optimization for Station Parameter Optimized Radiation Therapy (SPORT)

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

Zarepisheh, M; Li, R; Xing, L

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) andmore » 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

Optimal Appearance Model for Visual Tracking

PubMed Central

Wang, Yuru; Jiang, Longkui; Liu, Qiaoyuan; Yin, Minghao

2016-01-01

Many studies argue that integrating multiple cues in an adaptive way increases tracking performance. However, what is the definition of adaptiveness and how to realize it remains an open issue. On the premise that the model with optimal discriminative ability is also optimal for tracking the target, this work realizes adaptiveness and robustness through the optimization of multi-cue integration models. Specifically, based on prior knowledge and current observation, a set of discrete samples are generated to approximate the foreground and background distribution. With the goal of optimizing the classification margin, an objective function is defined, and the appearance model is optimized by introducing optimization algorithms. The proposed optimized appearance model framework is embedded into a particle filter for a field test, and it is demonstrated to be robust against various kinds of complex tracking conditions. This model is general and can be easily extended to other parameterized multi-cue models. PMID:26789639

Neuro-genetic system for optimization of GMI samples sensitivity.

PubMed

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

A New Wavelength Optimization and Energy-Saving Scheme Based on Network Coding in Software-Defined WDM-PON Networks

NASA Astrophysics Data System (ADS)

Ren, Danping; Wu, Shanshan; Zhang, Lijing

2016-09-01

In view of the characteristics of the global control and flexible monitor of software-defined networks (SDN), we proposes a new optical access network architecture dedicated to Wavelength Division Multiplexing-Passive Optical Network (WDM-PON) systems based on SDN. The network coding (NC) technology is also applied into this architecture to enhance the utilization of wavelength resource and reduce the costs of light source. Simulation results show that this scheme can optimize the throughput of the WDM-PON network, greatly reduce the system time delay and energy consumption.

A Miniaturized Spectrometer for Optimized Selection of Subsurface Samples for Future MSR Missions

NASA Astrophysics Data System (ADS)

De Sanctis, M. C.; Altieri, F.; De Angelis, S.; Ferrari, M.; Frigeri, A.; Biondi, D.; Novi, S.; Antonacci, F.; Gabrieli, R.; Paolinetti, R.; Villa, F.; Ammannito, A.; Mugnuolo, R.; Pirrotta, S.

2018-04-01

We present the concept of a miniaturized spectrometer based on the ExoMars2020/Ma_MISS experiment. Coupled with a drill tool, it will allow an assessment of subsurface composition and optimize the selection of martian samples with a high astrobiological potential.

ACS sampling system: design, implementation, and performance evaluation

NASA Astrophysics Data System (ADS)

Di Marcantonio, Paolo; Cirami, Roberto; Chiozzi, Gianluca

2004-09-01

By means of ACS (ALMA Common Software) framework we designed and implemented a sampling system which allows sampling of every Characteristic Component Property with a specific, user-defined, sustained frequency limited only by the hardware. Collected data are sent to various clients (one or more Java plotting widgets, a dedicated GUI or a COTS application) using the ACS/CORBA Notification Channel. The data transport is optimized: samples are cached locally and sent in packets with a lower and user-defined frequency to keep network load under control. Simultaneous sampling of the Properties of different Components is also possible. Together with the design and implementation issues we present the performance of the sampling system evaluated on two different platforms: on a VME based system using VxWorks RTOS (currently adopted by ALMA) and on a PC/104+ embedded platform using Red Hat 9 Linux operating system. The PC/104+ solution offers, as an alternative, a low cost PC compatible hardware environment with free and open operating system.

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

PubMed

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

2014-10-07

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

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

NASA Astrophysics Data System (ADS)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

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.

Deterministic and reliability based optimization of integrated thermal protection system composite panel using adaptive sampling techniques

NASA Astrophysics Data System (ADS)

Ravishankar, Bharani

Conventional space vehicles have thermal protection systems (TPS) that provide protection to an underlying structure that carries the flight loads. In an attempt to save weight, there is interest in an integrated TPS (ITPS) that combines the structural function and the TPS function. This has weight saving potential, but complicates the design of the ITPS that now has both thermal and structural failure modes. The main objectives of this dissertation was to optimally design the ITPS subjected to thermal and mechanical loads through deterministic and reliability based optimization. The optimization of the ITPS structure requires computationally expensive finite element analyses of 3D ITPS (solid) model. To reduce the computational expenses involved in the structural analysis, finite element based homogenization method was employed, homogenizing the 3D ITPS model to a 2D orthotropic plate. However it was found that homogenization was applicable only for panels that are much larger than the characteristic dimensions of the repeating unit cell in the ITPS panel. Hence a single unit cell was used for the optimization process to reduce the computational cost. Deterministic and probabilistic optimization of the ITPS panel required evaluation of failure constraints at various design points. This further demands computationally expensive finite element analyses which was replaced by efficient, low fidelity surrogate models. In an optimization process, it is important to represent the constraints accurately to find the optimum design. Instead of building global surrogate models using large number of designs, the computational resources were directed towards target regions near constraint boundaries for accurate representation of constraints using adaptive sampling strategies. Efficient Global Reliability Analyses (EGRA) facilitates sequentially sampling of design points around the region of interest in the design space. EGRA was applied to the response surface construction of

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

PubMed

Wu, Yiman; Li, Liang

2012-12-18

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

A firmware-defined digital direct-sampling NMR spectrometer for condensed matter physics

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

Pikulski, M., E-mail: marekp@ethz.ch; Shiroka, T.; Ott, H.-R.

2014-09-15

We report on the design and implementation of a new digital, broad-band nuclear magnetic resonance (NMR) spectrometer suitable for probing condensed matter. The spectrometer uses direct sampling in both transmission and reception. It relies on a single, commercially-available signal processing device with a user-accessible field-programmable gate array (FPGA). Its functions are defined exclusively by the FPGA firmware and the application software. Besides allowing for fast replication, flexibility, and extensibility, our software-based solution preserves the option to reuse the components for other projects. The device operates up to 400 MHz without, and up to 800 MHz with undersampling, respectively. Digital down-conversion with ±10 MHzmore » passband is provided on the receiver side. The system supports high repetition rates and has virtually no intrinsic dead time. We describe briefly how the spectrometer integrates into the experimental setup and present test data which demonstrates that its performance is competitive with that of conventional designs.« less

A firmware-defined digital direct-sampling NMR spectrometer for condensed matter physics.

PubMed

Pikulski, M; Shiroka, T; Ott, H-R; Mesot, J

2014-09-01

We report on the design and implementation of a new digital, broad-band nuclear magnetic resonance (NMR) spectrometer suitable for probing condensed matter. The spectrometer uses direct sampling in both transmission and reception. It relies on a single, commercially-available signal processing device with a user-accessible field-programmable gate array (FPGA). Its functions are defined exclusively by the FPGA firmware and the application software. Besides allowing for fast replication, flexibility, and extensibility, our software-based solution preserves the option to reuse the components for other projects. The device operates up to 400 MHz without, and up to 800 MHz with undersampling, respectively. Digital down-conversion with ±10 MHz passband is provided on the receiver side. The system supports high repetition rates and has virtually no intrinsic dead time. We describe briefly how the spectrometer integrates into the experimental setup and present test data which demonstrates that its performance is competitive with that of conventional designs.

Effective optimization using sample persistence: A case study on quantum annealers and various Monte Carlo optimization methods

NASA Astrophysics Data System (ADS)

Karimi, Hamed; Rosenberg, Gili; Katzgraber, Helmut G.

2017-10-01

We present and apply a general-purpose, multistart algorithm for improving the performance of low-energy samplers used for solving optimization problems. The algorithm iteratively fixes the value of a large portion of the variables to values that have a high probability of being optimal. The resulting problems are smaller and less connected, and samplers tend to give better low-energy samples for these problems. The algorithm is trivially parallelizable since each start in the multistart algorithm is independent, and could be applied to any heuristic solver that can be run multiple times to give a sample. We present results for several classes of hard problems solved using simulated annealing, path-integral quantum Monte Carlo, parallel tempering with isoenergetic cluster moves, and a quantum annealer, and show that the success metrics and the scaling are improved substantially. When combined with this algorithm, the quantum annealer's scaling was substantially improved for native Chimera graph problems. In addition, with this algorithm the scaling of the time to solution of the quantum annealer is comparable to the Hamze-de Freitas-Selby algorithm on the weak-strong cluster problems introduced by Boixo et al. Parallel tempering with isoenergetic cluster moves was able to consistently solve three-dimensional spin glass problems with 8000 variables when combined with our method, whereas without our method it could not solve any.

Defining Optimal Head-Tilt Position of Resuscitation in Neonates and Young Infants Using Magnetic Resonance Imaging Data

PubMed Central

Bhalala, Utpal S.; Hemani, Malvi; Shah, Meehir; Kim, Barbara; Gu, Brian; Cruz, Angelo; Arunachalam, Priya; Tian, Elli; Yu, Christine; Punnoose, Joshua; Chen, Steven; Petrillo, Christopher; Brown, Alisa; Munoz, Karina; Kitchen, Grant; Lam, Taylor; Bosemani, Thangamadhan; Huisman, Thierry A. G. M.; Allen, Robert H.; Acharya, Soumyadipta

2016-01-01

Head-tilt maneuver assists with achieving airway patency during resuscitation. However, the relationship between angle of head-tilt and airway patency has not been defined. Our objective was to define an optimal head-tilt position for airway patency in neonates (age: 0–28 days) and young infants (age: 29 days–4 months). We performed a retrospective study of head and neck magnetic resonance imaging (MRI) of neonates and infants to define the angle of head-tilt for airway patency. We excluded those with an artificial airway or an airway malformation. We defined head-tilt angle a priori as the angle between occipito-ophisthion line and ophisthion-C7 spinous process line on the sagittal MR images. We evaluated medical records for Hypoxic Ischemic Encephalopathy (HIE) and exposure to sedation during MRI. We analyzed MRI of head and neck regions of 63 children (53 neonates and 10 young infants). Of these 63 children, 17 had evidence of airway obstruction and 46 had a patent airway on MRI. Also, 16/63 had underlying HIE and 47/63 newborn infants had exposure to sedative medications during MRI. In spontaneously breathing and neurologically depressed newborn infants, the head-tilt angle (median ± SD) associated with patent airway (125.3° ± 11.9°) was significantly different from that of blocked airway (108.2° ± 17.1°) (Mann Whitney U-test, p = 0.0045). The logistic regression analysis showed that the proportion of patent airways progressively increased with an increasing head-tilt angle, with > 95% probability of a patent airway at head-tilt angle 144–150°. PMID:27003759

Defining Optimal Head-Tilt Position of Resuscitation in Neonates and Young Infants Using Magnetic Resonance Imaging Data.

PubMed

Bhalala, Utpal S; Hemani, Malvi; Shah, Meehir; Kim, Barbara; Gu, Brian; Cruz, Angelo; Arunachalam, Priya; Tian, Elli; Yu, Christine; Punnoose, Joshua; Chen, Steven; Petrillo, Christopher; Brown, Alisa; Munoz, Karina; Kitchen, Grant; Lam, Taylor; Bosemani, Thangamadhan; Huisman, Thierry A G M; Allen, Robert H; Acharya, Soumyadipta

2016-01-01

Head-tilt maneuver assists with achieving airway patency during resuscitation. However, the relationship between angle of head-tilt and airway patency has not been defined. Our objective was to define an optimal head-tilt position for airway patency in neonates (age: 0-28 days) and young infants (age: 29 days-4 months). We performed a retrospective study of head and neck magnetic resonance imaging (MRI) of neonates and infants to define the angle of head-tilt for airway patency. We excluded those with an artificial airway or an airway malformation. We defined head-tilt angle a priori as the angle between occipito-ophisthion line and ophisthion-C7 spinous process line on the sagittal MR images. We evaluated medical records for Hypoxic Ischemic Encephalopathy (HIE) and exposure to sedation during MRI. We analyzed MRI of head and neck regions of 63 children (53 neonates and 10 young infants). Of these 63 children, 17 had evidence of airway obstruction and 46 had a patent airway on MRI. Also, 16/63 had underlying HIE and 47/63 newborn infants had exposure to sedative medications during MRI. In spontaneously breathing and neurologically depressed newborn infants, the head-tilt angle (median ± SD) associated with patent airway (125.3° ± 11.9°) was significantly different from that of blocked airway (108.2° ± 17.1°) (Mann Whitney U-test, p = 0.0045). The logistic regression analysis showed that the proportion of patent airways progressively increased with an increasing head-tilt angle, with > 95% probability of a patent airway at head-tilt angle 144-150°.

Family Life and Human Development: Sample Units, K-6. Revised.

ERIC Educational Resources Information Center

Prince George's County Public Schools, Upper Marlboro, MD.

Sample unit outlines, designed for kindergarten through grade six, define the content, activities, and assessment tasks appropriate to specific grade levels. The units have been extracted from the Board-approved curriculum, Health Education: The Curricular Approach to Optimal Health. The instructional guidelines for grade one are: describing a…

Evaluation and optimization of microbial DNA extraction from fecal samples of wild Antarctic bird species

PubMed Central

Eriksson, Per; Mourkas, Evangelos; González-Acuna, Daniel; Olsen, Björn; Ellström, Patrik

2017-01-01

ABSTRACT Introduction: Advances in the development of nucleic acid-based methods have dramatically facilitated studies of host–microbial interactions. Fecal DNA analysis can provide information about the host’s microbiota and gastrointestinal pathogen burden. Numerous studies have been conducted in mammals, yet birds are less well studied. Avian fecal DNA extraction has proved challenging, partly due to the mixture of fecal and urinary excretions and the deficiency of optimized protocols. This study presents an evaluation of the performance in avian fecal DNA extraction of six commercial kits from different bird species, focusing on penguins. Material and methods: Six DNA extraction kits were first tested according to the manufacturers’ instructions using mallard feces. The kit giving the highest DNA yield was selected for further optimization and evaluation using Antarctic bird feces. Results: Penguin feces constitute a challenging sample type: most of the DNA extraction kits failed to yield acceptable amounts of DNA. The QIAamp cador Pathogen kit (Qiagen) performed the best in the initial investigation. Further optimization of the protocol resulted in good yields of high-quality DNA from seven bird species of different avian orders. Conclusion: This study presents an optimized approach to DNA extraction from challenging avian fecal samples. PMID:29152162

Development and optimization of the determination of pharmaceuticals in water samples by SPE and HPLC with diode-array detection.

PubMed

Pavlović, Dragana Mutavdžić; Ašperger, Danijela; Tolić, Dijana; Babić, Sandra

2013-09-01

This paper describes the development, optimization, and validation of a method for the determination of five pharmaceuticals from different therapeutic classes (antibiotics, anthelmintics, glucocorticoides) in water samples. Water samples were prepared using SPE and extracts were analyzed by HPLC with diode-array detection. The efficiency of 11 different SPE cartridges to extract the investigated compounds from water was tested in preliminary experiments. Then, the pH of the water sample, elution solvent, and sorbent mass were optimized. Except for optimization of the SPE procedure, selection of the optimal HPLC column with different stationary phases from different manufacturers has been performed. The developed method was validated using spring water samples spiked with appropriate concentrations of pharmaceuticals. Good linearity was obtained in the range of 2.4-200 μg/L, depending on the pharmaceutical with the correlation coefficients >0.9930 in all cases, except for ciprofloxacin (0.9866). Also, the method has revealed that low LODs (0.7-3.9 μg/L), good precision (intra- and interday) with RSD below 17% and recoveries above 98% for all pharmaceuticals. The method has been successfully applied to the analysis of production wastewater samples from the pharmaceutical industry. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metagenomic Analysis of Dairy Bacteriophages: Extraction Method and Pilot Study on Whey Samples Derived from Using Undefined and Defined Mesophilic Starter Cultures.

PubMed

Muhammed, Musemma K; Kot, Witold; Neve, Horst; Mahony, Jennifer; Castro-Mejía, Josué L; Krych, Lukasz; Hansen, Lars H; Nielsen, Dennis S; Sørensen, Søren J; Heller, Knut J; van Sinderen, Douwe; Vogensen, Finn K

2017-10-01

Despite being potentially highly useful for characterizing the biodiversity of phages, metagenomic studies are currently not available for dairy bacteriophages, partly due to the lack of a standard procedure for phage extraction. We optimized an extraction method that allows the removal of the bulk protein from whey and milk samples with losses of less than 50% of spiked phages. The protocol was applied to extract phages from whey in order to test the notion that members of Lactococcus lactis 936 (now Sk1virus ), P335, c2 (now C2virus ) and Leuconostoc phage groups are the most frequently encountered in the dairy environment. The relative abundance and diversity of phages in eight and four whey mixtures from dairies using undefined mesophilic mixed-strain cultures containing Lactococcus lactis subsp. lactis biovar diacetylactis and Leuconostoc species (i.e., DL starter cultures) and defined cultures, respectively, were assessed. Results obtained from transmission electron microscopy and high-throughput sequence analyses revealed the dominance of Lc. lactis 936 phages (order Caudovirales , family Siphoviridae ) in dairies using undefined DL starter cultures and Lc. lactis c2 phages (order Caudovirales , family Siphoviridae ) in dairies using defined cultures. The 936 and Leuconostoc phages demonstrated limited diversity. Possible coinduction of temperate P335 prophages and satellite phages in one of the whey mixtures was also observed. IMPORTANCE The method optimized in this study could provide an important basis for understanding the dynamics of the phage community (abundance, development, diversity, evolution, etc.) in dairies with different sizes, locations, and production strategies. It may also enable the discovery of previously unknown phages, which is crucial for the development of rapid molecular biology-based methods for phage burden surveillance systems. The dominance of only a few phage groups in the dairy environment signifies the depth of knowledge

Metagenomic Analysis of Dairy Bacteriophages: Extraction Method and Pilot Study on Whey Samples Derived from Using Undefined and Defined Mesophilic Starter Cultures

PubMed Central

Muhammed, Musemma K.; Kot, Witold; Neve, Horst; Mahony, Jennifer; Castro-Mejía, Josué L.; Krych, Lukasz; Hansen, Lars H.; Nielsen, Dennis S.; Sørensen, Søren J.; Heller, Knut J.; van Sinderen, Douwe

2017-01-01

ABSTRACT Despite being potentially highly useful for characterizing the biodiversity of phages, metagenomic studies are currently not available for dairy bacteriophages, partly due to the lack of a standard procedure for phage extraction. We optimized an extraction method that allows the removal of the bulk protein from whey and milk samples with losses of less than 50% of spiked phages. The protocol was applied to extract phages from whey in order to test the notion that members of Lactococcus lactis 936 (now Sk1virus), P335, c2 (now C2virus) and Leuconostoc phage groups are the most frequently encountered in the dairy environment. The relative abundance and diversity of phages in eight and four whey mixtures from dairies using undefined mesophilic mixed-strain cultures containing Lactococcus lactis subsp. lactis biovar diacetylactis and Leuconostoc species (i.e., DL starter cultures) and defined cultures, respectively, were assessed. Results obtained from transmission electron microscopy and high-throughput sequence analyses revealed the dominance of Lc. lactis 936 phages (order Caudovirales, family Siphoviridae) in dairies using undefined DL starter cultures and Lc. lactis c2 phages (order Caudovirales, family Siphoviridae) in dairies using defined cultures. The 936 and Leuconostoc phages demonstrated limited diversity. Possible coinduction of temperate P335 prophages and satellite phages in one of the whey mixtures was also observed. IMPORTANCE The method optimized in this study could provide an important basis for understanding the dynamics of the phage community (abundance, development, diversity, evolution, etc.) in dairies with different sizes, locations, and production strategies. It may also enable the discovery of previously unknown phages, which is crucial for the development of rapid molecular biology-based methods for phage burden surveillance systems. The dominance of only a few phage groups in the dairy environment signifies the depth of knowledge

Optimization of sampling parameters for collection and preconcentration of alveolar air by needle traps.

PubMed

Filipiak, Wojciech; Filipiak, Anna; Ager, Clemens; Wiesenhofer, Helmut; Amann, Anton

2012-06-01

The approach for breath-VOCs' collection and preconcentration by applying needle traps was developed and optimized. The alveolar air was collected from only a few exhalations under visual control of expired CO(2) into a large gas-tight glass syringe and then warmed up to 45 °C for a short time to avoid condensation. Subsequently, a specially constructed sampling device equipped with Bronkhorst® electronic flow controllers was used for automated adsorption. This sampling device allows time-saving collection of expired/inspired air in parallel onto three different needle traps as well as improvement of sensitivity and reproducibility of NT-GC-MS analysis by collection of relatively large (up to 150 ml) volume of exhaled breath. It was shown that the collection of alveolar air derived from only a few exhalations into a large syringe followed by automated adsorption on needle traps yields better results than manual sorption by up/down cycles with a 1 ml syringe, mostly due to avoided condensation and electronically controlled stable sample flow rate. The optimal profile and composition of needle traps consists of 2 cm Carbopack X and 1 cm Carboxen 1000, allowing highly efficient VOCs' enrichment, while injection by a fast expansive flow technique requires no modifications in instrumentation and fully automated GC-MS analysis can be performed with a commercially available autosampler. This optimized analytical procedure considerably facilitates the collection and enrichment of alveolar air, and is therefore suitable for application at the bedside of critically ill patients in an intensive care unit. Due to its simplicity it can replace the time-consuming sampling of sufficient breath volume by numerous up/down cycles with a 1 ml syringe.

TestSTORM: Simulator for optimizing sample labeling and image acquisition in localization based super-resolution microscopy

PubMed Central

Sinkó, József; Kákonyi, Róbert; Rees, Eric; Metcalf, Daniel; Knight, Alex E.; Kaminski, Clemens F.; Szabó, Gábor; Erdélyi, Miklós

2014-01-01

Localization-based super-resolution microscopy image quality depends on several factors such as dye choice and labeling strategy, microscope quality and user-defined parameters such as frame rate and number as well as the image processing algorithm. Experimental optimization of these parameters can be time-consuming and expensive so we present TestSTORM, a simulator that can be used to optimize these steps. TestSTORM users can select from among four different structures with specific patterns, dye and acquisition parameters. Example results are shown and the results of the vesicle pattern are compared with experimental data. Moreover, image stacks can be generated for further evaluation using localization algorithms, offering a tool for further software developments. PMID:24688813

Gamut Volume Index: a color preference metric based on meta-analysis and optimized colour samples.

PubMed

Liu, Qiang; Huang, Zheng; Xiao, Kaida; Pointer, Michael R; Westland, Stephen; Luo, M Ronnier

2017-07-10

A novel metric named Gamut Volume Index (GVI) is proposed for evaluating the colour preference of lighting. This metric is based on the absolute gamut volume of optimized colour samples. The optimal colour set of the proposed metric was obtained by optimizing the weighted average correlation between the metric predictions and the subjective ratings for 8 psychophysical studies. The performance of 20 typical colour metrics was also investigated, which included colour difference based metrics, gamut based metrics, memory based metrics as well as combined metrics. It was found that the proposed GVI outperformed the existing counterparts, especially for the conditions where correlated colour temperatures differed.

Optimization for Peptide Sample Preparation for Urine Peptidomics

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

Sigdel, Tara K.; Nicora, Carrie D.; Hsieh, Szu-Chuan

2014-02-25

proteins 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.« less

Low-thrust trajectory optimization of asteroid sample return mission with multiple revolutions and moon gravity assists

NASA Astrophysics Data System (ADS)

Tang, Gao; Jiang, FanHuag; Li, JunFeng

2015-11-01

Near-Earth asteroids have gained a lot of interest and the development in low-thrust propulsion technology makes complex deep space exploration missions possible. A mission from low-Earth orbit using low-thrust electric propulsion system to rendezvous with near-Earth asteroid and bring sample back is investigated. By dividing the mission into five segments, the complex mission is solved separately. Then different methods are used to find optimal trajectories for every segment. Multiple revolutions around the Earth and multiple Moon gravity assists are used to decrease the fuel consumption to escape from the Earth. To avoid possible numerical difficulty of indirect methods, a direct method to parameterize the switching moment and direction of thrust vector is proposed. To maximize the mass of sample, optimal control theory and homotopic approach are applied to find the optimal trajectory. Direct methods of finding proper time to brake the spacecraft using Moon gravity assist are also proposed. Practical techniques including both direct and indirect methods are investigated to optimize trajectories for different segments and they can be easily extended to other missions and more precise dynamic model.

Population Pharmacokinetics and Optimal Sampling Strategy for Model-Based Precision Dosing of Melphalan in Patients Undergoing Hematopoietic Stem Cell Transplantation.

PubMed

Mizuno, Kana; Dong, Min; Fukuda, Tsuyoshi; Chandra, Sharat; Mehta, Parinda A; McConnell, Scott; Anaissie, Elias J; Vinks, Alexander A

2018-05-01

High-dose melphalan is an important component of conditioning regimens for patients undergoing hematopoietic stem cell transplantation. The current dosing strategy based on body surface area results in a high incidence of oral mucositis and gastrointestinal and liver toxicity. Pharmacokinetically guided dosing will individualize exposure and help minimize overexposure-related toxicity. The purpose of this study was to develop a population pharmacokinetic model and optimal sampling strategy. A population pharmacokinetic model was developed with NONMEM using 98 observations collected from 15 adult patients given the standard dose of 140 or 200 mg/m 2 by intravenous infusion. The determinant-optimal sampling strategy was explored with PopED software. Individual area under the curve estimates were generated by Bayesian estimation using full and the proposed sparse sampling data. The predictive performance of the optimal sampling strategy was evaluated based on bias and precision estimates. The feasibility of the optimal sampling strategy was tested using pharmacokinetic data from five pediatric patients. A two-compartment model best described the data. The final model included body weight and creatinine clearance as predictors of clearance. The determinant-optimal sampling strategies (and windows) were identified at 0.08 (0.08-0.19), 0.61 (0.33-0.90), 2.0 (1.3-2.7), and 4.0 (3.6-4.0) h post-infusion. An excellent correlation was observed between area under the curve estimates obtained with the full and the proposed four-sample strategy (R 2  = 0.98; p < 0.01) with a mean bias of -2.2% and precision of 9.4%. A similar relationship was observed in children (R 2  = 0.99; p < 0.01). The developed pharmacokinetic model-based sparse sampling strategy promises to achieve the target area under the curve as part of precision dosing.

Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks

USGS Publications Warehouse

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.

Fast Marching Tree: a Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions*

PubMed Central

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

A Two-Stage Method to Determine Optimal Product Sampling considering Dynamic Potential Market

PubMed Central

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

Determining Optimal Location and Numbers of Sample Transects for Characterization of UXO Sites

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

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 ofmore » 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

Defining an optimal surface chemistry for pluripotent stem cell culture in 2D and 3D

NASA Astrophysics Data System (ADS)

Zonca, Michael R., Jr.

Surface chemistry is critical for growing pluripotent stem cells in an undifferentiated state. There is great potential to engineer the surface chemistry at the nanoscale level to regulate stem cell adhesion. However, the challenge is to identify the optimal surface chemistry of the substrata for ES cell attachment and maintenance. Using a high-throughput polymerization and screening platform, a chemically defined, synthetic polymer grafted coating that supports strong attachment and high expansion capacity of pluripotent stem cells has been discovered using mouse embryonic stem (ES) cells as a model system. This optimal substrate, N-[3-(Dimethylamino)propyl] methacrylamide (DMAPMA) that is grafted on 2D synthetic poly(ether sulfone) (PES) membrane, sustains the self-renewal of ES cells (up to 7 passages). DMAPMA supports cell attachment of ES cells through integrin beta1 in a RGD-independent manner and is similar to another recently reported polymer surface. Next, DMAPMA has been able to be transferred to 3D by grafting to synthetic, polymeric, PES fibrous matrices through both photo-induced and plasma-induced polymerization. These 3D modified fibers exhibited higher cell proliferation and greater expression of pluripotency markers of mouse ES cells than 2D PES membranes. Our results indicated that desirable surfaces in 2D can be scaled to 3D and that both surface chemistry and structural dimension strongly influence the growth and differentiation of pluripotent stem cells. Lastly, the feasibility of incorporating DMAPMA into a widely used natural polymer, alginate, has been tested. Novel adhesive alginate hydrogels have been successfully synthesized by either direct polymerization of DMAPMA and methacrylic acid blended with alginate, or photo-induced DMAPMA polymerization on alginate nanofibrous hydrogels. In particular, DMAPMA-coated alginate hydrogels support strong ES cell attachment, exhibiting a concentration dependency of DMAPMA. This research provides a

Optimizing 4-Dimensional Magnetic Resonance Imaging Data Sampling for Respiratory Motion Analysis of Pancreatic Tumors

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

Stemkens, Bjorn, E-mail: b.stemkens@umcutrecht.nl; 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 foundmore » 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.« less

New multirate sampled-data control law structure and synthesis algorithm

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.; Yang, Gen-Sheng

1992-01-01

A new multirate sampled-data control law structure is defined and a new parameter-optimization-based synthesis algorithm for that structure is introduced. The synthesis algorithm can be applied to multirate, multiple-input/multiple-output, sampled-data control laws having a prescribed dynamic order and structure, and a priori specified sampling/update rates for all sensors, processor states, and control inputs. The synthesis algorithm is applied to design two-input, two-output tip position controllers of various dynamic orders for a sixth-order, two-link robot arm model.

Optimal timber harvest scheduling with spatially defined sediment objectives

Treesearch

Jon Hof; Michael Bevers

2000-01-01

This note presents a simple model formulation that focuses on the spatial relationships over time between timber harvesting and sediment levels in water runoff courses throughout the watershed being managed. A hypothetical example is developed to demonstrate the formulation and show how sediment objectives can be spatially defined anywhere in the watershed. Spatial...

Method optimization for non-equilibrium solid phase microextraction sampling of HAPs for GC/MS analysis

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.

Microwave resonances in dielectric samples probed in Corbino geometry: simulation and experiment.

PubMed

Felger, M Maximilian; Dressel, Martin; Scheffler, Marc

2013-11-01

The Corbino approach, where the sample of interest terminates a coaxial cable, is a well-established method for microwave spectroscopy. If the sample is dielectric and if the probe geometry basically forms a conductive cavity, this combination can sustain well-defined microwave resonances that are detrimental for broadband measurements. Here, we present detailed simulations and measurements to investigate the resonance frequencies as a function of sample and probe size and of sample permittivity. This allows a quantitative optimization to increase the frequency of the lowest-lying resonance.

Optimization of sampling pattern and the design of Fourier ptychographic illuminator.

PubMed

Guo, Kaikai; Dong, Siyuan; Nanda, Pariksheet; Zheng, Guoan

2015-03-09

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.

Efficiency enhancement of optimized Latin hypercube sampling strategies: Application to Monte Carlo uncertainty analysis and meta-modeling

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

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.

Gaussian mass optimization for kernel PCA parameters

NASA Astrophysics Data System (ADS)

Liu, Yong; Wang, Zulin

2011-10-01

This paper proposes a novel kernel parameter optimization method based on Gaussian mass, which aims to overcome the current brute force parameter optimization method in a heuristic way. Generally speaking, the choice of kernel parameter should be tightly related to the target objects while the variance between the samples, the most commonly used kernel parameter, doesn't possess much features of the target, which gives birth to Gaussian mass. Gaussian mass defined in this paper has the property of the invariance of rotation and translation and is capable of depicting the edge, topology and shape information. Simulation results show that Gaussian mass leads a promising heuristic optimization boost up for kernel method. In MNIST handwriting database, the recognition rate improves by 1.6% compared with common kernel method without Gaussian mass optimization. Several promising other directions which Gaussian mass might help are also proposed at the end of the paper.

Optimizing cord blood sample cryopreservation.

PubMed

Harris, David T

2012-03-01

Cord blood (CB) banking is becoming more and more commonplace throughout the medical community, both in the USA and elsewhere. It is now generally recognized that storage of CB samples in multiple aliquots is the preferred approach to banking because it allows the greatest number of uses of the sample. However, it is unclear which are the best methodologies for cryopreservation and storage of the sample aliquots. In the current study we analyzed variables that could affect these processes. CB were processed into mononuclear cells (MNC) and frozen in commercially available human serum albumin (HSA) or autologous CB plasma using cryovials of various sizes and cryobags. The bacteriophage phiX174 was used as a model virus to test for cross-contamination. We observed that cryopreservation of CB in HSA, undiluted autologous human plasma and 50% diluted plasma was equivalent in terms of cell recovery and cell viability. We also found that cryopreservation of CB samples in either cryovials or cryobags displayed equivalent thermal characteristics. Finally, we demonstrated that overwrapping the CB storage container in an impermeable plastic sheathing was sufficient to prevent cross-sample viral contamination during prolonged storage in the liquid phase of liquid nitrogen dewar storage. CB may be cryopreserved in either vials or bags without concern for temperature stability. Sample overwrapping is sufficient to prevent microbiologic contamination of the samples while in liquid-phase liquid nitrogen storage.

Downselection for Sample Return — Defining Sampling Strategies Using Lessons from Terrestrial Field Analogues

NASA Astrophysics Data System (ADS)

Stevens, A. H.; Gentry, D.; Amador, E.; Cable, M. L.; Cantrell, T.; Chaudry, N.; Cullen, T.; Duca, Z.; Jacobsen, M.; Kirby, J.; McCaig, H.; Murukesan, G.; Rader, E.; Rennie, V.; Schwieterman, E.; Sutton, S.; Tan, G.; Yin, C.; Cullen, D.; Geppert, W.; Stockton, A.

2018-04-01

We detail multi-year field investigations in Icelandic Mars analogue environments that have yielded results that can help inform strategies for sample selection and downselection for Mars Sample Return.

Improved detection of multiple environmental antibiotics through an optimized sample extraction strategy in liquid chromatography-mass spectrometry analysis.

PubMed

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.

Optimization of LC-Orbitrap-HRMS acquisition and MZmine 2 data processing for nontarget screening of environmental samples using design of experiments.

PubMed

Hu, Meng; Krauss, Martin; Brack, Werner; Schulze, Tobias

2016-11-01

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is a well-established technique for nontarget screening of contaminants in complex environmental samples. Automatic peak detection is essential, but its performance has only rarely been assessed and optimized so far. With the aim to fill this gap, we used pristine water extracts spiked with 78 contaminants as a test case to evaluate and optimize chromatogram and spectral data processing. To assess whether data acquisition strategies have a significant impact on peak detection, three values of MS cycle time (CT) of an LTQ Orbitrap instrument were tested. Furthermore, the key parameter settings of the data processing software MZmine 2 were optimized to detect the maximum number of target peaks from the samples by the design of experiments (DoE) approach and compared to a manual evaluation. The results indicate that short CT significantly improves the quality of automatic peak detection, which means that full scan acquisition without additional MS 2 experiments is suggested for nontarget screening. MZmine 2 detected 75-100 % of the peaks compared to manual peak detection at an intensity level of 10 5 in a validation dataset on both spiked and real water samples under optimal parameter settings. Finally, we provide an optimization workflow of MZmine 2 for LC-HRMS data processing that is applicable for environmental samples for nontarget screening. The results also show that the DoE approach is useful and effort-saving for optimizing data processing parameters. Graphical Abstract ᅟ.

Local activation time sampling density for atrial tachycardia contact mapping: how much is enough?

PubMed

Williams, Steven E; Harrison, James L; Chubb, Henry; Whitaker, John; Kiedrowicz, Radek; Rinaldi, Christopher A; Cooklin, Michael; Wright, Matthew; Niederer, Steven; O'Neill, Mark D

2018-02-01

Local activation time (LAT) mapping forms the cornerstone of atrial tachycardia diagnosis. Although anatomic and positional accuracy of electroanatomic mapping (EAM) systems have been validated, the effect of electrode sampling density on LAT map reconstruction is not known. Here, we study the effect of chamber geometry and activation complexity on optimal LAT sampling density using a combined in silico and in vivo approach. In vivo 21 atrial tachycardia maps were studied in three groups: (1) focal activation, (2) macro-re-entry, and (3) localized re-entry. In silico activation was simulated on a 4×4cm atrial monolayer, sampled randomly at 0.25-10 points/cm2 and used to re-interpolate LAT maps. Activation patterns were studied in the geometrically simple porcine right atrium (RA) and complex human left atrium (LA). Activation complexity was introduced into the porcine RA by incomplete inter-caval linear ablation. In all cases, optimal sampling density was defined as the highest density resulting in minimal further error reduction in the re-interpolated maps. Optimal sampling densities for LA tachycardias were 0.67 ± 0.17 points/cm2 (focal activation), 1.05 ± 0.32 points/cm2 (macro-re-entry) and 1.23 ± 0.26 points/cm2 (localized re-entry), P = 0.0031. Increasing activation complexity was associated with increased optimal sampling density both in silico (focal activation 1.09 ± 0.14 points/cm2; re-entry 1.44 ± 0.49 points/cm2; spiral-wave 1.50 ± 0.34 points/cm2, P < 0.0001) and in vivo (porcine RA pre-ablation 0.45 ± 0.13 vs. post-ablation 0.78 ± 0.17 points/cm2, P = 0.0008). Increasing chamber geometry was also associated with increased optimal sampling density (0.61 ± 0.22 points/cm2 vs. 1.0 ± 0.34 points/cm2, P = 0.0015). Optimal sampling densities can be identified to maximize diagnostic yield of LAT maps. Greater sampling density is required to correctly reveal complex activation and

Optimal molecular profiling of tissue and tissue components: defining the best processing and microdissection methods for biomedical applications.

PubMed

Bova, G Steven; Eltoum, Isam A; Kiernan, John A; Siegal, Gene P; Frost, Andra R; Best, Carolyn J M; Gillespie, John W; Emmert-Buck, Michael R

2005-01-01

Isolation of well-preserved pure cell populations is a prerequisite for sound studies of the molecular basis of pancreatic malignancy and other biological phenomena. This chapter reviews current methods for obtaining anatomically specific signals from molecules isolated from tissues, a basic requirement for productive linking of phenotype and genotype. The quality of samples isolated from tissue and used for molecular analysis is often glossed-over or omitted from publications, making interpretation and replication of data difficult or impossible. Fortunately, recently developed techniques allow life scientists to better document and control the quality of samples used for a given assay, creating a foundation for improvement in this area. Tissue processing for molecular studies usually involves some or all of the following steps: tissue collection, gross dissection/identification, fixation, processing/embedding, storage/archiving, sectioning, staining, microdissection/annotation, and pure analyte labeling/identification. High-quality tissue microdissection does not necessarily mean high-quality samples to analyze. The quality of biomaterials obtained for analysis is highly dependent on steps upstream and downstream from tissue microdissection. We provide protocols for each of these steps, and encourage you to improve upon these. It is worth the effort of every laboratory to optimize and document its technique at each stage of the process, and we provide a starting point for those willing to spend the time to optimize. In our view, poor documentation of tissue and cell type of origin and the use of nonoptimized protocols is a source of inefficiency in current life science research. Even incremental improvement in this area will increase productivity significantly.

Optimization of a sample processing protocol for recovery of Bacillus anthracis spores from soil

USGS Publications Warehouse

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.

Defining ADHD symptom persistence in adulthood: optimizing sensitivity and specificity.

PubMed

Sibley, Margaret H; Swanson, James M; Arnold, L Eugene; Hechtman, Lily T; Owens, Elizabeth B; Stehli, Annamarie; Abikoff, Howard; Hinshaw, Stephen P; Molina, Brooke S G; Mitchell, John T; Jensen, Peter S; Howard, Andrea L; Lakes, Kimberley D; Pelham, William E

2017-06-01

Longitudinal studies of children diagnosed with ADHD report widely ranging ADHD persistence rates in adulthood (5-75%). This study documents how information source (parent vs. self-report), method (rating scale vs. interview), and symptom threshold (DSM vs. norm-based) influence reported ADHD persistence rates in adulthood. Five hundred seventy-nine children were diagnosed with DSM-IV ADHD-Combined Type at baseline (ages 7.0-9.9 years) 289 classmates served as a local normative comparison group (LNCG), 476 and 241 of whom respectively were evaluated in adulthood (Mean Age = 24.7). Parent and self-reports of symptoms and impairment on rating scales and structured interviews were used to investigate ADHD persistence in adulthood. Persistence rates were higher when using parent rather than self-reports, structured interviews rather than rating scales (for self-report but not parent report), and a norm-based (NB) threshold of 4 symptoms rather than DSM criteria. Receiver-Operating Characteristics (ROC) analyses revealed that sensitivity and specificity were optimized by combining parent and self-reports on a rating scale and applying a NB threshold. The interview format optimizes young adult self-reporting when parent reports are not available. However, the combination of parent and self-reports from rating scales, using an 'or' rule and a NB threshold optimized the balance between sensitivity and specificity. With this definition, 60% of the ADHD group demonstrated symptom persistence and 41% met both symptom and impairment criteria in adulthood. © 2016 Association for Child and Adolescent Mental Health.

Association of body mass index (BMI) and percent body fat among BMI-defined non-obese middle-aged individuals: Insights from a population-based Canadian sample.

PubMed

Collins, Kelsey H; Sharif, Behnam; Sanmartin, Claudia; Reimer, Raylene A; Herzog, Walter; Chin, Rick; Marshall, Deborah A

2017-03-01

To evaluate the association between percent body fat (%BF) and body mass index (BMI) among BMI-defined non-obese individuals between 40 and 69 years of age using a population-based Canadian sample. Cross-sectional data from the Canadian Health Measures Survey (2007 and 2009) was used to select all middle-aged individuals with BMI < 30 kg/m2 (n = 2,656). %BF was determined from anthropometric skinfolds and categorized according to sex-specific equations. Association of other anthropometry measures and metabolic markers were evaluated across different %BF categories. Significance of proportions was evaluated using chi-squared and Bonferroni-adjusted Wald test. Diagnostic performance measures of BMI-defined overweight categories compared to those defined by %BF were reported. The majority (69%) of the sample was %BF-defined overweight/obese, while 55% were BMI-defined overweight. BMI category was not concordant with %BF classification for 30% of the population. The greatest discordance between %BF and BMI was observed among %BF-defined overweight/obese women (32%). Sensitivity and specificity of BMI-defined overweight compared to %BF-defined overweight/obese were (58%, 94%) among females and (82%, 59%) among males respectively. According to the estimated negative predictive value, if an individual is categorized as BMI-defined non-obese, he/she has a 52% chance of being in the %BF-defined overweight/obese category. Middle-aged individuals classified as normal by BMI may be overweight/obese based on measures of %BF. These individuals may be at risk for chronic diseases, but would not be identified as such based on their BMI classification. Quantifying %BF in this group could inform targeted strategies for disease prevention.

Surface-engineered substrates for improved human pluripotent stem cell culture under fully defined conditions.

PubMed

Saha, Krishanu; Mei, Ying; Reisterer, Colin M; Pyzocha, Neena Kenton; Yang, Jing; Muffat, Julien; Davies, Martyn C; Alexander, Morgan R; Langer, Robert; Anderson, Daniel G; Jaenisch, Rudolf

2011-11-15

The current gold standard for the culture of human pluripotent stem cells requires the use of a feeder layer of cells. Here, we develop a spatially defined culture system based on UV/ozone radiation modification of typical cell culture plastics to define a favorable surface environment for human pluripotent stem cell culture. Chemical and geometrical optimization of the surfaces enables control of early cell aggregation from fully dissociated cells, as predicted from a numerical model of cell migration, and results in significant increases in cell growth of undifferentiated cells. These chemically defined xeno-free substrates generate more than three times the number of cells than feeder-containing substrates per surface area. Further, reprogramming and typical gene-targeting protocols can be readily performed on these engineered surfaces. These substrates provide an attractive cell culture platform for the production of clinically relevant factor-free reprogrammed cells from patient tissue samples and facilitate the definition of standardized scale-up friendly methods for disease modeling and cell therapeutic applications.

Optimized measurement of radium-226 concentration in liquid samples with radon-222 emanation.

PubMed

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy

PubMed Central

Barish, Syndi; Ochs, Michael F.; Sontag, Eduardo D.; Gevertz, Jana L.

2017-01-01

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, mathematical modeling, and statistical analyses for identifying robust optimal treatment protocols. VEPART begins with time course experimental data for a sample population, and a mathematical model fit to aggregate data from that sample population. Using nonparametric statistics, the sample population is amplified and used to create a large number of virtual populations. At the final step of VEPART, robustness is assessed by identifying and analyzing the optimal therapy (perhaps restricted to a set of clinically realizable protocols) across each virtual population. As proof of concept, we have applied the VEPART method to study the robustness of treatment response in a mouse model of melanoma subject to treatment with immunostimulatory oncolytic viruses and dendritic cell vaccines. Our analysis (i) showed that every scheduling variant of the experimentally used treatment protocol is fragile (nonrobust) and (ii) discovered an alternative region of dosing space (lower oncolytic virus dose, higher dendritic cell dose) for which a robust optimal protocol exists. PMID:28716945

Spatio-temporal optimization of sampling for bluetongue vectors (Culicoides) near grazing livestock

PubMed Central

2013-01-01

Background Estimating the abundance of Culicoides using light traps is influenced by a large variation in abundance in time and place. This study investigates the optimal trapping strategy to estimate the abundance or presence/absence of Culicoides on a field with grazing animals. We used 45 light traps to sample specimens from the Culicoides obsoletus species complex on a 14 hectare field during 16 nights in 2009. Findings The large number of traps and catch nights enabled us to simulate a series of samples consisting of different numbers of traps (1-15) on each night. We also varied the number of catch nights when simulating the sampling, and sampled with increasing minimum distances between traps. We used resampling to generate a distribution of different mean and median abundance in each sample. Finally, we used the hypergeometric distribution to estimate the probability of falsely detecting absence of vectors on the field. The variation in the estimated abundance decreased steeply when using up to six traps, and was less pronounced when using more traps, although no clear cutoff was found. Conclusions Despite spatial clustering in vector abundance, we found no effect of increasing the distance between traps. We found that 18 traps were generally required to reach 90% probability of a true positive catch when sampling just one night. But when sampling over two nights the same probability level was obtained with just three traps per night. The results are useful for the design of vector monitoring programmes on fields with grazing animals. PMID:23705770

An artifact caused by undersampling optimal trees in supermatrix analyses of locally sampled characters.

PubMed

Simmons, Mark P; Goloboff, Pablo A

2013-10-01

Empirical and simulated examples are used to demonstrate an artifact caused by undersampling optimal trees in data matrices that consist mostly or entirely of locally sampled (as opposed to globally, for most or all terminals) characters. The artifact is that unsupported clades consisting entirely of terminals scored for the same locally sampled partition may be resolved and assigned high resampling support-despite their being properly unsupported (i.e., not resolved in the strict consensus of all optimal trees). This artifact occurs despite application of random-addition sequences for stepwise terminal addition. The artifact is not necessarily obviated with thorough conventional branch swapping methods (even tree-bisection-reconnection) when just a single tree is held, as is sometimes implemented in parsimony bootstrap pseudoreplicates, and in every GARLI, PhyML, and RAxML pseudoreplicate and search for the most likely tree for the matrix as a whole. Hence GARLI, RAxML, and PhyML-based likelihood results require extra scrutiny, particularly when they provide high resolution and support for clades that are entirely unsupported by methods that perform more thorough searches, as in most parsimony analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

Dynamic routing and spectrum assignment based on multilayer virtual topology and ant colony optimization in elastic software-defined optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Zhang, Qi; Tian, Qinghua; Tian, Feng; Rao, Lan; Xin, Xiangjun

2017-07-01

Elastic software-defined optical networks greatly improve the flexibility of the optical switching network while it has brought challenges to the routing and spectrum assignment (RSA). A multilayer virtual topology model is proposed to solve RSA problems. Two RSA algorithms based on the virtual topology are proposed, which are the ant colony optimization (ACO) algorithm of minimum consecutiveness loss and the ACO algorithm of maximum spectrum consecutiveness. Due to the computing power of the control layer in the software-defined network, the routing algorithm avoids the frequent link-state information between routers. Based on the effect of the spectrum consecutiveness loss on the pheromone in the ACO, the path and spectrum of the minimal impact on the network are selected for the service request. The proposed algorithms have been compared with other algorithms. The results show that the proposed algorithms can reduce the blocking rate by at least 5% and perform better in spectrum efficiency. Moreover, the proposed algorithms can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness.

Optimized, Budget-constrained Monitoring Well Placement Using DREAM

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

Yonkofski, Catherine M. R.; Davidson, Casie L.; Rodriguez, Luke R.

Defining the ideal suite of monitoring technologies to be deployed at a carbon capture and storage (CCS) site presents a challenge to project developers, financers, insurers, regulators and other stakeholders. The monitoring, verification, and accounting (MVA) toolkit offers a suite of technologies to monitor an extensive range of parameters across a wide span of spatial and temporal resolutions, each with their own degree of sensitivity to changes in the parameter being monitored. Understanding how best to optimize MVA budgets to minimize the time to leak detection could help to address issues around project risks, and in turn help support broadmore » CCS deployment. This paper presents a case study demonstrating an application of the Designs for Risk Evaluation and Management (DREAM) tool using an ensemble of CO 2 leakage scenarios taken from a previous study on leakage impacts to groundwater. Impacts were assessed and monitored as a function of pH, total dissolved solids (TDS), and trace metal concentrations of arsenic (As), cadmium (Cd), chromium (Cr), and lead (Pb). Using output from the previous study, DREAM was used to optimize monitoring system designs based on variable sampling locations and parameters. The algorithm requires the user to define a finite budget to limit the number of monitoring wells and technologies deployed, and then iterates well placement and sensor type and location until it converges on the configuration with the lowest time to first detection of the leak averaged across all scenarios. To facilitate an understanding of the optimal number of sampling wells, DREAM was used to assess the marginal utility of additional sampling locations. Based on assumptions about monitoring costs and replacement costs of degraded water, the incremental cost of each additional sampling well can be compared against its marginal value in terms of avoided aquifer degradation. Applying this method, DREAM identified the most cost-effective ensemble with 14

Optimized, Budget-constrained Monitoring Well Placement Using DREAM

DOE PAGES

Yonkofski, Catherine M. R.; Davidson, Casie L.; Rodriguez, Luke R.; ...

2017-08-18

Defining the ideal suite of monitoring technologies to be deployed at a carbon capture and storage (CCS) site presents a challenge to project developers, financers, insurers, regulators and other stakeholders. The monitoring, verification, and accounting (MVA) toolkit offers a suite of technologies to monitor an extensive range of parameters across a wide span of spatial and temporal resolutions, each with their own degree of sensitivity to changes in the parameter being monitored. Understanding how best to optimize MVA budgets to minimize the time to leak detection could help to address issues around project risks, and in turn help support broadmore » CCS deployment. This paper presents a case study demonstrating an application of the Designs for Risk Evaluation and Management (DREAM) tool using an ensemble of CO 2 leakage scenarios taken from a previous study on leakage impacts to groundwater. Impacts were assessed and monitored as a function of pH, total dissolved solids (TDS), and trace metal concentrations of arsenic (As), cadmium (Cd), chromium (Cr), and lead (Pb). Using output from the previous study, DREAM was used to optimize monitoring system designs based on variable sampling locations and parameters. The algorithm requires the user to define a finite budget to limit the number of monitoring wells and technologies deployed, and then iterates well placement and sensor type and location until it converges on the configuration with the lowest time to first detection of the leak averaged across all scenarios. To facilitate an understanding of the optimal number of sampling wells, DREAM was used to assess the marginal utility of additional sampling locations. Based on assumptions about monitoring costs and replacement costs of degraded water, the incremental cost of each additional sampling well can be compared against its marginal value in terms of avoided aquifer degradation. Applying this method, DREAM identified the most cost-effective ensemble with 14

info-gibbs: a motif discovery algorithm that directly optimizes information content during sampling.

PubMed

Defrance, Matthieu; van Helden, Jacques

2009-10-15

Discovering cis-regulatory elements in genome sequence remains a challenging issue. Several methods rely on the optimization of some target scoring function. The information content (IC) or relative entropy of the motif has proven to be a good estimator of transcription factor DNA binding affinity. However, these information-based metrics are usually used as a posteriori statistics rather than during the motif search process itself. We introduce here info-gibbs, a Gibbs sampling algorithm that efficiently optimizes the IC or the log-likelihood ratio (LLR) of the motif while keeping computation time low. The method compares well with existing methods like MEME, BioProspector, Gibbs or GAME on both synthetic and biological datasets. Our study shows that motif discovery techniques can be enhanced by directly focusing the search on the motif IC or the motif LLR. http://rsat.ulb.ac.be/rsat/info-gibbs

A soil sampling reference site: the challenge in defining reference material for sampling.

PubMed

de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Jacimovic, Radojko; Jeran, Zvonka; Sansone, Umberto; van der Perk, Marcel

2008-11-01

In the frame of the international SOILSAMP project, funded and coordinated by the Italian Environmental Protection Agency, an agricultural area was established as a reference site suitable for performing soil sampling inter-comparison exercises. The reference site was characterized for trace element content in soil, in terms of the spatial and temporal variability of their mass fraction. Considering that the behaviour of long-lived radionuclides in soil can be expected to be similar to that of some stable trace elements and that the distribution of these trace elements in soil can simulate the distribution of radionuclides, the reference site characterised in term of trace elements, can be also used to compare the soil sampling strategies developed for radionuclide investigations.

Optimization of Sample Preparation for the Identification and Quantification of Saxitoxin in Proficiency Test Mussel Sample using Liquid Chromatography-Tandem Mass Spectrometry

PubMed Central

Harju, Kirsi; Rapinoja, Marja-Leena; Avondet, Marc-André; Arnold, Werner; Schär, Martin; Burrell, Stephen; Luginbühl, Werner; Vanninen, Paula

2015-01-01

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). PMID:26610567

Optimization of groundwater sampling approach under various hydrogeological conditions using a numerical simulation model

NASA Astrophysics Data System (ADS)

Qi, Shengqi; Hou, Deyi; Luo, Jian

2017-09-01

This study presents a numerical model based on field data to simulate groundwater flow in both the aquifer and the well-bore for the low-flow sampling method and the well-volume sampling method. The numerical model was calibrated to match well with field drawdown, and calculated flow regime in the well was used to predict the variation of dissolved oxygen (DO) concentration during the purging period. The model was then used to analyze sampling representativeness and sampling time. Site characteristics, such as aquifer hydraulic conductivity, and sampling choices, such as purging rate and screen length, were found to be significant determinants of sampling representativeness and required sampling time. Results demonstrated that: (1) DO was the most useful water quality indicator in ensuring groundwater sampling representativeness in comparison with turbidity, pH, specific conductance, oxidation reduction potential (ORP) and temperature; (2) it is not necessary to maintain a drawdown of less than 0.1 m when conducting low flow purging. However, a high purging rate in a low permeability aquifer may result in a dramatic decrease in sampling representativeness after an initial peak; (3) the presence of a short screen length may result in greater drawdown and a longer sampling time for low-flow purging. Overall, the present study suggests that this new numerical model is suitable for describing groundwater flow during the sampling process, and can be used to optimize sampling strategies under various hydrogeological conditions.

An optimal sampling approach to modelling whole-body vibration exposure in all-terrain vehicle driving.

PubMed

Lü, Xiaoshu; Takala, Esa-Pekka; Toppila, Esko; Marjanen, Ykä; Kaila-Kangas, Leena; Lu, Tao

2017-08-01

Exposure to whole-body vibration (WBV) presents an occupational health risk and several safety standards obligate to measure WBV. The high cost of direct measurements in large epidemiological studies raises the question of the optimal sampling for estimating WBV exposures given by a large variation in exposure levels in real worksites. This paper presents a new approach to addressing this problem. A daily exposure to WBV was recorded for 9-24 days among 48 all-terrain vehicle drivers. Four data-sets based on root mean squared recordings were obtained from the measurement. The data were modelled using semi-variogram with spectrum analysis and the optimal sampling scheme was derived. The optimum sampling period was 140 min apart. The result was verified and validated in terms of its accuracy and statistical power. Recordings of two to three hours are probably needed to get a sufficiently unbiased daily WBV exposure estimate in real worksites. The developed model is general enough that is applicable to other cumulative exposures or biosignals. Practitioner Summary: Exposure to whole-body vibration (WBV) presents an occupational health risk and safety standards obligate to measure WBV. However, direct measurements can be expensive. This paper presents a new approach to addressing this problem. The developed model is general enough that is applicable to other cumulative exposures or biosignals.

Simultaneous optimization of limited sampling points for pharmacokinetic analysis of amrubicin and amrubicinol in cancer patients.

PubMed

Makino, Yoshinori; Watanabe, Michiko; Makihara, Reiko Ando; Nokihara, Hiroshi; Yamamoto, Noboru; Ohe, Yuichiro; Sugiyama, Erika; Sato, Hitoshi; Hayashi, Yoshikazu

2016-09-01

Limited sampling points for both amrubicin (AMR) and its active metabolite amrubicinol (AMR-OH) were simultaneously optimized using Akaike's information criterion (AIC) calculated by pharmacokinetic modeling. In this pharmacokinetic study, 40 mg/m(2) of AMR was administered as a 5-min infusion on three consecutive days to 21 Japanese lung cancer patients. Blood samples were taken at 0, 0.08, 0.25, 0.5, 1, 2, 4, 8 and 24 h after drug infusion, and AMR and AMR-OH concentrations in plasma were quantitated using a high-performance liquid chromatography. The pharmacokinetic profile of AMR was characterized using a three-compartment model and that of AMR-OH using a one-compartment model following a first-order absorption process. These pharmacokinetic profiles were then integrated into one pharmacokinetic model for simultaneous fitting of AMR and AMR-OH. After fitting to the pharmacokinetic model, 65 combinations of four sampling points from the concentration profiles were evaluated for their AICs. Stepwise regression analysis was applied to select the sampling points for AMR and AMR-OH to predict the area under the concentration-time curves (AUCs) at best. Of the three combinations that yielded favorable AIC values, 0.25, 2, 4 and 8 h yielded the best AUC prediction for both AMR (R(2) = 0.977) and AMR-OH (R(2) = 0.886). The prediction error for AUC was less than 15%. The optimal limited sampling points of AMR and AMR-OH after AMR infusion were found to be 0.25, 2, 4 and 8 h, enabling less frequent blood sampling in further expanded pharmacokinetic studies for both AMR and AMR-OH. © 2016 John Wiley & Sons Australia, Ltd.

Design Optimization of a Centrifugal Fan with Splitter Blades

NASA Astrophysics Data System (ADS)

Heo, Man-Woong; Kim, Jin-Hyuk; Kim, Kwang-Yong

2015-05-01

Multi-objective optimization of a centrifugal fan with additionally installed splitter blades was performed to simultaneously maximize the efficiency and pressure rise using three-dimensional Reynolds-averaged Navier-Stokes equations and hybrid multi-objective evolutionary algorithm. Two design variables defining the location of splitter, and the height ratio between inlet and outlet of impeller were selected for the optimization. In addition, the aerodynamic characteristics of the centrifugal fan were investigated with the variation of design variables in the design space. Latin hypercube sampling was used to select the training points, and response surface approximation models were constructed as surrogate models of the objective functions. With the optimization, both the efficiency and pressure rise of the centrifugal fan with splitter blades were improved considerably compared to the reference model.

Optimal molecular profiling of tissue and tissue components: defining the best processing and microdissection methods for biomedical applications.

PubMed

Bova, G Steven; Eltoum, Isam A; Kiernan, John A; Siegal, Gene P; Frost, Andra R; Best, Carolyn J M; Gillespie, John W; Su, Gloria H; Emmert-Buck, Michael R

2005-02-01

Isolation of well-preserved pure cell populations is a prerequisite for sound studies of the molecular basis of any tissue-based biological phenomenon. This article reviews current methods for obtaining anatomically specific signals from molecules isolated from tissues, a basic requirement for productive linking of phenotype and genotype. The quality of samples isolated from tissue and used for molecular analysis is often glossed over or omitted from publications, making interpretation and replication of data difficult or impossible. Fortunately, recently developed techniques allow life scientists to better document and control the quality of samples used for a given assay, creating a foundation for improvement in this area. Tissue processing for molecular studies usually involves some or all of the following steps: tissue collection, gross dissection/identification, fixation, processing/embedding, storage/archiving, sectioning, staining, microdissection/annotation, and pure analyte labeling/identification and quantification. We provide a detailed comparison of some current tissue microdissection technologies, and provide detailed example protocols for tissue component handling upstream and downstream from microdissection. We also discuss some of the physical and chemical issues related to optimal tissue processing, and include methods specific to cytology specimens. We encourage each laboratory to use these as a starting point for optimization of their overall process of moving from collected tissue to high quality, appropriately anatomically tagged scientific results. In optimized protocols is a source of inefficiency in current life science research. Improvement in this area will significantly increase life science quality and productivity. The article is divided into introduction, materials, protocols, and notes sections. Because many protocols are covered in each of these sections, information relating to a single protocol is not contiguous. To get the

A predictive control framework for optimal energy extraction of wind farms

NASA Astrophysics Data System (ADS)

Vali, M.; van Wingerden, J. W.; Boersma, S.; Petrović, V.; Kühn, M.

2016-09-01

This paper proposes an adjoint-based model predictive control for optimal energy extraction of wind farms. It employs the axial induction factor of wind turbines to influence their aerodynamic interactions through the wake. The performance index is defined here as the total power production of the wind farm over a finite prediction horizon. A medium-fidelity wind farm model is utilized to predict the inflow propagation in advance. The adjoint method is employed to solve the formulated optimization problem in a cost effective way and the first part of the optimal solution is implemented over the control horizon. This procedure is repeated at the next controller sample time providing the feedback into the optimization. The effectiveness and some key features of the proposed approach are studied for a two turbine test case through simulations.

Foam generation and sample composition optimization for the FOAM-C experiment of the ISS

NASA Astrophysics Data System (ADS)

Carpy, R.; Picker, G.; Amann, B.; Ranebo, H.; Vincent-Bonnieu, S.; Minster, O.; Winter, J.; Dettmann, J.; Castiglione, L.; Höhler, R.; Langevin, D.

2011-12-01

End of 2009 and early 2010 a sealed cell, for foam generation and observation, has been designed and manufactured at Astrium Friedrichshafen facilities. With the use of this cell, different sample compositions of "wet foams" have been optimized for mixtures of chemicals such as water, dodecanol, pluronic, aethoxisclerol, glycerol, CTAB, SDS, as well as glass beads. This development is performed in the frame of the breadboarding development activities of the Experiment Container FOAM-C for operation in the ISS Fluid Science Laboratory (ISS). The sample cell supports multiple observation methods such as: Diffusing-Wave and Diffuse Transmission Spectrometry, Time Resolved Correlation Spectroscopy [1] and microscope observation, all of these methods are applied in the cell with a relatively small experiment volume <3cm3. These units, will be on orbit replaceable sets, that will allow multiple sample compositions processing (in the range of >40).

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.

Development of fire shutters based on numerical optimizations

NASA Astrophysics Data System (ADS)

Novak, Ondrej; Kulhavy, Petr; Martinec, Tomas; Petru, Michal; Srb, Pavel

2018-06-01

This article deals with a prototype concept, real experiment and numerical simulation of a layered industrial fire shutter, based on some new insulating composite materials. The real fire shutter has been developed and optimized in laboratory and subsequently tested in the certified test room. A simulation of whole concept has been carried out as the non-premixed combustion process in the commercial final volume sw Pyrosim. Model of the combustion based on a stoichiometric defined mixture of gas and the tested layered samples showed good conformity with experimental results - i.e. thermal distribution inside and heat release rate that has gone through the sample.

The optimally sampled galaxy-wide stellar initial mass function. Observational tests and the publicly available GalIMF code

NASA Astrophysics Data System (ADS)

Yan, Zhiqiang; Jerabkova, Tereza; Kroupa, Pavel

2017-11-01

Here we present a full description of the integrated galaxy-wide initial mass function (IGIMF) theory in terms of the optimal sampling and compare it with available observations. Optimal sampling is the method we use to discretize the IMF deterministically into stellar masses. Evidence indicates that nature may be closer to deterministic sampling as observations suggest a smaller scatter of various relevant observables than random sampling would give, which may result from a high level of self-regulation during the star formation process. We document the variation of IGIMFs under various assumptions. The results of the IGIMF theory are consistent with the empirical relation between the total mass of a star cluster and the mass of its most massive star, and the empirical relation between the star formation rate (SFR) of a galaxy and the mass of its most massive cluster. Particularly, we note a natural agreement with the empirical relation between the IMF power-law index and the SFR of a galaxy. The IGIMF also results in a relation between the SFR of a galaxy and the mass of its most massive star such that, if there were no binaries, galaxies with SFR < 10-4M⊙/yr should host no Type II supernova events. In addition, a specific list of initial stellar masses can be useful in numerical simulations of stellar systems. For the first time, we show optimally sampled galaxy-wide IMFs (OSGIMF) that mimic the IGIMF with an additional serrated feature. Finally, a Python module, GalIMF, is provided allowing the calculation of the IGIMF and OSGIMF dependent on the galaxy-wide SFR and metallicity. A copy of the python code model is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/607/A126

Sampling Long- versus Short-Range Interactions Defines the Ability of Force Fields To Reproduce the Dynamics of Intrinsically Disordered Proteins.

PubMed

Mercadante, Davide; Wagner, Johannes A; Aramburu, Iker V; Lemke, Edward A; Gräter, Frauke

2017-09-12

Molecular dynamics (MD) simulations have valuably complemented experiments describing the dynamics of intrinsically disordered proteins (IDPs), particularly since the proposal of models to solve the artificial collapse of IDPs in silico. Such models suggest redefining nonbonded interactions, by either increasing water dispersion forces or adopting the Kirkwood-Buff force field. These approaches yield extended conformers that better comply with experiments, but it is unclear if they all sample the same intrachain dynamics of IDPs. We have tested this by employing MD simulations and single-molecule Förster resonance energy transfer spectroscopy to sample the dimensions of systems with different sequence compositions, namely strong and weak polyelectrolytes. For strong polyelectrolytes in which charge effects dominate, all the proposed solutions equally reproduce the expected ensemble's dimensions. For weak polyelectrolytes, at lower cutoffs, force fields abnormally alter intrachain dynamics, overestimating excluded volume over chain flexibility or reporting no difference between the dynamics of different chains. The TIP4PD water model alone can reproduce experimentally observed changes in extensions (dimensions), but not quantitatively and with only weak statistical significance. Force field limitations are reversed with increased interaction cutoffs, showing that chain dynamics are critically defined by the presence of long-range interactions. Force field analysis aside, our study provides the first insights into how long-range interactions critically define IDP dimensions and raises the question of which length range is crucial to correctly sample the overall dimensions and internal dynamics of the large group of weakly charged yet highly polar IDPs.

Optimization of sample preparation variables for wedelolactone from Eclipta alba using Box-Behnken experimental design followed by HPLC identification.

PubMed

Patil, A A; Sachin, B S; Shinde, D B; Wakte, P S

2013-07-01

Coumestan wedelolactone is an important phytocomponent from Eclipta alba (L.) Hassk. It possesses diverse pharmacological activities, which have prompted the development of various extraction techniques and strategies for its better utilization. The aim of the present study is to develop and optimize supercritical carbon dioxide assisted sample preparation and HPLC identification of wedelolactone from E. alba (L.) Hassk. The response surface methodology was employed to study the optimization of sample preparation using supercritical carbon dioxide for wedelolactone from E. alba (L.) Hassk. The optimized sample preparation involves the investigation of quantitative effects of sample preparation parameters viz. operating pressure, temperature, modifier concentration and time on yield of wedelolactone using Box-Behnken design. The wedelolactone content was determined using validated HPLC methodology. The experimental data were fitted to second-order polynomial equation using multiple regression analysis and analyzed using the appropriate statistical method. By solving the regression equation and analyzing 3D plots, the optimum extraction conditions were found to be: extraction pressure, 25 MPa; temperature, 56 °C; modifier concentration, 9.44% and extraction time, 60 min. Optimum extraction conditions demonstrated wedelolactone yield of 15.37 ± 0.63 mg/100 g E. alba (L.) Hassk, which was in good agreement with the predicted values. Temperature and modifier concentration showed significant effect on the wedelolactone yield. The supercritical carbon dioxide extraction showed higher selectivity than the conventional Soxhlet assisted extraction method. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Structural topology optimization with fuzzy constraint

NASA Astrophysics Data System (ADS)

Rosko, Peter

2011-12-01

The paper deals with the structural topology optimization with fuzzy constraint. The optimal topology of structure is defined as a material distribution problem. The objective is the weight of the structure. The multifrequency dynamic loading is considered. The optimal topology design of the structure has to eliminate the danger of the resonance vibration. The uncertainty of the loading is defined with help of fuzzy loading. Special fuzzy constraint is created from exciting frequencies. Presented study is applicable in engineering and civil engineering. Example demonstrates the presented theory.

Rats track odour trails accurately using a multi-layered strategy with near-optimal sampling.

PubMed

Khan, Adil Ghani; Sarangi, Manaswini; Bhalla, Upinder Singh

2012-02-28

Tracking odour trails is a crucial behaviour for many animals, often leading to food, mates or away from danger. It is an excellent example of active sampling, where the animal itself controls how to sense the environment. Here we show that rats can track odour trails accurately with near-optimal sampling. We trained rats to follow odour trails drawn on paper spooled through a treadmill. By recording local field potentials (LFPs) from the olfactory bulb, and sniffing rates, we find that sniffing but not LFPs differ between tracking and non-tracking conditions. Rats can track odours within ~1 cm, and this accuracy is degraded when one nostril is closed. Moreover, they show path prediction on encountering a fork, wide 'casting' sweeps on encountering a gap and detection of reappearance of the trail in 1-2 sniffs. We suggest that rats use a multi-layered strategy, and achieve efficient sampling and high accuracy in this complex task.

Building Extraction Based on an Optimized Stacked Sparse Autoencoder of Structure and Training Samples Using LIDAR DSM and Optical Images.

PubMed

Yan, Yiming; Tan, Zhichao; Su, Nan; Zhao, Chunhui

2017-08-24

In this paper, a building extraction method is proposed based on a stacked sparse autoencoder with an optimized structure and training samples. Building extraction plays an important role in urban construction and planning. However, some negative effects will reduce the accuracy of extraction, such as exceeding resolution, bad correction and terrain influence. Data collected by multiple sensors, as light detection and ranging (LIDAR), optical sensor etc., are used to improve the extraction. Using digital surface model (DSM) obtained from LIDAR data and optical images, traditional method can improve the extraction effect to a certain extent, but there are some defects in feature extraction. Since stacked sparse autoencoder (SSAE) neural network can learn the essential characteristics of the data in depth, SSAE was employed to extract buildings from the combined DSM data and optical image. A better setting strategy of SSAE network structure is given, and an idea of setting the number and proportion of training samples for better training of SSAE was presented. The optical data and DSM were combined as input of the optimized SSAE, and after training by an optimized samples, the appropriate network structure can extract buildings with great accuracy and has good robustness.

Optimal sampling theory and population modelling - Application to determination of the influence of the microgravity environment on drug distribution and elimination

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.

Simulation-assisted design of microfluidic sample traps for optimal trapping and culture of non-adherent single cells, tissues, and spheroids.

PubMed

Rousset, Nassim; Monet, Frédéric; Gervais, Thomas

2017-03-21

This work focuses on modelling design and operation of "microfluidic sample traps" (MSTs). MSTs regroup a widely used class of microdevices that incorporate wells, recesses or chambers adjacent to a channel to individually trap, culture and/or release submicroliter 3D tissue samples ranging from simple cell aggregates and spheroids, to ex vivo tissue samples and other submillimetre-scale tissue models. Numerous MST designs employing various trapping mechanisms have been proposed in the literature, spurring the development of 3D tissue models for drug discovery and personalized medicine. Yet, there lacks a general framework to optimize trapping stability, trapping time, shear stress, and sample metabolism. Herein, the effects of hydrodynamics and diffusion-reaction on tissue viability and device operation are investigated using analytical and finite element methods with systematic parametric sweeps over independent design variables chosen to correspond to the four design degrees of freedom. Combining different results, we show that, for a spherical tissue of diameter d < 500 μm, the simplest, closest to optimal trap shape is a cube of dimensions w equal to twice the tissue diameter: w = 2d. Furthermore, to sustain tissues without perfusion, available medium volume per trap needs to be 100× the tissue volume to ensure optimal metabolism for at least 24 hours.

Persistent Organic Pollutant Determination in Killer Whale Scat Samples: Optimization of a Gas Chromatography/Mass Spectrometry Method and Application to Field Samples.

PubMed

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.

Sleep and optimism: A longitudinal study of bidirectional causal relationship and its mediating and moderating variables in a Chinese student sample.

PubMed

Lau, Esther Yuet Ying; Hui, C Harry; Lam, Jasmine; Cheung, Shu-Fai

2017-01-01

While both sleep and optimism have been found to be predictive of well-being, few studies have examined their relationship with each other. Neither do we know much about the mediators and moderators of the relationship. This study investigated (1) the causal relationship between sleep quality and optimism in a college student sample, (2) the role of symptoms of depression, anxiety, and stress as mediators, and (3) how circadian preference might moderate the relationship. Internet survey data were collected from 1,684 full-time university students (67.6% female, mean age = 20.9 years, SD = 2.66) at three time-points, spanning about 19 months. Measures included the Attributional Style Questionnaire, the Pittsburgh Sleep Quality Index, the Composite Scale of Morningness, and the Depression Anxiety Stress Scale-21. Moderate correlations were found among sleep quality, depressive mood, stress symptoms, anxiety symptoms, and optimism. Cross-lagged analyses showed a bidirectional effect between optimism and sleep quality. Moreover, path analyses demonstrated that anxiety and stress symptoms partially mediated the influence of optimism on sleep quality, while depressive mood partially mediated the influence of sleep quality on optimism. In support of our hypothesis, sleep quality affects mood symptoms and optimism differently for different circadian preferences. Poor sleep results in depressive mood and thus pessimism in non-morning persons only. In contrast, the aggregated (direct and indirect) effects of optimism on sleep quality were invariant of circadian preference. Taken together, people who are pessimistic generally have more anxious mood and stress symptoms, which adversely affect sleep while morningness seems to have a specific protective effect countering the potential damage poor sleep has on optimism. In conclusion, optimism and sleep quality were both cause and effect of each other. Depressive mood partially explained the effect of sleep quality on optimism

Ecological and sampling constraints on defining landscape fire severity

USGS Publications Warehouse

Key, C.H.

2006-01-01

Ecological definition and detection of fire severity are influenced by factors of spatial resolution and timing. Resolution determines the aggregation of effects within a sampling unit or pixel (alpha variation), hence limiting the discernible ecological responses, and controlling the spatial patchiness of responses distributed throughout a burn (beta variation). As resolution decreases, alpha variation increases, extracting beta variation and complexity from the spatial model of the whole burn. Seasonal timing impacts the quality of radiometric data in terms of transmittance, sun angle, and potential contrast between responses within burns. Detection sensitivity candegrade toward the end of many fire seasons when low sun angles, vegetation senescence, incomplete burning, hazy conditions, or snow are common. Thus, a need exists to supersede many rapid response applications when remote sensing conditions improve. Lag timing, or timesince fire, notably shapes the ecological character of severity through first-order effects that only emerge with time after fire, including delayed survivorship and mortality. Survivorship diminishes the detected magnitude of severity, as burned vegetation remains viable and resprouts, though at first it may appear completely charred or consumed above ground. Conversely, delayed mortality increases the severity estimate when apparently healthy vegetation is in fact damaged by heat to the extent that it dies over time. Both responses dependon fire behavior and various species-specific adaptations to fire that are unique to the pre-firecomposition of each burned area. Both responses can lead initially to either over- or underestimating severity. Based on such implications, three sampling intervals for short-term burn severity are identified; rapid, initial, and extended assessment, sampled within about two weeks, two months, and depending on the ecotype, from three months to one year after fire, respectively. Spatial and temporal

Low-noise correlation measurements based on software-defined-radio receivers and cooled microwave amplifiers.

PubMed

Nieminen, Teemu; Lähteenmäki, Pasi; Tan, Zhenbing; Cox, Daniel; Hakonen, Pertti J

2016-11-01

We present a microwave correlation measurement system based on two low-cost USB-connected software defined radio dongles modified to operate as coherent receivers by using a common local oscillator. Existing software is used to obtain I/Q samples from both dongles simultaneously at a software tunable frequency. To achieve low noise, we introduce an easy low-noise solution for cryogenic amplification at 600-900 MHz based on single discrete HEMT with 21 dB gain and 7 K noise temperature. In addition, we discuss the quantization effects in a digital correlation measurement and determination of optimal integration time by applying Allan deviation analysis.

Stabilization for sampled-data neural-network-based control systems.

PubMed

Zhu, Xun-Lin; Wang, Youyi

2011-02-01

This paper studies the problem of stabilization for sampled-data neural-network-based control systems with an optimal guaranteed cost. Unlike previous works, the resulting closed-loop system with variable uncertain sampling cannot simply be regarded as an ordinary continuous-time system with a fast-varying delay in the state. By defining a novel piecewise Lyapunov functional and using a convex combination technique, the characteristic of sampled-data systems is captured. A new delay-dependent stabilization criterion is established in terms of linear matrix inequalities such that the maximal sampling interval and the minimal guaranteed cost control performance can be obtained. It is shown that the newly proposed approach can lead to less conservative and less complex results than the existing ones. Application examples are given to illustrate the effectiveness and the benefits of the proposed method.

Adaptive Sampling-Based Information Collection for Wireless Body Area Networks.

PubMed

Xu, Xiaobin; Zhao, Fang; Wang, Wendong; Tian, Hui

2016-08-31

To collect important health information, WBAN applications typically sense data at a high frequency. However, limited by the quality of wireless link, the uploading of sensed data has an upper frequency. To reduce upload frequency, most of the existing WBAN data collection approaches collect data with a tolerable error. These approaches can guarantee precision of the collected data, but they are not able to ensure that the upload frequency is within the upper frequency. Some traditional sampling based approaches can control upload frequency directly, however, they usually have a high loss of information. Since the core task of WBAN applications is to collect health information, this paper aims to collect optimized information under the limitation of upload frequency. The importance of sensed data is defined according to information theory for the first time. Information-aware adaptive sampling is proposed to collect uniformly distributed data. Then we propose Adaptive Sampling-based Information Collection (ASIC) which consists of two algorithms. An adaptive sampling probability algorithm is proposed to compute sampling probabilities of different sensed values. A multiple uniform sampling algorithm provides uniform samplings for values in different intervals. Experiments based on a real dataset show that the proposed approach has higher performance in terms of data coverage and information quantity. The parameter analysis shows the optimized parameter settings and the discussion shows the underlying reason of high performance in the proposed approach.

Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Birge, Brian

2013-01-01

The design priority for manned space exploration missions is almost always placed on human safety. Proposed manned surface exploration tasks (lunar, asteroid sample returns, Mars) have the possibility of astronauts traveling several kilometers away from a home base. Deviations from preplanned paths are expected while exploring. In a time-critical emergency situation, there is a need to develop an optimal home base return path. The return path may or may not be similar to the outbound path, and what defines optimal may change with, and even within, each mission. A novel path planning algorithm and prototype program was developed using biologically inspired particle swarm optimization (PSO) that generates an optimal path of traversal while avoiding obstacles. Applications include emergency path planning on lunar, Martian, and/or asteroid surfaces, generating multiple scenarios for outbound missions, Earth-based search and rescue, as well as human manual traversal and/or path integration into robotic control systems. The strategy allows for a changing environment, and can be re-tasked at will and run in real-time situations. Given a random extraterrestrial planetary or small body surface position, the goal was to find the fastest (or shortest) path to an arbitrary position such as a safe zone or geographic objective, subject to possibly varying constraints. The problem requires a workable solution 100% of the time, though it does not require the absolute theoretical optimum. Obstacles should be avoided, but if they cannot be, then the algorithm needs to be smart enough to recognize this and deal with it. With some modifications, it works with non-stationary error topologies as well.

Architecture and settings optimization procedure of a TES frequency domain multiplexed readout firmware

NASA Astrophysics Data System (ADS)

Clenet, A.; Ravera, L.; Bertrand, B.; den Hartog, R.; Jackson, B.; van Leeuwen, B.-J.; van Loon, D.; Parot, Y.; Pointecouteau, E.; Sournac, A.

2014-11-01

IRAP is developing the readout electronics of the SPICA-SAFARI's TES bolometer arrays. Based on the frequency domain multiplexing technique the readout electronics provides the AC-signals to voltage-bias the detectors; it demodulates the data; and it computes a feedback to linearize the detection chain. The feedback is computed with a specific technique, so called baseband feedback (BBFB) which ensures that the loop is stable even with long propagation and processing delays (i.e. several μ s) and with fast signals (i.e. frequency carriers of the order of 5 MHz). To optimize the power consumption we took advantage of the reduced science signal bandwidth to decouple the signal sampling frequency and the data processing rate. This technique allowed a reduction of the power consumption of the circuit by a factor of 10. Beyond the firmware architecture the optimization of the instrument concerns the characterization routines and the definition of the optimal parameters. Indeed, to operate an array TES one has to properly define about 21000 parameters. We defined a set of procedures to automatically characterize these parameters and find out the optimal settings.

The ARIEL mission reference sample

NASA Astrophysics Data System (ADS)

Zingales, Tiziano; Tinetti, Giovanna; Pillitteri, Ignazio; Leconte, Jérémy; Micela, Giuseppina; Sarkar, Subhajit

2018-02-01

The ARIEL (Atmospheric Remote-sensing Exoplanet Large-survey) mission concept is one of the three M4 mission candidates selected by the European Space Agency (ESA) for a Phase A study, competing for a launch in 2026. ARIEL has been designed to study the physical and chemical properties of a large and diverse sample of exoplanets and, through those, understand how planets form and evolve in our galaxy. Here we describe the assumptions made to estimate an optimal sample of exoplanets - including already known exoplanets and expected ones yet to be discovered - observable by ARIEL and define a realistic mission scenario. To achieve the mission objectives, the sample should include gaseous and rocky planets with a range of temperatures around stars of different spectral type and metallicity. The current ARIEL design enables the observation of ˜1000 planets, covering a broad range of planetary and stellar parameters, during its four year mission lifetime. This nominal list of planets is expected to evolve over the years depending on the new exoplanet discoveries.

Optimization of microwave digestion for mercury determination in marine biological samples by cold vapour atomic absorption spectrometry.

PubMed

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.

Using Approximations to Accelerate Engineering Design Optimization

NASA Technical Reports Server (NTRS)

Torczon, Virginia; Trosset, Michael W.

1998-01-01

Optimization problems that arise in engineering design are often characterized by several features that hinder the use of standard nonlinear optimization techniques. Foremost among these features is that the functions used to define the engineering optimization problem often are computationally intensive. Within a standard nonlinear optimization algorithm, the computational expense of evaluating the functions that define the problem would necessarily be incurred for each iteration of the optimization algorithm. Faced with such prohibitive computational costs, an attractive alternative is to make use of surrogates within an optimization context since surrogates can be chosen or constructed so that they are typically much less expensive to compute. For the purposes of this paper, we will focus on the use of algebraic approximations as surrogates for the objective. In this paper we introduce the use of so-called merit functions that explicitly recognize the desirability of improving the current approximation to the objective during the course of the optimization. We define and experiment with the use of merit functions chosen to simultaneously improve both the solution to the optimization problem (the objective) and the quality of the approximation. Our goal is to further improve the effectiveness of our general approach without sacrificing any of its rigor.

Optimizing stream water mercury sampling for calculation of fish bioaccumulation factors

USGS Publications Warehouse

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.

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning

PubMed Central

Baykal, Cenk; Torres, Luis G.; Alterovitz, Ron

2015-01-01

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot’s behavior and reachable workspace. Optimizing a robot’s design by appropriately selecting tube parameters can improve the robot’s effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot’s configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy. PMID:26951790

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning.

PubMed

Baykal, Cenk; Torres, Luis G; Alterovitz, Ron

2015-09-28

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot's behavior and reachable workspace. Optimizing a robot's design by appropriately selecting tube parameters can improve the robot's effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot's configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy.

Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

NASA Astrophysics Data System (ADS)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright

Determining the optimal forensic DNA analysis procedure following investigation of sample quality.

PubMed

Hedell, Ronny; Hedman, Johannes; Mostad, Petter

2018-07-01

Crime scene traces of various types are routinely sent to forensic laboratories for analysis, generally with the aim of addressing questions about the source of the trace. The laboratory may choose to analyse the samples in different ways depending on the type and quality of the sample, the importance of the case and the cost and performance of the available analysis methods. Theoretically well-founded guidelines for the choice of analysis method are, however, lacking in most situations. In this paper, it is shown how such guidelines can be created using Bayesian decision theory. The theory is applied to forensic DNA analysis, showing how the information from the initial qPCR analysis can be utilized. It is assumed the alternatives for analysis are using a standard short tandem repeat (STR) DNA analysis assay, using the standard assay and a complementary assay, or the analysis may be cancelled following quantification. The decision is based on information about the DNA amount and level of DNA degradation of the forensic sample, as well as case circumstances and the cost for analysis. Semi-continuous electropherogram models are used for simulation of DNA profiles and for computation of likelihood ratios. It is shown how tables and graphs, prepared beforehand, can be used to quickly find the optimal decision in forensic casework.

Conditional optimal spacing in exponential distribution.

PubMed

Park, Sangun

2006-12-01

In this paper, we propose the conditional optimal spacing defined as the optimal spacing after specifying a predetermined order statistic. If we specify a censoring time, then the optimal inspection times for grouped inspection can be determined from this conditional optimal spacing. We take an example of exponential distribution, and provide a simple method of finding the conditional optimal spacing.

Optimal Auxiliary-Covariate Based Two-Phase Sampling Design for Semiparametric Efficient Estimation of a Mean or Mean Difference, with Application to Clinical Trials

PubMed Central

Gilbert, Peter B.; Yu, Xuesong; Rotnitzky, Andrea

2014-01-01

To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semi-parametric efficient estimator is applied. This approach is made efficient by specifying the phase-two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. Simulations are performed to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. Proofs and R code are provided. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean “importance-weighted” breadth (Y) of the T cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y, and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24% in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y∣W] is important for realizing the efficiency gain, which is aided by an ample phase-two sample and by using a robust fitting method. PMID:24123289

Focusing light through dynamical samples using fast continuous wavefront optimization.

PubMed

Blochet, B; Bourdieu, L; Gigan, S

2017-12-01

We describe a fast continuous optimization wavefront shaping system able to focus light through dynamic scattering media. A micro-electro-mechanical system-based spatial light modulator, a fast photodetector, and field programmable gate array electronics are combined to implement a continuous optimization of a wavefront with a single-mode optimization rate of 4.1 kHz. The system performances are demonstrated by focusing light through colloidal solutions of TiO 2 particles in glycerol with tunable temporal stability.

Two Topics in Data Analysis: Sample-based Optimal Transport and Analysis of Turbulent Spectra from Ship Track Data

NASA Astrophysics Data System (ADS)

Kuang, Simeng Max

This thesis contains two topics in data analysis. The first topic consists of the introduction of algorithms for sample-based optimal transport and barycenter problems. In chapter 1, a family of algorithms is introduced to solve both the L2 optimal transport problem and the Wasserstein barycenter problem. Starting from a theoretical perspective, the new algorithms are motivated from a key characterization of the barycenter measure, which suggests an update that reduces the total transportation cost and stops only when the barycenter is reached. A series of general theorems is given to prove the convergence of all the algorithms. We then extend the algorithms to solve sample-based optimal transport and barycenter problems, in which only finite sample sets are available instead of underlying probability distributions. A unique feature of the new approach is that it compares sample sets in terms of the expected values of a set of feature functions, which at the same time induce the function space of optimal maps and can be chosen by users to incorporate their prior knowledge of the data. All the algorithms are implemented and applied to various synthetic example and practical applications. On synthetic examples it is found that both the SOT algorithm and the SCB algorithm are able to find the true solution and often converge in a handful of iterations. On more challenging applications including Gaussian mixture models, color transfer and shape transform problems, the algorithms give very good results throughout despite the very different nature of the corresponding datasets. In chapter 2, a preconditioning procedure is developed for the L2 and more general optimal transport problems. The procedure is based on a family of affine map pairs, which transforms the original measures into two new measures that are closer to each other, while preserving the optimality of solutions. It is proved that the preconditioning procedure minimizes the remaining transportation cost

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization.

PubMed

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Wong, Wai Peng; Chen, Chun-Hung

2017-04-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort.

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization

PubMed Central

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Chen, Chun-Hung

2017-01-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort. PMID:29170617

Optimizing the implementation of the target motion sampling temperature treatment technique - How fast can it get?

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

Tuomas, V.; Jaakko, L.

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 becomesmore » 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)« less

Age differences in optimism bias are mediated by reliance on intuition and religiosity.

PubMed

Klaczynski, Paul A

2017-11-01

The relationships among age, optimism bias, religiosity, creationist beliefs, and reliance on intuition were examined in a sample of 211 high school students (M age =16.54years). Optimism bias was defined as the difference between predictions for positive and negative live events (e.g., divorce) for the self and age peers. Results indicated that older adolescents displayed less optimism bias, were less religious, believed less in creationism, and relied on intuition less than younger adolescents. Furthermore, the association between age and optimism bias was mediated by religiosity and reliance on intuition but not by creationist beliefs. These findings are considered from a dual-process theoretic perspective that emphasizes age increases in metacognitive abilities and epistemological beliefs and age declines in impulsive judgments. Research directed toward examining alternative explanations of the association among religiosity, age, and optimism bias is recommended. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimal auxiliary-covariate-based two-phase sampling design for semiparametric efficient estimation of a mean or mean difference, with application to clinical trials.

PubMed

Gilbert, Peter B; Yu, Xuesong; Rotnitzky, Andrea

2014-03-15

To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semiparametric efficient estimator is applied. This approach is made efficient by specifying the phase two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. We perform simulations to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. We provide proofs and R code. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean 'importance-weighted' breadth (Y) of the T-cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24 % in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y | W] is important for realizing the efficiency gain, which is aided by an ample phase two sample and by using a robust fitting method. Copyright © 2013 John Wiley & Sons, Ltd.

Optimal molecular profiling of tissue and tissue components: defining the best processing and microdissection methods for biomedical applications.

PubMed

Rodriguez-Canales, Jaime; Hanson, Jeffrey C; Hipp, Jason D; Balis, Ulysses J; Tangrea, Michael A; Emmert-Buck, Michael R; Bova, G Steven

2013-01-01

Isolation of well-preserved pure cell populations is a prerequisite for sound studies of the molecular basis of any tissue-based biological phenomenon. This updated chapter reviews current methods for obtaining anatomically specific signals from molecules isolated from tissues, a basic requirement for productive linking of phenotype and genotype. The quality of samples isolated from tissue and used for molecular analysis is often glossed over or omitted from publications, making interpretation and replication of data difficult or impossible. Fortunately, recently developed techniques allow life scientists to better document and control the quality of samples used for a given assay, creating a foundation for improvement in this area. Tissue processing for molecular studies usually involves some or all of the following steps: tissue collection, gross dissection/identification, fixation, processing/embedding, storage/archiving, sectioning, staining, microdissection/annotation, and pure analyte labeling/identification and quantification. We provide a detailed comparison of some current tissue microdissection technologies and provide detailed example protocols for tissue component handling upstream and downstream from microdissection. We also discuss some of the physical and chemical issues related to optimal tissue processing and include methods specific to cytology specimens. We encourage each laboratory to use these as a starting point for optimization of their overall process of moving from collected tissue to high-quality, appropriately anatomically tagged scientific results. Improvement in this area will significantly increase life science quality and productivity. The chapter is divided into introduction, materials, protocols, and notes subheadings. Because many protocols are covered in each of these sections, information relating to a single protocol is not contiguous. To get the greatest benefit from this chapter, readers are advised to read through the entire

Adaptive Sampling-Based Information Collection for Wireless Body Area Networks

PubMed Central

Xu, Xiaobin; Zhao, Fang; Wang, Wendong; Tian, Hui

2016-01-01

To collect important health information, WBAN applications typically sense data at a high frequency. However, limited by the quality of wireless link, the uploading of sensed data has an upper frequency. To reduce upload frequency, most of the existing WBAN data collection approaches collect data with a tolerable error. These approaches can guarantee precision of the collected data, but they are not able to ensure that the upload frequency is within the upper frequency. Some traditional sampling based approaches can control upload frequency directly, however, they usually have a high loss of information. Since the core task of WBAN applications is to collect health information, this paper aims to collect optimized information under the limitation of upload frequency. The importance of sensed data is defined according to information theory for the first time. Information-aware adaptive sampling is proposed to collect uniformly distributed data. Then we propose Adaptive Sampling-based Information Collection (ASIC) which consists of two algorithms. An adaptive sampling probability algorithm is proposed to compute sampling probabilities of different sensed values. A multiple uniform sampling algorithm provides uniform samplings for values in different intervals. Experiments based on a real dataset show that the proposed approach has higher performance in terms of data coverage and information quantity. The parameter analysis shows the optimized parameter settings and the discussion shows the underlying reason of high performance in the proposed approach. PMID:27589758

Sterile Reverse Osmosis Water Combined with Friction Are Optimal for Channel and Lever Cavity Sample Collection of Flexible Duodenoscopes.

PubMed

Alfa, Michelle J; Singh, Harminder; Nugent, Zoann; Duerksen, Donald; Schultz, Gale; Reidy, Carol; DeGagne, Patricia; Olson, Nancy

2017-01-01

Simulated-use buildup biofilm (BBF) model was used to assess various extraction fluids and friction methods to determine the optimal sample collection method for polytetrafluorethylene channels. In addition, simulated-use testing was performed for the channel and lever cavity of duodenoscopes. BBF was formed in polytetrafluorethylene channels using Enterococcus faecalis, Escherichia coli , and Pseudomonas aeruginosa . Sterile reverse osmosis (RO) water, and phosphate-buffered saline with and without Tween80 as well as two neutralizing broths (Letheen and Dey-Engley) were each assessed with and without friction. Neutralizer was added immediately after sample collection and samples concentrated using centrifugation. Simulated-use testing was done using TJF-Q180V and JF-140F Olympus duodenoscopes. Despite variability in the bacterial CFU in the BBF model, none of the extraction fluids tested were significantly better than RO. Borescope examination showed far less residual material when friction was part of the extraction protocol. The RO for flush-brush-flush (FBF) extraction provided significantly better recovery of E. coli ( p  = 0.02) from duodenoscope lever cavities compared to the CDC flush method. We recommend RO with friction for FBF extraction of the channel and lever cavity of duodenoscopes. Neutralizer and sample concentration optimize recovery of viable bacteria on culture.

Performance index and meta-optimization of a direct search optimization method

NASA Astrophysics Data System (ADS)

Krus, P.; Ölvander, J.

2013-10-01

Design optimization is becoming an increasingly important tool for design, often using simulation as part of the evaluation of the objective function. A measure of the efficiency of an optimization algorithm is of great importance when comparing methods. The main contribution of this article is the introduction of a singular performance criterion, the entropy rate index based on Shannon's information theory, taking both reliability and rate of convergence into account. It can also be used to characterize the difficulty of different optimization problems. Such a performance criterion can also be used for optimization of the optimization algorithms itself. In this article the Complex-RF optimization method is described and its performance evaluated and optimized using the established performance criterion. Finally, in order to be able to predict the resources needed for optimization an objective function temperament factor is defined that indicates the degree of difficulty of the objective function.

An introduction to the COLIN optimization interface.

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

Hart, William Eugene

2003-03-01

We describe COLIN, a Common Optimization Library INterface for C++. COLIN provides C++ template classes that define a generic interface for both optimization problems and optimization solvers. COLIN is specifically designed to facilitate the development of hybrid optimizers, for which one optimizer calls another to solve an optimization subproblem. We illustrate the capabilities of COLIN with an example of a memetic genetic programming solver.

Population pharmacokinetic analysis of clopidogrel in healthy Jordanian subjects with emphasis optimal sampling strategy.

PubMed

Yousef, A M; Melhem, M; Xue, B; Arafat, T; Reynolds, D K; Van Wart, S A

2013-05-01

Clopidogrel is metabolized primarily into an inactive carboxyl metabolite (clopidogrel-IM) or to a lesser extent an active thiol metabolite. A population pharmacokinetic (PK) model was developed using NONMEM(®) to describe the time course of clopidogrel-IM in plasma and to design a sparse-sampling strategy to predict clopidogrel-IM exposures for use in characterizing anti-platelet activity. Serial blood samples from 76 healthy Jordanian subjects administered a single 75 mg oral dose of clopidogrel were collected and assayed for clopidogrel-IM using reverse phase high performance liquid chromatography. A two-compartment (2-CMT) PK model with first-order absorption and elimination plus an absorption lag-time was evaluated, as well as a variation of this model designed to mimic enterohepatic recycling (EHC). Optimal PK sampling strategies (OSS) were determined using WinPOPT based upon collection of 3-12 post-dose samples. A two-compartment model with EHC provided the best fit and reduced bias in C(max) (median prediction error (PE%) of 9.58% versus 12.2%) relative to the basic two-compartment model, AUC(0-24) was similar for both models (median PE% = 1.39%). The OSS for fitting the two-compartment model with EHC required the collection of seven samples (0.25, 1, 2, 4, 5, 6 and 12 h). Reasonably unbiased and precise exposures were obtained when re-fitting this model to a reduced dataset considering only these sampling times. A two-compartment model considering EHC best characterized the time course of clopidogrel-IM in plasma. Use of the suggested OSS will allow for the collection of fewer PK samples when assessing clopidogrel-IM exposures. Copyright © 2013 John Wiley & Sons, Ltd.

OptSSeq: High-throughput sequencing readout of growth enrichment defines optimal gene expression elements for homoethanologenesis

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

Ghosh, Indro Neil; Landick, Robert

The optimization of synthetic pathways is a central challenge in metabolic engineering. OptSSeq (Optimization by Selection and Sequencing) is one approach to this challenge. OptSSeq couples selection of optimal enzyme expression levels linked to cell growth rate with high-throughput sequencing to track enrichment of gene expression elements (promoters and ribosomebinding sites) from a combinatorial library. OptSSeq yields information on both optimal and suboptimal enzyme levels, and helps identify constraints that limit maximal product formation. Here we report a proof-of-concept implementation of OptSSeq using homoethanologenesis, a two-step pathway consisting of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh) that converts pyruvate tomore » ethanol and is naturally optimized in the bacterium Zymomonas mobilis. We used OptSSeq to determine optimal gene expression elements and enzyme levels for Z. mobilis Pdc, AdhA, and AdhB expressed in Escherichia coli. By varying both expression signals and gene order, we identified an optimal solution using only Pdc and AdhB. We resolved current uncertainty about the functions of the Fe 2+-dependent AdhB and Zn 2+- dependent AdhA by showing that AdhB is preferred over AdhA for rapid growth in both E. coli and Z. mobilis. Finally, by comparing predictions of growth-linked metabolic flux to enzyme synthesis costs, we established that optimal E. coli homoethanologenesis was achieved by our best pdc-adhB expression cassette and that the remaining constraints lie in the E. coli metabolic network or inefficient Pdc or AdhB function in E. coli. Furthermore, OptSSeq is a general tool for synthetic biology to tune enzyme levels in any pathway whose optimal function can be linked to cell growth or survival.« less

OptSSeq: High-throughput sequencing readout of growth enrichment defines optimal gene expression elements for homoethanologenesis

DOE PAGES

Ghosh, Indro Neil; Landick, Robert

2016-07-16

The optimization of synthetic pathways is a central challenge in metabolic engineering. OptSSeq (Optimization by Selection and Sequencing) is one approach to this challenge. OptSSeq couples selection of optimal enzyme expression levels linked to cell growth rate with high-throughput sequencing to track enrichment of gene expression elements (promoters and ribosomebinding sites) from a combinatorial library. OptSSeq yields information on both optimal and suboptimal enzyme levels, and helps identify constraints that limit maximal product formation. Here we report a proof-of-concept implementation of OptSSeq using homoethanologenesis, a two-step pathway consisting of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh) that converts pyruvate tomore » ethanol and is naturally optimized in the bacterium Zymomonas mobilis. We used OptSSeq to determine optimal gene expression elements and enzyme levels for Z. mobilis Pdc, AdhA, and AdhB expressed in Escherichia coli. By varying both expression signals and gene order, we identified an optimal solution using only Pdc and AdhB. We resolved current uncertainty about the functions of the Fe 2+-dependent AdhB and Zn 2+- dependent AdhA by showing that AdhB is preferred over AdhA for rapid growth in both E. coli and Z. mobilis. Finally, by comparing predictions of growth-linked metabolic flux to enzyme synthesis costs, we established that optimal E. coli homoethanologenesis was achieved by our best pdc-adhB expression cassette and that the remaining constraints lie in the E. coli metabolic network or inefficient Pdc or AdhB function in E. coli. Furthermore, OptSSeq is a general tool for synthetic biology to tune enzyme levels in any pathway whose optimal function can be linked to cell growth or survival.« less

Low temperature magnetic structure of CeRhIn 5 by neutron diffraction on absorption-optimized samples

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

Fobes, David M.; Bauer, Eric Dietzgen; Thompson, Joe David

Here, two aspects of the ambient pressure magnetic structure of heavy fermion material CeRhIn 5 have remained under some debate since its discovery: whether the structure is indeed an incommensurate helix or a spin density wave, and what is the precise magnitude of the ordered magnetic moment. By using a single crystal sample optimized for hot neutrons to minimize neutron absorption by Rh and In, here we report an ordered moment ofmore » $$m=0.54(2)\\,{{\\mu}_{\\text{B}}}$$. In addition, by using spherical neutron polarimetry measurements on a similar single crystal sample, we have confirmed the helical nature of the magnetic structure, and identified a single chiral domain.« less

Low temperature magnetic structure of CeRhIn 5 by neutron diffraction on absorption-optimized samples

DOE PAGES

Fobes, David M.; Bauer, Eric Dietzgen; Thompson, Joe David; ...

2017-03-28

Here, two aspects of the ambient pressure magnetic structure of heavy fermion material CeRhIn 5 have remained under some debate since its discovery: whether the structure is indeed an incommensurate helix or a spin density wave, and what is the precise magnitude of the ordered magnetic moment. By using a single crystal sample optimized for hot neutrons to minimize neutron absorption by Rh and In, here we report an ordered moment ofmore » $$m=0.54(2)\\,{{\\mu}_{\\text{B}}}$$. In addition, by using spherical neutron polarimetry measurements on a similar single crystal sample, we have confirmed the helical nature of the magnetic structure, and identified a single chiral domain.« less

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

Demonstration and Optimization of BNFL's Pulsed Jet Mixing and RFD Sampling Systems Using NCAW Simulant

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

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 systemsmore » 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%.« less

Optimal experience among teachers: new insights into the work paradox.

PubMed

Bassi, Marta; Delle Fave, Antonella

2012-01-01

Several studies highlighted that individuals perceive work as an opportunity for flow or optimal experience, but not as desirable and pleasant. This finding was defined as the work paradox. The present study addressed this issue among teachers from the perspective of self-determination theory, investigating work-related intrinsic and extrinsic motivation, as well as autonomous and controlled behavior regulation. In Study 1, 14 teachers were longitudinally monitored with Experience Sampling Method for one work week. In Study 2, 184 teachers were administered Flow Questionnaire and Work Preference Inventory, respectively investigating opportunities for optimal experience, and motivational orientations at work. Results showed that work-related optimal experiences were associated with both autonomous regulation and with controlled regulation. Moreover, teachers reported both intrinsic and extrinsic motivation at work, with a prevailing intrinsic orientation. Findings provide novel insights on the work paradox, and suggestions for teachers' well-being promotion.

Defining therapy goals for major molecular remission in chronic myeloid leukemia: results of the randomized CML Study IV.

PubMed

Saussele, Susanne; Hehlmann, Rüdiger; Fabarius, Alice; Jeromin, Sabine; Proetel, Ulrike; Rinaldetti, Sebastien; Kohlbrenner, Katharina; Einsele, Hermann; Falge, Christiane; Kanz, Lothar; Neubauer, Andreas; Kneba, Michael; Stegelmann, Frank; Pfreundschuh, Michael; Waller, Cornelius F; Oppliger Leibundgut, Elisabeth; Heim, Dominik; Krause, Stefan W; Hofmann, Wolf-Karsten; Hasford, Joerg; Pfirrmann, Markus; Müller, Martin C; Hochhaus, Andreas; Lauseker, Michael

2018-05-01

Major molecular remission (MMR) is an important therapy goal in chronic myeloid leukemia (CML). So far, MMR is not a failure criterion according to ELN management recommendation leading to uncertainties when to change therapy in CML patients not reaching MMR after 12 months. At monthly landmarks, for different molecular remission status Hazard ratios (HR) were estimated for patients registered to CML study IV who were divided in a learning and a validation sample. The minimum HR for MMR was found at 2.5 years with 0.28 (compared to patients without remission). In the validation sample, a significant advantage for progression-free survival (PFS) for patients in MMR could be detected (p-value 0.007). The optimal time to predict PFS in patients with MMR could be validated in an independent sample at 2.5 years. With our model we provide a suggestion when to define lack of MMR as therapy failure and thus treatment change should be considered. The optimal response time for 1% BCR-ABL at about 12-15 months was confirmed and for deep molecular remission no specific time point was detected. Nevertheless, it was demonstrated that the earlier the MMR is achieved the higher is the chance to attain deep molecular response later.

[Dispositional optimism, pessimism and realism in technological potential entrepreneurs].

PubMed

López Puga, Jorge; García García, Juan

2011-11-01

Optimism has been classically considered a key trait in entrepreneurs' personality but it has been studied from a psychological point of view only in recent years. The main aim of this research is to study the relationship between dispositional optimism, pessimism and realism as a function of the tendency to create technology-based businesses. A sample of undergraduate students (n= 205) filled in an electronic questionnaire containing the Life Orientation Test-Revised after they were classified as potential technological entrepreneurs, potential general entrepreneurs and non-potential entrepreneurs. Our results show that technology-based entrepreneurs are more optimistic than non-potential entrepreneurs, whereas there were no statistical differences in pessimism and realism. The results are interpreted theoretically to define the potential entrepreneur and, from an applied perspective, to design training programmes to support future technological entrepreneurs.

Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies

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

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

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 onmore » 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.« less

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.

Mapping quantitative trait loci for traits defined as ratios.

PubMed

Yang, Runqing; Li, Jiahan; Xu, Shizhong

2008-03-01

Many traits are defined as ratios of two quantitative traits. Methods of QTL mapping for regular quantitative traits are not optimal when applied to ratios due to lack of normality for traits defined as ratios. We develop a new method of QTL mapping for traits defined as ratios. The new method uses a special linear combination of the two component traits, and thus takes advantage of the normal property of the new variable. Simulation study shows that the new method can substantially increase the statistical power of QTL detection relative to the method which treats ratios as regular quantitative traits. The new method also outperforms the method that uses Box-Cox transformed ratio as the phenotype. A real example of QTL mapping for relative growth rate in soybean demonstrates that the new method can detect more QTL than existing methods of QTL mapping for traits defined as ratios.

Optimal Scaling of Digital Transcriptomes

PubMed Central

Glusman, Gustavo; Caballero, Juan; Robinson, Max; Kutlu, Burak; Hood, Leroy

2013-01-01

Deep sequencing of transcriptomes has become an indispensable tool for biology, enabling expression levels for thousands of genes to be compared across multiple samples. Since transcript counts scale with sequencing depth, counts from different samples must be normalized to a common scale prior to comparison. We analyzed fifteen existing and novel algorithms for normalizing transcript counts, and evaluated the effectiveness of the resulting normalizations. For this purpose we defined two novel and mutually independent metrics: (1) the number of “uniform” genes (genes whose normalized expression levels have a sufficiently low coefficient of variation), and (2) low Spearman correlation between normalized expression profiles of gene pairs. We also define four novel algorithms, one of which explicitly maximizes the number of uniform genes, and compared the performance of all fifteen algorithms. The two most commonly used methods (scaling to a fixed total value, or equalizing the expression of certain ‘housekeeping’ genes) yielded particularly poor results, surpassed even by normalization based on randomly selected gene sets. Conversely, seven of the algorithms approached what appears to be optimal normalization. Three of these algorithms rely on the identification of “ubiquitous” genes: genes expressed in all the samples studied, but never at very high or very low levels. We demonstrate that these include a “core” of genes expressed in many tissues in a mutually consistent pattern, which is suitable for use as an internal normalization guide. The new methods yield robustly normalized expression values, which is a prerequisite for the identification of differentially expressed and tissue-specific genes as potential biomarkers. PMID:24223126

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.

Optimization and determination of Cd (II) in different environmental water samples with dispersive liquid-liquid microextraction preconcentration combined with inductively coupled plasma optical emission spectrometry.

PubMed

Salahinejad, Maryam; Aflaki, Fereydoon

2011-06-01

Dispersive liquid-liquid microextraction followed by inductively coupled plasma-optical emission spectrometry has been investigated for determination of Cd(II) ions in water samples. Ammonium pyrrolidine dithiocarbamate was used as chelating agent. Several factors influencing the microextraction efficiency of Cd (II) ions such as extracting and dispersing solvent type and their volumes, pH, sample volume, and salting effect were optimized. The optimization was performed both via one variable at a time, and central composite design methods and the optimum conditions were selected. Both optimization methods showed nearly the same results: sample size 5 mL; dispersive solvent ethanol; dispersive solvent volume 2 mL; extracting solvent chloroform; extracting solvent volume 200 [Formula: see text]L; pH and salt amount do not affect significantly the microextraction efficiency. The limits of detection and quantification were 0.8 and 2.5 ng L( - 1), respectively. The relative standard deviation for five replicate measurements of 0.50 mg L( - 1) of Cd (II) was 4.4%. The recoveries for the spiked real samples from tap, mineral, river, dam, and sea waters samples ranged from 92.2% to 104.5%.

Flight plan optimization

NASA Astrophysics Data System (ADS)

Dharmaseelan, Anoop; Adistambha, Keyne D.

2015-05-01

Fuel cost accounts for 40 percent of the operating cost of an airline. Fuel cost can be minimized by planning a flight on optimized routes. The routes can be optimized by searching best connections based on the cost function defined by the airline. The most common algorithm that used to optimize route search is Dijkstra's. Dijkstra's algorithm produces a static result and the time taken for the search is relatively long. This paper experiments a new algorithm to optimize route search which combines the principle of simulated annealing and genetic algorithm. The experimental results of route search, presented are shown to be computationally fast and accurate compared with timings from generic algorithm. The new algorithm is optimal for random routing feature that is highly sought by many regional operators.

Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

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

Man, Jun; Zhang, Jiangjiang; Li, Weixuan

2016-10-01

The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees ofmore » freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.« less

[Sampling optimization for tropical invertebrates: an example using dung beetles (Coleoptera: Scarabaeinae) in Venezuela].

PubMed

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

Optimization of alcohol-assisted dispersive liquid-liquid microextraction by experimental design for the rapid determination of fluoxetine in biological samples.

PubMed

Hamedi, Raheleh; Hadjmohammadi, Mohammad Reza

2016-12-01

A sensitive and rapid method based on alcohol-assisted dispersive liquid-liquid microextraction followed by high-performance liquid chromatography for the determination of fluoxetine in human plasma and urine samples was developed. The effects of six parameters on the extraction recovery were investigated and optimized utilizing Plackett-Burman design and Box-Benken design, respectively. According to the Plackett-Burman design results, the volume of disperser solvent, extraction time, and stirring speed had no effect on the recovery of fluoxetine. The optimized conditions included a mixture of 172 μL of 1-octanol as extraction solvent and 400 μL of methanol as disperser solvent, pH of 11.3 and 0% w/v of salt in the sample solution. Replicating the experiment in optimized condition for five times, gave the average extraction recoveries equal to 90.15%. The detection limit of fluoxetine in human plasma was obtained 3 ng/mL, and the linearity was in the range of 10-1200 ng/mL. The corresponding values for human urine were 4.2 ng/mL with the linearity range from 10 to 2000 ng/mL. Relative standard deviations for intra and inter day extraction of fluoxetine were less than 7% in five measurements. The developed method was successfully applied for the determination of fluoxetine in human plasma and urine samples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An optimization based sampling approach for multiple metrics uncertainty analysis using generalized likelihood uncertainty estimation

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.

Clinical implementation of stereotaxic brain implant optimization

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

Rosenow, U.F.; Wojcicka, J.B.

1991-03-01

This optimization method for stereotaxic brain implants is based on seed/strand configurations of the basic type developed for the National Cancer Institute (NCI) atlas of regular brain implants. Irregular target volume shapes are determined from delineation in a stack of contrast enhanced computed tomography scans. The neurosurgeon may then select up to ten directions, or entry points, of surgical approach of which the program finds the optimal one under the criterion of smallest target volume diameter. Target volume cross sections are then reconstructed in 5-mm-spaced planes perpendicular to the implantation direction defined by the entry point and the target volumemore » center. This information is used to define a closed line in an implant cross section along which peripheral seed strands are positioned and which has now an irregular shape. Optimization points are defined opposite peripheral seeds on the target volume surface to which the treatment dose rate is prescribed. Three different optimization algorithms are available: linear least-squares programming, quadratic programming with constraints, and a simplex method. The optimization routine is implemented into a commercial treatment planning system. It generates coordinate and source strength information of the optimized seed configurations for further dose rate distribution calculation with the treatment planning system, and also the coordinate settings for the stereotaxic Brown-Roberts-Wells (BRW) implantation device.« less

Evaluation of optimized b-value sampling schemas for diffusion kurtosis imaging with an application to stroke patient data

PubMed Central

Yan, Xu; Zhou, Minxiong; Ying, Lingfang; Yin, Dazhi; Fan, Mingxia; Yang, Guang; Zhou, Yongdi; Song, Fan; Xu, Dongrong

2013-01-01

Diffusion kurtosis imaging (DKI) is a new method of magnetic resonance imaging (MRI) that provides non-Gaussian information that is not available in conventional diffusion tensor imaging (DTI). DKI requires data acquisition at multiple b-values for parameter estimation; this process is usually time-consuming. Therefore, fewer b-values are preferable to expedite acquisition. In this study, we carefully evaluated various acquisition schemas using different numbers and combinations of b-values. Acquisition schemas that sampled b-values that were distributed to two ends were optimized. Compared to conventional schemas using equally spaced b-values (ESB), optimized schemas require fewer b-values to minimize fitting errors in parameter estimation and may thus significantly reduce scanning time. Following a ranked list of optimized schemas resulted from the evaluation, we recommend the 3b schema based on its estimation accuracy and time efficiency, which needs data from only 3 b-values at 0, around 800 and around 2600 s/mm2, respectively. Analyses using voxel-based analysis (VBA) and region-of-interest (ROI) analysis with human DKI datasets support the use of the optimized 3b (0, 1000, 2500 s/mm2) DKI schema in practical clinical applications. PMID:23735303

Optimization of separation and online sample concentration of N,N-dimethyltryptamine and related compounds using MEKC.

PubMed

Wang, Man-Juing; Tsai, Chih-Hsin; Hsu, Wei-Ya; Liu, Ju-Tsung; Lin, Cheng-Huang

2009-02-01

The optimal separation conditions and online sample concentration for N,N-dimethyltryptamine (DMT) and related compounds, including alpha-methyltryptamine (AMT), 5-methoxy-AMT (5-MeO-AMT), N,N-diethyltryptamine (DET), N,N-dipropyltryptamine (DPT), N,N-dibutyltryptamine (DBT), N,N-diisopropyltryptamine (DiPT), 5-methoxy-DMT (5-MeO-DMT), and 5-methoxy-N,N-DiPT (5-MeO-DiPT), using micellar EKC (MEKC) with UV-absorbance detection are described. The LODs (S/N = 3) for MEKC ranged from 1.0 1.8 microg/mL. Use of online sample concentration methods, including sweeping-MEKC and cation-selective exhaustive injection-sweep-MEKC (CSEI-sweep-MEKC) improved the LODs to 2.2 8.0 ng/mL and 1.3 2.7 ng/mL, respectively. In addition, the order of migration of the nine tryptamines was investigated. A urine sample, obtained by spiking urine collected from a human volunteer with DMT, was also successfully examined.

Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty

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

Ampomah, William; Balch, Robert; Will, Robert

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parametersmore » as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about

Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty

DOE PAGES

Ampomah, William; Balch, Robert; Will, Robert; ...

2017-07-01

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parametersmore » as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about

Drug-drug interaction predictions with PBPK models and optimal multiresponse sampling time designs: application to midazolam and a phase I compound. Part 1: comparison of uniresponse and multiresponse designs using PopDes.

PubMed

Chenel, Marylore; Bouzom, François; Aarons, Leon; Ogungbenro, Kayode

2008-12-01

To determine the optimal sampling time design of a drug-drug interaction (DDI) study for the estimation of apparent clearances (CL/F) of two co-administered drugs (SX, a phase I compound, potentially a CYP3A4 inhibitor, and MDZ, a reference CYP3A4 substrate) without any in vivo data using physiologically based pharmacokinetic (PBPK) predictions, population PK modelling and multiresponse optimal design. PBPK models were developed with AcslXtreme using only in vitro data to simulate PK profiles of both drugs when they were co-administered. Then, using simulated data, population PK models were developed with NONMEM and optimal sampling times were determined by optimizing the determinant of the population Fisher information matrix with PopDes using either two uniresponse designs (UD) or a multiresponse design (MD) with joint sampling times for both drugs. Finally, the D-optimal sampling time designs were evaluated by simulation and re-estimation with NONMEM by computing the relative root mean squared error (RMSE) and empirical relative standard errors (RSE) of CL/F. There were four and five optimal sampling times (=nine different sampling times) in the UDs for SX and MDZ, respectively, whereas there were only five sampling times in the MD. Whatever design and compound, CL/F was well estimated (RSE < 20% for MDZ and <25% for SX) and expected RSEs from PopDes were in the same range as empirical RSEs. Moreover, there was no bias in CL/F estimation. Since MD required only five sampling times compared to the two UDs, D-optimal sampling times of the MD were included into a full empirical design for the proposed clinical trial. A joint paper compares the designs with real data. This global approach including PBPK simulations, population PK modelling and multiresponse optimal design allowed, without any in vivo data, the design of a clinical trial, using sparse sampling, capable of estimating CL/F of the CYP3A4 substrate and potential inhibitor when co-administered together.

Stepped Care to Optimize Pain care Effectiveness (SCOPE) trial study design and sample characteristics.

PubMed

Kroenke, Kurt; Krebs, Erin; Wu, Jingwei; Bair, Matthew J; Damush, Teresa; Chumbler, Neale; York, Tish; Weitlauf, Sharon; McCalley, Stephanie; Evans, Erica; Barnd, Jeffrey; Yu, Zhangsheng

2013-03-01

Pain is the most common physical symptom in primary care, accounting for an enormous burden in terms of patient suffering, quality of life, work and social disability, and health care and societal costs. Although collaborative care interventions are well-established for conditions such as depression, fewer systems-based interventions have been tested for chronic pain. This paper describes the study design and baseline characteristics of the enrolled sample for the Stepped Care to Optimize Pain care Effectiveness (SCOPE) study, a randomized clinical effectiveness trial conducted in five primary care clinics. SCOPE has enrolled 250 primary care veterans with persistent (3 months or longer) musculoskeletal pain of moderate severity and randomized them to either the stepped care intervention or usual care control group. Using a telemedicine collaborative care approach, the intervention couples automated symptom monitoring with a telephone-based, nurse care manager/physician pain specialist team to treat pain. The goal is to optimize analgesic management using a stepped care approach to drug selection, symptom monitoring, dose adjustment, and switching or adding medications. All subjects undergo comprehensive outcome assessments at baseline, 1, 3, 6 and 12 months by interviewers blinded to treatment group. The primary outcome is pain severity/disability, and secondary outcomes include pain beliefs and behaviors, psychological functioning, health-related quality of life and treatment satisfaction. Innovations of SCOPE include optimized analgesic management (including a stepped care approach, opioid risk stratification, and criteria-based medication adjustment), automated monitoring, and centralized care management that can cover multiple primary care practices. Published by Elsevier Inc.

TRO-2D - A code for rational transonic aerodynamic optimization

NASA Technical Reports Server (NTRS)

Davis, W. H., Jr.

1985-01-01

Features and sample applications of the transonic rational optimization (TRO-2D) code are outlined. TRO-2D includes the airfoil analysis code FLO-36, the CONMIN optimization code and a rational approach to defining aero-function shapes for geometry modification. The program is part of an effort to develop an aerodynamically smart optimizer that will simplify and shorten the design process. The user has a selection of drag minimization and associated minimum lift, moment, and the pressure distribution, a choice among 14 resident aero-function shapes, and options on aerodynamic and geometric constraints. Design variables such as the angle of attack, leading edge radius and camber, shock strength and movement, supersonic pressure plateau control, etc., are discussed. The results of calculations of a reduced leading edge camber transonic airfoil and an airfoil with a natural laminar flow are provided, showing that only four design variables need be specified to obtain satisfactory results.

Optimal ciliary beating patterns

NASA Astrophysics Data System (ADS)

Vilfan, Andrej; Osterman, Natan

2011-11-01

We introduce a measure for energetic efficiency of single or collective biological cilia. We define the efficiency of a single cilium as Q2 / P , where Q is the volume flow rate of the pumped fluid and P is the dissipated power. For ciliary arrays, we define it as (ρQ) 2 / (ρP) , with ρ denoting the surface density of cilia. We then numerically determine the optimal beating patterns according to this criterion. For a single cilium optimization leads to curly, somewhat counterintuitive patterns. But when looking at a densely ciliated surface, the optimal patterns become remarkably similar to what is observed in microorganisms like Paramecium. The optimal beating pattern then consists of a fast effective stroke and a slow sweeping recovery stroke. Metachronal waves lead to a significantly higher efficiency than synchronous beating. Efficiency also increases with an increasing density of cilia up to the point where crowding becomes a problem. We finally relate the pumping efficiency of cilia to the swimming efficiency of a spherical microorganism and show that the experimentally estimated efficiency of Paramecium is surprisingly close to the theoretically possible optimum.

Optimization of Composite Structures with Curved Fiber Trajectories

NASA Astrophysics Data System (ADS)

Lemaire, Etienne; Zein, Samih; Bruyneel, Michael

2014-06-01

This paper studies the problem of optimizing composites shells manufactured using Automated Tape Layup (ATL) or Automated Fiber Placement (AFP) processes. The optimization procedure relies on a new approach to generate equidistant fiber trajectories based on Fast Marching Method. Starting with a (possibly curved) reference fiber direction defined on a (possibly curved) meshed surface, the new method allows determining fibers orientation resulting from a uniform thickness layup. The design variables are the parameters defining the position and the shape of the reference curve which results in very few design variables. Thanks to this efficient parameterization, maximum stiffness optimization numerical applications are proposed. The shape of the design space is discussed, regarding local and global optimal solutions.

Criteria to define a more relevant reference sample of titanium dioxide in the context of food: a multiscale approach.

PubMed

Dudefoi, William; Terrisse, Hélène; Richard-Plouet, Mireille; Gautron, Eric; Popa, Florin; Humbert, Bernard; Ropers, Marie-Hélène

2017-05-01

Titanium dioxide (TiO 2 ) is a transition metal oxide widely used as a white pigment in various applications, including food. Due to the classification of TiO 2 nanoparticles by the International Agency for Research on Cancer as potentially harmful for humans by inhalation, the presence of nanoparticles in food products needed to be confirmed by a set of independent studies. Seven samples of food-grade TiO 2 (E171) were extensively characterised for their size distribution, crystallinity and surface properties by the currently recommended methods. All investigated E171 samples contained a fraction of nanoparticles, however, below the threshold defining the labelling of nanomaterial. On the basis of these results and a statistical analysis, E171 food-grade TiO 2 totally differs from the reference material P25, confirming the few published data on this kind of particle. Therefore, the reference material P25 does not appear to be the most suitable model to study the fate of food-grade TiO 2 in the gastrointestinal tract. The criteria currently to obtain a representative food-grade sample of TiO 2 are the following: (1) crystalline-phase anatase, (2) a powder with an isoelectric point very close to 4.1, (3) a fraction of nanoparticles comprised between 15% and 45%, and (4) a low specific surface area around 10 m 2  g - 1 .

Reconstructing metabolic flux vectors from extreme pathways: defining the alpha-spectrum.

PubMed

Wiback, Sharon J; Mahadevan, Radhakrishnan; Palsson, Bernhard Ø

2003-10-07

The move towards genome-scale analysis of cellular functions has necessitated the development of analytical (in silico) methods to understand such large and complex biochemical reaction networks. One such method is extreme pathway analysis that uses stoichiometry and thermodynamic irreversibly to define mathematically unique, systemic metabolic pathways. These extreme pathways form the edges of a high-dimensional convex cone in the flux space that contains all the attainable steady state solutions, or flux distributions, for the metabolic network. By definition, any steady state flux distribution can be described as a nonnegative linear combination of the extreme pathways. To date, much effort has been focused on calculating, defining, and understanding these extreme pathways. However, little work has been performed to determine how these extreme pathways contribute to a given steady state flux distribution. This study represents an initial effort aimed at defining how physiological steady state solutions can be reconstructed from a network's extreme pathways. In general, there is not a unique set of nonnegative weightings on the extreme pathways that produce a given steady state flux distribution but rather a range of possible values. This range can be determined using linear optimization to maximize and minimize the weightings of a particular extreme pathway in the reconstruction, resulting in what we have termed the alpha-spectrum. The alpha-spectrum defines which extreme pathways can and cannot be included in the reconstruction of a given steady state flux distribution and to what extent they individually contribute to the reconstruction. It is shown that accounting for transcriptional regulatory constraints can considerably shrink the alpha-spectrum. The alpha-spectrum is computed and interpreted for two cases; first, optimal states of a skeleton representation of core metabolism that include transcriptional regulation, and second for human red blood cell

Defined PEG smears as an alternative approach to enhance the search for crystallization conditions and crystal-quality improvement in reduced screens

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

Chaikuad, Apirat, E-mail: apirat.chaikuad@sgc.ox.ac.uk; Knapp, Stefan; Johann Wolfgang Goethe-University, Building N240 Room 3.03, Max-von-Laue-Strasse 9, 60438 Frankfurt am Main

An alternative strategy for PEG sampling is suggested through the use of four newly defined PEG smears to enhance chemical space in reduced screens with a benefit towards protein crystallization. The quest for an optimal limited set of effective crystallization conditions remains a challenge in macromolecular crystallography, an issue that is complicated by the large number of chemicals which have been deemed to be suitable for promoting crystal growth. The lack of rational approaches towards the selection of successful chemical space and representative combinations has led to significant overlapping conditions, which are currently present in a multitude of commercially availablemore » crystallization screens. Here, an alternative approach to the sampling of widely used PEG precipitants is suggested through the use of PEG smears, which are mixtures of different PEGs with a requirement of either neutral or cooperatively positive effects of each component on crystal growth. Four newly defined smears were classified by molecular-weight groups and enabled the preservation of specific properties related to different polymer sizes. These smears not only allowed a wide coverage of properties of these polymers, but also reduced PEG variables, enabling greater sampling of other parameters such as buffers and additives. The efficiency of the smear-based screens was evaluated on more than 220 diverse recombinant human proteins, which overall revealed a good initial crystallization success rate of nearly 50%. In addition, in several cases successful crystallizations were only obtained using PEG smears, while various commercial screens failed to yield crystals. The defined smears therefore offer an alternative approach towards PEG sampling, which will benefit the design of crystallization screens sampling a wide chemical space of this key precipitant.« less

On optimal soft-decision demodulation. [in digital communication system

NASA Technical Reports Server (NTRS)

Lee, L.-N.

1976-01-01

A necessary condition is derived for optimal J-ary coherent demodulation of M-ary (M greater than 2) signals. Optimality is defined as maximality of the symmetric cutoff rate of the resulting discrete memoryless channel. Using a counterexample, it is shown that the condition derived is generally not sufficient for optimality. This condition is employed as the basis for an iterative optimization method to find the optimal demodulator decision regions from an initial 'good guess'. In general, these regions are found to be bounded by hyperplanes in likelihood space; the corresponding regions in signal space are found to have hyperplane asymptotes for the important case of additive white Gaussian noise. Some examples are presented, showing that the regions in signal space bounded by these asymptotic hyperplanes define demodulator decision regions that are virtually optimal.

A framework for parallelized efficient global optimization with application to vehicle crashworthiness optimization

NASA Astrophysics Data System (ADS)

Hamza, Karim; Shalaby, Mohamed

2014-09-01

This article presents a framework for simulation-based design optimization of computationally expensive problems, where economizing the generation of sample designs is highly desirable. One popular approach for such problems is efficient global optimization (EGO), where an initial set of design samples is used to construct a kriging model, which is then used to generate new 'infill' sample designs at regions of the search space where there is high expectancy of improvement. This article attempts to address one of the limitations of EGO, where generation of infill samples can become a difficult optimization problem in its own right, as well as allow the generation of multiple samples at a time in order to take advantage of parallel computing in the evaluation of the new samples. The proposed approach is tested on analytical functions, and then applied to the vehicle crashworthiness design of a full Geo Metro model undergoing frontal crash conditions.

Experimental test of an online ion-optics optimizer

NASA Astrophysics Data System (ADS)

Amthor, A. M.; Schillaci, Z. M.; Morrissey, D. J.; Portillo, M.; Schwarz, S.; Steiner, M.; Sumithrarachchi, Ch.

2018-07-01

A technique has been developed and tested to automatically adjust multiple electrostatic or magnetic multipoles on an ion optical beam line - according to a defined optimization algorithm - until an optimal tune is found. This approach simplifies the process of determining high-performance optical tunes, satisfying a given set of optical properties, for an ion optical system. The optimization approach is based on the particle swarm method and is entirely model independent, thus the success of the optimization does not depend on the accuracy of an extant ion optical model of the system to be optimized. Initial test runs of a first order optimization of a low-energy (<60 keV) all-electrostatic beamline at the NSCL show reliable convergence of nine quadrupole degrees of freedom to well-performing tunes within a reasonable number of trial solutions, roughly 500, with full beam optimization run times of roughly two hours. Improved tunes were found both for quasi-local optimizations and for quasi-global optimizations, indicating a good ability of the optimizer to find a solution with or without a well defined set of initial multipole settings.

Automation of sample preparation for mass cytometry barcoding in support of clinical research: protocol optimization.

PubMed

Nassar, Ala F; Wisnewski, Adam V; Raddassi, Khadir

2017-03-01

Analysis of multiplexed assays is highly important for clinical diagnostics and other analytical applications. Mass cytometry enables multi-dimensional, single-cell analysis of cell type and state. In mass cytometry, the rare earth metals used as reporters on antibodies allow determination of marker expression in individual cells. Barcode-based bioassays for CyTOF are able to encode and decode for different experimental conditions or samples within the same experiment, facilitating progress in producing straightforward and consistent results. Herein, an integrated protocol for automated sample preparation for barcoding used in conjunction with mass cytometry for clinical bioanalysis samples is described; we offer results of our work with barcoding protocol optimization. In addition, we present some points to be considered in order to minimize the variability of quantitative mass cytometry measurements. For example, we discuss the importance of having multiple populations during titration of the antibodies and effect of storage and shipping of labelled samples on the stability of staining for purposes of CyTOF analysis. Data quality is not affected when labelled samples are stored either frozen or at 4 °C and used within 10 days; we observed that cell loss is greater if cells are washed with deionized water prior to shipment or are shipped in lower concentration. Once the labelled samples for CyTOF are suspended in deionized water, the analysis should be performed expeditiously, preferably within the first hour. Damage can be minimized if the cells are resuspended in phosphate-buffered saline (PBS) rather than deionized water while waiting for data acquisition.

Integrated multidisciplinary design optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Mantay, Wayne R.

1989-01-01

The NASA/Army research plan for developing the logic elements for helicopter rotor design optimization by integrating appropriate disciplines and accounting for important interactions among the disciplines is discussed. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. The analysis aspects are discussed, and an initial effort at defining the interdisciplinary coupling is summarized. Results are presented on the achievements made in the rotor aerodynamic performance optimization for minimum hover horsepower, rotor dynamic optimization for vibration reduction, rotor structural optimization for minimum weight, and integrated aerodynamic load/dynamics optimization for minimum vibration and weight.

Application of Chitosan-Zinc Oxide Nanoparticles for Lead Extraction From Water Samples by Combining Ant Colony Optimization with Artificial Neural Network

NASA Astrophysics Data System (ADS)

Khajeh, M.; Pourkarami, A.; Arefnejad, E.; Bohlooli, M.; Khatibi, A.; Ghaffari-Moghaddam, M.; Zareian-Jahromi, S.

2017-09-01

Chitosan-zinc oxide nanoparticles (CZPs) were developed for solid-phase extraction. Combined artificial neural network-ant colony optimization (ANN-ACO) was used for the simultaneous preconcentration and determination of lead (Pb2+) ions in water samples prior to graphite furnace atomic absorption spectrometry (GF AAS). The solution pH, mass of adsorbent CZPs, amount of 1-(2-pyridylazo)-2-naphthol (PAN), which was used as a complexing agent, eluent volume, eluent concentration, and flow rates of sample and eluent were used as input parameters of the ANN model, and the percentage of extracted Pb2+ ions was used as the output variable of the model. A multilayer perception network with a back-propagation learning algorithm was used to fit the experimental data. The optimum conditions were obtained based on the ACO. Under the optimized conditions, the limit of detection for Pb2+ ions was found to be 0.078 μg/L. This procedure was also successfully used to determine the amounts of Pb2+ ions in various natural water samples.

Optimization of microwave-assisted extraction with saponification (MAES) for the determination of polybrominated flame retardants in aquaculture samples.

PubMed

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.

Gas chromatographic-mass spectrometric analysis of urinary volatile organic metabolites: Optimization of the HS-SPME procedure and sample storage conditions.

PubMed

Živković Semren, Tanja; Brčić Karačonji, Irena; Safner, Toni; Brajenović, Nataša; Tariba Lovaković, Blanka; Pizent, Alica

2018-01-01

Non-targeted metabolomics research of human volatile urinary metabolome can be used to identify potential biomarkers associated with the changes in metabolism related to various health disorders. To ensure reliable analysis of urinary volatile organic metabolites (VOMs) by gas chromatography-mass spectrometry (GC-MS), parameters affecting the headspace-solid phase microextraction (HS-SPME) procedure have been evaluated and optimized. The influence of incubation and extraction temperatures and times, coating fibre material and salt addition on SPME efficiency was investigated by multivariate optimization methods using reduced factorial and Doehlert matrix designs. The results showed optimum values for temperature to be 60°C, extraction time 50min, and incubation time 35min. The proposed conditions were applied to investigate urine samples' stability regarding different storage conditions and freeze-thaw processes. The sum of peak areas of urine samples stored at 4°C, -20°C, and -80°C up to six months showed a time dependent decrease over time although storage at -80°C resulted in a slight non-significant reduction comparing to the fresh sample. However, due to the volatile nature of the analysed compounds, more than two cycles of freezing/thawing of the sample stored for six months at -80°C should be avoided whenever possible. Copyright © 2017 Elsevier B.V. All rights reserved.

Software/hardware optimization for attenuation-based microtomography using SR at PETRA III (Conference Presentation)

NASA Astrophysics Data System (ADS)

Beckmann, Felix

2016-10-01

The Helmholtz-Zentrum Geesthacht, Germany, is operating the user experiments for microtomography at the beamlines P05 and P07 using synchrotron radiation produced in the storage ring PETRA III at DESY, Hamburg, Germany. In recent years the software pipeline, sample changing hardware for performing high throughput experiments were developed. In this talk the current status of the beamlines will be given. Furthermore, optimisation and automatisation of scanning techniques, will be presented. These are required to scan samples which are larger than the field of view defined by the X-ray beam. The integration into an optimized reconstruction pipeline will be shown.

An initiative in multidisciplinary optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Mantay, Wayne R.

1989-01-01

Described is a joint NASA/Army initiative at the Langley Research Center to develop optimization procedures aimed at improving the rotor blade design process by integrating appropriate disciplines and accounting for important interactions among the disciplines. The activity is being guided by a Steering Committee made up of key NASA and Army researchers and managers. The committee, which has been named IRASC (Integrated Rotorcraft Analysis Steering Committee), has defined two principal foci for the activity: a white paper which sets forth the goals and plans of the effort; and a rotor design project which will validate the basic constituents, as well as the overall design methodology for multidisciplinary optimization. The optimization formulation is described in terms of the objective function, design variables, and constraints. Additionally, some of the analysis aspects are discussed and an initial attempt at defining the interdisciplinary couplings is summarized. At this writing, some significant progress has been made, principally in the areas of single discipline optimization. Results are given which represent accomplishments in rotor aerodynamic performance optimization for minimum hover horsepower, rotor dynamic optimization for vibration reduction, and rotor structural optimization for minimum weight.

An initiative in multidisciplinary optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Mantay, Wayne R.

1988-01-01

Described is a joint NASA/Army initiative at the Langley Research Center to develop optimization procedures aimed at improving the rotor blade design process by integrating appropriate disciplines and accounting for important interactions among the disciplines. The activity is being guided by a Steering Committee made up of key NASA and Army researchers and managers. The committee, which has been named IRASC (Integrated Rotorcraft Analysis Steering Committee), has defined two principal foci for the activity: a white paper which sets forth the goals and plans of the effort; and a rotor design project which will validate the basic constituents, as well as the overall design methodology for multidisciplinary optimization. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. Additionally, some of the analysis aspects are discussed and an initial attempt at defining the interdisciplinary couplings is summarized. At this writing, some significant progress has been made, principally in the areas of single discipline optimization. Results are given which represent accomplishments in rotor aerodynamic performance optimization for minimum hover horsepower, rotor dynamic optimization for vibration reduction, and rotor structural optimization for minimum weight.

Variance of discharge estimates sampled using acoustic Doppler current profilers from moving boats

USGS Publications Warehouse

Garcia, Carlos M.; Tarrab, Leticia; Oberg, Kevin; Szupiany, Ricardo; Cantero, Mariano I.

2012-01-01

This paper presents a model for quantifying the random errors (i.e., variance) of acoustic Doppler current profiler (ADCP) discharge measurements from moving boats for different sampling times. The model focuses on the random processes in the sampled flow field and has been developed using statistical methods currently available for uncertainty analysis of velocity time series. Analysis of field data collected using ADCP from moving boats from three natural rivers of varying sizes and flow conditions shows that, even though the estimate of the integral time scale of the actual turbulent flow field is larger than the sampling interval, the integral time scale of the sampled flow field is on the order of the sampling interval. Thus, an equation for computing the variance error in discharge measurements associated with different sampling times, assuming uncorrelated flow fields is appropriate. The approach is used to help define optimal sampling strategies by choosing the exposure time required for ADCPs to accurately measure flow discharge.

Optimizing read-out of the NECTAr front-end electronics

NASA Astrophysics Data System (ADS)

Vorobiov, S.; Feinstein, F.; Bolmont, J.; Corona, P.; Delagnes, E.; Falvard, A.; Gascón, D.; Glicenstein, J.-F.; Naumann, C. L.; Nayman, P.; Ribo, M.; Sanuy, A.; Tavernet, J.-P.; Toussenel, F.; Vincent, P.

2012-12-01

We describe the optimization of the read-out specifications of the NECTAr front-end electronics for the Cherenkov Telescope Array (CTA). The NECTAr project aims at building and testing a demonstrator module of a new front-end electronics design, which takes an advantage of the know-how acquired while building the cameras of the CAT, H.E.S.S.-I and H.E.S.S.-II experiments. The goal of the optimization work is to define the specifications of the digitizing electronics of a CTA camera, in particular integration time window, sampling rate, analog bandwidth using physics simulations. We employed for this work real photomultiplier pulses, sampled at 100 ps with a 600 MHz bandwidth oscilloscope. The individual pulses are drawn randomly at the times at which the photo-electrons, originating from atmospheric showers, arrive at the focal planes of imaging atmospheric Cherenkov telescopes. The timing information is extracted from the existing CTA simulations on the GRID and organized in a local database, together with all the relevant physical parameters (energy, primary particle type, zenith angle, distance from the shower axis, pixel offset from the optical axis, night-sky background level, etc.), and detector configurations (telescope types, camera/mirror configurations, etc.). While investigating the parameter space, an optimal pixel charge integration time window, which minimizes relative error in the measured charge, has been determined. This will allow to gain in sensitivity and to lower the energy threshold of CTA telescopes. We present results of our optimizations and first measurements obtained using the NECTAr demonstrator module.

[Transfusion supply optimization in multiple-discipline surgical hospital].

PubMed

Solov'eva, I N; Trekova, N A; Krapivkin, I A

2016-01-01

To define optimal variant of transfusion supply of hospital by blood components and to decrease donor blood expense via application of blood preserving technologies. Donor blood components expense, volume of hemotransfusions and their proportion for the period 2012-2014 were analyzed. Number of recipients of packed red cells, fresh-frozen plasma and packed platelets reduced 18.5%, 25% and 80% respectively. Need for donor plasma decreased 35%. Expense of autologous plasma in cardiac surgery was 76% of overall volume. Preoperative plasma sampling is introduced in patients with aortic aneurysm. Number of cardiac interventions performed without donor blood is increased 7-31% depending on its complexity.

Two-dimensional T2 distribution mapping in rock core plugs with optimal k-space sampling.

PubMed

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. Copyright © 2012 Elsevier Inc. All rights reserved.

General shape optimization capability

NASA Technical Reports Server (NTRS)

Chargin, Mladen K.; Raasch, Ingo; Bruns, Rudolf; Deuermeyer, Dawson

1991-01-01

A method is described for calculating shape sensitivities, within MSC/NASTRAN, in a simple manner without resort to external programs. The method uses natural design variables to define the shape changes in a given structure. Once the shape sensitivities are obtained, the shape optimization process is carried out in a manner similar to property optimization processes. The capability of this method is illustrated by two examples: the shape optimization of a cantilever beam with holes, loaded by a point load at the free end (with the shape of the holes and the thickness of the beam selected as the design variables), and the shape optimization of a connecting rod subjected to several different loading and boundary conditions.

Development of defined microbial population standards using fluorescence activated cell sorting for the absolute quantification of S. aureus using real-time PCR.

PubMed

Martinon, Alice; Cronin, Ultan P; Wilkinson, Martin G

2012-01-01

In this article, four types of standards were assessed in a SYBR Green-based real-time PCR procedure for the quantification of Staphylococcus aureus (S. aureus) in DNA samples. The standards were purified S. aureus genomic DNA (type A), circular plasmid DNA containing a thermonuclease (nuc) gene fragment (type B), DNA extracted from defined populations of S. aureus cells generated by Fluorescence Activated Cell Sorting (FACS) technology with (type C) or without purification of DNA by boiling (type D). The optimal efficiency of 2.016 was obtained on Roche LightCycler(®) 4.1. software for type C standards, whereas the lowest efficiency (1.682) corresponded to type D standards. Type C standards appeared to be more suitable for quantitative real-time PCR because of the use of defined populations for construction of standard curves. Overall, Fieller Confidence Interval algorithm may be improved for replicates having a low standard deviation in Cycle Threshold values such as found for type B and C standards. Stabilities of diluted PCR standards stored at -20°C were compared after 0, 7, 14 and 30 days and were lower for type A or C standards compared with type B standards. However, FACS generated standards may be useful for bacterial quantification in real-time PCR assays once optimal storage and temperature conditions are defined.

Taking Stock of Unrealistic Optimism.

PubMed

Shepperd, James A; Klein, William M P; Waters, Erika A; Weinstein, Neil D

2013-07-01

Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type-the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention.

Taking Stock of Unrealistic Optimism

PubMed Central

Shepperd, James A.; Klein, William M. P.; Waters, Erika A.; Weinstein, Neil D.

2015-01-01

Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type—the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention. PMID:26045714

Selection of optimal spectral sensitivity functions for color filter arrays.

PubMed

Parmar, Manu; Reeves, Stanley J

2010-12-01

A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color filter array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ∆E error metric and a qualitative assessment.

An Optimized Configuration for the Brazilian Decimetric Array

NASA Astrophysics Data System (ADS)

Sawant, Hanumant; Faria, Claudio; Stephany, Stephan

The Brazilian Decimetric Array (BDA) is a radio interferometer designed to operate in the frequency range of 1.2-1.7, 2.8 and 5.6 GHz and to obtain images of radio sources with high dynamic range. A 5-antenna configuration is already operational being implemented in BDA phase I. Phase II will provide a 26-antenna configuration forming a compact T-array, whereas phase III will include further 12 antennas. However, the BDA site has topographic constraints that preclude the placement of these antennas along the lines defined by the 3 arms of the T-array. Therefore, some antennas must be displaced in a direction that is slightly transverse tothese lines. This work presents the investigation of possible optimized configurations for all 38 antennas spread over the distances of 2.5 x 1.25 km. It was required to determine the optimal position of the last 12 antennas.A new optimization strategy was then proposed in order to obtain the optimal array configuration. It is based on the entropy of the distribution of the sampled points in the Fourier plane. A stochastic model, Ant Colony Optimization, uses the entropy of the such distribution to iteratively refine the candidate solutions. The proposed strategy can be used to determine antenna locations for free-shape arrays in order to provide uniform u-v coverage with minimum redundancy of sampled points in u-v plane that are less susceptible to errors due to unmeasured Fourier components. A different distribution could be chosen for the coverage. It also allows to consider the topographical constraints of the available site. Furthermore, it provides an optimal configuration even considering the predetermined placement of the 26 antennas that compose the central T-array. In this case, the optimal location of the last 12 antennas was determined. Performance results corresponding to the Fourier plane coverage, synthesized beam and sidelobes levels are shown for this optimized BDA configuration and are compared to the results of

Social support, acculturation, and optimism: understanding positive health practices in Asian American college students.

PubMed

Ayres, Cynthia G; Mahat, Ganga

2012-07-01

This study developed and tested a theory to better understand positive health practices (PHP) among Asian Americans aged 18 to 21 years. It tested theoretical relationships postulated between PHP and (a) social support (SS), (b) optimism, and (c) acculturation, and between SS and optimism and acculturation. Optimism and acculturation were also tested as possible mediators in the relationship between SS and PHP. A correlational study design was used. A convenience sample of 163 Asian college students in an urban setting completed four questionnaires assessing SS, PHP, optimism, and acculturation and one demographic questionnaire. There were statistically significant positive relationships between SS and optimism with PHP, between acculturation and PHP, and between optimism and SS. Optimism mediated the relationship between SS and PHP, whereas acculturation did not. Findings extend knowledge regarding these relationships to a defined population of Asian Americans aged 18 to 21 years. Findings contribute to a more comprehensive knowledge base regarding health practices among Asian Americans. The theoretical and empirical findings of this study provide the direction for future research as well. Further studies need to be conducted to identify and test other mediators in order to better understand the relationship between these two variables.

Efficient dynamic optimization of logic programs

NASA Technical Reports Server (NTRS)

Laird, Phil

1992-01-01

A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

Sampling bee communities using pan traps: alternative methods increase sample size

USDA-ARS?s Scientific Manuscript database

Monitoring of the status of bee populations and inventories of bee faunas require systematic sampling. Efficiency and ease of implementation has encouraged the use of pan traps to sample bees. Efforts to find an optimal standardized sampling method for pan traps have focused on pan trap color. Th...

CENTRAL PLATEAU REMEDIATION OPTIMIZATION STUDY

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

BERGMAN, T. B.; STEFANSKI, L. D.; SEELEY, P. N.

2012-09-19

THE CENTRAL PLATEAU REMEDIATION OPTIMIZATION STUDY WAS CONDUCTED TO DEVELOP AN OPTIMAL SEQUENCE OF REMEDIATION ACTIVITIES IMPLEMENTING THE CERCLA DECISION ON THE CENTRAL PLATEAU. THE STUDY DEFINES A SEQUENCE OF ACTIVITIES THAT RESULT IN AN EFFECTIVE USE OF RESOURCES FROM A STRATEGIC PERSPECTIVE WHEN CONSIDERING EQUIPMENT PROCUREMENT AND STAGING, WORKFORCE MOBILIZATION/DEMOBILIZATION, WORKFORCE LEVELING, WORKFORCE SKILL-MIX, AND OTHER REMEDIATION/DISPOSITION PROJECT EXECUTION PARAMETERS.

An optimization model to agroindustrial sector in antioquia (Colombia, South America)

NASA Astrophysics Data System (ADS)

Fernandez, J.

2015-06-01

This paper develops a proposal of a general optimization model for the flower industry, which is defined by using discrete simulation and nonlinear optimization, whose mathematical models have been solved by using ProModel simulation tools and Gams optimization. It defines the operations that constitute the production and marketing of the sector, statistically validated data taken directly from each operation through field work, the discrete simulation model of the operations and the linear optimization model of the entire industry chain are raised. The model is solved with the tools described above and presents the results validated in a case study.

Comparison of Optimal Design Methods in Inverse Problems

PubMed Central

Banks, H. T.; Holm, Kathleen; Kappel, Franz

2011-01-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher Information Matrix (FIM). A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criteria with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model [13], the standard harmonic oscillator model [13] and a popular glucose regulation model [16, 19, 29]. PMID:21857762

Monitoring of trace elements in breast milk sampling and measurement procedures.

PubMed

Spĕvácková, V; Rychlík, S; Cejchanová, M; Spĕvácek, V

2005-06-01

The aims of this study were to test analytical procedures for the determination of Cd, Cu, Mn, Pb, Se and Zn in breast milk and to establish optimum sampling conditions for monitoring purposes. Two population groups were analysed: (1) Seven women from Prague whose breast milk was sampled on days 1,2, 3, 4, 10, 20 and 30 after delivery; (2) 200 women from four (two industrial and two rural) regions whose breast milk was sampled at defined intervals. All samples were mineralised in a microwave oven in the mixture of HNO3 + H2O2 and analysed by atomic absorption spectrometry. Conditions for the measurement of the elements under study (i.e. those for the electrothermal atomisation for Cd, Mn and Pb, flame technique for Cu and Zn, and hydride generation technique for Se) were optimized. Using optimized parameters the analysis was performed and the following conclusion has been made: the concentrations of zinc and manganese decreased very sharply over the first days, that of copper slightly increased within the first two days and then slightly decreased, that of selenium did not change significantly. Partial "stabilisation" was achieved after the second decade. No correlation among the elements was found. A significant difference between whole and skim milk was only found for selenium (26% rel. higher in whole milk). The majority concentrations of cadmium and lead were below the detection limit of the method (0.3 microg x l(-1) and 8.2 microg x l(-1), respectively, as calculated for the original sample). To provide biological monitoring, the maintenance of sampling conditions and especially the time of sampling is crucial.

An Optimized DNA Analysis Workflow for the Sampling, Extraction, and Concentration of DNA obtained from Archived Latent Fingerprints.

PubMed

Solomon, April D; Hytinen, Madison E; McClain, Aryn M; Miller, Marilyn T; Dawson Cruz, Tracey

2018-01-01

DNA profiles have been obtained from fingerprints, but there is limited knowledge regarding DNA analysis from archived latent fingerprints-touch DNA "sandwiched" between adhesive and paper. Thus, this study sought to comparatively analyze a variety of collection and analytical methods in an effort to seek an optimized workflow for this specific sample type. Untreated and treated archived latent fingerprints were utilized to compare different biological sampling techniques, swab diluents, DNA extraction systems, DNA concentration practices, and post-amplification purification methods. Archived latent fingerprints disassembled and sampled via direct cutting, followed by DNA extracted using the QIAamp® DNA Investigator Kit, and concentration with Centri-Sep™ columns increased the odds of obtaining an STR profile. Using the recommended DNA workflow, 9 of the 10 samples provided STR profiles, which included 7-100% of the expected STR alleles and two full profiles. Thus, with carefully selected procedures, archived latent fingerprints can be a viable DNA source for criminal investigations including cold/postconviction cases. © 2017 American Academy of Forensic Sciences.

Multidisciplinary design optimization: An emerging new engineering discipline

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1993-01-01

This paper defines the Multidisciplinary Design Optimization (MDO) as a new field of research endeavor and as an aid in the design of engineering systems. It examines the MDO conceptual components in relation to each other and defines their functions.

Evaluation of the pre-posterior distribution of optimized sampling times for the design of pharmacokinetic studies.

PubMed

Duffull, Stephen B; Graham, Gordon; Mengersen, Kerrie; Eccleston, John

2012-01-01

Information theoretic methods are often used to design studies that aim to learn about pharmacokinetic and linked pharmacokinetic-pharmacodynamic systems. These design techniques, such as D-optimality, provide the optimum experimental conditions. The performance of the optimum design will depend on the ability of the investigator to comply with the proposed study conditions. However, in clinical settings it is not possible to comply exactly with the optimum design and hence some degree of unplanned suboptimality occurs due to error in the execution of the study. In addition, due to the nonlinear relationship of the parameters of these models to the data, the designs are also locally dependent on an arbitrary choice of a nominal set of parameter values. A design that is robust to both study conditions and uncertainty in the nominal set of parameter values is likely to be of use clinically. We propose an adaptive design strategy to account for both execution error and uncertainty in the parameter values. In this study we investigate designs for a one-compartment first-order pharmacokinetic model. We do this in a Bayesian framework using Markov-chain Monte Carlo (MCMC) methods. We consider log-normal prior distributions on the parameters and investigate several prior distributions on the sampling times. An adaptive design was used to find the sampling window for the current sampling time conditional on the actual times of all previous samples.

Diagnostic performance and optimal cut-off scores of the Massachusetts youth screening instrument-second version in a sample of Swiss youths in welfare and juvenile justice institutions.

PubMed

Dölitzsch, Claudia; Leenarts, Laura E W; Schmeck, Klaus; Fegert, Jorg M; Grisso, Thomas; Schmid, Marc

2017-02-08

There is a growing consensus about the importance of mental health screening of youths in welfare and juvenile justice institutions. The Massachusetts Youth Screening Instrument-second version (MAYSI-2) was specifically designed, normed and validated to assist juvenile justice facilities in the United States of America (USA), in identifying youths with potential emotional or behavioral problems. However, it is not known if the USA norm-based cut-off scores can be used in Switzerland. Therefore, the primary purpose of the current study was to estimate the diagnostic performance and optimal cut-off scores of the MAYSI-2 in a sample of Swiss youths in welfare and juvenile justice institutions. As the sample was drawn from the French-, German- and Italian-speaking parts of Switzerland, the three languages were represented in the total sample of the current study and consequently we could estimate the diagnostic performance and the optimal cut-off scores of the MAYSI-2 for the language regions separately. The other main purpose of the current study was to identify potential gender differences in the diagnostic performance and optimal cut-off scores. Participants were 297 boys and 149 girls (mean age = 16.2, SD = 2.5) recruited from 64 youth welfare and juvenile justice institutions (drawn from the French-, German- and Italian-speaking parts of Switzerland). The MAYSI-2 was used to screen for mental health or behavioral problems that could require further evaluation. Psychiatric classification was based on the Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present and Lifetime version (K-SADS-PL). The MAYSI-2 scores were submitted into Receiver-Operating Characteristic (ROC) analyses to estimate the diagnostic performance and optimal 'caution' cut-off scores of the MAYSI-2. The ROC analyses revealed that nearly all homotypic mappings of MAYSI-2 scales onto (cluster of) psychiatric disorders revealed above chance level accuracy. The

DEFINED CONTRIBUTION PLANS, DEFINED BENEFIT PLANS, AND THE ACCUMULATION OF RETIREMENT WEALTH

PubMed Central

Poterba, James; Rauh, Joshua; Venti, Steven; Wise, David

2010-01-01

The private pension structure in the United States, once dominated by defined benefit (DB) plans, is currently divided between defined contribution (DC) and DB plans. Wealth accumulation in DC plans depends on the participant's contribution behavior and on financial market returns, while accumulation in DB plans is sensitive to a participant's labor market experience and to plan parameters. This paper simulates the distribution of retirement wealth under representative DB and DC plans. It uses data from the Health and Retirement Study (HRS) to explore how asset returns, earnings histories, and retirement plan characteristics contribute to the variation in retirement wealth outcomes. We simulate DC plan accumulation by randomly assigning individuals a share of wages that they and their employer contribute to the plan. We consider several possible asset allocation strategies, with asset returns drawn from the historical return distribution. Our DB plan simulations draw earnings histories from the HRS, and randomly assign each individual a pension plan drawn from a sample of large private and public defined benefit plans. The simulations yield distributions of both DC and DB wealth at retirement. Average retirement wealth accruals under current DC plans exceed average accruals under private sector DB plans, although DC plans are also more likely to generate very low retirement wealth outcomes. The comparison of current DC plans with more generous public sector DB plans is less definitive, because public sector DB plans are more generous on average than their private sector counterparts. PMID:21057597

A comparative study on stress and compliance based structural topology optimization

NASA Astrophysics Data System (ADS)

Hailu Shimels, G.; Dereje Engida, W.; Fakhruldin Mohd, H.

2017-10-01

Most of structural topology optimization problems have been formulated and solved to either minimize compliance or weight of a structure under volume or stress constraints, respectively. Even if, a lot of researches are conducted on these two formulation techniques separately, there is no clear comparative study between the two approaches. This paper intends to compare these formulation techniques, so that an end user or designer can choose the best one based on the problems they have. Benchmark problems under the same boundary and loading conditions are defined, solved and results are compared based on these formulations. Simulation results shows that the two formulation techniques are dependent on the type of loading and boundary conditions defined. Maximum stress induced in the design domain is higher when the design domains are formulated using compliance based formulations. Optimal layouts from compliance minimization formulation has complex layout than stress based ones which may lead the manufacturing of the optimal layouts to be challenging. Optimal layouts from compliance based formulations are dependent on the material to be distributed. On the other hand, optimal layouts from stress based formulation are dependent on the type of material used to define the design domain. High computational time for stress based topology optimization is still a challenge because of the definition of stress constraints at element level. Results also shows that adjustment of convergence criterions can be an alternative solution to minimize the maximum stress developed in optimal layouts. Therefore, a designer or end user should choose a method of formulation based on the design domain defined and boundary conditions considered.

Immunosuppressant therapeutic drug monitoring by LC-MS/MS: workflow optimization through automated processing of whole blood samples.

PubMed

Marinova, Mariela; Artusi, Carlo; Brugnolo, Laura; Antonelli, Giorgia; Zaninotto, Martina; Plebani, Mario

2013-11-01

Although, due to its high specificity and sensitivity, LC-MS/MS is an efficient technique for the routine determination of immunosuppressants in whole blood, it involves time-consuming manual sample preparation. The aim of the present study was therefore to develop an automated sample-preparation protocol for the quantification of sirolimus, everolimus and tacrolimus by LC-MS/MS using a liquid handling platform. Six-level commercially available blood calibrators were used for assay development, while four quality control materials and three blood samples from patients under immunosuppressant treatment were employed for the evaluation of imprecision. Barcode reading, sample re-suspension, transfer of whole blood samples into 96-well plates, addition of internal standard solution, mixing, and protein precipitation were performed with a liquid handling platform. After plate filtration, the deproteinised supernatants were submitted for SPE on-line. The only manual steps in the entire process were de-capping of the tubes, and transfer of the well plates to the HPLC autosampler. Calibration curves were linear throughout the selected ranges. The imprecision and accuracy data for all analytes were highly satisfactory. The agreement between the results obtained with manual and those obtained with automated sample preparation was optimal (n=390, r=0.96). In daily routine (100 patient samples) the typical overall total turnaround time was less than 6h. Our findings indicate that the proposed analytical system is suitable for routine analysis, since it is straightforward and precise. Furthermore, it incurs less manual workload and less risk of error in the quantification of whole blood immunosuppressant concentrations than conventional methods. © 2013.

Optimization of polymerase chain reaction for detection of Clostridium botulinum type C and D in bovine samples.

PubMed

Prévot, V; Tweepenninckx, F; Van Nerom, E; Linden, A; Content, J; Kimpe, A

2007-01-01

Botulism is a rare but serious paralytic illness caused by a nerve toxin that is produced by the bacterium Clostridium botulinum. The economic, medical and alimentary consequences can be catastrophic in case of an epizooty. A polymerase chain reaction (PCR)-based assay was developed for the detection of C. botulinum toxigenic strains type C and D in bovine samples. This assay has proved to be less expensive, faster and simpler to use than the mouse bioassay, the current reference method for diagnosis of C. botulinum toxigenic strains. Three pairs of primers were designed, one for global detection of C. botulinum types C and D (primer pair Y), and two strain-specific pairs specifically designed for types C (primer pair VC) and D (primer pair VD). The PCR amplification conditions were optimized and evaluated on 13 bovine and two duck samples that had been previously tested by the mouse bioassay. In order to assess the impact of sample treatment, both DNA extracted from crude samples and three different enrichment broths (TYG, CMM, CMM followed by TYG) were tested. A 100% sensitivity was observed when samples were enriched for 5 days in CMM followed by 1 day in TYG broth. False-negative results were encountered when C. botulinum was screened for in crude samples. These findings indicate that the current PCR is a reliable method for the detection of C. botulinum toxigenic strains type C and D in bovine samples but only after proper enrichment in CMM and TYG broth.

DNASynth: a software application to optimization of artificial gene synthesis

NASA Astrophysics Data System (ADS)

Muczyński, Jan; Nowak, Robert M.

2017-08-01

DNASynth is a client-server software application in which the client runs in a web browser. The aim of this program is to support and optimize process of artificial gene synthesizing using Ligase Chain Reaction. Thanks to LCR it is possible to obtain DNA strand coding defined by user peptide. The DNA sequence is calculated by optimization algorithm that consider optimal codon usage, minimal energy of secondary structures and minimal number of required LCR. Additionally absence of sequences characteristic for defined by user set of restriction enzymes is guaranteed. The presented software was tested on synthetic and real data.

Application of an Optimal Search Strategy for the DNAPL Source Identification to a Field Site in Nanjing, China

NASA Astrophysics Data System (ADS)

Longting, M.; Ye, S.; Wu, J.

2014-12-01

Identification and removing the DNAPL source in aquifer system is vital in rendering remediation successful and lowering the remediation time and cost. Our work is to apply an optimal search strategy introduced by Zoi and Pinder[1], with some modifications, to a field site in Nanjing City, China to define the strength, and location of DNAPL sources using the least samples. The overall strategy uses Monte Carlo stochastic groundwater flow and transport modeling, incorporates existing sampling data into the search strategy, and determines optimal sampling locations that are selected according to the reduction in overall uncertainty of the field and the proximity to the source locations. After a sample is taken, the plume is updated using a Kalman filter. The updated plume is then compared to the concentration fields that emanate from each individual potential source using fuzzy set technique. The comparison followed provides weights that reflect the degree of truth regarding the location of the source. The above steps are repeated until the optimal source characteristics are determined. Considering our site case, some specific modifications and work have been done as follows. K random fields are generated after fitting the measurement K data to the variogram model. The locations of potential sources that are given initial weights are targeted based on the field survey, with multiple potential source locations around the workshops and wastewater basin. Considering the short history (1999-2010) of manufacturing optical brightener PF at the site, and the existing sampling data, a preliminary source strength is then estimated, which will be optimized by simplex method or GA later. The whole algorithm then will guide us for optimal sampling and update as the investigation proceeds, until the weights finally stabilized. Reference [1] Dokou Zoi, and George F. Pinder. "Optimal search strategy for the definition of a DNAPL source." Journal of Hydrology 376.3 (2009): 542

Optimizing the models for rapid determination of chlorogenic acid, scopoletin and rutin in plant samples by near-infrared diffuse reflectance spectroscopy

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.

An optimal sample data usage strategy to minimize overfitting and underfitting effects in regression tree models based on remotely-sensed data

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.; Boyte, Stephen; Picotte, Joshua J.; Howard, Danny; Smith, Kelcy; Nelson, Kurtis

2016-01-01

Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any dataset and identify an appropriate number of rules in the regression tree model that will improve its accuracy and robustness. Landsat 8 data and Moderate-Resolution Imaging Spectroradiometer-scaled Normalized Difference Vegetation Index (NDVI) were used to develop regression tree models. A Python procedure was designed to generate random replications of model parameter options across a range of model development data sizes and rule number constraints. The mean absolute difference (MAD) between the predicted and actual NDVI (scaled NDVI, value from 0–200) and its variability across the different randomized replications were calculated to assess the accuracy and stability of the models. In our case study, a six-rule regression tree model developed from 80% of the sample data had the lowest MAD (MADtraining = 2.5 and MADtesting = 2.4), which was suggested as the optimal model. This study demonstrates how the training data and rule number selections impact model accuracy and provides important guidance for future remote-sensing-based ecosystem modeling.

7 CFR 90.2 - General terms defined.

Code of Federal Regulations, 2011 CFR

2011-01-01

... agency, or other agency, organization or person that defines in the general terms the basis on which the... analytical data using proficiency check sample or analyte recovery techniques. In addition, the certainty.... Quality control. The system of close examination of the critical details of an analytical procedure in...

Defined PEG smears as an alternative approach to enhance the search for crystallization conditions and crystal-quality improvement in reduced screens

PubMed Central

Chaikuad, Apirat; Knapp, Stefan; von Delft, Frank

2015-01-01

The quest for an optimal limited set of effective crystallization conditions remains a challenge in macromolecular crystallography, an issue that is complicated by the large number of chemicals which have been deemed to be suitable for promoting crystal growth. The lack of rational approaches towards the selection of successful chemical space and representative combinations has led to significant overlapping conditions, which are currently present in a multitude of commercially available crystallization screens. Here, an alternative approach to the sampling of widely used PEG precipitants is suggested through the use of PEG smears, which are mixtures of different PEGs with a requirement of either neutral or cooperatively positive effects of each component on crystal growth. Four newly defined smears were classified by molecular-weight groups and enabled the preservation of specific properties related to different polymer sizes. These smears not only allowed a wide coverage of properties of these polymers, but also reduced PEG variables, enabling greater sampling of other parameters such as buffers and additives. The efficiency of the smear-based screens was evaluated on more than 220 diverse recombinant human proteins, which overall revealed a good initial crystallization success rate of nearly 50%. In addition, in several cases successful crystallizations were only obtained using PEG smears, while various commercial screens failed to yield crystals. The defined smears therefore offer an alternative approach towards PEG sampling, which will benefit the design of crystallization screens sampling a wide chemical space of this key precipitant. PMID:26249344

Defined PEG smears as an alternative approach to enhance the search for crystallization conditions and crystal-quality improvement in reduced screens.

PubMed

Chaikuad, Apirat; Knapp, Stefan; von Delft, Frank

2015-08-01

The quest for an optimal limited set of effective crystallization conditions remains a challenge in macromolecular crystallography, an issue that is complicated by the large number of chemicals which have been deemed to be suitable for promoting crystal growth. The lack of rational approaches towards the selection of successful chemical space and representative combinations has led to significant overlapping conditions, which are currently present in a multitude of commercially available crystallization screens. Here, an alternative approach to the sampling of widely used PEG precipitants is suggested through the use of PEG smears, which are mixtures of different PEGs with a requirement of either neutral or cooperatively positive effects of each component on crystal growth. Four newly defined smears were classified by molecular-weight groups and enabled the preservation of specific properties related to different polymer sizes. These smears not only allowed a wide coverage of properties of these polymers, but also reduced PEG variables, enabling greater sampling of other parameters such as buffers and additives. The efficiency of the smear-based screens was evaluated on more than 220 diverse recombinant human proteins, which overall revealed a good initial crystallization success rate of nearly 50%. In addition, in several cases successful crystallizations were only obtained using PEG smears, while various commercial screens failed to yield crystals. The defined smears therefore offer an alternative approach towards PEG sampling, which will benefit the design of crystallization screens sampling a wide chemical space of this key precipitant.

Optimal resource states for local state discrimination

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Somshubhro; Halder, Saronath; Nathanson, Michael

2018-02-01

We study the problem of locally distinguishing pure quantum states using shared entanglement as a resource. For a given set of locally indistinguishable states, we define a resource state to be useful if it can enhance local distinguishability and optimal if it can distinguish the states as well as global measurements and is also minimal with respect to a partial ordering defined by entanglement and dimension. We present examples of useful resources and show that an entangled state need not be useful for distinguishing a given set of states. We obtain optimal resources with explicit local protocols to distinguish multipartite Greenberger-Horne-Zeilinger and graph states and also show that a maximally entangled state is an optimal resource under one-way local operations and classical communication to distinguish any bipartite orthonormal basis which contains at least one entangled state of full Schmidt rank.

Regularizing portfolio optimization

NASA Astrophysics Data System (ADS)

Still, Susanne; Kondor, Imre

2010-07-01

The optimization of large portfolios displays an inherent instability due to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting, which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification 'pressure'. This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade off between the two, depending on the size of the available dataset.

Automatic Aircraft Structural Topology Generation for Multidisciplinary Optimization and Weight Estimation

NASA Technical Reports Server (NTRS)

Sensmeier, Mark D.; Samareh, Jamshid A.

2005-01-01

An approach is proposed for the application of rapid generation of moderate-fidelity structural finite element models of air vehicle structures to allow more accurate weight estimation earlier in the vehicle design process. This should help to rapidly assess many structural layouts before the start of the preliminary design phase and eliminate weight penalties imposed when actual structure weights exceed those estimated during conceptual design. By defining the structural topology in a fully parametric manner, the structure can be mapped to arbitrary vehicle configurations being considered during conceptual design optimization. A demonstration of this process is shown for two sample aircraft wing designs.

Actinobacteria consortium as an efficient biotechnological tool for mixed polluted soil reclamation: Experimental factorial design for bioremediation process optimization.

PubMed

Aparicio, Juan Daniel; Raimondo, Enzo Emanuel; Gil, Raúl Andrés; Benimeli, Claudia Susana; Polti, Marta Alejandra

2018-01-15

The objective of the present work was to establish optimal biological and physicochemical parameters in order to remove simultaneously lindane and Cr(VI) at high and/or low pollutants concentrations from the soil by an actinobacteria consortium formed by Streptomyces sp. M7, MC1, A5, and Amycolatopsis tucumanensis AB0. Also, the final aim was to treat real soils contaminated with Cr(VI) and/or lindane from the Northwest of Argentina employing the optimal biological and physicochemical conditions. In this sense, after determining the optimal inoculum concentration (2gkg -1 ), an experimental design model with four factors (temperature, moisture, initial concentration of Cr(VI) and lindane) was employed for predicting the system behavior during bioremediation process. According to response optimizer, the optimal moisture level was 30% for all bioremediation processes. However, the optimal temperature was different for each situation: for low initial concentrations of both pollutants, the optimal temperature was 25°C; for low initial concentrations of Cr(VI) and high initial concentrations of lindane, the optimal temperature was 30°C; and for high initial concentrations of Cr(VI), the optimal temperature was 35°C. In order to confirm the model adequacy and the validity of the optimization procedure, experiments were performed in six real contaminated soils samples. The defined actinobacteria consortium reduced the contaminants concentrations in five of the six samples, by working at laboratory scale and employing the optimal conditions obtained through the factorial design. Copyright © 2017 Elsevier B.V. All rights reserved.

Lie theory and control systems defined on spheres

NASA Technical Reports Server (NTRS)

Brockett, R. W.

1972-01-01

It is shown that in constructing a theory for the most elementary class of control problems defined on spheres, some results from the Lie theory play a natural role. To understand controllability, optimal control, and certain properties of stochastic equations, Lie theoretic ideas are needed. The framework considered here is the most natural departure from the usual linear system/vector space problems which have dominated control systems literature. For this reason results are compared with those previously available for the finite dimensional vector space case.

Exact and Optimal Quantum Mechanics/Molecular Mechanics Boundaries.

PubMed

Sun, Qiming; Chan, Garnet Kin-Lic

2014-09-09

Motivated by recent work in density matrix embedding theory, we define exact link orbitals that capture all quantum mechanical (QM) effects across arbitrary quantum mechanics/molecular mechanics (QM/MM) boundaries. Exact link orbitals are rigorously defined from the full QM solution, and their number is equal to the number of orbitals in the primary QM region. Truncating the exact set yields a smaller set of link orbitals optimal with respect to reproducing the primary region density matrix. We use the optimal link orbitals to obtain insight into the limits of QM/MM boundary treatments. We further analyze the popular general hybrid orbital (GHO) QM/MM boundary across a test suite of molecules. We find that GHOs are often good proxies for the most important optimal link orbital, although there is little detailed correlation between the detailed GHO composition and optimal link orbital valence weights. The optimal theory shows that anions and cations cannot be described by a single link orbital. However, expanding to include the second most important optimal link orbital in the boundary recovers an accurate description. The second optimal link orbital takes the chemically intuitive form of a donor or acceptor orbital for charge redistribution, suggesting that optimal link orbitals can be used as interpretative tools for electron transfer. We further find that two optimal link orbitals are also sufficient for boundaries that cut across double bonds. Finally, we suggest how to construct "approximately" optimal link orbitals for practical QM/MM calculations.

Least squares polynomial chaos expansion: A review of sampling strategies

NASA Astrophysics Data System (ADS)

Hadigol, Mohammad; Doostan, Alireza

2018-04-01

As non-institutive polynomial chaos expansion (PCE) techniques have gained growing popularity among researchers, we here provide a comprehensive review of major sampling strategies for the least squares based PCE. Traditional sampling methods, such as Monte Carlo, Latin hypercube, quasi-Monte Carlo, optimal design of experiments (ODE), Gaussian quadratures, as well as more recent techniques, such as coherence-optimal and randomized quadratures are discussed. We also propose a hybrid sampling method, dubbed alphabetic-coherence-optimal, that employs the so-called alphabetic optimality criteria used in the context of ODE in conjunction with coherence-optimal samples. A comparison between the empirical performance of the selected sampling methods applied to three numerical examples, including high-order PCE's, high-dimensional problems, and low oversampling ratios, is presented to provide a road map for practitioners seeking the most suitable sampling technique for a problem at hand. We observed that the alphabetic-coherence-optimal technique outperforms other sampling methods, specially when high-order ODE are employed and/or the oversampling ratio is low.

Optimization of the monitoring of landfill gas and leachate in closed methanogenic landfills.

PubMed

Jovanov, Dejan; Vujić, Bogdana; Vujić, Goran

2018-06-15

Monitoring of the gas and leachate parameters in a closed landfill is a long-term activity defined by national legislative worldwide. Serbian Waste Disposal Law defines the monitoring of a landfill at least 30 years after its closing, but the definition of the monitoring extent (number and type of parameters) is incomplete. In order to define and clear all the uncertainties, this research focuses on process of monitoring optimization, using the closed landfill in Zrenjanin, Serbia, as the experimental model. The aim of optimization was to find representative parameters which would define the physical, chemical and biological processes in the closed methanogenic landfill and to make this process less expensive. Research included development of the five monitoring models with different number of gas and leachate parameters and each model has been processed in open source software GeoGebra which is often used for solving optimization problems. The results of optimization process identified the most favorable monitoring model which fulfills all the defined criteria not only from the point of view of mathematical analyses, but also from the point of view of environment protection. The final outcome of this research - the minimal required parameters which should be included in the landfill monitoring are precisely defined. Copyright © 2017 Elsevier Ltd. All rights reserved.

Defining clogging potential for permeable concrete.

PubMed

Kia, Alalea; Wong, Hong S; Cheeseman, Christopher R

2018-08-15

Permeable concrete is used to reduce urban flooding as it allows water to flow through normally impermeable infrastructure. It is prone to clogging by particulate matter and predicting the long-term performance of permeable concrete is challenging as there is currently no reliable means of characterising clogging potential. This paper reports on the performance of a range of laboratory-prepared and commercial permeable concretes, close packed glass spheres and aggregate particles of varying size, exposed to different clogging methods to understand this phenomena. New methods were developed to study clogging and define clogging potential. The tests involved applying flowing water containing sand and/or clay in cycles, and measuring the change in permeability. Substantial permeability reductions were observed in all samples, particularly when exposed to sand and clay simultaneously. Three methods were used to define clogging potential based on measuring the initial permeability decay, half-life cycle and number of cycles to full clogging. We show for the first time strong linear correlations between these parameters for a wide range of samples, indicating their use for service-life prediction. Copyright © 2018 Elsevier Ltd. All rights reserved.

Generating moment matching scenarios using optimization techniques

DOE PAGES

Mehrotra, Sanjay; Papp, Dávid

2013-05-16

An optimization based method is proposed to generate moment matching scenarios for numerical integration and its use in stochastic programming. The main advantage of the method is its flexibility: it can generate scenarios matching any prescribed set of moments of the underlying distribution rather than matching all moments up to a certain order, and the distribution can be defined over an arbitrary set. This allows for a reduction in the number of scenarios and allows the scenarios to be better tailored to the problem at hand. The method is based on a semi-infinite linear programming formulation of the problem thatmore » is shown to be solvable with polynomial iteration complexity. A practical column generation method is implemented. The column generation subproblems are polynomial optimization problems; however, they need not be solved to optimality. It is found that the columns in the column generation approach can be efficiently generated by random sampling. The number of scenarios generated matches a lower bound of Tchakaloff's. The rate of convergence of the approximation error is established for continuous integrands, and an improved bound is given for smooth integrands. Extensive numerical experiments are presented in which variants of the proposed method are compared to Monte Carlo and quasi-Monte Carlo methods on both numerical integration problems and stochastic optimization problems. The benefits of being able to match any prescribed set of moments, rather than all moments up to a certain order, is also demonstrated using optimization problems with 100-dimensional random vectors. Here, empirical results show that the proposed approach outperforms Monte Carlo and quasi-Monte Carlo based approaches on the tested problems.« less

Depth-discrete sampling port

DOEpatents

Pemberton, Bradley E [Aiken, SC; May, Christopher P [Columbia, MD; Rossabi, Joseph [Aiken, SC; Riha, Brian D [Augusta, GA; Nichols, Ralph L [North Augusta, SC

1998-07-07

A sampling port is provided which has threaded ends for incorporating the port into a length of subsurface pipe. The port defines an internal receptacle which is in communication with subsurface fluids through a series of fine filtering slits. The receptacle is in further communication through a bore with a fitting carrying a length of tubing there which samples are transported to the surface. Each port further defines an additional bore through which tubing, cables, or similar components of adjacent ports may pass.

Depth-discrete sampling port

DOEpatents

Pemberton, Bradley E.; May, Christopher P.; Rossabi, Joseph; Riha, Brian D.; Nichols, Ralph L.

1999-01-01

A sampling port is provided which has threaded ends for incorporating the port into a length of subsurface pipe. The port defines an internal receptacle which is in communication with subsurface fluids through a series of fine filtering slits. The receptacle is in further communication through a bore with a fitting carrying a length of tubing there which samples are transported to the surface. Each port further defines an additional bore through which tubing, cables, or similar components of adjacent ports may pass.

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

Finding optimal inputs for a multiple-input, single-output system is taxing for a system operator. Population-based optimization is used to create sets of functions that produce a locally optimal input based on a desired output. An operator or higher level planner could use one of the functions in real time. For the optimization, each agent in the population uses the cost and output gradients to take steps lowering the cost while maintaining their current output. When an agent reaches an optimal input for its current output, additional agents are generated in the output gradient directions. The new agents then settle to the local optima for the new output values. The set of associated optimal points forms an inverse function, via spline interpolation, from a desired output to an optimal input. In this manner, multiple locally optimal functions can be created. These functions are naturally clustered in input and output spaces allowing for a continuous inverse function. The operator selects the best cluster over the anticipated range of desired outputs and adjusts the set point (desired output) while maintaining optimality. This reduces the demand from controlling multiple inputs, to controlling a single set point with no loss in performance. Results are demonstrated on a sample set of functions and on a robot control problem.

Matrix-assisted laser desorption/ionization sample preparation optimization for structural characterization of poly(styrene-co-pentafluorostyrene) copolymers.

PubMed

Tisdale, Evgenia; Kennedy, Devin; Xu, Xiaodong; Wilkins, Charles

2014-01-15

The influence of the sample preparation parameters (the choice of the matrix, matrix:analyte ratio, salt:analyte ratio) was investigated and optimal conditions were established for the MALDI time-of-flight mass spectrometry analysis of the poly(styrene-co-pentafluorostyrene) copolymers. These were synthesized by atom transfer radical polymerization. Use of 2,5-dihydroxybenzoic acid as matrix resulted in spectra with consistently high ion yields for all matrix:analyte:salt ratios tested. The optimized MALDI procedure was successfully applied to the characterization of three copolymers obtained by varying the conditions of polymerization reaction. It was possible to establish the nature of the end groups, calculate molecular weight distributions, and determine the individual length distributions for styrene and pentafluorostyrene monomers, contained in the resulting copolymers. Based on the data obtained, it was concluded that individual styrene chain length distributions are more sensitive to the change in the composition of the catalyst (the addition of small amount of CuBr2) than is the pentafluorostyrene component distribution. Copyright © 2013 Elsevier B.V. All rights reserved.

Gear optimization

NASA Technical Reports Server (NTRS)

Vanderplaats, G. N.; Chen, Xiang; Zhang, Ning-Tian

1988-01-01

The use of formal numerical optimization methods for the design of gears is investigated. To achieve this, computer codes were developed for the analysis of spur gears and spiral bevel gears. These codes calculate the life, dynamic load, bending strength, surface durability, gear weight and size, and various geometric parameters. It is necessary to calculate all such important responses because they all represent competing requirements in the design process. The codes developed here were written in subroutine form and coupled to the COPES/ADS general purpose optimization program. This code allows the user to define the optimization problem at the time of program execution. Typical design variables include face width, number of teeth and diametral pitch. The user is free to choose any calculated response as the design objective to minimize or maximize and may impose lower and upper bounds on any calculated responses. Typical examples include life maximization with limits on dynamic load, stress, weight, etc. or minimization of weight subject to limits on life, dynamic load, etc. The research codes were written in modular form for easy expansion and so that they could be combined to create a multiple reduction optimization capability in future.

Design and Sampling Plan Optimization for RT-qPCR Experiments in Plants: A Case Study in Blueberry.

PubMed

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.

A Higher Harmonic Optimal Controller to Optimise Rotorcraft Aeromechanical Behaviour

NASA Technical Reports Server (NTRS)

Leyland, Jane Anne

1996-01-01

Three methods to optimize rotorcraft aeromechanical behavior for those cases where the rotorcraft plant can be adequately represented by a linear model system matrix were identified and implemented in a stand-alone code. These methods determine the optimal control vector which minimizes the vibration metric subject to constraints at discrete time points, and differ from the commonly used non-optimal constraint penalty methods such as those employed by conventional controllers in that the constraints are handled as actual constraints to an optimization problem rather than as just additional terms in the performance index. The first method is to use a Non-linear Programming algorithm to solve the problem directly. The second method is to solve the full set of non-linear equations which define the necessary conditions for optimality. The third method is to solve each of the possible reduced sets of equations defining the necessary conditions for optimality when the constraints are pre-selected to be either active or inactive, and then to simply select the best solution. The effects of maneuvers and aeroelasticity on the systems matrix are modelled by using a pseudo-random pseudo-row-dependency scheme to define the systems matrix. Cases run to date indicate that the first method of solution is reliable, robust, and easiest to use, and that it was superior to the conventional controllers which were considered.

Chance-Constrained AC Optimal Power Flow: Reformulations and Efficient Algorithms

DOE PAGES

Roald, Line Alnaes; Andersson, Goran

2017-08-29

Higher levels of renewable electricity generation increase uncertainty in power system operation. To ensure secure system operation, new tools that account for this uncertainty are required. Here, in this paper, we adopt a chance-constrained AC optimal power flow formulation, which guarantees that generation, power flows and voltages remain within their bounds with a pre-defined probability. We then discuss different chance-constraint reformulations and solution approaches for the problem. Additionally, we first discuss an analytical reformulation based on partial linearization, which enables us to obtain a tractable representation of the optimization problem. We then provide an efficient algorithm based on an iterativemore » solution scheme which alternates between solving a deterministic AC OPF problem and assessing the impact of uncertainty. This more flexible computational framework enables not only scalable implementations, but also alternative chance-constraint reformulations. In particular, we suggest two sample based reformulations that do not require any approximation or relaxation of the AC power flow equations.« less

A mesh gradient technique for numerical optimization

NASA Technical Reports Server (NTRS)

Willis, E. A., Jr.

1973-01-01

A class of successive-improvement optimization methods in which directions of descent are defined in the state space along each trial trajectory are considered. The given problem is first decomposed into two discrete levels by imposing mesh points. Level 1 consists of running optimal subarcs between each successive pair of mesh points. For normal systems, these optimal two-point boundary value problems can be solved by following a routine prescription if the mesh spacing is sufficiently close. A spacing criterion is given. Under appropriate conditions, the criterion value depends only on the coordinates of the mesh points, and its gradient with respect to those coordinates may be defined by interpreting the adjoint variables as partial derivatives of the criterion value function. In level 2, the gradient data is used to generate improvement steps or search directions in the state space which satisfy the boundary values and constraints of the given problem.

Constrained Optimal Transport

NASA Astrophysics Data System (ADS)

Ekren, Ibrahim; Soner, H. Mete

2018-03-01

The classical duality theory of Kantorovich (C R (Doklady) Acad Sci URSS (NS) 37:199-201, 1942) and Kellerer (Z Wahrsch Verw Gebiete 67(4):399-432, 1984) for classical optimal transport is generalized to an abstract framework and a characterization of the dual elements is provided. This abstract generalization is set in a Banach lattice X with an order unit. The problem is given as the supremum over a convex subset of the positive unit sphere of the topological dual of X and the dual problem is defined on the bi-dual of X. These results are then applied to several extensions of the classical optimal transport.

Optimized method for atmospheric signal reduction in irregular sampled InSAR time series assisted by external atmospheric information

NASA Astrophysics Data System (ADS)

Gong, W.; Meyer, F. J.

2013-12-01

It is well known that spatio-temporal the tropospheric phase signatures complicate the interpretation and detection of smaller magnitude deformation signals or unstudied motion fields. Several advanced time-series InSAR techniques were developed in the last decade that make assumptions about the stochastic properties of the signal components in interferometric phases to reduce atmospheric delay effects on surface deformation estimates. However, their need for large datasets to successfully separate the different phase contributions limits their performance if data is scarce and irregularly sampled. Limited SAR data coverage is true for many areas affected by geophysical deformation. This is either due to their low priority in mission programming, unfavorable ground coverage condition, or turbulent seasonal weather effects. In this paper, we present new adaptive atmospheric phase filtering algorithms that are specifically designed to reconstruct surface deformation signals from atmosphere-affected and irregularly sampled InSAR time series. The filters take advantage of auxiliary atmospheric delay information that is extracted from various sources, e.g. atmospheric weather models. They are embedded into a model-free Persistent Scatterer Interferometry (PSI) approach that was selected to accommodate non-linear deformation patterns that are often observed near volcanoes and earthquake zones. Two types of adaptive phase filters were developed that operate in the time dimension and separate atmosphere from deformation based on their different temporal correlation properties. Both filter types use the fact that atmospheric models can reliably predict the spatial statistics and signal power of atmospheric phase delay fields in order to automatically optimize the filter's shape parameters. In essence, both filter types will attempt to maximize the linear correlation between a-priori and the extracted atmospheric phase information. Topography-related phase components, orbit

Sample Training Based Wildfire Segmentation by 2D Histogram θ-Division with Minimum Error

PubMed Central

Dong, Erqian; Sun, Mingui; Jia, Wenyan; Zhang, Dengyi; Yuan, Zhiyong

2013-01-01

A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. Based on minimum error principle and 2D color histogram, the θ-division methods were presented recently, but application of prior knowledge on them has not been explored. For the specific problem of wildfire segmentation, we collect sample images with manually labeled fire pixels. Then we define the probability function of error division to evaluate θ-division segmentations, and the optimal angle θ is determined by sample training. Performances in different color channels are compared, and the suitable channel is selected. To further improve the accuracy, the combination approach is presented with both θ-division and other segmentation methods such as GMM. Our approach is tested on real images, and the experiments prove its efficiency for wildfire segmentation. PMID:23878526

Optimization of the intravenous glucose tolerance test in T2DM patients using optimal experimental design.

PubMed

Silber, Hanna E; Nyberg, Joakim; Hooker, Andrew C; Karlsson, Mats O

2009-06-01

Intravenous glucose tolerance test (IVGTT) provocations are informative, but complex and laborious, for studying the glucose-insulin system. The objective of this study was to evaluate, through optimal design methodology, the possibilities of more informative and/or less laborious study design of the insulin modified IVGTT in type 2 diabetic patients. A previously developed model for glucose and insulin regulation was implemented in the optimal design software PopED 2.0. The following aspects of the study design of the insulin modified IVGTT were evaluated; (1) glucose dose, (2) insulin infusion, (3) combination of (1) and (2), (4) sampling times, (5) exclusion of labeled glucose. Constraints were incorporated to avoid prolonged hyper- and/or hypoglycemia and a reduced design was used to decrease run times. Design efficiency was calculated as a measure of the improvement with an optimal design compared to the basic design. The results showed that the design of the insulin modified IVGTT could be substantially improved by the use of an optimized design compared to the standard design and that it was possible to use a reduced number of samples. Optimization of sample times gave the largest improvement followed by insulin dose. The results further showed that it was possible to reduce the total sample time with only a minor loss in efficiency. Simulations confirmed the predictions from PopED. The predicted uncertainty of parameter estimates (CV) was low in all tested cases, despite the reduction in the number of samples/subject. The best design had a predicted average CV of parameter estimates of 19.5%. We conclude that improvement can be made to the design of the insulin modified IVGTT and that the most important design factor was the placement of sample times followed by the use of an optimal insulin dose. This paper illustrates how complex provocation experiments can be improved by sequential modeling and optimal design.

Ant algorithms for discrete optimization.

PubMed

Dorigo, M; Di Caro, G; Gambardella, L M

1999-01-01

This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms to combinatorial optimization and routing in communications networks are described. We conclude with a discussion of related work and of some of the most important aspects of the ACO metaheuristic.

(Sample) Size Matters: Best Practices for Defining Error in Planktic Foraminiferal Proxy Records

NASA Astrophysics Data System (ADS)

Lowery, C.; Fraass, A. J.

2016-02-01

Paleoceanographic research is a vital tool to extend modern observational datasets and to study the impact of climate events for which there is no modern analog. Foraminifera are one of the most widely used tools for this type of work, both as paleoecological indicators and as carriers for geochemical proxies. However, the use of microfossils as proxies for paleoceanographic conditions brings about a unique set of problems. This is primarily due to the fact that groups of individual foraminifera, which usually live about a month, are used to infer average conditions for time periods ranging from hundreds to tens of thousands of years. Because of this, adequate sample size is very important for generating statistically robust datasets, particularly for stable isotopes. In the early days of stable isotope geochemistry, instrumental limitations required hundreds of individual foraminiferal tests to return a value. This had the fortunate side-effect of smoothing any seasonal to decadal changes within the planktic foram population. With the advent of more sensitive mass spectrometers, smaller sample sizes have now become standard. While this has many advantages, the use of smaller numbers of individuals to generate a data point has lessened the amount of time averaging in the isotopic analysis and decreased precision in paleoceanographic datasets. With fewer individuals per sample, the differences between individual specimens will result in larger variation, and therefore error, and less precise values for each sample. Unfortunately, most (the authors included) do not make a habit of reporting the error associated with their sample size. We have created an open-source model in R to quantify the effect of sample sizes under various realistic and highly modifiable parameters (calcification depth, diagenesis in a subset of the population, improper identification, vital effects, mass, etc.). For example, a sample in which only 1 in 10 specimens is diagenetically altered can

Modeling Optimal Cutoffs for the Brazilian Household Food Insecurity Measurement Scale in a Nationwide Representative Sample.

PubMed

Interlenghi, Gabriela S; Reichenheim, Michael E; Segall-Corrêa, Ana M; Pérez-Escamilla, Rafael; Moraes, Claudia L; Salles-Costa, Rosana

2017-07-01

Background: This is the second part of a model-based approach to examine the suitability of the current cutoffs applied to the raw score of the Brazilian Household Food Insecurity Measurement Scale [Escala Brasileira de Insegurança Alimentar (EBIA)]. The approach allows identification of homogeneous groups who correspond to severity levels of food insecurity (FI) and, by extension, discriminant cutoffs able to accurately distinguish these groups. Objective: This study aims to examine whether the model-based approach for identifying optimal cutoffs first implemented in a local sample is replicated in a countrywide representative sample. Methods: Data were derived from the Brazilian National Household Sample Survey of 2013 ( n = 116,543 households). Latent class factor analysis (LCFA) models from 2 to 5 classes were applied to the scale's items to identify the number of underlying FI latent classes. Next, identification of optimal cutoffs on the overall raw score was ascertained from these identified classes. Analyses were conducted in the aggregate data and by macroregions. Finally, model-based classifications (latent classes and groupings identified thereafter) were contrasted to the traditionally used classification. Results: LCFA identified 4 homogeneous groups with a very high degree of class separation (entropy = 0.934-0.975). The following cutoffs were identified in the aggregate data: between 1 and 2 (1/2), 5 and 6 (5/6), and 10 and 11 (10/11) in households with children and/or adolescents <18 y of age (score range: 0-14), and 1/2, between 4 and 5 (4/5), and between 6 and 7 (6/7) in adult-only households (range: 0-8). With minor variations, the same cutoffs were also identified in the macroregions. Although our findings confirm, in general, the classification currently used, the limit of 1/2 (compared with 0/1) for separating the milder from the baseline category emerged consistently in all analyses. Conclusions: Nationwide findings corroborate previous

First-pass myocardial perfusion MRI with reduced subendocardial dark-rim artifact using optimized Cartesian sampling.

PubMed

Zhou, Zhengwei; Bi, Xiaoming; Wei, Janet; Yang, Hsin-Jung; Dharmakumar, Rohan; Arsanjani, Reza; Bairey Merz, C Noel; Li, Debiao; Sharif, Behzad

2017-02-01

The presence of subendocardial dark-rim artifact (DRA) remains an ongoing challenge in first-pass perfusion (FPP) cardiac magnetic resonance imaging (MRI). We propose a free-breathing FPP imaging scheme with Cartesian sampling that is optimized to minimize the DRA and readily enables near-instantaneous image reconstruction. The proposed FPP method suppresses Gibbs ringing effects-a major underlying factor for the DRA-by "shaping" the underlying point spread function through a two-step process: 1) an undersampled Cartesian sampling scheme that widens the k-space coverage compared to the conventional scheme; and 2) a modified parallel-imaging scheme that incorporates optimized apodization (k-space data filtering) to suppress Gibbs-ringing effects. Healthy volunteer studies (n = 10) were performed to compare the proposed method against the conventional Cartesian technique-both using a saturation-recovery gradient-echo sequence at 3T. Furthermore, FPP imaging studies using the proposed method were performed in infarcted canines (n = 3), and in two symptomatic patients with suspected coronary microvascular dysfunction for assessment of myocardial hypoperfusion. Width of the DRA and the number of DRA-affected myocardial segments were significantly reduced in the proposed method compared to the conventional approach (width: 1.3 vs. 2.9 mm, P < 0.001; number of segments: 2.6 vs. 8.7; P < 0.0001). The number of slices with severe DRA was markedly lower for the proposed method (by 10-fold). The reader-assigned image quality scores were similar (P = 0.2), although the quantified myocardial signal-to-noise ratio was lower for the proposed method (P < 0.05). Animal studies showed that the proposed method can detect subendocardial perfusion defects and patient results were consistent with the gold-standard invasive test. The proposed free-breathing Cartesian FPP imaging method significantly reduces the prevalence of severe DRAs compared to the conventional approach

Elucidating the 16S rRNA 3' boundaries and defining optimal SD/aSD pairing in Escherichia coli and Bacillus subtilis using RNA-Seq data.

PubMed

Wei, Yulong; Silke, Jordan R; Xia, Xuhua

2017-12-15

Bacterial translation initiation is influenced by base pairing between the Shine-Dalgarno (SD) sequence in the 5' UTR of mRNA and the anti-SD (aSD) sequence at the free 3' end of the 16S rRNA (3' TAIL) due to: 1) the SD/aSD sequence binding location and 2) SD/aSD binding affinity. In order to understand what makes an SD/aSD interaction optimal, we must define: 1) terminus of the 3' TAIL and 2) extent of the core aSD sequence within the 3' TAIL. Our approach to characterize these components in Escherichia coli and Bacillus subtilis involves 1) mapping the 3' boundary of the mature 16S rRNA using high-throughput RNA sequencing (RNA-Seq), and 2) identifying the segment within the 3' TAIL that is strongly preferred in SD/aSD pairing. Using RNA-Seq data, we resolve previous discrepancies in the reported 3' TAIL in B. subtilis and recovered the established 3' TAIL in E. coli. Furthermore, we extend previous studies to suggest that both highly and lowly expressed genes favor SD sequences with intermediate binding affinity, but this trend is exclusive to SD sequences that complement the core aSD sequences defined herein.

Parameter optimization of a hydrologic model in a snow-dominated basin using a modular Python framework

NASA Astrophysics Data System (ADS)

Volk, J. M.; Turner, M. A.; Huntington, J. L.; Gardner, M.; Tyler, S.; Sheneman, L.

2016-12-01

Many distributed models that simulate watershed hydrologic processes require a collection of multi-dimensional parameters as input, some of which need to be calibrated before the model can be applied. The Precipitation Runoff Modeling System (PRMS) is a physically-based and spatially distributed hydrologic model that contains a considerable number of parameters that often need to be calibrated. Modelers can also benefit from uncertainty analysis of these parameters. To meet these needs, we developed a modular framework in Python to conduct PRMS parameter optimization, uncertainty analysis, interactive visual inspection of parameters and outputs, and other common modeling tasks. Here we present results for multi-step calibration of sensitive parameters controlling solar radiation, potential evapo-transpiration, and streamflow in a PRMS model that we applied to the snow-dominated Dry Creek watershed in Idaho. We also demonstrate how our modular approach enables the user to use a variety of parameter optimization and uncertainty methods or easily define their own, such as Monte Carlo random sampling, uniform sampling, or even optimization methods such as the downhill simplex method or its commonly used, more robust counterpart, shuffled complex evolution.

Antecedent and Consequence of School Academic Optimism and Teachers' Academic Optimism Model

ERIC Educational Resources Information Center

Hong, Fu-Yuan

2017-01-01

The main purpose of this research was to examine the relationships among school principals' transformational leadership, school academic optimism, teachers' academic optimism and teachers' professional commitment. This study conducted a questionnaire survey on 367 teachers from 20 high schools in Taiwan by random sampling, using principals'…

Experimental validation of structural optimization methods

NASA Technical Reports Server (NTRS)

Adelman, Howard M.

1992-01-01

The topic of validating structural optimization methods by use of experimental results is addressed. The need for validating the methods as a way of effecting a greater and an accelerated acceptance of formal optimization methods by practicing engineering designers is described. The range of validation strategies is defined which includes comparison of optimization results with more traditional design approaches, establishing the accuracy of analyses used, and finally experimental validation of the optimization results. Examples of the use of experimental results to validate optimization techniques are described. The examples include experimental validation of the following: optimum design of a trussed beam; combined control-structure design of a cable-supported beam simulating an actively controlled space structure; minimum weight design of a beam with frequency constraints; minimization of the vibration response of helicopter rotor blade; minimum weight design of a turbine blade disk; aeroelastic optimization of an aircraft vertical fin; airfoil shape optimization for drag minimization; optimization of the shape of a hole in a plate for stress minimization; optimization to minimize beam dynamic response; and structural optimization of a low vibration helicopter rotor.

An Optimal Estimation Method to Obtain Surface Layer Turbulent Fluxes from Profile Measurements

NASA Astrophysics Data System (ADS)

Kang, D.

2015-12-01

In the absence of direct turbulence measurements, the turbulence characteristics of the atmospheric surface layer are often derived from measurements of the surface layer mean properties based on Monin-Obukhov Similarity Theory (MOST). This approach requires two levels of the ensemble mean wind, temperature, and water vapor, from which the fluxes of momentum, sensible heat, and water vapor can be obtained. When only one measurement level is available, the roughness heights and the assumed properties of the corresponding variables at the respective roughness heights are used. In practice, the temporal mean with large number of samples are used in place of the ensemble mean. However, in many situations the samples of data are taken from multiple levels. It is thus desirable to derive the boundary layer flux properties using all measurements. In this study, we used an optimal estimation approach to derive surface layer properties based on all available measurements. This approach assumes that the samples are taken from a population whose ensemble mean profile follows the MOST. An optimized estimate is obtained when the results yield a minimum cost function defined as a weighted summation of all error variance at each sample altitude. The weights are based one sample data variance and the altitude of the measurements. This method was applied to measurements in the marine atmospheric surface layer from a small boat using radiosonde on a tethered balloon where temperature and relative humidity profiles in the lowest 50 m were made repeatedly in about 30 minutes. We will present the resultant fluxes and the derived MOST mean profiles using different sets of measurements. The advantage of this method over the 'traditional' methods will be illustrated. Some limitations of this optimization method will also be discussed. Its application to quantify the effects of marine surface layer environment on radar and communication signal propagation will be shown as well.

GEOTHERMAL EFFLUENT SAMPLING WORKSHOP

EPA Science Inventory

This report outlines the major recommendations resulting from a workshop to identify gaps in existing geothermal effluent sampling methodologies, define needed research to fill those gaps, and recommend strategies to lead to a standardized sampling methodology.

Improvements of the Vis-NIRS Model in the Prediction of Soil Organic Matter Content Using Spectral Pretreatments, Sample Selection, and Wavelength Optimization

NASA Astrophysics Data System (ADS)

Lin, Z. D.; Wang, Y. B.; Wang, R. J.; Wang, L. S.; Lu, C. P.; Zhang, Z. Y.; Song, L. T.; Liu, Y.

2017-07-01

A total of 130 topsoil samples collected from Guoyang County, Anhui Province, China, were used to establish a Vis-NIR model for the prediction of organic matter content (OMC) in lime concretion black soils. Different spectral pretreatments were applied for minimizing the irrelevant and useless information of the spectra and increasing the spectra correlation with the measured values. Subsequently, the Kennard-Stone (KS) method and sample set partitioning based on joint x-y distances (SPXY) were used to select the training set. Successive projection algorithm (SPA) and genetic algorithm (GA) were then applied for wavelength optimization. Finally, the principal component regression (PCR) model was constructed, in which the optimal number of principal components was determined using the leave-one-out cross validation technique. The results show that the combination of the Savitzky-Golay (SG) filter for smoothing and multiplicative scatter correction (MSC) can eliminate the effect of noise and baseline drift; the SPXY method is preferable to KS in the sample selection; both the SPA and the GA can significantly reduce the number of wavelength variables and favorably increase the accuracy, especially GA, which greatly improved the prediction accuracy of soil OMC with Rcc, RMSEP, and RPD up to 0.9316, 0.2142, and 2.3195, respectively.

A model of cloud application assignments in software-defined storages

NASA Astrophysics Data System (ADS)

Bolodurina, Irina P.; Parfenov, Denis I.; Polezhaev, Petr N.; E Shukhman, Alexander

2017-01-01

The aim of this study is to analyze the structure and mechanisms of interaction of typical cloud applications and to suggest the approaches to optimize their placement in storage systems. In this paper, we describe a generalized model of cloud applications including the three basic layers: a model of application, a model of service, and a model of resource. The distinctive feature of the model suggested implies analyzing cloud resources from the user point of view and from the point of view of a software-defined infrastructure of the virtual data center (DC). The innovation character of this model is in describing at the same time the application data placements, as well as the state of the virtual environment, taking into account the network topology. The model of software-defined storage has been developed as a submodel within the resource model. This model allows implementing the algorithm for control of cloud application assignments in software-defined storages. Experimental researches returned this algorithm decreases in cloud application response time and performance growth in user request processes. The use of software-defined data storages allows the decrease in the number of physical store devices, which demonstrates the efficiency of our algorithm.

Active SAmpling Protocol (ASAP) to Optimize Individual Neurocognitive Hypothesis Testing: A BCI-Inspired Dynamic Experimental Design.

PubMed

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.

Non-Contact Conductivity Measurement for Automated Sample Processing Systems

NASA Technical Reports Server (NTRS)

Beegle, Luther W.; Kirby, James P.

2012-01-01

A new method has been developed for monitoring and control of automated sample processing and preparation especially focusing on desalting of samples before analytical analysis (described in more detail in Automated Desalting Apparatus, (NPO-45428), NASA Tech Briefs, Vol. 34, No. 8 (August 2010), page 44). The use of non-contact conductivity probes, one at the inlet and one at the outlet of the solid phase sample preparation media, allows monitoring of the process, and acts as a trigger for the start of the next step in the sequence (see figure). At each step of the muti-step process, the system is flushed with low-conductivity water, which sets the system back to an overall low-conductivity state. This measurement then triggers the next stage of sample processing protocols, and greatly minimizes use of consumables. In the case of amino acid sample preparation for desalting, the conductivity measurement will define three key conditions for the sample preparation process. First, when the system is neutralized (low conductivity, by washing with excess de-ionized water); second, when the system is acidified, by washing with a strong acid (high conductivity); and third, when the system is at a basic condition of high pH (high conductivity). Taken together, this non-contact conductivity measurement for monitoring sample preparation will not only facilitate automation of the sample preparation and processing, but will also act as a way to optimize the operational time and use of consumables

Simulation and optimization of faceted structure for illumination

NASA Astrophysics Data System (ADS)

Liu, Lihong; Engel, Thierry; Flury, Manuel

2016-04-01

The re-direction of incoherent light using a surface containing only facets with specific angular values is proposed. A new photometric approach is adopted since the size of each facet is large in comparison with the wavelength. A reflective configuration is employed to avoid the dispersion problems of materials. The irradiance distribution of the reflected beam is determined by the angular position of each facet. In order to obtain the specific irradiance distribution, the angular position of each facet is optimized using Zemax OpticStudio 15 software. A detector is placed in the direction which is perpendicular to the reflected beam. According to the incoherent irradiance distribution on the detector, a merit function needs to be defined to pilot the optimization process. The two dimensional angular position of each facet is defined as a variable which is optimized within a specified varying range. Because the merit function needs to be updated, a macro program is carried out to update this function within Zemax. In order to reduce the complexity of the manual operation, an automatic optimization approach is established. Zemax is in charge of performing the optimization task and sending back the irradiance data to Matlab for further analysis. Several simulation results are given for the verification of the optimization method. The simulation results are compared to those obtained with the LightTools software in order to verify our optimization method.

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

GROUND WATER SAMPLING ISSUES

EPA Science Inventory

Obtaining representative ground water samples is important for site assessment and
remedial performance monitoring objectives. Issues which must be considered prior to initiating a ground-water monitoring program include defining monitoring goals and objectives, sampling point...

Optimal approaches for inline sampling of organisms in ballast water: L-shaped vs. Straight sample probes

NASA Astrophysics Data System (ADS)

Wier, Timothy P.; Moser, Cameron S.; Grant, Jonathan F.; Riley, Scott C.; Robbins-Wamsley, Stephanie H.; First, Matthew R.; Drake, Lisa A.

2017-10-01

Both L-shaped ("L") and straight ("Straight") sample probes have been used to collect water samples from a main ballast line in land-based or shipboard verification testing of ballast water management systems (BWMS). A series of experiments was conducted to quantify and compare the sampling efficiencies of L and Straight sample probes. The findings from this research-that both L and Straight probes sample organisms with similar efficiencies-permit increased flexibility for positioning sample probes aboard ships.

Visualizing the Sample Standard Deviation

ERIC Educational Resources Information Center

Sarkar, Jyotirmoy; Rashid, Mamunur

2017-01-01

The standard deviation (SD) of a random sample is defined as the square-root of the sample variance, which is the "mean" squared deviation of the sample observations from the sample mean. Here, we interpret the sample SD as the square-root of twice the mean square of all pairwise half deviations between any two sample observations. This…

Why sampling scheme matters: the effect of sampling scheme on landscape genetic results

Treesearch

Michael K. Schwartz; Kevin S. McKelvey

2008-01-01

There has been a recent trend in genetic studies of wild populations where researchers have changed their sampling schemes from sampling pre-defined populations to sampling individuals uniformly across landscapes. This reflects the fact that many species under study are continuously distributed rather than clumped into obvious "populations". Once individual...

Optimizing sample pretreatment for compound-specific stable carbon isotopic analysis of amino sugars in marine sediment

NASA Astrophysics Data System (ADS)

Zhu, R.; Lin, Y.-S.; Lipp, J. S.; Meador, T. B.; Hinrichs, K.-U.

2014-01-01

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. Our results obtained from δ13C analysis of amino sugars in selected marine sediment samples showed that muramic acid had isotopic imprints from indigenous bacterial activities, whereas glucosamine and galactosamine were mainly derived from organic detritus. The analysis of stable carbon isotopic compositions of amino sugars opens a promising window for the investigation of microbial metabolisms in marine sediments and the deep marine biosphere.

Method of optimization onboard communication network

NASA Astrophysics Data System (ADS)

Platoshin, G. A.; Selvesuk, N. I.; Semenov, M. E.; Novikov, V. M.

2018-02-01

In this article the optimization levels of onboard communication network (OCN) are proposed. We defined the basic parameters, which are necessary for the evaluation and comparison of modern OCN, we identified also a set of initial data for possible modeling of the OCN. We also proposed a mathematical technique for implementing the OCN optimization procedure. This technique is based on the principles and ideas of binary programming. It is shown that the binary programming technique allows to obtain an inherently optimal solution for the avionics tasks. An example of the proposed approach implementation to the problem of devices assignment in OCN is considered.

Self-defining memories related to alcohol dependence and their integration in the construction of the self in a sample of abstinent alcoholics.

PubMed

Martínez-Hernández, Nieves; Ricarte, Jorge

2018-06-26

Using a self-defining memory task, this work studies the exact moment in which abstinent alcoholics perceived themselves as addicted. Phenomenological variables involved in the memory were obtained asking participants to evaluate their cognitions, perceptions and emotions associated with that self-defining memory. The sample consisted of 12 female and 31 male ex-alcoholics, with abstinence ranging from 6 months to 23 years. Mean age was 52.91 years. Our findings showed that awareness of the alcoholic self emerges in the context of uncontrolled consumption or an ultimatum from family members. This type of memory had a positive valence for most of the participants, regardless of the memory perspective (actor versus spectator). Those who remembered from an actor perspective, perceived the event as providing higher growth and personal learning. These results show the importance of exploring situations of uncontrolled consumption and family dynamics in the self-recognition of alcohol dependence. In addition, reinforcing an actor perspective compared to a spectator perspective might results in higher levels of personal enrichment, which may help maintain a patient's long-term recovery. These results support the use of autobiographical memory techniques to enhance awareness of the addicted self, and suggest the need to include these interventions in rehabilitation programmes.

PhyloChip™ microarray comparison of sampling methods used for coral microbial ecology

USGS Publications Warehouse

Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.; DeSantis, Todd Z.; Zawada, David G.; Andersen, Gary L.

2012-01-01

Interest in coral microbial ecology has been increasing steadily over the last decade, yet standardized methods of sample collection still have not been defined. Two methods were compared for their ability to sample coral-associated microbial communities: tissue punches and foam swabs, the latter being less invasive and preferred by reef managers. Four colonies of star coral, Montastraea annularis, were sampled in the Dry Tortugas National Park (two healthy and two with white plague disease). The PhyloChip™ G3 microarray was used to assess microbial community structure of amplified 16S rRNA gene sequences. Samples clustered based on methodology rather than coral colony. Punch samples from healthy and diseased corals were distinct. All swab samples clustered closely together with the seawater control and did not group according to the health state of the corals. Although more microbial taxa were detected by the swab method, there is a much larger overlap between the water control and swab samples than punch samples, suggesting some of the additional diversity is due to contamination from water absorbed by the swab. While swabs are useful for noninvasive studies of the coral surface mucus layer, these results show that they are not optimal for studies of coral disease.

PhyloChip™ microarray comparison of sampling methods used for coral microbial ecology.

PubMed

Kellogg, Christina A; Piceno, Yvette M; Tom, Lauren M; DeSantis, Todd Z; Zawada, David G; Andersen, Gary L

2012-01-01

Interest in coral microbial ecology has been increasing steadily over the last decade, yet standardized methods of sample collection still have not been defined. Two methods were compared for their ability to sample coral-associated microbial communities: tissue punches and foam swabs, the latter being less invasive and preferred by reef managers. Four colonies of star coral, Montastraea annularis, were sampled in the Dry Tortugas National Park (two healthy and two with white plague disease). The PhyloChip™ G3 microarray was used to assess microbial community structure of amplified 16S rRNA gene sequences. Samples clustered based on methodology rather than coral colony. Punch samples from healthy and diseased corals were distinct. All swab samples clustered closely together with the seawater control and did not group according to the health state of the corals. Although more microbial taxa were detected by the swab method, there is a much larger overlap between the water control and swab samples than punch samples, suggesting some of the additional diversity is due to contamination from water absorbed by the swab. While swabs are useful for noninvasive studies of the coral surface mucus layer, these results show that they are not optimal for studies of coral disease. Published by Elsevier B.V.

Inadequate Iodine Intake in Population Groups Defined by Age, Life Stage and Vegetarian Dietary Practice in a Norwegian Convenience Sample.

PubMed

Brantsæter, Anne Lise; Knutsen, Helle Katrine; Johansen, Nina Cathrine; Nyheim, Kristine Aastad; Erlund, Iris; Meltzer, Helle Margrete; Henjum, Sigrun

2018-02-17

Inadequate iodine intake has been identified in populations considered iodine replete for decades. The objective of the current study is to evaluate urinary iodine concentration (UIC) and the probability of adequate iodine intake in subgroups of the Norwegian population defined by age, life stage and vegetarian dietary practice. In a cross-sectional survey, we assessed the probability of adequate iodine intake by two 24-h food diaries and UIC from two fasting morning spot urine samples in 276 participants. The participants included children ( n = 47), adolescents ( n = 46), adults ( n = 71), the elderly ( n = 23), pregnant women ( n = 45), ovo-lacto vegetarians ( n = 25), and vegans ( n = 19). In all participants combined, the median (95% CI) UIC was 101 (90, 110) µg/L, median (25th, 75th percentile) calculated iodine intake was 112 (77, 175) µg/day and median (25th, 75th percentile) estimated usual iodine intake was 101 (75, 150) µg/day. According to WHOs criteria for evaluation of median UIC, iodine intake was inadequate in the elderly, pregnant women, vegans and non-pregnant women of childbearing age. Children had the highest (82%) and vegans the lowest (14%) probability of adequate iodine intake according to reported food and supplement intakes. This study confirms the need for monitoring iodine intake and status in nationally representative study samples in Norway.

Inadequate Iodine Intake in Population Groups Defined by Age, Life Stage and Vegetarian Dietary Practice in a Norwegian Convenience Sample

PubMed Central

Knutsen, Helle Katrine; Johansen, Nina Cathrine; Nyheim, Kristine Aastad; Erlund, Iris; Meltzer, Helle Margrete

2018-01-01

Inadequate iodine intake has been identified in populations considered iodine replete for decades. The objective of the current study is to evaluate urinary iodine concentration (UIC) and the probability of adequate iodine intake in subgroups of the Norwegian population defined by age, life stage and vegetarian dietary practice. In a cross-sectional survey, we assessed the probability of adequate iodine intake by two 24-h food diaries and UIC from two fasting morning spot urine samples in 276 participants. The participants included children (n = 47), adolescents (n = 46), adults (n = 71), the elderly (n = 23), pregnant women (n = 45), ovo-lacto vegetarians (n = 25), and vegans (n = 19). In all participants combined, the median (95% CI) UIC was 101 (90, 110) µg/L, median (25th, 75th percentile) calculated iodine intake was 112 (77, 175) µg/day and median (25th, 75th percentile) estimated usual iodine intake was 101 (75, 150) µg/day. According to WHOs criteria for evaluation of median UIC, iodine intake was inadequate in the elderly, pregnant women, vegans and non-pregnant women of childbearing age. Children had the highest (82%) and vegans the lowest (14%) probability of adequate iodine intake according to reported food and supplement intakes. This study confirms the need for monitoring iodine intake and status in nationally representative study samples in Norway. PMID:29462974

Mixed integer simulation optimization for optimal hydraulic fracturing and production of shale gas fields

NASA Astrophysics Data System (ADS)

Li, J. C.; Gong, B.; Wang, H. G.

2016-08-01

Optimal development of shale gas fields involves designing a most productive fracturing network for hydraulic stimulation processes and operating wells appropriately throughout the production time. A hydraulic fracturing network design-determining well placement, number of fracturing stages, and fracture lengths-is defined by specifying a set of integer ordered blocks to drill wells and create fractures in a discrete shale gas reservoir model. The well control variables such as bottom hole pressures or production rates for well operations are real valued. Shale gas development problems, therefore, can be mathematically formulated with mixed-integer optimization models. A shale gas reservoir simulator is used to evaluate the production performance for a hydraulic fracturing and well control plan. To find the optimal fracturing design and well operation is challenging because the problem is a mixed integer optimization problem and entails computationally expensive reservoir simulation. A dynamic simplex interpolation-based alternate subspace (DSIAS) search method is applied for mixed integer optimization problems associated with shale gas development projects. The optimization performance is demonstrated with the example case of the development of the Barnett Shale field. The optimization results of DSIAS are compared with those of a pattern search algorithm.

Novel synthesis of nanocomposite for the extraction of Sildenafil Citrate (Viagra) from water and urine samples: Process screening and optimization.

PubMed

Asfaram, Arash; Ghaedi, Mehrorang; Purkait, Mihir Kumar

2017-09-01

A sensitive analytical method is investigated to concentrate and determine trace level of Sildenafil Citrate (SLC) present in water and urine samples. The method is based on a sample treatment using dispersive solid-phase micro-extraction (DSPME) with laboratory-made Mn@ CuS/ZnS nanocomposite loaded on activated carbon (Mn@ CuS/ZnS-NCs-AC) as a sorbent for the target analyte. The efficiency was enhanced by ultrasound-assisted (UA) with dispersive nanocomposite solid-phase micro-extraction (UA-DNSPME). Four significant variables affecting SLC recovery like; pH, eluent volume, sonication time and adsorbent mass were selected by the Plackett-Burman design (PBD) experiments. These selected factors were optimized by the central composite design (CCD) to maximize extraction of SLC. The results exhibited that the optimum conditions for maximizing extraction of SLC were 6.0 pH, 300μL eluent (acetonitrile) volume, 10mg of adsorbent and 6min sonication time. Under optimized conditions, virtuous linearity of SLC was ranged from 30 to 4000ngmL -1 with R 2 of 0.99. The limit of detection (LOD) was 2.50ngmL -1 and the recoveries at two spiked levels were ranged from 97.37 to 103.21% with the relative standard deviation (RSD) less than 4.50% (n=15). The enhancement factor (EF) was 81.91. The results show that the combination UAE with DNSPME is a suitable method for the determination of SLC in water and urine samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Design of a Sample Recovery Assembly for Magnetic Ramp-Wave Loading

NASA Astrophysics Data System (ADS)

Chantrenne, S.; Wise, J. L.; Asay, J. R.; Kipp, M. E.; Hall, C. A.

2009-06-01

Characterization of material behavior under dynamic loading requires studies at strain rates ranging from quasi-static to the limiting values of shock compression. For completeness, these studies involve complementary time-resolved data, which define the mechanical constitutive properties, and microstructural data, which reveal physical mechanisms underlying the observed mechanical response. Well-preserved specimens must be recovered for microstructural investigations. Magnetically generated ramp waves produce strain rates lower than those associated with shock waves, but recovery methods have been lacking for this type of loading. We adapted existing shock recovery techniques for application to magnetic ramp loading using 2-D and 3-D ALEGRA MHD code calculations to optimize the recovery design for mitigation of undesired late-time processing of the sample due to edge effects and secondary stress waves. To assess the validity of our simulations, measurements of sample deformation were compared to wavecode predictions.

Tractable Pareto Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Robert; Morris, Paul; Khatib, Lina; Venable, Brent

2003-01-01

This paper focuses on temporal constraint problems where the objective is to optimize a set of local preferences for when events occur. In previous work, a subclass of these problems has been formalized as a generalization of Temporal CSPs, and a tractable strategy for optimization has been proposed, where global optimality is defined as maximizing the minimum of the component preference values. This criterion for optimality, which we call 'Weakest Link Optimization' (WLO), is known to have limited practical usefulness because solutions are compared only on the basis of their worst value; thus, there is no requirement to improve the other values. To address this limitation, we introduce a new algorithm that re-applies WLO iteratively in a way that leads to improvement of all the values. We show the value of this strategy by proving that, with suitable preference functions, the resulting solutions are Pareto Optimal.

Advanced Structural Optimization Under Consideration of Cost Tracking

NASA Astrophysics Data System (ADS)

Zell, D.; Link, T.; Bickelmaier, S.; Albinger, J.; Weikert, S.; Cremaschi, F.; Wiegand, A.

2014-06-01

In order to improve the design process of launcher configurations in the early development phase, the software Multidisciplinary Optimization (MDO) was developed. The tool combines different efficient software tools such as Optimal Design Investigations (ODIN) for structural optimizations, Aerospace Trajectory Optimization Software (ASTOS) for trajectory and vehicle design optimization for a defined payload and mission.The present paper focuses to the integration and validation of ODIN. ODIN enables the user to optimize typical axis-symmetric structures by means of sizing the stiffening designs concerning strength and stability while minimizing the structural mass. In addition a fully automatic finite element model (FEM) generator module creates ready-to-run FEM models of a complete stage or launcher assembly.Cost tracking respectively future improvements concerning cost optimization are indicated.

Pervious concrete mix optimization for sustainable pavement solution

NASA Astrophysics Data System (ADS)

Barišić, Ivana; Galić, Mario; Netinger Grubeša, Ivanka

2017-10-01

In order to fulfill requirements of sustainable road construction, new materials for pavement construction are investigated with the main goal to preserve natural resources and achieve energy savings. One of such sustainable pavement material is pervious concrete as a new solution for low volume pavements. To accommodate required strength and porosity as the measure of appropriate drainage capability, four mixtures of pervious concrete are investigated and results of laboratory tests of compressive and flexural strength and porosity are presented. For defining the optimal pervious concrete mixture in a view of aggregate and financial savings, optimization model is utilized and optimal mixtures defined according to required strength and porosity characteristics. Results of laboratory research showed that comparing single-sized aggregate pervious concrete mixtures, coarse aggregate mixture result in increased porosity but reduced strengths. The optimal share of the coarse aggregate turn to be 40.21%, the share of fine aggregate is 49.79% for achieving required compressive strength of 25 MPa, flexural strength of 4.31 MPa and porosity of 21.66%.

Optimization of the treatment of wheat samples for the determination of phytic acid by HPLC with refractive index detection.

PubMed

Amaro, Rosa; Murillo, Miguel; González, Zurima; Escalona, Andrés; Hernández, Luís

2009-01-01

The treatment of wheat samples was optimized before the determination of phytic acid by high-performance liquid chromatography with refractive index detection. Drying by lyophilization and oven drying were studied; drying by lyophilization gave better results, confirming that this step is critical in preventing significant loss of analyte. In the extraction step, washing of the residue and collection of this water before retention of the phytates in the NH2 Sep-Pak cartridge were important. The retention of phytates in the NH2 Sep-Pak cartridge and elimination of the HCI did not produce significant loss (P = 0.05) in the phytic acid content of the sample. Recoveries of phytic acid averaged 91%, which is a substantial improvement with respect to values reported by others using this methodology.

A concept analysis of optimality in perinatal health.

PubMed

Kennedy, Holly Powell

2006-01-01

This analysis was conducted to describe the concept of optimality and its appropriateness for perinatal health care. The concept was identified in 24 scientific disciplines. Across all disciplines, the universal definition of optimality is the robust, efficient, and cost-effective achievement of best possible outcomes within a rule-governed framework. Optimality, specifically defined for perinatal health care, is the maximal perinatal outcome with minimal intervention placed against the context of the woman's social, medical, and obstetric history.

Detecting glaucomatous change in visual fields: Analysis with an optimization framework.

PubMed

Yousefi, Siamak; Goldbaum, Michael H; Varnousfaderani, Ehsan S; Belghith, Akram; Jung, Tzyy-Ping; Medeiros, Felipe A; Zangwill, Linda M; Weinreb, Robert N; Liebmann, Jeffrey M; Girkin, Christopher A; Bowd, Christopher

2015-12-01

Detecting glaucomatous progression is an important aspect of glaucoma management. The assessment of longitudinal series of visual fields, measured using Standard Automated Perimetry (SAP), is considered the reference standard for this effort. We seek efficient techniques for determining progression from longitudinal visual fields by formulating the problem as an optimization framework, learned from a population of glaucoma data. The longitudinal data from each patient's eye were used in a convex optimization framework to find a vector that is representative of the progression direction of the sample population, as a whole. Post-hoc analysis of longitudinal visual fields across the derived vector led to optimal progression (change) detection. The proposed method was compared to recently described progression detection methods and to linear regression of instrument-defined global indices, and showed slightly higher sensitivities at the highest specificities than other methods (a clinically desirable result). The proposed approach is simpler, faster, and more efficient for detecting glaucomatous changes, compared to our previously proposed machine learning-based methods, although it provides somewhat less information. This approach has potential application in glaucoma clinics for patient monitoring and in research centers for classification of study participants. Copyright © 2015 Elsevier Inc. All rights reserved.

Optimal Distinctiveness Signals Membership Trust.

PubMed

Leonardelli, Geoffrey J; Loyd, Denise Lewin

2016-07-01

According to optimal distinctiveness theory, sufficiently small minority groups are associated with greater membership trust, even among members otherwise unknown, because the groups are seen as optimally distinctive. This article elaborates on the prediction's motivational and cognitive processes and tests whether sufficiently small minorities (defined by relative size; for example, 20%) are associated with greater membership trust relative to mere minorities (45%), and whether such trust is a function of optimal distinctiveness. Two experiments, examining observers' perceptions of minority and majority groups and using minimal groups and (in Experiment 2) a trust game, revealed greater membership trust in minorities than majorities. In Experiment 2, participants also preferred joining minorities over more powerful majorities. Both effects occurred only when minorities were 20% rather than 45%. In both studies, perceptions of optimal distinctiveness mediated effects. Discussion focuses on the value of relative size and optimal distinctiveness, and when membership trust manifests. © 2016 by the Society for Personality and Social Psychology, Inc.

Optimal Resource Allocation in Library Systems

ERIC Educational Resources Information Center

Rouse, William B.

1975-01-01

Queueing theory is used to model processes as either waiting or balking processes. The optimal allocation of resources to these processes is defined as that which maximizes the expected value of the decision-maker's utility function. (Author)

Comparison of optimal design methods in inverse problems

NASA Astrophysics Data System (ADS)

Banks, H. T.; Holm, K.; Kappel, F.

2011-07-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667-77 De Gaetano A and Arino O 2000 J. Math. Biol. 40 136-68 Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979-90).

A Bayesian Sampler for Optimization of Protein Domain Hierarchies

PubMed Central

2014-01-01

Abstract The process of identifying and modeling functionally divergent subgroups for a specific protein domain class and arranging these subgroups hierarchically has, thus far, largely been done via manual curation. How to accomplish this automatically and optimally is an unsolved statistical and algorithmic problem that is addressed here via Markov chain Monte Carlo sampling. Taking as input a (typically very large) multiple-sequence alignment, the sampler creates and optimizes a hierarchy by adding and deleting leaf nodes, by moving nodes and subtrees up and down the hierarchy, by inserting or deleting internal nodes, and by redefining the sequences and conserved patterns associated with each node. All such operations are based on a probability distribution that models the conserved and divergent patterns defining each subgroup. When we view these patterns as sequence determinants of protein function, each node or subtree in such a hierarchy corresponds to a subgroup of sequences with similar biological properties. The sampler can be applied either de novo or to an existing hierarchy. When applied to 60 protein domains from multiple starting points in this way, it converged on similar solutions with nearly identical log-likelihood ratio scores, suggesting that it typically finds the optimal peak in the posterior probability distribution. Similarities and differences between independently generated, nearly optimal hierarchies for a given domain help distinguish robust from statistically uncertain features. Thus, a future application of the sampler is to provide confidence measures for various features of a domain hierarchy. PMID:24494927

Repeatable Battery for the Assessment of Neuropsychological Status: Effort Index Cutoff Scores for Psychometrically Defined Malingering Groups in a Military Sample.

PubMed

Jones, Alvin

2016-05-01

This research examined cutoff scores for the Effort Index (EI), an embedded measure of performance validity, for the Repeatable Battery for the Assessment of Neuropsychological Status. EI cutoffs were explored for an active-duty military sample composed mostly of patients with traumatic brain injury. Four psychometrically defined malingering groups including a definite malingering, probable to definite malingering, probable malingering, and a combined group were formed based on the number of validity tests failed. Excellent specificities (0.97 or greater) were found for all cutoffs examined (EI ≥ 1 to EI ≥ 3). Excellent sensitivities (0.80 to 0.89) were also found for the definite malingering group. Sensitivities were 0.49 or below for the other groups. Positive and negative predictive values and likelihood ratios indicated that the cutoffs for EI were much stronger for ruling-in than ruling-out malingering. Analyses indicated the validity tests used to form the malingering groups were uncorrelated, which serves to enhance the validity of the formation of the malingering groups. Cutoffs were similar to other research using samples composed predominantly of head-injured individuals. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Brief report: Assessing dispositional optimism in adolescence--factor structure and concurrent validity of the Life Orientation Test--Revised.

PubMed

Monzani, Dario; Steca, Patrizia; Greco, Andrea

2014-02-01

Dispositional optimism is an individual difference promoting psychosocial adjustment and well-being during adolescence. Dispositional optimism was originally defined as a one-dimensional construct; however, empirical evidence suggests two correlated factors in the Life Orientation Test - Revised (LOT-R). The main aim of the study was to evaluate the dimensionality of the LOT-R. This study is the first attempt to identify the best factor structure, comparing congeneric, two correlated-factor, and two orthogonal-factor models in a sample of adolescents. Concurrent validity was also assessed. The results demonstrated the superior fit of the two orthogonal-factor model thus reconciling the one-dimensional definition of dispositional optimism with the bi-dimensionality of the LOT-R. Moreover, the results of correlational analyses proved the concurrent validity of this self-report measure: optimism is moderately related to indices of psychosocial adjustment and well-being. Thus, the LOT-R is a useful, valid, and reliable self-report measure to properly assess optimism in adolescence. Copyright © 2013 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

A Language for Specifying Compiler Optimizations for Generic Software

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

Willcock, Jeremiah J.

2007-01-01

Compiler optimization is important to software performance, and modern processor architectures make optimization even more critical. However, many modern software applications use libraries providing high levels of abstraction. Such libraries often hinder effective optimization — the libraries are difficult to analyze using current compiler technology. For example, high-level libraries often use dynamic memory allocation and indirectly expressed control structures, such as iteratorbased loops. Programs using these libraries often cannot achieve an optimal level of performance. On the other hand, software libraries have also been recognized as potentially aiding in program optimization. One proposed implementation of library-based optimization is to allowmore » the library author, or a library user, to define custom analyses and optimizations. Only limited systems have been created to take advantage of this potential, however. One problem in creating a framework for defining new optimizations and analyses is how users are to specify them: implementing them by hand inside a compiler is difficult and prone to errors. Thus, a domain-specific language for librarybased compiler optimizations would be beneficial. Many optimization specification languages have appeared in the literature, but they tend to be either limited in power or unnecessarily difficult to use. Therefore, I have designed, implemented, and evaluated the Pavilion language for specifying program analyses and optimizations, designed for library authors and users. These analyses and optimizations can be based on the implementation of a particular library, its use in a specific program, or on the properties of a broad range of types, expressed through concepts. The new system is intended to provide a high level of expressiveness, even though the intended users are unlikely to be compiler experts.« less

The Internet of Samples in the Earth Sciences (iSamples)

NASA Astrophysics Data System (ADS)

Carter, M. R.; Lehnert, K. A.

2015-12-01

Across most Earth Science disciplines, research depends on the availability of samples collected above, at, and beneath Earth's surface, on the moon and in space, or generated in experiments. Many domains in the Earth Sciences have recently expressed the need for better discovery, access, and sharing of scientific samples and collections (EarthCube End-User Domain workshops, 2012 and 2013, http://earthcube.org/info/about/end-user-workshops), as has the US government (OSTP Memo, March 2014). The Internet of Samples in the Earth Sciences (iSamples) is an initiative funded as a Research Coordination Network (RCN) within the EarthCube program to address this need. iSamples aims to advance the use of innovative cyberinfrastructure to connect physical samples and sample collections across the Earth Sciences with digital data infrastructures to revolutionize their utility for science. iSamples strives to build, grow, and foster a new community of practice, in which domain scientists, curators of sample repositories and collections, computer and information scientists, software developers and technology innovators engage in and collaborate on defining, articulating, and addressing the needs and challenges of physical samples as a critical component of digital data infrastructure. A primary goal of iSamples is to deliver a community-endorsed set of best practices and standards for the registration, description, identification, and citation of physical specimens and define an actionable plan for implementation. iSamples conducted a broad community survey about sample sharing and has created 5 different working groups to address the different challenges of developing the internet of samples - from metadata schemas and unique identifiers to an architecture of a shared cyberinfrastructure for collections, to digitization of existing collections, to education, and ultimately to establishing the physical infrastructure that will ensure preservation and access of the physical

Optimization and application of octadecyl-modified monolithic silica for solid-phase extraction of drugs in whole blood samples.

PubMed

Namera, Akira; Saito, Takeshi; Ota, Shigenori; Miyazaki, Shota; Oikawa, Hiroshi; Murata, Kazuhiro; Nagao, Masataka

2017-09-29

Monolithic silica in MonoSpin for solid-phase extraction of drugs from whole blood samples was developed to facilitate high-throughput analysis. Monolithic silica of various pore sizes and octadecyl contents were synthesized, and their effects on recovery rates were evaluated. The silica monolith M18-200 (20μm through-pore size, 10.4nm mesopore size, and 17.3% carbon content) achieved the best recovery of the target analytes in whole blood samples. The extraction proceeded with centrifugal force at 1000rpm for 2min, and the eluate was directly injected into the liquid chromatography-mass spectrometry system without any tedious steps such as evaporation of extraction solvents. Under the optimized condition, low detection limits of 0.5-2.0ngmL -1 and calibration ranges up to 1000ngmL -1 were obtained. The recoveries of the target drugs in the whole blood were 76-108% with relative standard deviation of less than 14.3%. These results indicate that the developed method based on monolithic silica is convenient, highly efficient, and applicable for detecting drugs in whole blood samples. Copyright © 2017 Elsevier B.V. All rights reserved.

An EGO-like optimization framework for sensor placement optimization in modal analysis

NASA Astrophysics Data System (ADS)

Morlier, Joseph; Basile, Aniello; Chiplunkar, Ankit; Charlotte, Miguel

2018-07-01

In aircraft design, ground/flight vibration tests are conducted to extract aircraft’s modal parameters (natural frequencies, damping ratios and mode shapes) also known as the modal basis. The main problem in aircraft modal identification is the large number of sensors needed, which increases operational time and costs. The goal of this paper is to minimize the number of sensors by optimizing their locations in order to reconstruct a truncated modal basis of N mode shapes with a high level of accuracy in the reconstruction. There are several methods to solve sensors placement optimization (SPO) problems, but for this case an original approach has been established based on an iterative process for mode shapes reconstruction through an adaptive Kriging metamodeling approach so called efficient global optimization (EGO)-SPO. The main idea in this publication is to solve an optimization problem where the sensors locations are variables and the objective function is defined by maximizing the trace of criteria so called AutoMAC. The results on a 2D wing demonstrate a reduction of sensors by 30% using our EGO-SPO strategy.

Development of an Optimization Methodology for the Aluminum Alloy Wheel Casting Process

NASA Astrophysics Data System (ADS)

Duan, Jianglan; Reilly, Carl; Maijer, Daan M.; Cockcroft, Steve L.; Phillion, Andre B.

2015-08-01

An optimization methodology has been developed for the aluminum alloy wheel casting process. The methodology is focused on improving the timing of cooling processes in a die to achieve improved casting quality. This methodology utilizes (1) a casting process model, which was developed within the commercial finite element package, ABAQUS™—ABAQUS is a trademark of Dassault Systèms; (2) a Python-based results extraction procedure; and (3) a numerical optimization module from the open-source Python library, Scipy. To achieve optimal casting quality, a set of constraints have been defined to ensure directional solidification, and an objective function, based on the solidification cooling rates, has been defined to either maximize, or target a specific, cooling rate. The methodology has been applied to a series of casting and die geometries with different cooling system configurations, including a 2-D axisymmetric wheel and die assembly generated from a full-scale prototype wheel. The results show that, with properly defined constraint and objective functions, solidification conditions can be improved and optimal cooling conditions can be achieved leading to process productivity and product quality improvements.

Knowledge-based nonuniform sampling in multidimensional NMR.

PubMed

Schuyler, Adam D; Maciejewski, Mark W; Arthanari, Haribabu; Hoch, Jeffrey C

2011-07-01

The full resolution afforded by high-field magnets is rarely realized in the indirect dimensions of multidimensional NMR experiments because of the time cost of uniformly sampling to long evolution times. Emerging methods utilizing nonuniform sampling (NUS) enable high resolution along indirect dimensions by sampling long evolution times without sampling at every multiple of the Nyquist sampling interval. While the earliest NUS approaches matched the decay of sampling density to the decay of the signal envelope, recent approaches based on coupled evolution times attempt to optimize sampling by choosing projection angles that increase the likelihood of resolving closely-spaced resonances. These approaches employ knowledge about chemical shifts to predict optimal projection angles, whereas prior applications of tailored sampling employed only knowledge of the decay rate. In this work we adapt the matched filter approach as a general strategy for knowledge-based nonuniform sampling that can exploit prior knowledge about chemical shifts and is not restricted to sampling projections. Based on several measures of performance, we find that exponentially weighted random sampling (envelope matched sampling) performs better than shift-based sampling (beat matched sampling). While shift-based sampling can yield small advantages in sensitivity, the gains are generally outweighed by diminished robustness. Our observation that more robust sampling schemes are only slightly less sensitive than schemes highly optimized using prior knowledge about chemical shifts has broad implications for any multidimensional NMR study employing NUS. The results derived from simulated data are demonstrated with a sample application to PfPMT, the phosphoethanolamine methyltransferase of the human malaria parasite Plasmodium falciparum.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements

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

Qian, Chen; Hettich, Robert L.

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling, perhaps most specifically with respect to impact on plant growth but also more broadly to global impact on carbon and nitrogen-cycling. Liquid chromatography coupled to high performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to soil proteome extraction and subsequent MS measurement. To address some of the major issues, we have designed and optimized an experimental method to enhance microbialmore » proteome extraction concomitant with minimizing the soil-borne humic substances co-extraction from soils. Among the range of interferences, humic substances are often the worst in terms of adversely impacting proteome extraction and mass spectrometry measurement. Our approach employs an in-situ detergent-based microbial lysis / TCA precipitation coupled with an additional acidification precipitation step at the peptide level which efficiently removes humic acids. By combing filtration and pH adjustment of the final peptide solution, the remaining humic acids can be differentially precipitated and removed with a membrane filter, thereby leaving much cleaner proteolytic peptide samples for MS measurement. As a result, this modified method is a reliable and straight-forward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or reducing or biasing protein identification in mass spectrometry.« less

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements

DOE PAGES

Qian, Chen; Hettich, Robert L.

2017-05-24

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling, perhaps most specifically with respect to impact on plant growth but also more broadly to global impact on carbon and nitrogen-cycling. Liquid chromatography coupled to high performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to soil proteome extraction and subsequent MS measurement. To address some of the major issues, we have designed and optimized an experimental method to enhance microbialmore » proteome extraction concomitant with minimizing the soil-borne humic substances co-extraction from soils. Among the range of interferences, humic substances are often the worst in terms of adversely impacting proteome extraction and mass spectrometry measurement. Our approach employs an in-situ detergent-based microbial lysis / TCA precipitation coupled with an additional acidification precipitation step at the peptide level which efficiently removes humic acids. By combing filtration and pH adjustment of the final peptide solution, the remaining humic acids can be differentially precipitated and removed with a membrane filter, thereby leaving much cleaner proteolytic peptide samples for MS measurement. As a result, this modified method is a reliable and straight-forward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or reducing or biasing protein identification in mass spectrometry.« less

Use of CFD for static sampling hood design: An example for methane flux assessment on landfill surfaces.

PubMed

Lucernoni, Federico; Rizzotto, Matteo; Tapparo, Federica; Capelli, Laura; Sironi, Selena; Busini, Valentina

2016-11-01

The work focuses on the principles for the design of a specific static hood and on the definition of an optimal sampling procedure for the assessment of landfill gas (LFG) surface emissions. This is carried out by means of computational fluid dynamics (CFD) simulations to investigate the fluid dynamics conditions of the hood. The study proves that understanding the fluid dynamic conditions is fundamental in order to understand the sampling results and correctly interpret the measured concentration values by relating them to a suitable LFG emission model, and therefore to estimate emission rates. For this reason, CFD is a useful tool for the design and evaluation of sampling systems, among others, to verify the fundamental hypotheses on which the mass balance for the sampling hood is defined. The procedure here discussed, which is specific for the case of the investigated landfill, can be generalized to be applied also to different scenarios, where hood sampling is involved. Copyright © 2016 Elsevier Ltd. All rights reserved.

Delaunay-based derivative-free optimization for efficient minimization of time-averaged statistics of turbulent flows

NASA Astrophysics Data System (ADS)

Beyhaghi, Pooriya

2016-11-01

This work considers the problem of the efficient minimization of the infinite time average of a stationary ergodic process in the space of a handful of independent parameters which affect it. Problems of this class, derived from physical or numerical experiments which are sometimes expensive to perform, are ubiquitous in turbulence research. In such problems, any given function evaluation, determined with finite sampling, is associated with a quantifiable amount of uncertainty, which may be reduced via additional sampling. This work proposes the first algorithm of this type. Our algorithm remarkably reduces the overall cost of the optimization process for problems of this class. Further, under certain well-defined conditions, rigorous proof of convergence is established to the global minimum of the problem considered.

Optimal networks of future gravitational-wave telescopes

NASA Astrophysics Data System (ADS)

Raffai, Péter; Gondán, László; Heng, Ik Siong; Kelecsényi, Nándor; Logue, Josh; Márka, Zsuzsa; Márka, Szabolcs

2013-08-01

We aim to find the optimal site locations for a hypothetical network of 1-3 triangular gravitational-wave telescopes. We define the following N-telescope figures of merit (FoMs) and construct three corresponding metrics: (a) capability of reconstructing the signal polarization; (b) accuracy in source localization; and (c) accuracy in reconstructing the parameters of a standard binary source. We also define a combined metric that takes into account the three FoMs with practically equal weight. After constructing a geomap of possible telescope sites, we give the optimal 2-telescope networks for the four FoMs separately in example cases where the location of the first telescope has been predetermined. We found that based on the combined metric, placing the first telescope to Australia provides the most options for optimal site selection when extending the network with a second instrument. We suggest geographical regions where a potential second and third telescope could be placed to get optimal network performance in terms of our FoMs. Additionally, we use a similar approach to find the optimal location and orientation for the proposed LIGO-India detector within a five-detector network with Advanced LIGO (Hanford), Advanced LIGO (Livingston), Advanced Virgo, and KAGRA. We found that the FoMs do not change greatly in sites within India, though the network can suffer a significant loss in reconstructing signal polarizations if the orientation angle of an L-shaped LIGO-India is not set to the optimal value of ˜58.2°( + k × 90°) (measured counterclockwise from East to the bisector of the arms).

The optimal design of UAV wing structure

NASA Astrophysics Data System (ADS)

Długosz, Adam; Klimek, Wiktor

2018-01-01

The paper presents an optimal design of UAV wing, made of composite materials. The aim of the optimization is to improve strength and stiffness together with reduction of the weight of the structure. Three different types of functionals, which depend on stress, stiffness and the total mass are defined. The paper presents an application of the in-house implementation of the evolutionary multi-objective algorithm in optimization of the UAV wing structure. Values of the functionals are calculated on the basis of results obtained from numerical simulations. Numerical FEM model, consisting of different composite materials is created. Adequacy of the numerical model is verified by results obtained from the experiment, performed on a tensile testing machine. Examples of multi-objective optimization by means of Pareto-optimal set of solutions are presented.

Optimality, sample size, and power calculations for the sequential parallel comparison design.

PubMed

Ivanova, Anastasia; Qaqish, Bahjat; Schoenfeld, David A

2011-10-15

The sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials in therapeutic areas where high-placebo response is a concern. The trial is run in two stages, and subjects are randomized into three groups: (i) placebo in both stages; (ii) placebo in the first stage and drug in the second stage; and (iii) drug in both stages. We consider the case of binary response data (response/no response). In the SPCD, all first-stage and second-stage data from placebo subjects who failed to respond in the first stage of the trial are utilized in the efficacy analysis. We develop 1 and 2 degree of freedom score tests for treatment effect in the SPCD. We give formulae for asymptotic power and for sample size computations and evaluate their accuracy via simulation studies. We compute the optimal allocation ratio between drug and placebo in stage 1 for the SPCD to determine from a theoretical viewpoint whether a single-stage design, a two-stage design with placebo only in the first stage, or a two-stage design is the best design for a given set of response rates. As response rates are not known before the trial, a two-stage approach with allocation to active drug in both stages is a robust design choice. Copyright © 2011 John Wiley & Sons, Ltd.

Optimization of the Hartmann-Shack microlens array

NASA Astrophysics Data System (ADS)

de Oliveira, Otávio Gomes; de Lima Monteiro, Davies William

2011-04-01

In this work we propose to optimize the microlens-array geometry for a Hartmann-Shack wavefront sensor. The optimization makes possible that regular microlens arrays with a larger number of microlenses are replaced by arrays with fewer microlenses located at optimal sampling positions, with no increase in the reconstruction error. The goal is to propose a straightforward and widely accessible numerical method to calculate an optimized microlens array for a known aberration statistics. The optimization comprises the minimization of the wavefront reconstruction error and/or the number of necessary microlenses in the array. We numerically generate, sample and reconstruct the wavefront, and use a genetic algorithm to discover the optimal array geometry. Within an ophthalmological context, as a case study, we demonstrate that an array with only 10 suitably located microlenses can be used to produce reconstruction errors as small as those of a 36-microlens regular array. The same optimization procedure can be employed for any application where the wavefront statistics is known.

The Optimization by Using the Learning Styles in the Adaptive Hypermedia Applications

ERIC Educational Resources Information Center

Hamza, Lamia; Tlili, Guiassa Yamina

2018-01-01

This article addresses the learning style as a criterion for optimization of adaptive content in hypermedia applications. First, the authors present the different optimization approaches proposed in the area of adaptive hypermedia systems whose goal is to define the optimization problem in this type of system. Then, they present the architecture…

Defining and evaluating quality for ambulatory care educational programs.

PubMed

Bowen, J L; Stearns, J A; Dohner, C; Blackman, J; Simpson, D

1997-06-01

As the training of medical students and residents increasingly moves to ambulatory care settings, clerkship and program directors must find a way to use their limited resources to guide the development and evaluation of the quality of these ambulatory-based learning experiences. To evaluate quality, directors must first define, in operational and measurable terms, what is meant by the term "quality" as it is applied to ambulatory-based education. Using educational theories and the definition of quality used by health care systems, the authors propose an operational definition of quality for guiding the planning, implementation, and evaluation of ambulatory care educational programs. They assert that quality is achieved through the interaction of an optimal learning environment, defined educational goals and positive outcomes, participant satisfaction, and cost-effectiveness. By describing the components of quality along with examples of measurable indicators, the authors provide a foundation for the evaluation and improvement of instructional innovations in ambulatory care education for the benefit of teachers, learners, and patients.

Optimization of batteries for plug-in hybrid electric vehicles

NASA Astrophysics Data System (ADS)

English, Jeffrey Robb

This thesis presents a method to quickly determine the optimal battery for an electric vehicle given a set of vehicle characteristics and desired performance metrics. The model is based on four independent design variables: cell count, cell capacity, state-of-charge window, and battery chemistry. Performance is measured in seven categories: cost, all-electric range, maximum speed, acceleration, battery lifetime, lifetime greenhouse gas emissions, and charging time. The performance of each battery is weighted according to a user-defined objective function to determine its overall fitness. The model is informed by a series of battery tests performed on scaled-down battery samples. Seven battery chemistries were tested for capacity at different discharge rates, maximum output power at different charge levels, and performance in a real-world automotive duty cycle. The results of these tests enable a prediction of the performance of the battery in an automobile. Testing was performed at both room temperature and low temperature to investigate the effects of battery temperature on operation. The testing highlighted differences in behavior between lithium, nickel, and lead based batteries. Battery performance decreased with temperature across all samples with the largest effect on nickel-based chemistries. Output power also decreased with lead acid batteries being the least affected by temperature. Lithium-ion batteries were found to be highly efficient (>95%) under a vehicular duty cycle; nickel and lead batteries have greater losses. Low temperatures hindered battery performance and resulted in accelerated failure in several samples. Lead acid, lead tin, and lithium nickel alloy batteries were unable to complete the low temperature testing regime without losing significant capacity and power capability. This is a concern for their applicability in electric vehicles intended for cold climates which have to maintain battery temperature during long periods of inactivity

Optimal parameters uncoupling vibration modes of oscillators

NASA Astrophysics Data System (ADS)

Le, K. C.; Pieper, A.

2017-07-01

This paper proposes a novel optimization concept for an oscillator with two degrees of freedom. By using specially defined motion ratios, we control the action of springs to each degree of freedom of the oscillator. We aim at showing that, if the potential action of the springs in one period of vibration, used as the payoff function for the conservative oscillator, is maximized among all admissible parameters and motions satisfying Lagrange's equations, then the optimal motion ratios uncouple vibration modes. A similar result holds true for the dissipative oscillator having dampers. The application to optimal design of vehicle suspension is discussed.

Optimized design and analysis of sparse-sampling FMRI experiments.

PubMed

Perrachione, Tyler K; Ghosh, Satrajit S

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase

THE NIST-EPA INTERAGENCY AGREEMENT ON MEASUREMENTS AND STANDARDS IN AEROSOL CARBON: SAMPLING REGIONAL PM 2.5 FOR THE CHEMOMETRIC OPTIMIZATION OF THERMAL-OPTICAL ANALYSIS

EPA Science Inventory

Results from the NIST-EPA Interagency Agreement on Measurements and Standards in Aerosol Carbon: Sampling Regional PM2.5 for the Chemometric Optimization of Thermal-Optical Analysis Study will be presented at the American Association for Aerosol Research (AAAR) 24th Annual Confer...

Integrated multidisciplinary optimization of rotorcraft: A plan for development

NASA Technical Reports Server (NTRS)

Adelman, Howard M. (Editor); Mantay, Wayne R. (Editor)

1989-01-01

This paper describes a joint NASA/Army initiative at the Langley Research Center to develop optimization procedures aimed at improving the rotor blade design process by integrating appropriate disciplines and accounting for important interactions among the disciplines. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. Additionally, some of the analysis aspects are discussed, validation strategies are described, and an initial attempt at defining the interdisciplinary couplings is summarized. At this writing, significant progress has been made, principally in the areas of single discipline optimization. Accomplishments are described in areas of rotor aerodynamic performance optimization for minimum hover horsepower, rotor dynamic optimization for vibration reduction, and rotor structural optimization for minimum weight.

Mean-variance portfolio selection for defined-contribution pension funds with stochastic salary.

PubMed

Zhang, Chubing

2014-01-01

This paper focuses on a continuous-time dynamic mean-variance portfolio selection problem of defined-contribution pension funds with stochastic salary, whose risk comes from both financial market and nonfinancial market. By constructing a special Riccati equation as a continuous (actually a viscosity) solution to the HJB equation, we obtain an explicit closed form solution for the optimal investment portfolio as well as the efficient frontier.

Homosexual, gay, and lesbian: defining the words and sampling the populations.

PubMed

Donovan, J M

1992-01-01

The lack of both specificity and consensus about definitions for homosexual, homosexuality, gay, and lesbian are first shown to confound comparative research and cumulative understanding because criteria for inclusion within the subject populations are often not consistent. The Description section examines sociolinguistic variables which determine patterns of preferred choice of terminology, and considers how these might impact gay and lesbian studies. Attitudes and style are found to influence word choice. These results are used in the second section to devise recommended definitional limits which would satisfy both communication needs and methodological purposes, especially those of sampling.

Toward Optimal Transport Networks

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

2008-01-01

Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

Systematic Propulsion Optimization Tools (SPOT)

NASA Technical Reports Server (NTRS)

Bower, Mark; Celestian, John

1992-01-01

This paper describes a computer program written by senior-level Mechanical Engineering students at the University of Alabama in Huntsville which is capable of optimizing user-defined delivery systems for carrying payloads into orbit. The custom propulsion system is designed by the user through the input of configuration, payload, and orbital parameters. The primary advantages of the software, called Systematic Propulsion Optimization Tools (SPOT), are a user-friendly interface and a modular FORTRAN 77 code designed for ease of modification. The optimization of variables in an orbital delivery system is of critical concern in the propulsion environment. The mass of the overall system must be minimized within the maximum stress, force, and pressure constraints. SPOT utilizes the Design Optimization Tools (DOT) program for the optimization techniques. The SPOT program is divided into a main program and five modules: aerodynamic losses, orbital parameters, liquid engines, solid engines, and nozzles. The program is designed to be upgraded easily and expanded to meet specific user needs. A user's manual and a programmer's manual are currently being developed to facilitate implementation and modification.

Optimal flow for brown trout: Habitat - prey optimization.

PubMed

Fornaroli, Riccardo; Cabrini, Riccardo; Sartori, Laura; Marazzi, Francesca; Canobbio, Sergio; Mezzanotte, Valeria

2016-10-01

The correct definition of ecosystem needs is essential in order to guide policy and management strategies to optimize the increasing use of freshwater by human activities. Commonly, the assessment of the optimal or minimum flow rates needed to preserve ecosystem functionality has been done by habitat-based models that define a relationship between in-stream flow and habitat availability for various species of fish. We propose a new approach for the identification of optimal flows using the limiting factor approach and the evaluation of basic ecological relationships, considering the appropriate spatial scale for different organisms. We developed density-environment relationships for three different life stages of brown trout that show the limiting effects of hydromorphological variables at habitat scale. In our analyses, we found that the factors limiting the densities of trout were water velocity, substrate characteristics and refugia availability. For all the life stages, the selected models considered simultaneously two variables and implied that higher velocities provided a less suitable habitat, regardless of other physical characteristics and with different patterns. We used these relationships within habitat based models in order to select a range of flows that preserve most of the physical habitat for all the life stages. We also estimated the effect of varying discharge flows on macroinvertebrate biomass and used the obtained results to identify an optimal flow maximizing habitat and prey availability. Copyright © 2016 Elsevier B.V. All rights reserved.

Factorial design optimization of experimental variables in the on-line separation/preconcentration of copper in water samples using solid phase extraction and ICP-OES determination.

PubMed

Escudero, Luis A; Cerutti, S; Olsina, R A; Salonia, J A; Gasquez, J A

2010-11-15

An on-line preconcentration procedure using solid phase extraction (SPE) for the determination of copper in different water samples by inductively coupled plasma optical emission spectrometry (ICP-OES) is proposed. The copper was retained on a minicolumn filled with ethyl vinyl acetate (EVA) at pH 8.0 without using any complexing reagent. The experimental optimization step was performed using a two-level full factorial design. The results showed that pH, sample loading flow rate, and their interaction (at the tested levels) were statistically significant. In order to determine the best conditions for preconcentration and determination of copper, a final optimization of the significant factors was carried out using a central composite design (CCD). The calibration graph was linear with a regression coefficient of 0.995 at levels near the detection limit up to at least 300 μg L(-1). An enrichment factor (EF) of 54 with a preconcentration time of 187.5 s was obtained. The limit of detection (3σ) was 0.26 μg L(-1). The sampling frequency for the developed methodology was about 15 samples/h. The relative standard deviation (RSD) for six replicates containing 50 μg L(-1) of copper was 3.76%. The methodology was successfully applied to the determination of Cu in tap, mineral, river water samples, and in a certified VKI standard reference material. Copyright © 2010 Elsevier B.V. All rights reserved.

In-Space Radiator Shape Optimization using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Hull, Patrick V.; Kittredge, Ken; Tinker, Michael; SanSoucie, Michael

2006-01-01

Future space exploration missions will require the development of more advanced in-space radiators. These radiators should be highly efficient and lightweight, deployable heat rejection systems. Typical radiators for in-space heat mitigation commonly comprise a substantial portion of the total vehicle mass. A small mass savings of even 5-10% can greatly improve vehicle performance. The objective of this paper is to present the development of detailed tools for the analysis and design of in-space radiators using evolutionary computation techniques. The optimality criterion is defined as a two-dimensional radiator with a shape demonstrating the smallest mass for the greatest overall heat transfer, thus the end result is a set of highly functional radiator designs. This cross-disciplinary work combines topology optimization and thermal analysis design by means of a genetic algorithm The proposed design tool consists of the following steps; design parameterization based on the exterior boundary of the radiator, objective function definition (mass minimization and heat loss maximization), objective function evaluation via finite element analysis (thermal radiation analysis) and optimization based on evolutionary algorithms. The radiator design problem is defined as follows: the input force is a driving temperature and the output reaction is heat loss. Appropriate modeling of the space environment is added to capture its effect on the radiator. The design parameters chosen for this radiator shape optimization problem fall into two classes, variable height along the width of the radiator and a spline curve defining the -material boundary of the radiator. The implementation of multiple design parameter schemes allows the user to have more confidence in the radiator optimization tool upon demonstration of convergence between the two design parameter schemes. This tool easily allows the user to manipulate the driving temperature regions thus permitting detailed design of in

Disc valve for sampling erosive process streams

DOEpatents

Mrochek, J.E.; Dinsmore, S.R.; Chandler, E.W.

1986-01-07

A four-port disc valve is described for sampling erosive, high temperature process streams. A rotatable disc defining opposed first and second sampling cavities rotates between fired faceplates defining flow passageways positioned to be alternatively in axial alignment with the first and second cavities. Silicon carbide inserts and liners composed of [alpha] silicon carbide are provided in the faceplates and in the sampling cavities to limit erosion while providing lubricity for a smooth and precise operation when used under harsh process conditions. 1 fig.

Trajectory Optimization: OTIS 4

NASA Technical Reports Server (NTRS)

Riehl, John P.; Sjauw, Waldy K.; Falck, Robert D.; Paris, Stephen W.

2010-01-01

The latest release of the Optimal Trajectories by Implicit Simulation (OTIS4) allows users to simulate and optimize aerospace vehicle trajectories. With OTIS4, one can seamlessly generate optimal trajectories and parametric vehicle designs simultaneously. New features also allow OTIS4 to solve non-aerospace continuous time optimal control problems. The inputs and outputs of OTIS4 have been updated extensively from previous versions. Inputs now make use of objectoriented constructs, including one called a metastring. Metastrings use a greatly improved calculator and common nomenclature to reduce the user s workload. They allow for more flexibility in specifying vehicle physical models, boundary conditions, and path constraints. The OTIS4 calculator supports common mathematical functions, Boolean operations, and conditional statements. This allows users to define their own variables for use as outputs, constraints, or objective functions. The user-defined outputs can directly interface with other programs, such as spreadsheets, plotting packages, and visualization programs. Internally, OTIS4 has more explicit and implicit integration procedures, including high-order collocation methods, the pseudo-spectral method, and several variations of multiple shooting. Users may switch easily between the various methods. Several unique numerical techniques such as automated variable scaling and implicit integration grid refinement, support the integration methods. OTIS4 is also significantly more user friendly than previous versions. The installation process is nearly identical on various platforms, including Microsoft Windows, Apple OS X, and Linux operating systems. Cross-platform scripts also help make the execution of OTIS and post-processing of data easier. OTIS4 is supplied free by NASA and is subject to ITAR (International Traffic in Arms Regulations) restrictions. Users must have a Fortran compiler, and a Python interpreter is highly recommended.

Forecasting Electricity Prices in an Optimization Hydrothermal Problem

NASA Astrophysics Data System (ADS)

Matías, J. M.; Bayón, L.; Suárez, P.; Argüelles, A.; Taboada, J.

2007-12-01

This paper presents an economic dispatch algorithm in a hydrothermal system within the framework of a competitive and deregulated electricity market. The optimization problem of one firm is described, whose objective function can be defined as its profit maximization. Since next-day price forecasting is an aspect crucial, this paper proposes an efficient yet highly accurate next-day price new forecasting method using a functional time series approach trying to exploit the daily seasonal structure of the series of prices. For the optimization problem, an optimal control technique is applied and Pontryagin's theorem is employed.

Processor design optimization methodology for synthetic vision systems

NASA Astrophysics Data System (ADS)

Wren, Bill; Tarleton, Norman G.; Symosek, Peter F.

1997-06-01

Architecture optimization requires numerous inputs from hardware to software specifications. The task of varying these input parameters to obtain an optimal system architecture with regard to cost, specified performance and method of upgrade considerably increases the development cost due to the infinitude of events, most of which cannot even be defined by any simple enumeration or set of inequalities. We shall address the use of a PC-based tool using genetic algorithms to optimize the architecture for an avionics synthetic vision system, specifically passive millimeter wave system implementation.

Deficient motion-defined and texture-defined figure-ground segregation in amblyopic children.

PubMed

Wang, Jane; Ho, Cindy S; Giaschi, Deborah E

2007-01-01

Motion-defined form deficits in the fellow eye and the amblyopic eye of children with amblyopia implicate possible direction-selective motion processing or static figure-ground segregation deficits. Deficient motion-defined form perception in the fellow eye of amblyopic children may not be fully accounted for by a general motion processing deficit. This study investigates the contribution of figure-ground segregation deficits to the motion-defined form perception deficits in amblyopia. Performances of 6 amblyopic children (5 anisometropic, 1 anisostrabismic) and 32 control children with normal vision were assessed on motion-defined form, texture-defined form, and global motion tasks. Performance on motion-defined and texture-defined form tasks was significantly worse in amblyopic children than in control children. Performance on global motion tasks was not significantly different between the 2 groups. Faulty figure-ground segregation mechanisms are likely responsible for the observed motion-defined form perception deficits in amblyopia.

SynGenics Optimization System (SynOptSys)

NASA Technical Reports Server (NTRS)

Ventresca, Carol; McMilan, Michelle L.; Globus, Stephanie

2013-01-01

The SynGenics Optimization System (SynOptSys) software application optimizes a product with respect to multiple, competing criteria using statistical Design of Experiments, Response-Surface Methodology, and the Desirability Optimization Methodology. The user is not required to be skilled in the underlying math; thus, SynOptSys can help designers and product developers overcome the barriers that prevent them from using powerful techniques to develop better pro ducts in a less costly manner. SynOpt-Sys is applicable to the design of any product or process with multiple criteria to meet, and at least two factors that influence achievement of those criteria. The user begins with a selected solution principle or system concept and a set of criteria that needs to be satisfied. The criteria may be expressed in terms of documented desirements or defined responses that the future system needs to achieve. Documented desirements can be imported into SynOptSys or created and documented directly within SynOptSys. Subsequent steps include identifying factors, specifying model order for each response, designing the experiment, running the experiment and gathering the data, analyzing the results, and determining the specifications for the optimized system. The user may also enter textual information as the project progresses. Data is easily edited within SynOptSys, and the software design enables full traceability within any step in the process, and facilitates reporting as needed. SynOptSys is unique in the way responses are defined and the nuances of the goodness associated with changes in response values for each of the responses of interest. The Desirability Optimization Methodology provides the basis of this novel feature. Moreover, this is a complete, guided design and optimization process tool with embedded math that can remain invisible to the user. It is not a standalone statistical program; it is a design and optimization system.

Nuclear Electric Vehicle Optimization Toolset (NEVOT)

NASA Technical Reports Server (NTRS)

Tinker, Michael L.; Steincamp, James W.; Stewart, Eric T.; Patton, Bruce W.; Pannell, William P.; Newby, Ronald L.; Coffman, Mark E.; Kos, Larry D.; Qualls, A. Lou; Greene, Sherrell

2004-01-01

The Nuclear Electric Vehicle Optimization Toolset (NEVOT) optimizes the design of all major nuclear electric propulsion (NEP) vehicle subsystems for a defined mission within constraints and optimization parameters chosen by a user. The tool uses a genetic algorithm (GA) search technique to combine subsystem designs and evaluate the fitness of the integrated design to fulfill a mission. The fitness of an individual is used within the GA to determine its probability of survival through successive generations in which the designs with low fitness are eliminated and replaced with combinations or mutations of designs with higher fitness. The program can find optimal solutions for different sets of fitness metrics without modification and can create and evaluate vehicle designs that might never be considered through traditional design techniques. It is anticipated that the flexible optimization methodology will expand present knowledge of the design trade-offs inherent in designing nuclear powered space vehicles and lead to improved NEP designs.

Dispositional optimism and coping with pain.

PubMed

Bargiel-Matusiewicz, K; Krzyszkowska, A

2009-12-07

The aim of this article is to analyze the relation between dispositional optimism and coping with chronic pain. The study seeks to define the relation between life orientation (optimism vs. pessimism) and coping with pain (believes about pain control and the choice of coping strategy). The following questionnaires were used: LOT-R - Life Orientation Test, BPCQ - The Beliefs about Pain Control Questionnaire and CSQ - The Pain Coping Strategies Questionnaire. The results show that dispositional optimism correlates positively with: internal locus of pain control r=0.6, P<0.01; declared coping with pain r=0.38, P<0.05; diverting attention r = 0.93, P<0.01; and behavioral activity r = 0.82, P<0.01. Dispositional optimism correlates negatively with catastrophizing r = -0.28, P<0.05. We conclude that dispositional optimism plays a key role in forming the mechanisms of coping with chronic pain and thereby in improving the psychophysical comfort of patients.

Development and optimization of a novel sample preparation method cored on functionalized nanofibers mat-solid-phase extraction for the simultaneous efficient extraction of illegal anionic and cationic dyes in foods.

PubMed

Qi, Feifei; Jian, Ningge; Qian, Liangliang; Cao, Weixin; Xu, Qian; Li, Jian

2017-09-01

A simple and efficient three-step sample preparation method was developed and optimized for the simultaneous analysis of illegal anionic and cationic dyes (acid orange 7, metanil yellow, auramine-O, and chrysoidine) in food samples. A novel solid-phase extraction (SPE) procedure based on nanofibers mat (NFsM) was proposed after solvent extraction and freeze-salting out purification. The preferred SPE sorbent was selected from five functionalized NFsMs by orthogonal experimental design, and the optimization of SPE parameters was achieved through response surface methodology (RSM) based on the Box-Behnken design (BBD). Under the optimal conditions, the target analytes could be completely adsorbed by polypyrrole-functionalized polyacrylonitrile NFsM (PPy/PAN NFsM), and the eluent was directly analyzed by high-performance liquid chromatography-diode array detection (HPLC-DAD). The limits of detection (LODs) were between 0.002 and 0.01 mg kg -1 , and satisfactory linearity with correlation coefficients (R > 0.99) for each dye in all samples was achieved. Compared with the Chinese standard method and the published methods, the proposed method was simplified greatly with much lower requirement of sorbent (5.0 mg) and organic solvent (2.8 mL) and higher sample preparation speed (10 min/sample), while higher recovery (83.6-116.5%) and precision (RSDs < 7.1%) were obtained. With this developed method, we have successfully detected illegal ionic dyes in three common representative foods: yellow croaker, soybean products, and chili seasonings. Graphical abstract Schematic representation of the process of the three-step sample preparation.

Optimal consensus algorithm integrated with obstacle avoidance

NASA Astrophysics Data System (ADS)

Wang, Jianan; Xin, Ming

2013-01-01

This article proposes a new consensus algorithm for the networked single-integrator systems in an obstacle-laden environment. A novel optimal control approach is utilised to achieve not only multi-agent consensus but also obstacle avoidance capability with minimised control efforts. Three cost functional components are defined to fulfil the respective tasks. In particular, an innovative nonquadratic obstacle avoidance cost function is constructed from an inverse optimal control perspective. The other two components are designed to ensure consensus and constrain the control effort. The asymptotic stability and optimality are proven. In addition, the distributed and analytical optimal control law only requires local information based on the communication topology to guarantee the proposed behaviours, rather than all agents' information. The consensus and obstacle avoidance are validated through simulations.

Finite element approximation of an optimal control problem for the von Karman equations

NASA Technical Reports Server (NTRS)

Hou, L. Steven; Turner, James C.

1994-01-01

This paper is concerned with optimal control problems for the von Karman equations with distributed controls. We first show that optimal solutions exist. We then show that Lagrange multipliers may be used to enforce the constraints and derive an optimality system from which optimal states and controls may be deduced. Finally we define finite element approximations of solutions for the optimality system and derive error estimates for the approximations.

Implicitly defined criteria for vector optimization in technological process of hydroponic germination of wheat grain

NASA Astrophysics Data System (ADS)

Koneva, M. S.; Rudenko, O. V.; Usatikov, S. V.; Bugaets, N. A.; Tereshchenko, I. V.

2018-05-01

To reduce the duration of the process and to ensure the microbiological purity of the germinated material, an improved method of germination has been developed based on the complex use of physical factors: electrochemically activated water (ECHA-water), electromagnetic field of extremely low frequencies (EMF ELF) with round-the-clock artificial illumination by LED lamps. The increase in the efficiency of the "numerical" technology for solving computational problems of parametric optimization of the technological process of hydroponic germination of wheat grains is considered. In this situation, the quality criteria are contradictory and part of them is given by implicit functions of many variables. A solution algorithm is offered without the construction of a Pareto set in which a relatively small number of elements of a set of alternatives is used to obtain a linear convolution of the criteria with given weights, normalized to their "ideal" values from the solution of the problems of single-criterion private optimizations. The use of the proposed mathematical models describing the processes of hydroponic germination of wheat grains made it possible to intensify the germination process and to shorten the time of obtaining wheat sprouts "Altayskaya 105" for 27 hours.

Conditional Optimal Design in Three- and Four-Level Experiments

ERIC Educational Resources Information Center

Hedges, Larry V.; Borenstein, Michael

2014-01-01

The precision of estimates of treatment effects in multilevel experiments depends on the sample sizes chosen at each level. It is often desirable to choose sample sizes at each level to obtain the smallest variance for a fixed total cost, that is, to obtain optimal sample allocation. This article extends previous results on optimal allocation to…

Automatic genetic optimization approach to two-dimensional blade profile design for steam turbines

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

Trigg, M.A.; Tubby, G.R.; Sheard, A.G.

1999-01-01

In this paper a systematic approach to the optimization of two-dimensional blade profiles is presented. A genetic optimizer has been developed that modifies the blade profile and calculates its profile loss. This process is automatic, producing profile designs significantly faster and with significantly lower loss than has previously been possible. The optimizer developed uses a genetic algorithm to optimize a two-dimensional profile, defined using 17 parameters, for minimum loss with a given flow condition. The optimizer works with a population of two-dimensional profiles with varied parameters. A CFD mesh is generated for each profile, and the result is analyzed usingmore » a two-dimensional blade-to-blade solver, written for steady viscous compressible flow, to determine profile loss. The loss is used as the measure of a profile`s fitness. The optimizer uses this information to select the members of the next population, applying crossovers, mutations, and elitism in the process. Using this method, the optimizer tends toward the best values for the parameters defining the profile with minimum loss.« less

Mean-Variance Portfolio Selection for Defined-Contribution Pension Funds with Stochastic Salary

PubMed Central

Zhang, Chubing

2014-01-01

This paper focuses on a continuous-time dynamic mean-variance portfolio selection problem of defined-contribution pension funds with stochastic salary, whose risk comes from both financial market and nonfinancial market. By constructing a special Riccati equation as a continuous (actually a viscosity) solution to the HJB equation, we obtain an explicit closed form solution for the optimal investment portfolio as well as the efficient frontier. PMID:24782667

Optimal satellite sampling to resolve global-scale dynamics in the I-T system

NASA Astrophysics Data System (ADS)

Rowland, D. E.; Zesta, E.; Connor, H. K.; Pfaff, R. F., Jr.

2016-12-01

The recent Decadal Survey highlighted the need for multipoint measurements of ion-neutral coupling processes to study the pathways by which solar wind energy drives dynamics in the I-T system. The emphasis in the Decadal Survey is on global-scale dynamics and processes, and in particular, mission concepts making use of multiple identical spacecraft in low earth orbit were considered for the GDC and DYNAMIC missions. This presentation will provide quantitative assessments of the optimal spacecraft sampling needed to significantly advance our knowledge of I-T dynamics on the global scale.We will examine storm time and quiet time conditions as simulated by global circulation models, and determine how well various candidate satellite constellations and satellite schemes can quantify the plasma and neutral convection patterns and global-scale distributions of plasma density, neutral density, and composition, and their response to changes in the IMF. While the global circulation models are data-starved, and do not contain all the physics that we might expect to observe with a global-scale constellation mission, they are nonetheless an excellent "starting point" for discussions of the implementation of such a mission. The result will be of great utility for the design of future missions, such as GDC, to study the global-scale dynamics of the I-T system.

Defining hypotension in moderate to severely injured trauma patients: raising the bar for the elderly.

PubMed

Edwards, Meghan; Ley, Eric; Mirocha, James; Hadjibashi, Anoushiravan Amini; Margulies, Daniel R; Salim, Ali

2010-10-01

Hypotension, defined as systolic blood pressure less than 90 mm Hg, is recognized as a sign of hemorrhagic shock and is a validated prognostic indicator. The definition of hypotension, particularly in the elderly population, deserves attention. We hypothesized that the systolic blood pressure associated with increased mortality resulting from hemorrhagic shock increases with increasing age. The Los Angeles County Trauma Database was queried for all moderate to severely injured patients without major head injuries admitted between 1998 and 2005. Several fit statistic analyses were performed for each systolic blood pressure from 50 to 180 mm Hg to identify the model that most accurately defined hypotension for three age groups. The optimal definition of hypotension for each group was determined from the best fit model. A total of 24,438 patients were analyzed. The optimal definition of hypotension was systolic blood pressure of 100 mm Hg for patients 20 to 49 years, 120 mm Hg for patients 50 to 69 years, and 140 mm Hg for patients 70 years and older. The optimal systolic blood pressure for improved mortality in hemorrhagic shock increases significantly with increasing age. Elderly trauma patients without major head injuries should be considered hypotensive for systolic blood pressure less than 140 mm Hg.

Parent driver characteristics associated with sub-optimal restraint of child passengers.

PubMed

Winston, Flaura K; Chen, Irene G; Smith, Rebecca; Elliott, Michael R

2006-12-01

To identify parent driver demographic and socioeconomic characteristics associated with the use of sub-optimal restraints for child passengers under nine years. Cross-sectional study using in-depth, validated telephone interviews with parent drivers in a probability sample of 3,818 vehicle crashes involving 5,146 children. Sub-optimal restraint was defined as use of forward-facing child safety seats for infants under one or weighing under 20 lbs, and any seat-belt use for children under 9. Sub-optimal restraint was more common among children under one and between four and eight years than among children aged one to three years (18%, 65%, and 5%, respectively). For children under nine, independent risk factors for sub-optimal restraint were: non-Hispanic black parent drivers (with non-Hispanic white parents as reference, adjusted relative risk, adjusted RR = 1.24, 95% CI: 1.09-1.41); less educated parents (with college graduate or above as reference: high school, adjusted RR = 1.27, 95% CI: 1.12-1.44; less than high school graduate, adjusted RR = 1.36, 95% CI: 1.13-1.63); and lower family income (with $50,000 or more as reference: <$20,000, adjusted RR = 1.23, 95% CI: 1.07-1.40). Multivariate analysis revealed the following independent risk factors for sub-optimal restraint among four-to-eight-year-olds: older parent age, limited education, black race, and income below $20,000. Parents with low educational levels or of non-Hispanic black background may require additional anticipatory guidance regarding child passenger safety. The importance of poverty in predicting sub-optimal restraint underscores the importance of child restraint and booster seat disbursement and education programs, potentially through Medicaid.

Defining a genetic ideotype for crop improvement.

PubMed

Trethowan, Richard M

2014-01-01

While plant breeders traditionally base selection on phenotype, the development of genetic ideotypes can help focus the selection process. This chapter provides a road map for the establishment of a refined genetic ideotype. The first step is an accurate definition of the target environment including the underlying constraints, their probability of occurrence, and impact on phenotype. Once the environmental constraints are established, the wealth of information on plant physiological responses to stresses, known gene information, and knowledge of genotype ×environment and gene × environment interaction help refine the target ideotype and form a basis for cross prediction.Once a genetic ideotype is defined the challenge remains to build the ideotype in a plant breeding program. A number of strategies including marker-assisted recurrent selection and genomic selection can be used that also provide valuable information for the optimization of genetic ideotype. However, the informatics required to underpin the realization of the genetic ideotype then becomes crucial. The reduced cost of genotyping and the need to combine pedigree, phenotypic, and genetic data in a structured way for analysis and interpretation often become the rate-limiting steps, thus reducing genetic gain. Systems for managing these data and an example of ideotype construction for a defined environment type are discussed.

Young investigator challenge: Validation and optimization of immunohistochemistry protocols for use on cellient cell block specimens.

PubMed

Sauter, Jennifer L; Grogg, Karen L; Vrana, Julie A; Law, Mark E; Halvorson, Jennifer L; Henry, Michael R

2016-02-01

The objective of the current study was to establish a process for validating immunohistochemistry (IHC) protocols for use on the Cellient cell block (CCB) system. Thirty antibodies were initially tested on CCBs using IHC protocols previously validated on formalin-fixed, paraffin-embedded tissue (FFPE). Cytology samples were split to generate thrombin cell blocks (TCB) and CCBs. IHC was performed in parallel. Antibody immunoreactivity was scored, and concordance or discordance in immunoreactivity between the TCBs and CCBs for each sample was determined. Criteria for validation of an antibody were defined as concordant staining in expected positive and negative cells, in at least 5 samples each, and concordance in at least 90% of the samples total. Antibodies that failed initial validation were retested after alterations in IHC conditions. Thirteen of the 30 antibodies (43%) did not meet initial validation criteria. Of those, 8 antibodies (calretinin, clusters of differentiation [CD] 3, CD20, CDX2, cytokeratin 20, estrogen receptor, MOC-31, and p16) were optimized for CCBs and subsequently validated. Despite several alterations in conditions, 3 antibodies (Ber-EP4, D2-40, and paired box gene 8 [PAX8]) were not successfully validated. Nearly one-half of the antibodies tested in the current study failed initial validation using IHC conditions that were established in the study laboratory for FFPE material. Although some antibodies subsequently met validation criteria after optimization of conditions, a few continued to demonstrate inadequate immunoreactivity. These findings emphasize the importance of validating IHC protocols for methanol-fixed tissue before clinical use and suggest that optimization for alcohol fixation may be needed to obtain adequate immunoreactivity on CCBs. © 2016 American Cancer Society.

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.

"Dermatitis" defined.

PubMed

Smith, Suzanne M; Nedorost, Susan T

2010-01-01

The term "dermatitis" can be defined narrowly or broadly, clinically or histologically. A common and costly condition, dermatitis is underresourced compared to other chronic skin conditions. The lack of a collectively understood definition of dermatitis and its subcategories could be the primary barrier. To investigate how dermatologists define the term "dermatitis" and determine if a consensus on the definition of this term and other related terms exists. A seven-question survey of dermatologists nationwide was conducted. Of respondents (n  =  122), half consider dermatitis to be any inflammation of the skin. Nearly half (47.5%) use the term interchangeably with "eczema." Virtually all (> 96%) endorse the subcategory "atopic" under the terms "dermatitis" and "eczema," but the subcategories "contact," "drug hypersensitivity," and "occupational" are more highly endorsed under the term "dermatitis" than under the term "eczema." Over half (55.7%) personally consider "dermatitis" to have a broad meaning, and even more (62.3%) believe that dermatologists as a whole define the term broadly. There is a lack of consensus among experts in defining dermatitis, eczema, and their related subcategories.

Optimization of dynamic headspace extraction system for measurement of halogenated volatile organic compounds in liquid or viscous samples

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.

Optimization of the solvent-based dissolution method to sample volatile organic compound vapors for compound-specific isotope analysis.

PubMed

Bouchard, Daniel; Wanner, Philipp; Luo, Hong; McLoughlin, Patrick W; Henderson, James K; Pirkle, Robert J; Hunkeler, Daniel

2017-10-20

The methodology of the solvent-based dissolution method used to sample gas phase volatile organic compounds (VOC) for compound-specific isotope analysis (CSIA) was optimized to lower the method detection limits for TCE and benzene. The sampling methodology previously evaluated by [1] consists in pulling the air through a solvent to dissolve and accumulate the gaseous VOC. After the sampling process, the solvent can then be treated similarly as groundwater samples to perform routine CSIA by diluting an aliquot of the solvent into water to reach the required concentration of the targeted contaminant. Among solvents tested, tetraethylene glycol dimethyl ether (TGDE) showed the best aptitude for the method. TGDE has a great affinity with TCE and benzene, hence efficiently dissolving the compounds during their transition through the solvent. The method detection limit for TCE (5±1μg/m 3 ) and benzene (1.7±0.5μg/m 3 ) is lower when using TGDE compared to methanol, which was previously used (385μg/m 3 for TCE and 130μg/m 3 for benzene) [2]. The method detection limit refers to the minimal gas phase concentration in ambient air required to load sufficient VOC mass into TGDE to perform δ 13 C analysis. Due to a different analytical procedure, the method detection limit associated with δ 37 Cl analysis was found to be 156±6μg/m 3 for TCE. Furthermore, the experimental results validated the relationship between the gas phase TCE and the progressive accumulation of dissolved TCE in the solvent during the sampling process. Accordingly, based on the air-solvent partitioning coefficient, the sampling methodology (e.g. sampling rate, sampling duration, amount of solvent) and the final TCE concentration in the solvent, the concentration of TCE in the gas phase prevailing during the sampling event can be determined. Moreover, the possibility to analyse for TCE concentration in the solvent after sampling (or other targeted VOCs) allows the field deployment of the sampling

Determining optimal gestational weight gain in a multiethnic Asian population.

PubMed

Ee, Tat Xin; Allen, John Carson; Malhotra, Rahul; Koh, Huishan; Østbye, Truls; Tan, Thiam Chye

2014-04-01

To define the optimal gestational weight gain (GWG) for the multiethnic Singaporean population. Data from 1529 live singleton deliveries was analyzed. A multinomial logistic regression analysis, with GWG as the predictor, was conducted to determine the lowest aggregated risk of a composite perinatal outcome, stratified by Asia-specific body mass index (BMI) categories. The composite perinatal outcome, based on a combination of delivery type (cesarean section [CS], vaginal delivery [VD]) and size for gestational age (small [SGA], appropriate [AGA], large [LGA]), had six categories: (i) VD with LGA; (ii) VD with SGA; (iii) CS with AGA; (iv) CS with SGA; (v) CS with LGA; (vi) and VD with AGA. The last was considered as the 'normal' reference category. In each BMI category, the GWG value corresponding to the lowest aggregated risk was defined as the optimal GWG, and the GWG values at which the aggregated risk did not exceed a 5% increase from the lowest aggregated risk were defined as the margins of the optimal GWG range. The optimal GWG by pre-pregnancy BMI category, was 19.5 kg (range, 12.9 to 23.9) for underweight, 13.7 kg (7.7 to 18.8) for normal weight, 7.9 kg (2.6 to 14.0) for overweight and 1.8 kg (-5.0 to 7.0) for obese. The results of this study, the first to determine optimal GWG in the multiethnic Singaporean population, concur with the Institute of Medicine (IOM) guidelines in that GWG among Asian women who are heavier prior to pregnancy, especially those who are obese, should be lower. However, the optimal GWG for underweight and obese women was outside the IOM recommended range. © 2014 The Authors. Journal of Obstetrics and Gynaecology Research © 2014 Japan Society of Obstetrics and Gynecology.

7 CFR 275.11 - Sampling.

Code of Federal Regulations, 2013 CFR

2013-01-01

... between 1 and k. The value of k is dependent upon the estimated size of the universe and the sample size... included in the active universe defined in paragraph (e)(1) of this section) during the annual review... review (i.e., households which are part of the negative universe defined in paragraph (e)(2) of this...

7 CFR 275.11 - Sampling.

Code of Federal Regulations, 2012 CFR

2012-01-01

... between 1 and k. The value of k is dependent upon the estimated size of the universe and the sample size... included in the active universe defined in paragraph (e)(1) of this section) during the annual review... review (i.e., households which are part of the negative universe defined in paragraph (e)(2) of this...

7 CFR 275.11 - Sampling.

Code of Federal Regulations, 2014 CFR

2014-01-01

... between 1 and k. The value of k is dependent upon the estimated size of the universe and the sample size... included in the active universe defined in paragraph (e)(1) of this section) during the annual review... review (i.e., households which are part of the negative universe defined in paragraph (e)(2) of this...

MCMC-ODPR: primer design optimization using Markov Chain Monte Carlo sampling.