Two-step optimization of pressure and recovery of reverse osmosis desalination process.

PubMed

Liang, Shuang; Liu, Cui; Song, Lianfa

2009-05-01

Driving pressure and recovery are two primary design variables of a reverse osmosis process that largely determine the total cost of seawater and brackish water desalination. A two-step optimization procedure was developed in this paper to determine the values of driving pressure and recovery that minimize the total cost of RO desalination. It was demonstrated that the optimal net driving pressure is solely determined by the electricity price and the membrane price index, which is a lumped parameter to collectively reflect membrane price, resistance, and service time. On the other hand, the optimal recovery is determined by the electricity price, initial osmotic pressure, and costs for pretreatment of raw water and handling of retentate. Concise equations were derived for the optimal net driving pressure and recovery. The dependences of the optimal net driving pressure and recovery on the electricity price, membrane price, and costs for raw water pretreatment and retentate handling were discussed.

Influence of moisture content, particle size and forming temperature on productivity and quality of rice straw pellets

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

Ishii, Kazuei, E-mail: k-ishii@eng.hokudai.ac.jp; Furuichi, Toru

Highlights: • Optimized conditions were determined for the production of rice straw pellets. • The moisture content and forming temperature are key factors. • High quality rice pellets in the lower heating value and durability were produced. - Abstract: A large amount of rice straw is generated and left as much in paddy fields, which causes greenhouse gas emissions as methane. Rice straw can be used as bioenergy. Rice straw pellets are a promising technology because pelletization of rice straw is a form of mass and energy densification, which leads to a product that is easy to handle, transport, storemore » and utilize because of the increase in the bulk density. The operational conditions required to produce high quality rice straw pellets have not been determined. This study determined the optimal moisture content range required to produce rice straw pellets with high yield ratio and high heating value, and also determined the influence of particle size and the forming temperature on the yield ratio and durability of rice straw pellets. The optimal moisture content range was between 13% and 20% under a forming temperature of 60 or 80 °C. The optimal particle size was between 10 and 20 mm, considering the time and energy required for shredding, although the particle size did not significantly affect the yield ratio and durability of the pellets. The optimized conditions provided high quality rice straw pellets with nearly 90% yield ratio, ⩾12 MJ/kg for the lower heating value, and >95% durability.« less

Accounting for between-study variation in incremental net benefit in value of information methodology.

PubMed

Willan, Andrew R; Eckermann, Simon

2012-10-01

Previous applications of value of information methods for determining optimal sample size in randomized clinical trials have assumed no between-study variation in mean incremental net benefit. By adopting a hierarchical model, we provide a solution for determining optimal sample size with this assumption relaxed. The solution is illustrated with two examples from the literature. Expected net gain increases with increasing between-study variation, reflecting the increased uncertainty in incremental net benefit and reduced extent to which data are borrowed from previous evidence. Hence, a trial can become optimal where current evidence is sufficient assuming no between-study variation. However, despite the expected net gain increasing, the optimal sample size in the illustrated examples is relatively insensitive to the amount of between-study variation. Further percentage losses in expected net gain were small even when choosing sample sizes that reflected widely different between-study variation. Copyright © 2011 John Wiley & Sons, Ltd.

Cutoff value of thyroid uptake of (99m)Tc-pertechnetate to discriminate between Graves' disease and painless thyroiditis: a single center retrospective study.

PubMed

Uchida, Toyoyoshi; Suzuki, Ruriko; Kasai, Takatoshi; Onose, Hiroyuki; Komiya, Koji; Goto, Hiromasa; Takeno, Kageumi; Ishii, Shinya; Sato, Junko; Honda, Akira; Kawano, Yui; Himuro, Miwa; Yamada, Emiko; Yamada, Tetsu; Watada, Hirotaka

2016-01-01

Thyroid uptake of (99m)Tc-pertechnetate is a useful way to determine the cause of thyrotoxicosis. In daily clinical practice, (99m)Tc-pertechnetate uptake is used to discriminate between Graves' disease and painless thyroiditis when clinical information is not enough to make the distinction. However, since the optimal cutoff value of (99m)Tc-pertechnetate uptake has not yet been elucidated, our aim was to determine this value. We recruited patients with thyrotoxicosis in whom (99m)Tc-pertechnetate uptake was measured in clinical settings between 2009 and 2013. Three experienced endocrinologists (who were blinded to the value of (99m)Tc-pertechnetate uptake and initial treatment) diagnosed the cause of thyrotoxicosis based on thyrotropin, free triiodothyronine, free thyroxine, and thyrotropin receptor antibody levels, and by ultrasound findings and using images of thyroid uptake of (99m)Tc-pertechnetate without the actual values. Ninety-four patients diagnosed as having Graves' disease or painless thyroiditis were finally included. According to the diagnosis, the optimal cutoff value of (99m)Tc-pertechnetate uptake was determined by receiver operating characteristics analysis. A cutoff value of 1.0% provided optimal sensitivity and specificity of 96.6% and 97.1%, respectively. Then, its validity was confirmed in 78 patients with confirmed Graves' disease or painless thyroiditis diagnosed at another institute. Applying this cutoff value to the patients with thyrotoxicosis revealed positive and negative predictive values for Graves' disease of 100% and 88.9%, respectively. In conclusion, a cutoff value for (99m)Tc-pertechnetate uptake of 1.0% was useful to discriminate between Graves' disease and painless thyroiditis.

Apparent diffusion coefficient in the analysis of prostate cancer: determination of optimal b-value pair to differentiate normal from malignant tissue.

PubMed

Adubeiro, Nuno; Nogueira, Maria Luísa; Nunes, Rita G; Ferreira, Hugo Alexandre; Ribeiro, Eduardo; La Fuente, José Maria Ferreira

Determining optimal b-value pair for differentiation between normal and prostate cancer (PCa) tissues. Forty-three patients with diagnosis or PCa symptoms were included. Apparent diffusion coefficient (ADC) was estimated using minimum and maximum b-values of 0, 50, 100, 150, 200, 500s/mm2 and 500, 800, 1100, 1400, 1700 and 2000s/mm2, respectively. Diagnostic performances were evaluated when Area-under-the-curve (AUC)>95%. 15 of the 35 b-values pair surpassed this AUC threshold. The pair (50, 2000s/mm2) provided the highest AUC (96%) with ADC cutoff 0.89×10- 3 mm 2 /s, sensitivity 95.5%, specificity 93.2% and accuracy 94.4%. The best b-value pair was b=50, 2000s/mm2. Copyright © 2017 Elsevier Inc. All rights reserved.

The 2013 Frank Stinchfield Award: Diagnosis of infection in the early postoperative period after total hip arthroplasty.

PubMed

Yi, Paul H; Cross, Michael B; Moric, Mario; Sporer, Scott M; Berger, Richard A; Della Valle, Craig J

2014-02-01

Diagnosis of periprosthetic joint infection (PJI) can be difficult in the early postoperative period after total hip arthroplasty (THA) because normal cues from the physical examination often are unreliable, and serological markers commonly used for diagnosis are elevated from the recent surgery. The purposes of this study were to determine the optimal cutoff values for erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), synovial fluid white blood cell (WBC) count, and differential for diagnosing PJI in the early postoperative period after primary THA. We reviewed 6033 consecutive primary THAs and identified 73 patients (1.2%) who underwent reoperation for any reason within the first 6 weeks postoperatively. Thirty-six of these patients were infected according to modified Musculoskeletal Infection Society criteria. Mean values for the diagnostic tests were compared between groups and receiver operating characteristic curves generated along with an area under the curve (AUC) to determine test performance and optimal cutoff values to diagnose infection. The best test for the diagnosis of PJI was the synovial fluid WBC count (AUC = 98%; optimal cutoff value 12,800 cells/μL) followed by the CRP (AUC = 93%; optimal cutoff value 93 mg/L), and synovial fluid differential (AUC = 91%; optimal cutoff value 89% PMN). The mean ESR (infected = 69 mm/hr, not infected = 46 mm/hr), CRP (infected = 192 mg/L, not infected = 30 mg/L), synovial fluid WBC count (infected = 84,954 cells/μL, not infected = 2391 cells/μL), and differential (infected = 91% polymorphonuclear cells [PMN], not infected = 63% PMN) all were significantly higher in the infected group. Optimal cutoff values for the diagnosis of PJI in the acute postoperative period were higher than those traditionally used for the diagnosis of chronic PJI. The serum CRP is an excellent screening test, whereas the synovial fluid WBC count is more specific.

Mixture optimization for mixed gas Joule-Thomson cycle

NASA Astrophysics Data System (ADS)

Detlor, J.; Pfotenhauer, J.; Nellis, G.

2017-12-01

An appropriate gas mixture can provide lower temperatures and higher cooling power when used in a Joule-Thomson (JT) cycle than is possible with a pure fluid. However, selecting gas mixtures to meet specific cooling loads and cycle parameters is a challenging design problem. This study focuses on the development of a computational tool to optimize gas mixture compositions for specific operating parameters. This study expands on prior research by exploring higher heat rejection temperatures and lower pressure ratios. A mixture optimization model has been developed which determines an optimal three-component mixture based on the analysis of the maximum value of the minimum value of isothermal enthalpy change, ΔhT , that occurs over the temperature range. This allows optimal mixture compositions to be determined for a mixed gas JT system with load temperatures down to 110 K and supply temperatures above room temperature for pressure ratios as small as 3:1. The mixture optimization model has been paired with a separate evaluation of the percent of the heat exchanger that exists in a two-phase range in order to begin the process of selecting a mixture for experimental investigation.

Optimal trajectories of aircraft and spacecraft

NASA Technical Reports Server (NTRS)

Miele, A.

1990-01-01

Work done on algorithms for the numerical solutions of optimal control problems and their application to the computation of optimal flight trajectories of aircraft and spacecraft is summarized. General considerations on calculus of variations, optimal control, numerical algorithms, and applications of these algorithms to real-world problems are presented. The sequential gradient-restoration algorithm (SGRA) is examined for the numerical solution of optimal control problems of the Bolza type. Both the primal formulation and the dual formulation are discussed. Aircraft trajectories, in particular, the application of the dual sequential gradient-restoration algorithm (DSGRA) to the determination of optimal flight trajectories in the presence of windshear are described. Both take-off trajectories and abort landing trajectories are discussed. Take-off trajectories are optimized by minimizing the peak deviation of the absolute path inclination from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. The survival capability of an aircraft in a severe windshear is discussed, and the optimal trajectories are found to be superior to both constant pitch trajectories and maximum angle of attack trajectories. Spacecraft trajectories, in particular, the application of the primal sequential gradient-restoration algorithm (PSGRA) to the determination of optimal flight trajectories for aeroassisted orbital transfer are examined. Both the coplanar case and the noncoplanar case are discussed within the frame of three problems: minimization of the total characteristic velocity; minimization of the time integral of the square of the path inclination; and minimization of the peak heating rate. The solution of the second problem is called nearly-grazing solution, and its merits are pointed out as a useful engineering compromise between energy requirements and aerodynamics heating requirements.

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

NASA Astrophysics Data System (ADS)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters.

Comparison and optimization of radar-based hail detection algorithms in Slovenia

NASA Astrophysics Data System (ADS)

Stržinar, Gregor; Skok, Gregor

2018-05-01

Four commonly used radar-based hail detection algorithms are evaluated and optimized in Slovenia. The algorithms are verified against ground observations of hail at manned stations in the period between May and August, from 2002 to 2010. The algorithms are optimized by determining the optimal values of all possible algorithm parameters. A number of different contingency-table-based scores are evaluated with a combination of Critical Success Index and frequency bias proving to be the best choice for optimization. The best performance indexes are given by Waldvogel and the severe hail index, followed by vertically integrated liquid and maximum radar reflectivity. Using the optimal parameter values, a hail frequency climatology map for the whole of Slovenia is produced. The analysis shows that there is a considerable variability of hail occurrence within the Republic of Slovenia. The hail frequency ranges from almost 0 to 1.7 hail days per year with an average value of about 0.7 hail days per year.

Harmony search optimization for HDR prostate brachytherapy

NASA Astrophysics Data System (ADS)

Panchal, Aditya

In high dose-rate (HDR) prostate brachytherapy, multiple catheters are inserted interstitially into the target volume. The process of treating the prostate involves calculating and determining the best dose distribution to the target and organs-at-risk by means of optimizing the time that the radioactive source dwells at specified positions within the catheters. It is the goal of this work to investigate the use of a new optimization algorithm, known as Harmony Search, in order to optimize dwell times for HDR prostate brachytherapy. The new algorithm was tested on 9 different patients and also compared with the genetic algorithm. Simulations were performed to determine the optimal value of the Harmony Search parameters. Finally, multithreading of the simulation was examined to determine potential benefits. First, a simulation environment was created using the Python programming language and the wxPython graphical interface toolkit, which was necessary to run repeated optimizations. DICOM RT data from Varian BrachyVision was parsed and used to obtain patient anatomy and HDR catheter information. Once the structures were indexed, the volume of each structure was determined and compared to the original volume calculated in BrachyVision for validation. Dose was calculated using the AAPM TG-43 point source model of the GammaMed 192Ir HDR source and was validated against Varian BrachyVision. A DVH-based objective function was created and used for the optimization simulation. Harmony Search and the genetic algorithm were implemented as optimization algorithms for the simulation and were compared against each other. The optimal values for Harmony Search parameters (Harmony Memory Size [HMS], Harmony Memory Considering Rate [HMCR], and Pitch Adjusting Rate [PAR]) were also determined. Lastly, the simulation was modified to use multiple threads of execution in order to achieve faster computational times. Experimental results show that the volume calculation that was implemented in this thesis was within 2% of the values computed by Varian BrachyVision for the prostate, within 3% for the rectum and bladder and 6% for the urethra. The calculation of dose compared to BrachyVision was determined to be different by only 0.38%. Isodose curves were also generated and were found to be similar to BrachyVision. The comparison between Harmony Search and genetic algorithm showed that Harmony Search was over 4 times faster when compared over multiple data sets. The optimal Harmony Memory Size was found to be 5 or lower; the Harmony Memory Considering Rate was determined to be 0.95, and the Pitch Adjusting Rate was found to be 0.9. Ultimately, the effect of multithreading showed that as intensive computations such as optimization and dose calculation are involved, the threads of execution scale with the number of processors, achieving a speed increase proportional to the number of processor cores. In conclusion, this work showed that Harmony Search is a viable alternative to existing algorithms for use in HDR prostate brachytherapy optimization. Coupled with the optimal parameters for the algorithm and a multithreaded simulation, this combination has the capability to significantly decrease the time spent on minimizing optimization problems in the clinic that are time intensive, such as brachytherapy, IMRT and beam angle optimization.

Cut-off optimization for 13C-urea breath test in a community-based trial by mathematic, histology and serology approach.

PubMed

Li, Zhe-Xuan; Huang, Lei-Lei; Liu, Cong; Formichella, Luca; Zhang, Yang; Wang, Yu-Mei; Zhang, Lian; Ma, Jun-Ling; Liu, Wei-Dong; Ulm, Kurt; Wang, Jian-Xi; Zhang, Lei; Bajbouj, Monther; Li, Ming; Vieth, Michael; Quante, Michael; Zhou, Tong; Wang, Le-Hua; Suchanek, Stepan; Soutschek, Erwin; Schmid, Roland; Classen, Meinhard; You, Wei-Cheng; Gerhard, Markus; Pan, Kai-Feng

2017-05-18

The performance of diagnostic tests in intervention trials of Helicobacter pylori (H.pylori) eradication is crucial, since even minor inaccuracies can have major impact. To determine the cut-off point for 13 C-urea breath test ( 13 C-UBT) and to assess if it can be further optimized by serologic testing, mathematic modeling, histopathology and serologic validation were applied. A finite mixture model (FMM) was developed in 21,857 subjects, and an independent validation by modified Giemsa staining was conducted in 300 selected subjects. H.pylori status was determined using recomLine H.pylori assay in 2,113 subjects with a borderline 13 C-UBT results. The delta over baseline-value (DOB) of 3.8 was an optimal cut-off point by a FMM in modelling dataset, which was further validated as the most appropriate cut-off point by Giemsa staining (sensitivity = 94.53%, specificity = 92.93%). In the borderline population, 1,468 subjects were determined as H.pylori positive by recomLine (69.5%). A significant correlation between the number of positive H.pylori serum responses and DOB value was found (r s  = 0.217, P < 0.001). A mathematical approach such as FMM might be an alternative measure in optimizing the cut-off point for 13 C-UBT in community-based studies, and a second method to determine H.pylori status for subjects with borderline value of 13 C-UBT was necessary and recommended.

A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process

NASA Astrophysics Data System (ADS)

Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa

2017-06-01

High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio ( S/ N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166 °C, Dimmer speed at 08 rpm, and Die head temperature to be 192 °C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.

The prognostic value of functional and anatomical parameters for the selection of patients receiving yttrium-90 microspheres for the treatment of liver cancer

NASA Astrophysics Data System (ADS)

Mesoloras, Geraldine

Yttrium-90 (90Y) microsphere therapy is being utilized as a treatment option for patients with primary and metastatic liver cancer due to its ability to target tumors within the liver. The success of this treatment is dependent on many factors, including the extent and type of disease and the nature of prior treatments received. Metabolic activity, as determined by PET imaging, may correlate with the number of viable cancer cells and reflect changes in viable cancer cell volume. However, contouring of PET images by hand is labor intensive and introduces an element of irreproducibility into the determination of functional target/tumor volume (FTV). A computer-assisted method to aid in the automatic contouring of FTV has the potential to substantially improve treatment individualization and outcome assessment. Commercial software to determine FTV in FDG-avid primary and metastatic liver tumors has been evaluated and optimized. Volumes determined using the automated technique were compared to those from manually drawn contours identified using the same cutoff in the standard uptake value (SUV). The reproducibility of FTV is improved through the introduction of an optimal threshold value determined from phantom experiments. Application of the optimal threshold value from the phantom experiments to patient scans was in good agreement with hand-drawn determinations of the FTV. It is concluded that computer-assisted contouring of the FTV for primary and metastatic liver tumors improves reproducibility and increases accuracy, especially when combined with the selection of an optimal SUV threshold determined from phantom experiments. A method to link the pre-treatment assessment of functional (PET based) and anatomical (CT based) parameters to post-treatment survival and time to progression was evaluated in 22 patients with colorectal cancer liver metastases treated using 90Y microspheres and chemotherapy. The values for pre-treatment parameters that were the best predictors of response were determined for FTV, anatomical tumor volume, total lesion glycolysis, and the tumor marker, CEA. Of the parameters considered, the best predictors of response were found to be pre-treatment FTV ≤153 cm3, ATV ≤163 cm3, TLG ≤144 g in the chemo-SIRT treated field, and CEA ≤11.6 ng/mL.

Prospective Study of Optimal Obesity Index Cut-Off Values for Predicting Incidence of Hypertension in 18–65-Year-Old Chinese Adults

PubMed Central

Ren, Qian; Su, Chang; Wang, Huijun; Wang, Zhihong; Du, Wenwen; Zhang, Bing

2016-01-01

Background Overweight and obesity increase the risk of elevated blood pressure; most of the studies that serve as a background for the debates on the optimal obesity index cut-off values used cross-sectional samples. The aim of this study was to determine the cut-off values of anthropometric markers for detecting hypertension in Chinese adults with data from prospective cohort. Methods This study determines the best cut-off values for the obesity indices that represent elevated incidence of hypertension in 18–65-year-old Chinese adults using data from the China Health and Nutrition Survey (CHNS) 2006–2011 prospective cohort. Individual body mass index (BMI), waist circumference (WC), waist:hip ratio (WHR) and waist:stature ratio (WSR) were assessed. ROC curves for these obesity indices were plotted to estimate and compare the usefulness of these obesity indices and the corresponding values for the maximum of the Youden indices were considered the optimal cut-off values. Results Five-year cumulative incidences of hypertension were 21.5% (95% CI: 19.4–23.6) in men and 16.5% (95% CI: 14.7–18.2) in women, and there was a significant trend of increased incidence of hypertension with an increase in BMI, WC, WHR or WSR (P for trend < 0.001) in both men and women. The Youden index indicated that the optimal BMI, WC, WHR, WSR cut-off values were 23.53 kg/m2, 83.7 cm, 0.90, and 0.51 among men. The optimal BMI, WC, WHR, WSR cut-off values were 24.25 kg/m2, 79.9 cm, 0.85 and 0.52 among women. Conclusions Our study supported the hypothesis that the cut-off values for BMI and WC that were recently developed by the Working Group on Obesity in China (WGOC), the cut-off values for WHR that were developed by the World Health Organization (WHO), and a global WSR cut-off value of 0.50 may be the appropriate upper limits for Chinese adults. PMID:26934390

Weighted sum of gray gases model optimization for numerical investigations of processes inside pulverized coal-fired furnaces

NASA Astrophysics Data System (ADS)

Crnomarkovic, Nenad; Belosevic, Srdjan; Tomanovic, Ivan; Milicevic, Aleksandar

2017-12-01

The effects of the number of significant figures (NSF) in the interpolation polynomial coefficients (IPCs) of the weighted sum of gray gases model (WSGM) on results of numerical investigations and WSGM optimization were investigated. The investigation was conducted using numerical simulations of the processes inside a pulverized coal-fired furnace. The radiative properties of the gas phase were determined using the simple gray gas model (SG), two-term WSGM (W2), and three-term WSGM (W3). Ten sets of the IPCs with the same NSF were formed for every weighting coefficient in both W2 and W3. The average and maximal relative difference values of the flame temperatures, wall temperatures, and wall heat fluxes were determined. The investigation showed that the results of numerical investigations were affected by the NSF unless it exceeded certain value. The increase in the NSF did not necessarily lead to WSGM optimization. The combination of the NSF (CNSF) was the necessary requirement for WSGM optimization.

Determination of the optimized single-layer ionospheric height for electron content measurements over China

NASA Astrophysics Data System (ADS)

Li, Min; Yuan, Yunbin; Zhang, Baocheng; Wang, Ningbo; Li, Zishen; Liu, Xifeng; Zhang, Xiao

2018-02-01

The ionosphere effective height (IEH) is a very important parameter in total electron content (TEC) measurements under the widely used single-layer model assumption. To overcome the requirement of a large amount of simultaneous vertical and slant ionospheric observations or dense "coinciding" pierce points data, a new approach comparing the converted vertical TEC (VTEC) value using mapping function based on a given IEH with the "ground truth" VTEC value provided by the combined International GNSS Service Global Ionospheric Maps is proposed for the determination of the optimal IEH. The optimal IEH in the Chinese region is determined using three different methods based on GNSS data. Based on the ionosonde data from three different locations in China, the altitude variation of the peak electron density (hmF2) is found to have clear diurnal, seasonal and latitudinal dependences, and the diurnal variation of hmF2 varies from approximately 210 to 520 km in Hainan. The determination of the optimal IEH employing the inverse method suggested by Birch et al. (Radio Sci 37, 2002. doi: 10.1029/2000rs002601) did not yield a consistent altitude in the Chinese region. Tests of the method minimizing the mapping function errors suggested by Nava et al. (Adv Space Res 39:1292-1297, 2007) indicate that the optimal IEH ranges from 400 to 600 km, and the height of 450 km is the most frequent IEH at both high and low solar activities. It is also confirmed that the IEH of 450-550 km is preferred for the Chinese region instead of the commonly adopted 350-450 km using the determination method of the optimal IEH proposed in this paper.

Protein dielectric constants determined from NMR chemical shift perturbations.

PubMed

Kukic, Predrag; Farrell, Damien; McIntosh, Lawrence P; García-Moreno E, Bertrand; Jensen, Kristine Steen; Toleikis, Zigmantas; Teilum, Kaare; Nielsen, Jens Erik

2013-11-13

Understanding the connection between protein structure and function requires a quantitative understanding of electrostatic effects. Structure-based electrostatic calculations are essential for this purpose, but their use has been limited by a long-standing discussion on which value to use for the dielectric constants (ε(eff) and ε(p)) required in Coulombic and Poisson-Boltzmann models. The currently used values for ε(eff) and ε(p) are essentially empirical parameters calibrated against thermodynamic properties that are indirect measurements of protein electric fields. We determine optimal values for ε(eff) and ε(p) by measuring protein electric fields in solution using direct detection of NMR chemical shift perturbations (CSPs). We measured CSPs in 14 proteins to get a broad and general characterization of electric fields. Coulomb's law reproduces the measured CSPs optimally with a protein dielectric constant (ε(eff)) from 3 to 13, with an optimal value across all proteins of 6.5. However, when the water-protein interface is treated with finite difference Poisson-Boltzmann calculations, the optimal protein dielectric constant (ε(p)) ranged from 2 to 5 with an optimum of 3. It is striking how similar this value is to the dielectric constant of 2-4 measured for protein powders and how different it is from the ε(p) of 6-20 used in models based on the Poisson-Boltzmann equation when calculating thermodynamic parameters. Because the value of ε(p) = 3 is obtained by analysis of NMR chemical shift perturbations instead of thermodynamic parameters such as pK(a) values, it is likely to describe only the electric field and thus represent a more general, intrinsic, and transferable ε(p) common to most folded proteins.

Determination of the Spatial Distribution in Hydraulic Conductivity Using Genetic Algorithm Optimization

NASA Astrophysics Data System (ADS)

Aksoy, A.; Lee, J. H.; Kitanidis, P. K.

2016-12-01

Heterogeneity in hydraulic conductivity (K) impacts the transport and fate of contaminants in subsurface as well as design and operation of managed aquifer recharge (MAR) systems. Recently, improvements in computational resources and availability of big data through electrical resistivity tomography (ERT) and remote sensing have provided opportunities to better characterize the subsurface. Yet, there is need to improve prediction and evaluation methods in order to obtain information from field measurements for better field characterization. In this study, genetic algorithm optimization, which has been widely used in optimal aquifer remediation designs, was used to determine the spatial distribution of K. A hypothetical 2 km by 2 km aquifer was considered. A genetic algorithm library, PGAPack, was linked with a fast Fourier transform based random field generator as well as a groundwater flow and contaminant transport simulation model (BIO2D-KE). The objective of the optimization model was to minimize the total squared error between measured and predicted field values. It was assumed measured K values were available through ERT. Performance of genetic algorithm in predicting the distribution of K was tested for different cases. In the first one, it was assumed that observed K values were evaluated using the random field generator only as the forward model. In the second case, as well as K-values obtained through ERT, measured head values were incorporated into evaluation in which BIO2D-KE and random field generator were used as the forward models. Lastly, tracer concentrations were used as additional information in the optimization model. Initial results indicated enhanced performance when random field generator and BIO2D-KE are used in combination in predicting the spatial distribution in K.

Validation of a dye stain assay for vaginally inserted HEC-filled microbicide applicators

PubMed Central

Katzen, Lauren L.; Fernández-Romero, José A.; Sarna, Avina; Murugavel, Kailapuri G.; Gawarecki, Daniel; Zydowsky, Thomas M.; Mensch, Barbara S.

2011-01-01

Background The reliability and validity of self-reports of vaginal microbicide use are questionable given the explicit understanding that participants are expected to comply with study protocols. Our objective was to optimize the Population Council's previously validated dye stain assay (DSA) and related procedures, and establish predictive values for the DSA's ability to identify vaginally inserted single-use, low-density polyethylene microbicide applicators filled with hydroxyethylcellulose gel. Methods Applicators, inserted by 252 female sex workers enrolled in a microbicide feasibility study in Southern India, served as positive controls for optimization and validation experiments. Prior to validation, optimal dye concentration and staining time were ascertained. Three validation experiments were conducted to determine sensitivity, specificity, negative predictive values and positive predictive values. Results The dye concentration of 0.05% (w/v) FD&C Blue No. 1 Granular Food Dye and staining time of five seconds were determined to be optimal and were used for the three validation experiments. There were a total of 1,848 possible applicator readings across validation experiments; 1,703 (92.2%) applicator readings were correct. On average, the DSA performed with 90.6% sensitivity, 93.9% specificity, and had a negative predictive value of 93.8% and a positive predictive value of 91.0%. No statistically significant differences between experiments were noted. Conclusions The DSA was optimized and successfully validated for use with single-use, low-density polyethylene applicators filled with hydroxyethylcellulose (HEC) gel. We recommend including the DSA in future microbicide trials involving vaginal gels in order to identify participants who have low adherence to dosing regimens. In doing so, we can develop strategies to improve adherence as well as investigate the association between product use and efficacy. PMID:21992983

Simulation Research on Vehicle Active Suspension Controller Based on G1 Method

NASA Astrophysics Data System (ADS)

Li, Gen; Li, Hang; Zhang, Shuaiyang; Luo, Qiuhui

2017-09-01

Based on the order relation analysis method (G1 method), the optimal linear controller of vehicle active suspension is designed. The system of the main and passive suspension of the single wheel vehicle is modeled and the system input signal model is determined. Secondly, the system motion state space equation is established by the kinetic knowledge and the optimal linear controller design is completed with the optimal control theory. The weighting coefficient of the performance index coefficients of the main passive suspension is determined by the relational analysis method. Finally, the model is simulated in Simulink. The simulation results show that: the optimal weight value is determined by using the sequence relation analysis method under the condition of given road conditions, and the vehicle acceleration, suspension stroke and tire motion displacement are optimized to improve the comprehensive performance of the vehicle, and the active control is controlled within the requirements.

The optimized V-V interval determined by interventricular conduction times versus invasive measurement by LVdP/dtMAX.

PubMed

van Gelder, Berry M; Meijer, Albert; Bracke, Frank A

2008-09-01

We compared the calculated optimal V-V interval derived from intracardiac electrograms (IEGM) with the optimized V-V interval determined by invasive measurement of LVdP/dt(MAX). Thirty-two patients with heart failure (six females, ages 68 +/- 7.8 years) had a CRT device implanted. After implantation of the atrial, right and a left ventricular lead, the optimal V-V interval was calculated using the QuickOpt formula (St. Jude Medical, Sylmar, CA, USA) applied to the respective IEGM recordings (V-V(IEGM)), and also determined by invasive measurement of LVdP/dt(MAX) (V-V(dP/dt)). The optimal V-V(IEGM) and V-V(dP/dt) intervals were 52.7 +/- 18 ms and 24.0 +/- 33 ms, respectively (P = 0.017), without correlation between the two. The baseline LVdP/dt(MAX) was 748 +/- 191 mmHg/s. The mean value of LVdP/dt(MAX) at invasive optimization was 947 +/- 198 mmHg/s, and at the calculated optimal V-V(IEGM) interval 920 +/- 191 mmHg/s (P < 0.0001). In spite of this significant difference, there was a good correlation between both methods (R = 0.991, P < 0.0001). However, a similarly good correlation existed between the maximum value of LVdP/dt(MAX) and LVdP/dt(MAX) at a fixed V-V interval of 0 ms (R = 0.993, P < 0.0001), or LVdP/dt(MAX) at a randomly selected V-V interval between 0 and +80 ms (R = 0.991, P < 0.0001). Optimizing the V-V interval with the IEGM method does not yield better hemodynamic results than simultaneous BiV pacing. Although a good correlation between LVdP/dt(MAX) determined with V-V(IEGM) and V-V(dP/dt) can be constructed, there is no correlation with the optimal settings of V-V interval in the individual patient.

Application of particle swarm optimization in path planning of mobile robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.

Multi Objective Controller Design for Linear System via Optimal Interpolation

NASA Technical Reports Server (NTRS)

Ozbay, Hitay

1996-01-01

We propose a methodology for the design of a controller which satisfies a set of closed-loop objectives simultaneously. The set of objectives consists of: (1) pole placement, (2) decoupled command tracking of step inputs at steady-state, and (3) minimization of step response transients with respect to envelope specifications. We first obtain a characterization of all controllers placing the closed-loop poles in a prescribed region of the complex plane. In this characterization, the free parameter matrix Q(s) is to be determined to attain objectives (2) and (3). Objective (2) is expressed as determining a Pareto optimal solution to a vector valued optimization problem. The solution of this problem is obtained by transforming it to a scalar convex optimization problem. This solution determines Q(O) and the remaining freedom in choosing Q(s) is used to satisfy objective (3). We write Q(s) = (l/v(s))bar-Q(s) for a prescribed polynomial v(s). Bar-Q(s) is a polynomial matrix which is arbitrary except that Q(O) and the order of bar-Q(s) are fixed. Obeying these constraints bar-Q(s) is now to be 'shaped' to minimize the step response characteristics of specific input/output pairs according to the maximum envelope violations. This problem is expressed as a vector valued optimization problem using the concept of Pareto optimality. We then investigate a scalar optimization problem associated with this vector valued problem and show that it is convex. The organization of the report is as follows. The next section includes some definitions and preliminary lemmas. We then give the problem statement which is followed by a section including a detailed development of the design procedure. We then consider an aircraft control example. The last section gives some concluding remarks. The Appendix includes the proofs of technical lemmas, printouts of computer programs, and figures.

The initial-value problem for viscous channel flows

NASA Technical Reports Server (NTRS)

Criminale, W. O.; Jackson, T. L.; Lasseigne, D. G.

1995-01-01

Plane viscous channel flows are perturbed and the ensuing initial-value problems are investigated in detail. Unlike traditional methods where traveling wave normal modes are assumed for solution, this works offers a means whereby completely arbitrary initial input can be specified without having to resort to eigenfunction expansions. The full temporal behavior, including both early time transients and the long time asymptotics, can be determined for any initial disturbance. Effects of three-dimensionality can be assessed. The bases for the analysis are: (a) linearization of the governing equations; (b) Fourier decomposition in the spanwise and streamwise directions of the flow; and (c) direct numerical integration of the resulting partial differential equations. All of the stability data that are known for such flows can be reproduced. Also, the optimal initial condition can be determined in a straight forward manner and such optimal conditions clearly reflect transient growth data that is easily determined by a rational choice of a basis for the initial conditions. Although there can be significant transient growth for subcritical values of the Reynolds number using this approach it does not appear possible that arbitrary initial conditions will lead to the exceptionally large transient amplitudes that have been determined by optimization of normal modes. The approach is general and can be applied to other classes of problems where only a finite discrete spectrum exists, such as the boundary layer for example.

Use of mathematical decomposition to optimize investments in gas production and distribution

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

Dougherty, E.L.; Lombardino, E.; Hutchinson, P.

1986-01-01

This paper presents an analytical approach based upon the decomposition method of mathematical programming for determining the optimal investment sequence in each year of a planning horizon for a group of reservoirs that produce gas and gas liquids through a trunk-line network and a gas processing plant. The paper describes the development of the simulation and investment planning system (SIPS) to perform the required calculations. Net present value (NPV) is maximized with the requirement that the incremental present value ratio (PWPI) of any investment in any reservoir be greater than a specified minimum value. A unique feature is a gasmore » reservoir simulation model that aids SIPS in evaluating field development investments. The optimal solution supplies specified dry gas offtake requirements through time until the remaining reserves are insufficient to meet requirements economically. The sales value of recovered liquids contributes significantly to NPV, while the required spare gas-producing capacity reduces NPV. Sips was used successfully for 4 years to generate annual investment plans and operating budgets, and to perform many special studies for a producing complex containing over 50 reservoirs. This experience is reviewed. In considering this large problem, SIPS converges to the optimal solution in 10 to 20 iterations. The primary factor that determines this number is how good the starting guess is. Although sips can generate a starting guess, beginning with a previous optimal solution ordinarily results in faster convergence. Computing time increases in proportion to the number of reservoirs because more than 90% of computing time is spent solving the, reservoir, subproblems.« less

Identifying messaging completion in a parallel computer by checking for change in message received and transmitted count at each node

DOEpatents

Archer, Charles J [Rochester, MN; Hardwick, Camesha R [Fayetteville, NC; McCarthy, Patrick J [Rochester, MN; Wallenfelt, Brian P [Eden Prairie, MN

2009-06-23

Methods, parallel computers, and products are provided for identifying messaging completion on a parallel computer. The parallel computer includes a plurality of compute nodes, the compute nodes coupled for data communications by at least two independent data communications networks including a binary tree data communications network optimal for collective operations that organizes the nodes as a tree and a torus data communications network optimal for point to point operations that organizes the nodes as a torus. Embodiments include reading all counters at each node of the torus data communications network; calculating at each node a current node value in dependence upon the values read from the counters at each node; and determining for all nodes whether the current node value for each node is the same as a previously calculated node value for each node. If the current node is the same as the previously calculated node value for all nodes of the torus data communications network, embodiments include determining that messaging is complete and if the current node is not the same as the previously calculated node value for all nodes of the torus data communications network, embodiments include determining that messaging is currently incomplete.

Optimal quantum observables

NASA Astrophysics Data System (ADS)

Haapasalo, Erkka; Pellonpää, Juha-Pekka

2017-12-01

Various forms of optimality for quantum observables described as normalized positive-operator-valued measures (POVMs) are studied in this paper. We give characterizations for observables that determine the values of the measured quantity with probabilistic certainty or a state of the system before or after the measurement. We investigate observables that are free from noise caused by classical post-processing, mixing, or pre-processing of quantum nature. Especially, a complete characterization of pre-processing and post-processing clean observables is given, and necessary and sufficient conditions are imposed on informationally complete POVMs within the set of pure states. We also discuss joint and sequential measurements of optimal quantum observables.

Optimal path planning for video-guided smart munitions via multitarget tracking

NASA Astrophysics Data System (ADS)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

User-customized brain computer interfaces using Bayesian optimization

NASA Astrophysics Data System (ADS)

Bashashati, Hossein; Ward, Rabab K.; Bashashati, Ali

2016-04-01

Objective. The brain characteristics of different people are not the same. Brain computer interfaces (BCIs) should thus be customized for each individual person. In motor-imagery based synchronous BCIs, a number of parameters (referred to as hyper-parameters) including the EEG frequency bands, the channels and the time intervals from which the features are extracted should be pre-determined based on each subject’s brain characteristics. Approach. To determine the hyper-parameter values, previous work has relied on manual or semi-automatic methods that are not applicable to high-dimensional search spaces. In this paper, we propose a fully automatic, scalable and computationally inexpensive algorithm that uses Bayesian optimization to tune these hyper-parameters. We then build different classifiers trained on the sets of hyper-parameter values proposed by the Bayesian optimization. A final classifier aggregates the results of the different classifiers. Main Results. We have applied our method to 21 subjects from three BCI competition datasets. We have conducted rigorous statistical tests, and have shown the positive impact of hyper-parameter optimization in improving the accuracy of BCIs. Furthermore, We have compared our results to those reported in the literature. Significance. Unlike the best reported results in the literature, which are based on more sophisticated feature extraction and classification methods, and rely on prestudies to determine the hyper-parameter values, our method has the advantage of being fully automated, uses less sophisticated feature extraction and classification methods, and yields similar or superior results compared to the best performing designs in the literature.

Multidisciplinary design optimization using genetic algorithms

NASA Technical Reports Server (NTRS)

Unal, Resit

1994-01-01

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

Construction Performance Optimization toward Green Building Premium Cost Based on Greenship Rating Tools Assessment with Value Engineering Method

NASA Astrophysics Data System (ADS)

Latief, Yusuf; Berawi, Mohammed Ali; Basten, Van; Riswanto; Budiman, Rachmat

2017-07-01

Green building concept becomes important in current building life cycle to mitigate environment issues. The purpose of this paper is to optimize building construction performance towards green building premium cost, achieving green building rating tools with optimizing life cycle cost. Therefore, this study helps building stakeholder determining building fixture to achieve green building certification target. Empirically the paper collects data of green building in the Indonesian construction industry such as green building fixture, initial cost, operational and maintenance cost, and certification score achievement. After that, using value engineering method optimized green building fixture based on building function and cost aspects. Findings indicate that construction performance optimization affected green building achievement with increasing energy and water efficiency factors and life cycle cost effectively especially chosen green building fixture.

An Improved DINEOF Algorithm for Filling Missing Values in Spatio-Temporal Sea Surface Temperature Data.

PubMed

Ping, Bo; Su, Fenzhen; Meng, Yunshan

2016-01-01

In this study, an improved Data INterpolating Empirical Orthogonal Functions (DINEOF) algorithm for determination of missing values in a spatio-temporal dataset is presented. Compared with the ordinary DINEOF algorithm, the iterative reconstruction procedure until convergence based on every fixed EOF to determine the optimal EOF mode is not necessary and the convergence criterion is only reached once in the improved DINEOF algorithm. Moreover, in the ordinary DINEOF algorithm, after optimal EOF mode determination, the initial matrix with missing data will be iteratively reconstructed based on the optimal EOF mode until the reconstruction is convergent. However, the optimal EOF mode may be not the best EOF for some reconstructed matrices generated in the intermediate steps. Hence, instead of using asingle EOF to fill in the missing data, in the improved algorithm, the optimal EOFs for reconstruction are variable (because the optimal EOFs are variable, the improved algorithm is called VE-DINEOF algorithm in this study). To validate the accuracy of the VE-DINEOF algorithm, a sea surface temperature (SST) data set is reconstructed by using the DINEOF, I-DINEOF (proposed in 2015) and VE-DINEOF algorithms. Four parameters (Pearson correlation coefficient, signal-to-noise ratio, root-mean-square error, and mean absolute difference) are used as a measure of reconstructed accuracy. Compared with the DINEOF and I-DINEOF algorithms, the VE-DINEOF algorithm can significantly enhance the accuracy of reconstruction and shorten the computational time.

Heart-type fatty acid binding protein (H-FABP) in patients in an emergency department setting, suspected of acute coronary syndrome: optimal cut-off point, diagnostic value and future opportunities in primary care.

PubMed

Willemsen, Robert T A; van Severen, Evie; Vandervoort, Pieter M; Grieten, Lars; Buntinx, Frank; Glatz, Jan F C; Dinant, Geert Jan

2015-01-01

Most patients presenting chest complaints in primary care are referred to secondary care facilities, whereas only a few are diagnosed with acute coronary syndrome (ACS). The aim is to determine the optimal cut-off value for a point-of-care heart-type fatty acid binding protein (H-FABP) test in patients presenting to the emergency department and to evaluate a possible future role of H-FABP in safely ruling out ACS in primary care. Serial plasma H-FABP (index test) and high sensitivity troponin T (hs-cTnT) (reference test) were determined in patients with any new-onset chest complaint. In a receiver operating characteristic (ROC) curve, the optimal cut-off value of H-FABP for ACS was determined. Predictive values of H-FABP for ACS were calculated. For 202 consecutive patients (prevalence ACS 59%), the ROC curve based on the results of the first H-FABP was equal to the ROC curve of hs-cTnT (AUC 0.79 versus 0.80). Using a cut-off value of 4.0 ng/ml for H-FABP, sensitivity for ACS of the H-FABP (hs-cTnT) tests was 73.9% (70.6%). Negative predictive value (NPV) of H-FABP for ACS in a population representative for primary care (incidence of ACS 22%) thus could reach 90.8%. In patients presenting chest pain, plasma H-FABP reaches the highest diagnostic value when a cut-off value of 4 ng/ml is used. Diagnostic values of an algorithm combining point-of-care H-FABP measurement and a score of signs and symptoms should be studied in primary care, to learn if such an algorithm could safely reduce referral rate by GPs.

Optimized angiotensin-converting enzyme activity assay for the accurate diagnosis of sarcoidosis.

PubMed

Csongrádi, Alexandra; Enyedi, Attila; Takács, István; Végh, Tamás; Mányiné, Ivetta S; Pólik, Zsófia; Altorjay, István Tibor; Balla, József; Balla, György; Édes, István; Kappelmayer, János; Tóth, Attila; Papp, Zoltán; Fagyas, Miklós

2018-06-27

Serum angiotensin-converting enzyme (ACE) activity determination can aid the early diagnosis of sarcoidosis. We aimed to optimize a fluorescent kinetic assay for ACE activity by screening the confounding effects of endogenous ACE inhibitors and interfering factors. Genotype-dependent and genotype-independent reference values of ACE activity were established, and their diagnostic accuracies were validated in a clinical study. Internally quenched fluorescent substrate, Abz-FRK(Dnp)P-OH was used for ACE-activity measurements. A total of 201 healthy individuals and 59 presumably sarcoidotic patients were enrolled into this study. ACE activity and insertion/deletion (I/D) genotype of the ACE gene were determined. Here we report that serum samples should be diluted at least 35-fold to eliminate the endogenous inhibitor effect of albumin. No significant interferences were detected: up to a triglyceride concentration of 16 mM, a hemoglobin concentration of 0.71 g/L and a bilirubin concentration of 150 μM. Genotype-dependent reference intervals were considered as 3.76-11.25 U/L, 5.22-11.59 U/L, 7.19-14.84 U/L for II, ID and DD genotypes, respectively. I/D genotype-independent reference interval was established as 4.85-13.79 U/L. An ACE activity value was considered positive for sarcoidosis when it exceeded the upper limit of the reference interval. The optimized assay with genotype-dependent reference ranges resulted in 42.5% sensitivity, 100% specificity, 100% positive predictive value and 32.4% negative predictive value in the clinical study, whereas the genotype-independent reference range proved to have inferior diagnostic efficiency. An optimized fluorescent kinetic assay of serum ACE activity combined with ACE I/D genotype determination is an alternative to invasive biopsy for confirming the diagnosis of sarcoidosis in a significant percentage of patients.

Differentiation between polycystic ovary syndrome and polycystic ovarian morphology by means of an anti-Müllerian hormone cutoff value.

PubMed

Song, Do Kyeong; Oh, Jee-Young; Lee, Hyejin; Sung, Yeon-Ah

2017-07-01

Although increased serum anti-Müllerian hormone (AMH) level has been suggested to be a surrogate marker of polycystic ovarian morphology (PCOM), its association with polycystic ovary syndrome (PCOS) is controversial, and its diagnostic value has not been determined. We aimed to observe the relationship between the AMH level and PCOS phenotypes and to determine the optimal cutoff value of AMH for the diagnosis of PCOS in young Korean women. We recruited 207 women with PCOS (120 with PCOM and 87 without PCOM) and 220 regular cycling women with normoandrogenemia (100 with PCOM and 120 without PCOM). Subjects underwent testing at a single outpatient visit. Serum AMH level was measured. Women with PCOS had higher serum AMH levels than did regular cycling women with normoandrogenemia ( p < 0.05). Women with PCOM had higher serum AMH levels than women without PCOM, regardless of PCOS status ( p < 0.05). The optimal AMH cutoff value for the diagnosis of PCOS was 10.0 ng/mL (71% sensitivity, 93% specificity). Serum AMH was an independent determinant of total testosterone after adjustment for age, body mass index, and the number of menses/year (β = 0.31, p < 0.01). An association between AMH and hyperandrogenism was only observed in women with PCOS, and it was independent of the presence of PCOM. The serum AMH level can be useful for the diagnosis of PCOS at any age less than 40 years, and the optimal cutoff value for the diagnosis of PCOS identified in this study of young Korean women was 10.0 ng/mL.

Optimal Threshold Determination for Interpreting Semantic Similarity and Particularity: Application to the Comparison of Gene Sets and Metabolic Pathways Using GO and ChEBI

PubMed Central

Bettembourg, Charles; Diot, Christian; Dameron, Olivier

2015-01-01

Background The analysis of gene annotations referencing back to Gene Ontology plays an important role in the interpretation of high-throughput experiments results. This analysis typically involves semantic similarity and particularity measures that quantify the importance of the Gene Ontology annotations. However, there is currently no sound method supporting the interpretation of the similarity and particularity values in order to determine whether two genes are similar or whether one gene has some significant particular function. Interpretation is frequently based either on an implicit threshold, or an arbitrary one (typically 0.5). Here we investigate a method for determining thresholds supporting the interpretation of the results of a semantic comparison. Results We propose a method for determining the optimal similarity threshold by minimizing the proportions of false-positive and false-negative similarity matches. We compared the distributions of the similarity values of pairs of similar genes and pairs of non-similar genes. These comparisons were performed separately for all three branches of the Gene Ontology. In all situations, we found overlap between the similar and the non-similar distributions, indicating that some similar genes had a similarity value lower than the similarity value of some non-similar genes. We then extend this method to the semantic particularity measure and to a similarity measure applied to the ChEBI ontology. Thresholds were evaluated over the whole HomoloGene database. For each group of homologous genes, we computed all the similarity and particularity values between pairs of genes. Finally, we focused on the PPAR multigene family to show that the similarity and particularity patterns obtained with our thresholds were better at discriminating orthologs and paralogs than those obtained using default thresholds. Conclusion We developed a method for determining optimal semantic similarity and particularity thresholds. We applied this method on the GO and ChEBI ontologies. Qualitative analysis using the thresholds on the PPAR multigene family yielded biologically-relevant patterns. PMID:26230274

Singular vector-based targeted observations of chemical constituents: description and first application of the EURAD-IM-SVA v1.0

NASA Astrophysics Data System (ADS)

Goris, N.; Elbern, H.

2015-12-01

Measurements of the large-dimensional chemical state of the atmosphere provide only sparse snapshots of the state of the system due to their typically insufficient temporal and spatial density. In order to optimize the measurement configurations despite those limitations, the present work describes the identification of sensitive states of the chemical system as optimal target areas for adaptive observations. For this purpose, the technique of singular vector analysis (SVA), which has proven effective for targeted observations in numerical weather prediction, is implemented in the EURAD-IM (EURopean Air pollution and Dispersion - Inverse Model) chemical transport model, yielding the EURAD-IM-SVA v1.0. Besides initial values, emissions are investigated as critical simulation controlling targeting variables. For both variants, singular vectors are applied to determine the optimal placement for observations and moreover to quantify which chemical compounds have to be observed with preference. Based on measurements of the airship based ZEPTER-2 campaign, the EURAD-IM-SVA v1.0 has been evaluated by conducting a comprehensive set of model runs involving different initial states and simulation lengths. For the sake of brevity, we concentrate our attention on the following chemical compounds, O3, NO, NO2, HCHO, CO, HONO, and OH, and focus on their influence on selected O3 profiles. Our analysis shows that the optimal placement for observations of chemical species is not entirely determined by mere transport and mixing processes. Rather, a combination of initial chemical concentrations, chemical conversions, and meteorological processes determines the influence of chemical compounds and regions. We furthermore demonstrate that the optimal placement of observations of emission strengths is highly dependent on the location of emission sources and that the benefit of including emissions as target variables outperforms the value of initial value optimization with growing simulation length. The obtained results confirm the benefit of considering both initial values and emission strengths as target variables and of applying the EURAD-IM-SVA v1.0 for measurement decision guidance with respect to chemical compounds.

A mathematical model for maximizing the value of phase 3 drug development portfolios incorporating budget constraints and risk.

PubMed

Patel, Nitin R; Ankolekar, Suresh; Antonijevic, Zoran; Rajicic, Natasa

2013-05-10

We describe a value-driven approach to optimizing pharmaceutical portfolios. Our approach incorporates inputs from research and development and commercial functions by simultaneously addressing internal and external factors. This approach differentiates itself from current practices in that it recognizes the impact of study design parameters, sample size in particular, on the portfolio value. We develop an integer programming (IP) model as the basis for Bayesian decision analysis to optimize phase 3 development portfolios using expected net present value as the criterion. We show how this framework can be used to determine optimal sample sizes and trial schedules to maximize the value of a portfolio under budget constraints. We then illustrate the remarkable flexibility of the IP model to answer a variety of 'what-if' questions that reflect situations that arise in practice. We extend the IP model to a stochastic IP model to incorporate uncertainty in the availability of drugs from earlier development phases for phase 3 development in the future. We show how to use stochastic IP to re-optimize the portfolio development strategy over time as new information accumulates and budget changes occur. Copyright © 2013 John Wiley & Sons, Ltd.

Social Support and Optimism as Predictors of Life Satisfaction of College Students

ERIC Educational Resources Information Center

Yalcin, Ilhan

2011-01-01

The purpose of this study was to investigate the predictive value of optimism, perceived support from family and perceived support from faculty in determining life satisfaction of college students in Turkey. One hundred and thirty three students completed the Satisfaction with Life Scale (Diener et al., Journal of Personality Assessment…

Data-driven design optimization for composite material characterization

Treesearch

John G. Michopoulos; John C. Hermanson; Athanasios Iliopoulos; Samuel G. Lambrakos; Tomonari Furukawa

2011-06-01

The main goal of the present paper is to demonstrate the value of design optimization beyond its use for structural shape determination in the realm of the constitutive characterization of anisotropic material systems such as polymer matrix composites with or without damage. The approaches discussed are based on the availability of massive experimental data...

OCT-measured plaque free wall angle is indicative for plaque burden: overcoming the main limitation of OCT?

PubMed

Hoogendoorn, Ayla; Gnanadesigan, Muthukaruppan; Zahnd, Guillaume; van Ditzhuijzen, Nienke S; Schuurbiers, Johan C H; van Soest, Gijs; Regar, Evelyn; Wentzel, Jolanda J

2016-10-01

The aim of this study was to investigate the relationship between the plaque free wall (PFW) measured by optical coherence tomography (OCT) and the plaque burden (PB) measured by intravascular ultrasound (IVUS). We hypothesize that measurement of the PFW could help to estimate the PB, thereby overcoming the limited ability of OCT to visualize the external elastic membrane in the presence of plaque. This could enable selection of the optimal stent-landing zone by OCT, which is traditionally defined by IVUS as a region with a PB < 40 %. PB (IVUS) and PFW angle (OCT and IVUS) were measured in 18 matched IVUS and OCT pullbacks acquired in the same coronary artery. We determined the relationship between OCT measured PFW (PFWOCT) and IVUS PB (PBIVUS) by non-linear regression analysis. An ROC-curve analysis was used to determine the optimal cut-off value of PFW angle for the detection of PB < 40 %. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated. There is a significant correlation between PFWOCT and PBIVUS (r(2) = 0.59). The optimal cut-off value of the PFWOCT for the prediction of a PBIVUS < 40 % is ≥220° with a PPV of 78 % and an NPV of 84 %. This study shows that PFWOCT can be considered as a surrogate marker for PBIVUS, which is currently a common criterion to select an optimal stent-landing zone.

Optimal pricing and replenishment policies for instantaneous deteriorating items with backlogging and trade credit under inflation

NASA Astrophysics Data System (ADS)

Sundara Rajan, R.; Uthayakumar, R.

2017-12-01

In this paper we develop an economic order quantity model to investigate the optimal replenishment policies for instantaneous deteriorating items under inflation and trade credit. Demand rate is a linear function of selling price and decreases negative exponentially with time over a finite planning horizon. Shortages are allowed and partially backlogged. Under these conditions, we model the retailer's inventory system as a profit maximization problem to determine the optimal selling price, optimal order quantity and optimal replenishment time. An easy-to-use algorithm is developed to determine the optimal replenishment policies for the retailer. We also provide optimal present value of profit when shortages are completely backlogged as a special case. Numerical examples are presented to illustrate the algorithm provided to obtain optimal profit. And we also obtain managerial implications from numerical examples to substantiate our model. The results show that there is an improvement in total profit from complete backlogging rather than the items being partially backlogged.

Optimization of torrefaction conditions of coffee industry residues using desirability function approach.

PubMed

Buratti, C; Barbanera, M; Lascaro, E; Cotana, F

2018-03-01

The aim of the present study is to analyze the influence of independent process variables such as temperature, residence time, and heating rate on the torrefaction process of coffee chaff (CC) and spent coffee grounds (SCGs). Response surface methodology and a three-factor and three-level Box-Behnken design were used in order to evaluate the effects of the process variables on the weight loss (W L ) and the Higher Heating Value (HHV) of the torrefied materials. Results showed that the effects of the three factors on both responses were sequenced as follows: temperature>residence time>heating rate. Data obtained from the experiments were analyzed by analysis of variance (ANOVA) and fitted to second-order polynomial models by using multiple regression analysis. Predictive models were determined, able to obtain satisfactory fittings of the experimental data, with coefficient of determination (R 2 ) values higher than 0.95. An optimization study using Derringer's desired function methodology was also carried out and the optimal torrefaction conditions were found: temperature 271.7°C, residence time 20min, heating rate 5°C/min for CC and 256.0°C, 20min, 25°C/min for SCGs. The experimental values closely agree with the corresponding predicted values. Copyright © 2017 Elsevier Ltd. All rights reserved.

Determination of the Optimal Fourier Number on the Dynamic Thermal Transmission

NASA Astrophysics Data System (ADS)

Bruzgevičius, P.; Burlingis, A.; Norvaišienė, R.

2016-12-01

This article represents the result of experimental research on transient heat transfer in a multilayered (heterogeneous) wall. Our non-steady thermal transmission simulation is based on a finite-difference calculation method. The value of a Fourier number shows the similarity of thermal variation in conditional layers of an enclosure. Most scientists recommend using no more than a value of 0.5 for the Fourier number when performing calculations on dynamic (transient) heat transfer. The value of the Fourier number is determined in order to acquire reliable calculation results with optimal accuracy. To compare the results of simulation with experimental research, a transient heat transfer calculation spreadsheet was created. Our research has shown that a Fourier number of around 0.5 or even 0.32 is not sufficient ({≈ }17 % of oscillation amplitude) for calculations of transient heat transfer in a multilayered wall. The least distorted calculation results were obtained when the multilayered enclosure was divided into conditional layers with almost equal Fourier number values and when the value of the Fourier number was around 1/6, i.e., approximately 0.17. Statistical deviation analysis using the Statistical Analysis System was applied to assess the accuracy of the spreadsheet calculation and was developed on the basis of our established methodology. The mean and median absolute error as well as their confidence intervals has been estimated by the two methods with optimal accuracy ({F}_{oMDF}= 0.177 and F_{oEPS}= 0.1633 values).

Rapid optimization of MRM-MS instrument parameters by subtle alteration of precursor and product m/z targets.

PubMed

Sherwood, Carly A; Eastham, Ashley; Lee, Lik Wee; Risler, Jenni; Mirzaei, Hamid; Falkner, Jayson A; Martin, Daniel B

2009-07-01

Multiple reaction monitoring (MRM) is a highly sensitive method of targeted mass spectrometry (MS) that can be used to selectively detect and quantify peptides based on the screening of specified precursor peptide-to-fragment ion transitions. MRM-MS sensitivity depends critically on the tuning of instrument parameters, such as collision energy and cone voltage, for the generation of maximal product ion signal. Although generalized equations and values exist for such instrument parameters, there is no clear indication that optimal signal can be reliably produced for all types of MRM transitions using such an algorithmic approach. To address this issue, we have devised a workflow functional on both Waters Quattro Premier and ABI 4000 QTRAP triple quadrupole instruments that allows rapid determination of the optimal value of any programmable instrument parameter for each MRM transition. Here, we demonstrate the strategy for the optimizations of collision energy and cone voltage, but the method could be applied to other instrument parameters, such as declustering potential, as well. The workflow makes use of the incremental adjustment of the precursor and product m/z values at the hundredth decimal place to create a series of MRM targets at different collision energies that can be cycled through in rapid succession within a single run, avoiding any run-to-run variability in execution or comparison. Results are easily visualized and quantified using the MRM software package Mr. M to determine the optimal instrument parameters for each transition.

Rapid Optimization of MRM-MS Instrument Parameters by Subtle Alteration of Precursor and Product m/z Targets

PubMed Central

Sherwood, Carly A.; Eastham, Ashley; Lee, Lik Wee; Risler, Jenni; Mirzaei, Hamid; Falkner, Jayson A.; Martin, Daniel B.

2009-01-01

Multiple reaction monitoring (MRM) is a highly sensitive method of targeted mass spectrometry (MS) that can be used to selectively detect and quantify peptides based on the screening of specified precursor peptide-to-fragment ion transitions. MRM-MS sensitivity depends critically on the tuning of instrument parameters, such as collision energy and cone voltage, for the generation of maximal product ion signal. Although generalized equations and values exist for such instrument parameters, there is no clear indication that optimal signal can be reliably produced for all types of MRM transitions using such an algorithmic approach. To address this issue, we have devised a workflow functional on both Waters Quattro Premier and ABI 4000 QTRAP triple quadrupole instruments that allows rapid determination of the optimal value of any programmable instrument parameter for each MRM transition. Here, we demonstrate the strategy for the optimizations of collision energy and cone voltage, but the method could be applied to other instrument parameters, such as declustering potential, as well. The workflow makes use of the incremental adjustment of the precursor and product m/z values at the hundredth decimal place to create a series of MRM targets at different collision energies that can be cycled through in rapid succession within a single run, avoiding any run-to-run variability in execution or comparison. Results are easily visualized and quantified using the MRM software package Mr. M to determine the optimal instrument parameters for each transition. PMID:19405522

Rheology and Extrusion of Cement-Fly Ashes Pastes

NASA Astrophysics Data System (ADS)

Micaelli, F.; Lanos, C.; Levita, G.

2008-07-01

The addition of fly ashes in cement pastes is tested to optimize the forming of cement based material by extrusion. Two sizes of fly ashes grains are examinated. The rheology of concentrated suspensions of ashes mixes is studied with a parallel plates rheometer. In stationary flow state, tested suspensions viscosities are satisfactorily described by the Krieger-Dougherty model. An "overlapped grain" suspensions model able to describe the bimodal suspensions behaviour is proposed. For higher values of solid volume fraction, Bingham viscoplastic behaviour is identified. Results showed that the plastic viscosity and plastic yield values present minimal values for the same optimal formulation of bimodal mixes. The rheological study is extended to more concentrated systems using an extruder. Finally it is observed that the addition of 30% vol. of optimized ashes mix determined a significant reduction of required extrusion load.

Examination of a Method to Determine the Reference Region for Calculating the Specific Binding Ratio in Dopamine Transporter Imaging.

PubMed

Watanabe, Ayumi; Inoue, Yusuke; Asano, Yuji; Kikuchi, Kei; Miyatake, Hiroki; Tokushige, Takanobu

2017-01-01

The specific binding ratio (SBR) was first reported by Tossici-Bolt et al. for quantitative indicators for dopamine transporter (DAT) imaging. It is defined as the ratio of the specific binding concentration of the striatum to the non-specific binding concentration of the whole brain other than the striatum. The non-specific binding concentration is calculated based on the region of interest (ROI), which is set 20 mm inside the outer contour, defined by a threshold technique. Tossici-Bolt et al. used a 50% threshold, but sometimes we couldn't define the ROI of non-specific binding concentration (reference region) and calculate SBR appropriately with a 50% threshold. Therefore, we sought a new method for determining the reference region when calculating SBR. We used data from 20 patients who had undergone DAT imaging in our hospital, to calculate the non-specific binding concentration by the following methods, the threshold to define a reference region was fixed at some specific values (the fixing method) and reference region was visually optimized by an examiner at every examination (the visual optimization method). First, we assessed the reference region of each method visually, and afterward, we quantitatively compared SBR calculated based on each method. In the visual assessment, the scores of the fixing method at 30% and visual optimization method were higher than the scores of the fixing method at other values, with or without scatter correction. In the quantitative assessment, the SBR obtained by visual optimization of the reference region, based on consensus of three radiological technologists, was used as a baseline (the standard method). The values of SBR showed good agreement between the standard method and both the fixing method at 30% and the visual optimization method, with or without scatter correction. Therefore, the fixing method at 30% and the visual optimization method were equally suitable for determining the reference region.

Principal Eigenvalue Minimization for an Elliptic Problem with Indefinite Weight and Robin Boundary Conditions

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

Hintermueller, M., E-mail: hint@math.hu-berlin.de; Kao, C.-Y., E-mail: Ckao@claremontmckenna.edu; Laurain, A., E-mail: laurain@math.hu-berlin.de

2012-02-15

This paper focuses on the study of a linear eigenvalue problem with indefinite weight and Robin type boundary conditions. We investigate the minimization of the positive principal eigenvalue under the constraint that the absolute value of the weight is bounded and the total weight is a fixed negative constant. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for a species to survive. For rectangular domains with Neumann boundary condition, it is known that there exists a threshold value such that if the total weight is below this thresholdmore » value then the optimal favorable region is like a section of a disk at one of the four corners; otherwise, the optimal favorable region is a strip attached to the shorter side of the rectangle. Here, we investigate the same problem with mixed Robin-Neumann type boundary conditions and study how this boundary condition affects the optimal spatial arrangement.« less

Box-Behnken statistical design to optimize thermal performance of energy storage systems

NASA Astrophysics Data System (ADS)

Jalalian, Iman Joz; Mohammadiun, Mohammad; Moqadam, Hamid Hashemi; Mohammadiun, Hamid

2018-05-01

Latent heat thermal storage (LHTS) is a technology that can help to reduce energy consumption for cooling applications, where the cold is stored in phase change materials (PCMs). In the present study a comprehensive theoretical and experimental investigation is performed on a LHTES system containing RT25 as phase change material (PCM). Process optimization of the experimental conditions (inlet air temperature and velocity and number of slabs) was carried out by means of Box-Behnken design (BBD) of Response surface methodology (RSM). Two parameters (cooling time and COP value) were chosen to be the responses. Both of the responses were significantly influenced by combined effect of inlet air temperature with velocity and number of slabs. Simultaneous optimization was performed on the basis of the desirability function to determine the optimal conditions for the cooling time and COP value. Maximum cooling time (186 min) and COP value (6.04) were found at optimum process conditions i.e. inlet temperature of (32.5), air velocity of (1.98) and slab number of (7).

Methods of increasing efficiency and maintainability of pipeline systems

NASA Astrophysics Data System (ADS)

Ivanov, V. A.; Sokolov, S. M.; Ogudova, E. V.

2018-05-01

This study is dedicated to the issue of pipeline transportation system maintenance. The article identifies two classes of technical-and-economic indices, which are used to select an optimal pipeline transportation system structure. Further, the article determines various system maintenance strategies and strategy selection criteria. Meanwhile, the maintenance strategies turn out to be not sufficiently effective due to non-optimal values of maintenance intervals. This problem could be solved by running the adaptive maintenance system, which includes a pipeline transportation system reliability improvement algorithm, especially an equipment degradation computer model. In conclusion, three model building approaches for determining optimal technical systems verification inspections duration were considered.

Optimization of the capillary zone electrophoresis method for Huperzine A determination using experimental design and artificial neural networks.

PubMed

Hameda, A Ben; Elosta, S; Havel, J

2005-08-19

Huperzine A, natural product from Huperzia serrata, is quite an important compound used to treat the Alzheimer's disease as a food supplement and also proposed as a prospective and prophylactic antidote against organophosphate poisoning. In this work, simple and fast capillary electrophoresis (CE) procedure with UV detection (at 230 nm) for determination of Huperzine A was developed and optimized. Capillary electrophoresis determination of Huperzine A was optimized using a combination of the experimental design (ED) and the artificial neural networks (ANN). In the first stage of optimization, the experiments were done according to the appropriate ED. Data evaluated by ANN allowed finding the optimal values of several analytical parameters (peak area, peak height, and analysis time). Optimal conditions found were 50 mM acetate buffer, pH 4.6, separation voltage 10 kV, hydrodynamic injection time 10 s and temperature 25 degrees C. The developed method shows good repeatability as relative standard division (R.S.D. = 0.9%) and it has been applied for determination of Huperzine A in various pharmaceutical products and in biological liquids. The limit of detection (LOD) in aqueous media was 0.226 ng/ml and 0.233 ng/ml for determination in the serum.

Optimization of a multiple headspace sorptive extraction method coupled to gas chromatography-mass spectrometry for the determination of volatile compounds in macroalgae.

PubMed

Maruti, Astrid; Durán-Guerrero, Enrique; Barroso, Carmelo G; Castro, Remedios

2018-05-25

A novel extraction technique is proposed in which the Multiple Headspace Extraction (MHE) approach is used in conjunction with Headspace Sorptive Extraction (HSSE) and Gas Chromatography-Mass Spectrometry (GC-MS) detection. The extraction method was developed to determine volatile compounds in macroalgae. Optimization of the extraction parameters was carried out using design of experiments to identify factors that affect the extraction: extraction time, temperature, twister length and amount of sample. The results of the optimization led to an extraction of 2 g of sample using a 20 mm Twister ® at 66 °C for 180 min. The progression constants (β) were calculated for 43 volatile compounds, 29 of which could be quantified using the method. Linearity was attained with a determination coefficient higher than 0.99 for all studied compounds. Inter-day and inter-twister precisions ranged from 0.22% to 19.01% and from 0.69% to 14.76% respectively, and values below 10% were obtained for the majority of compounds. LOD and LOQ values ranged from the values obtained for diethyl succinate (0.012 μg/L and 0.088 μg/L, respectively) and those obtained for dimethyl sulfide (5.544 μg/L and 40.286 μg/L, respectively). However, for the majority of compounds values obtained were below 1 μg/L (LOD) and 5 μg/L (LOQ). Compounds such as ethyl acetate, hexanal, heptadecane, 2-hexenal, 6-methyl-5-hepten-2-one, dimethyl sulfide, benzyl alcohol, beta ionone, or beta cyclocitral, among others were correctly determined in three species of macroalgae: Ulva sp., Gracillaria sp. and Enteromorpha sp. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Economic benefits of midseason reordering in apparel retailing

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

Lamont, A.; Elayat, H.

1995-09-27

This report presents a method for determining the value of reordering, explores factors that affect its value, and provides an estimate of the value under a range of conditions. The method is based on a stochastic process model of the demands the retailer faces. It uses a dynamic programming model to determine the optimal quantities to order and the expected profits. The analysis shows that the benefits of reordering are quite sensitive to the uncertainties in the demand and to the assumptions about the markdown of unsold merchandise at the end of the season.

Optimal Low Energy Earth-Moon Transfers

NASA Technical Reports Server (NTRS)

Griesemer, Paul Ricord; Ocampo, Cesar; Cooley, D. S.

2010-01-01

The optimality of a low-energy Earth-Moon transfer is examined for the first time using primer vector theory. An optimal control problem is formed with the following free variables: the location, time, and magnitude of the transfer insertion burn, and the transfer time. A constraint is placed on the initial state of the spacecraft to bind it to a given initial orbit around a first body, and on the final state of the spacecraft to limit its Keplerian energy with respect to a second body. Optimal transfers in the system are shown to meet certain conditions placed on the primer vector and its time derivative. A two point boundary value problem containing these necessary conditions is created for use in targeting optimal transfers. The two point boundary value problem is then applied to the ballistic lunar capture problem, and an optimal trajectory is shown. Additionally, the ballistic lunar capture trajectory is examined to determine whether one or more additional impulses may improve on the cost of the transfer.

Utilizing pretreatment and fungal incubation to enhance the nutritional value of canola meal

USDA-ARS?s Scientific Manuscript database

The objective of this study was to determine the optimal pretreatment and fungal strain to reduce glucosinolates (GLS), fiber, and residual sugars while increasing the nutritional value of canola meal. Submerged incubation conditions were used to evaluate four pretreatment methods (extrusion, hot wa...

Differentiation between polycystic ovary syndrome and polycystic ovarian morphology by means of an anti-Müllerian hormone cutoff value

PubMed Central

Song, Do Kyeong; Oh, Jee-Young; Lee, Hyejin; Sung, Yeon-Ah

2017-01-01

Background/Aims Although increased serum anti-Müllerian hormone (AMH) level has been suggested to be a surrogate marker of polycystic ovarian morphology (PCOM), its association with polycystic ovary syndrome (PCOS) is controversial, and its diagnostic value has not been determined. We aimed to observe the relationship between the AMH level and PCOS phenotypes and to determine the optimal cutoff value of AMH for the diagnosis of PCOS in young Korean women. Methods We recruited 207 women with PCOS (120 with PCOM and 87 without PCOM) and 220 regular cycling women with normoandrogenemia (100 with PCOM and 120 without PCOM). Subjects underwent testing at a single outpatient visit. Serum AMH level was measured. Results Women with PCOS had higher serum AMH levels than did regular cycling women with normoandrogenemia (p < 0.05). Women with PCOM had higher serum AMH levels than women without PCOM, regardless of PCOS status (p < 0.05). The optimal AMH cutoff value for the diagnosis of PCOS was 10.0 ng/mL (71% sensitivity, 93% specificity). Serum AMH was an independent determinant of total testosterone after adjustment for age, body mass index, and the number of menses/year (β = 0.31, p < 0.01). An association between AMH and hyperandrogenism was only observed in women with PCOS, and it was independent of the presence of PCOM. Conclusion The serum AMH level can be useful for the diagnosis of PCOS at any age less than 40 years, and the optimal cutoff value for the diagnosis of PCOS identified in this study of young Korean women was 10.0 ng/mL. PMID:27899014

Application of D-optimal experimental design method to optimize the formulation of O/W cosmetic emulsions.

PubMed

Djuris, J; Vasiljevic, D; Jokic, S; Ibric, S

2014-02-01

This study investigates the application of D-optimal mixture experimental design in optimization of O/W cosmetic emulsions. Cetearyl glucoside was used as a natural, biodegradable non-ionic emulsifier in the relatively low concentration (1%), and the mixture of co-emulsifiers (stearic acid, cetyl alcohol, stearyl alcohol and glyceryl stearate) was used to stabilize the formulations. To determine the optimal composition of co-emulsifiers mixture, D-optimal mixture experimental design was used. Prepared emulsions were characterized with rheological measurements, centrifugation test, specific conductivity and pH value measurements. All prepared samples appeared as white and homogenous creams, except for one homogenous and viscous lotion co-stabilized by stearic acid alone. Centrifugation testing revealed some phase separation only in the case of sample co-stabilized using glyceryl stearate alone. The obtained pH values indicated that all samples expressed mild acid value acceptable for cosmetic preparations. Specific conductivity values are attributed to the multiple phases O/W emulsions with high percentages of fixed water. Results of the rheological measurements have shown that the investigated samples exhibited non-Newtonian thixotropic behaviour. To determine the influence of each of the co-emulsifiers on emulsions properties, the obtained results were evaluated by the means of statistical analysis (ANOVA test). On the basis of comparison of statistical parameters for each of the studied responses, mixture reduced quadratic model was selected over the linear model implying that interactions between co-emulsifiers play the significant role in overall influence of co-emulsifiers on emulsions properties. Glyceryl stearate was found to be the dominant co-emulsifier affecting emulsions properties. Interactions between the glyceryl stearate and other co-emulsifiers were also found to significantly influence emulsions properties. These findings are especially important as they can be used for development of the product that meets users' requirements, as represented in the study. © 2013 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Efficient sensitivity analysis and optimization of a helicopter rotor

NASA Technical Reports Server (NTRS)

Lim, Joon W.; Chopra, Inderjit

1989-01-01

Aeroelastic optimization of a system essentially consists of the determination of the optimum values of design variables which minimize the objective function and satisfy certain aeroelastic and geometric constraints. The process of aeroelastic optimization analysis is illustrated. To carry out aeroelastic optimization effectively, one needs a reliable analysis procedure to determine steady response and stability of a rotor system in forward flight. The rotor dynamic analysis used in the present study developed inhouse at the University of Maryland is based on finite elements in space and time. The analysis consists of two major phases: vehicle trim and rotor steady response (coupled trim analysis), and aeroelastic stability of the blade. For a reduction of helicopter vibration, the optimization process requires the sensitivity derivatives of the objective function and aeroelastic stability constraints. For this, the derivatives of steady response, hub loads and blade stability roots are calculated using a direct analytical approach. An automated optimization procedure is developed by coupling the rotor dynamic analysis, design sensitivity analysis and constrained optimization code CONMIN.

Spectrophotometric determination of triclosan based on diazotization reaction: response surface optimization using Box-Behnken design.

PubMed

Kaur, Inderpreet; Gaba, Sonal; Kaur, Sukhraj; Kumar, Rajeev; Chawla, Jyoti

2018-05-01

A spectrophotometric method based on diazotization of aniline with triclosan has been developed for the determination of triclosan in water samples. The diazotization process involves two steps: (1) reaction of aniline with sodium nitrite in an acidic medium to form diazonium ion and (2) reaction of diazonium ion with triclosan to form a yellowish-orange azo compound in an alkaline medium. The resulting yellowish-orange product has a maximum absorption at 352 nm which allows the determination of triclosan in aqueous solution in the linear concentration range of 0.1-3.0 μM with R 2 = 0.998. The concentration of hydrochloric acid, sodium nitrite, and aniline was optimized for diazotization reaction to achieve good spectrophotometric determination of triclosan. The optimization of experimental conditions for spectrophotometric determination of triclosan in terms of concentration of sodium nitrite, hydrogen chloride and aniline was also carried out by using Box-Behnken design of response surface methodology and results obtained were in agreement with the experimentally optimized values. The proposed method was then successfully applied for analyses of triclosan content in water samples.

Expected value analysis for integrated supplier selection and inventory control of multi-product inventory system with fuzzy cost

NASA Astrophysics Data System (ADS)

Sutrisno, Widowati, Tjahjana, R. Heru

2017-12-01

The future cost in many industrial problem is obviously uncertain. Then a mathematical analysis for a problem with uncertain cost is needed. In this article, we deals with the fuzzy expected value analysis to solve an integrated supplier selection and supplier selection problem with uncertain cost where the costs uncertainty is approached by a fuzzy variable. We formulate the mathematical model of the problems fuzzy expected value based quadratic optimization with total cost objective function and solve it by using expected value based fuzzy programming. From the numerical examples result performed by the authors, the supplier selection problem was solved i.e. the optimal supplier was selected for each time period where the optimal product volume of all product that should be purchased from each supplier for each time period was determined and the product stock level was controlled as decided by the authors i.e. it was followed the given reference level.

Healthy Chilean Adolescents with HOMA-IR ≥ 2.6 Have Increased Cardiometabolic Risk: Association with Genetic, Biological, and Environmental Factors

PubMed Central

Burrows, R.; Correa-Burrows, P.; Reyes, M.; Blanco, E.; Albala, C.; Gahagan, S.

2015-01-01

Objective. To determine the optimal cutoff of the homeostasis model assessment-insulin resistance (HOMA-IR) for diagnosis of the metabolic syndrome (MetS) in adolescents and examine whether insulin resistance (IR), determined by this method, was related to genetic, biological, and environmental factors. Methods. In 667 adolescents (16.8 ± 0.3 y), BMI, waist circumference, glucose, insulin, adiponectin, diet, and physical activity were measured. Fat and fat-free mass were assessed by dual-energy X-ray absorptiometry. Family history of type 2 diabetes (FHDM) was reported. We determined the optimal cutoff of HOMA-IR to diagnose MetS (IDF criteria) using ROC analysis. IR was defined as HOMA-IR values above the cutoff. We tested the influence of genetic, biological, and environmental factors on IR using logistic regression analyses. Results. Of the participants, 16% were obese and 9.4 % met criteria for MetS. The optimal cutoff for MetS diagnosis was a HOMA-IR value of 2.6. Based on this value, 16.3% of participants had IR. Adolescents with IR had a significantly higher prevalence of obesity, abdominal obesity, fasting hyperglycemia, and MetS compared to those who were not IR. FHDM, sarcopenia, obesity, and low adiponectin significantly increased the risk of IR. Conclusions. In adolescents, HOMA-IR ≥ 2.6 was associated with greater cardiometabolic risk. PMID:26273675

Healthy Chilean Adolescents with HOMA-IR ≥ 2.6 Have Increased Cardiometabolic Risk: Association with Genetic, Biological, and Environmental Factors.

PubMed

Burrows, R; Correa-Burrows, P; Reyes, M; Blanco, E; Albala, C; Gahagan, S

2015-01-01

To determine the optimal cutoff of the homeostasis model assessment-insulin resistance (HOMA-IR) for diagnosis of the metabolic syndrome (MetS) in adolescents and examine whether insulin resistance (IR), determined by this method, was related to genetic, biological, and environmental factors. In 667 adolescents (16.8 ± 0.3 y), BMI, waist circumference, glucose, insulin, adiponectin, diet, and physical activity were measured. Fat and fat-free mass were assessed by dual-energy X-ray absorptiometry. Family history of type 2 diabetes (FHDM) was reported. We determined the optimal cutoff of HOMA-IR to diagnose MetS (IDF criteria) using ROC analysis. IR was defined as HOMA-IR values above the cutoff. We tested the influence of genetic, biological, and environmental factors on IR using logistic regression analyses. Of the participants, 16% were obese and 9.4 % met criteria for MetS. The optimal cutoff for MetS diagnosis was a HOMA-IR value of 2.6. Based on this value, 16.3% of participants had IR. Adolescents with IR had a significantly higher prevalence of obesity, abdominal obesity, fasting hyperglycemia, and MetS compared to those who were not IR. FHDM, sarcopenia, obesity, and low adiponectin significantly increased the risk of IR. In adolescents, HOMA-IR ≥ 2.6 was associated with greater cardiometabolic risk.

Multirate sampled-data yaw-damper and modal suppression system design

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.

1990-01-01

A multirate control law synthesized algorithm based on an infinite-time quadratic cost function, was developed along with a method for analyzing the robustness of multirate systems. A generalized multirate sampled-data control law structure (GMCLS) was introduced. A new infinite-time-based parameter optimization multirate sampled-data control law synthesis method and solution algorithm were developed. A singular-value-based method for determining gain and phase margins for multirate systems was also developed. The finite-time-based parameter optimization multirate sampled-data control law synthesis algorithm originally intended to be applied to the aircraft problem was instead demonstrated by application to a simpler problem involving the control of the tip position of a two-link robot arm. The GMCLS, the infinite-time-based parameter optimization multirate control law synthesis method and solution algorithm, and the singular-value based method for determining gain and phase margins were all demonstrated by application to the aircraft control problem originally proposed for this project.

A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation

PubMed Central

Eddy, Sean R.

2008-01-01

Sequence database searches require accurate estimation of the statistical significance of scores. Optimal local sequence alignment scores follow Gumbel distributions, but determining an important parameter of the distribution (λ) requires time-consuming computational simulation. Moreover, optimal alignment scores are less powerful than probabilistic scores that integrate over alignment uncertainty (“Forward” scores), but the expected distribution of Forward scores remains unknown. Here, I conjecture that both expected score distributions have simple, predictable forms when full probabilistic modeling methods are used. For a probabilistic model of local sequence alignment, optimal alignment bit scores (“Viterbi” scores) are Gumbel-distributed with constant λ = log 2, and the high scoring tail of Forward scores is exponential with the same constant λ. Simulation studies support these conjectures over a wide range of profile/sequence comparisons, using 9,318 profile-hidden Markov models from the Pfam database. This enables efficient and accurate determination of expectation values (E-values) for both Viterbi and Forward scores for probabilistic local alignments. PMID:18516236

Optimal correction and design parameter search by modern methods of rigorous global optimization

NASA Astrophysics Data System (ADS)

Makino, K.; Berz, M.

2011-07-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle optics for the computation of aberrations allow the determination of particularly sharp underestimators for large regions. As a consequence, the subsequent progressive pruning of the allowed search space as part of the optimization progresses is carried out particularly effectively. The end result is the rigorous determination of the single or multiple optimal solutions of the parameter optimization, regardless of their location, their number, and the starting values of optimization. The methods are particularly powerful if executed in interplay with genetic optimizers generating their new populations within the currently active unpruned space. Their current best guess provides rigorous upper bounds of the minima, which can then beneficially be used for better pruning. Examples of the method and its performance will be presented, including the determination of all operating points of desired tunes or chromaticities, etc. in storage ring lattices.

A risk-based multi-objective model for optimal placement of sensors in water distribution system

NASA Astrophysics Data System (ADS)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value of losses in WDS.

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.

Expected value information improves financial risk taking across the adult life span.

PubMed

Samanez-Larkin, Gregory R; Wagner, Anthony D; Knutson, Brian

2011-04-01

When making decisions, individuals must often compensate for cognitive limitations, particularly in the face of advanced age. Recent findings suggest that age-related variability in striatal activity may increase financial risk-taking mistakes in older adults. In two studies, we sought to further characterize neural contributions to optimal financial risk taking and to determine whether decision aids could improve financial risk taking. In Study 1, neuroimaging analyses revealed that individuals whose mesolimbic activation correlated with the expected value estimates of a rational actor made more optimal financial decisions. In Study 2, presentation of expected value information improved decision making in both younger and older adults, but the addition of a distracting secondary task had little impact on decision quality. Remarkably, provision of expected value information improved the performance of older adults to match that of younger adults at baseline. These findings are consistent with the notion that mesolimbic circuits play a critical role in optimal choice, and imply that providing simplified information about expected value may improve financial risk taking across the adult life span.

Optimizing the availability of a buffered industrial process

DOEpatents

Martz, Jr., Harry F.; Hamada, Michael S.; Koehler, Arthur J.; Berg, Eric C.

2004-08-24

A computer-implemented process determines optimum configuration parameters for a buffered industrial process. A population size is initialized by randomly selecting a first set of design and operation values associated with subsystems and buffers of the buffered industrial process to form a set of operating parameters for each member of the population. An availability discrete event simulation (ADES) is performed on each member of the population to determine the product-based availability of each member. A new population is formed having members with a second set of design and operation values related to the first set of design and operation values through a genetic algorithm and the product-based availability determined by the ADES. Subsequent population members are then determined by iterating the genetic algorithm with product-based availability determined by ADES to form improved design and operation values from which the configuration parameters are selected for the buffered industrial process.

Value of information analysis optimizing future trial design from a pilot study on catheter securement devices.

PubMed

Tuffaha, Haitham W; Reynolds, Heather; Gordon, Louisa G; Rickard, Claire M; Scuffham, Paul A

2014-12-01

Value of information analysis has been proposed as an alternative to the standard hypothesis testing approach, which is based on type I and type II errors, in determining sample sizes for randomized clinical trials. However, in addition to sample size calculation, value of information analysis can optimize other aspects of research design such as possible comparator arms and alternative follow-up times, by considering trial designs that maximize the expected net benefit of research, which is the difference between the expected cost of the trial and the expected value of additional information. To apply value of information methods to the results of a pilot study on catheter securement devices to determine the optimal design of a future larger clinical trial. An economic evaluation was performed using data from a multi-arm randomized controlled pilot study comparing the efficacy of four types of catheter securement devices: standard polyurethane, tissue adhesive, bordered polyurethane and sutureless securement device. Probabilistic Monte Carlo simulation was used to characterize uncertainty surrounding the study results and to calculate the expected value of additional information. To guide the optimal future trial design, the expected costs and benefits of the alternative trial designs were estimated and compared. Analysis of the value of further information indicated that a randomized controlled trial on catheter securement devices is potentially worthwhile. Among the possible designs for the future trial, a four-arm study with 220 patients/arm would provide the highest expected net benefit corresponding to 130% return-on-investment. The initially considered design of 388 patients/arm, based on hypothesis testing calculations, would provide lower net benefit with return-on-investment of 79%. Cost-effectiveness and value of information analyses were based on the data from a single pilot trial which might affect the accuracy of our uncertainty estimation. Another limitation was that different follow-up durations for the larger trial were not evaluated. The value of information approach allows efficient trial design by maximizing the expected net benefit of additional research. This approach should be considered early in the design of randomized clinical trials. © The Author(s) 2014.

Determination of glucosinolates in rapeseed and Thlaspi caerulescens plants by liquid chromatography-atmospheric pressure chemical ionization mass spectrometry.

PubMed

Tolrà, R P; Alonso, R; Poschenrieder, C; Barceló, D; Barceló, J

2000-08-11

Liquid chromatography-atmospheric pressure chemical ionization mass spectrometry was used to identify glucosinolates in plant extracts. Optimization of the analytical conditions and the determination of the method detection limit was performed using commercial 2-propenylglucosinolate (sinigrin). Optimal values for the following parameters were determined: nebulization pressure, gas temperature, flux of drying gas, capillar voltage, corona current and fragmentor conditions. The method detection limit for sinigrin was 2.85 ng. For validation of the method the glucosinolates in reference material (rapeseed) from the Community Bureau of Reference Materials (BCR) were analyzed. The method was applied for the determination of glucosinolates in Thlaspi caerulescens plants.

Optimization of preparation of antioxidative peptides from pumpkin seeds using response surface method.

PubMed

Fan, Sanhong; Hu, Yanan; Li, Chen; Liu, Yanrong

2014-01-01

Protein isolates of pumpkin (Cucurbita pepo L) seeds were hydrolyzed by acid protease to prepare antioxidative peptides. The hydrolysis conditions were optimized through Box-Behnken experimental design combined with response surface method (RSM). The second-order model, developed for the DPPH radical scavenging activity of pumpkin seed hydrolysates, showed good fit with the experiment data with a high value of coefficient of determination (0.9918). The optimal hydrolysis conditions were determined as follows: hydrolyzing temperature 50°C, pH 2.5, enzyme amount 6000 U/g, substrate concentration 0.05 g/ml and hydrolyzing time 5 h. Under the above conditions, the scavenging activity of DPPH radical was as high as 92.82%.

Attitude determination and parameter estimation using vector observations - Theory

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1989-01-01

Procedures for attitude determination based on Wahba's loss function are generalized to include the estimation of parameters other than the attitude, such as sensor biases. Optimization with respect to the attitude is carried out using the q-method, which does not require an a priori estimate of the attitude. Optimization with respect to the other parameters employs an iterative approach, which does require an a priori estimate of these parameters. Conventional state estimation methods require a priori estimates of both the parameters and the attitude, while the algorithm presented in this paper always computes the exact optimal attitude for given values of the parameters. Expressions for the covariance of the attitude and parameter estimates are derived.

A new potential for radiation studies of borosilicate glass

NASA Astrophysics Data System (ADS)

Alharbi, Amal F.; Jolley, Kenny; Smith, Roger; Archer, Andrew J.; Christie, Jamieson K.

2017-02-01

Borosilicate glass containing 70 mol% SiO2 and 30 mol% B2O3 is investigated theoretically using fixed charge potentials. An existing potential parameterisation for borosilicate glass is found to give good agreement for the bond angle and bond length distributions compared to experimental values but the optimal density is 30% higher than experiment. Therefore the potential parameters are refitted to give an optimal density of 2.1 g/cm3, in line with experiment. To determine the optimal density, a series of random initial structures are quenched at a rate of 5 × 1012 K/s using constant volume molecular dynamics. An average of 10 such quenches is carried out for each fixed volume. For each quenched structure, the bond angles, bond lengths, mechanical properties and melting points are determined. The new parameterisation is found to give the density, bond angles, bond lengths and Young's modulus comparable with experimental data, however, the melting points and Poisson's ratio are higher than the reported experimental values. The displacement energy thresholds are computed to be similar to those determined with the earlier parameterisation, which is lower than those for ionic crystalline materials.

Optimization of microwave-assisted extraction (MAE) of coriander phenolic antioxidants - response surface methodology approach.

PubMed

Zeković, Zoran; Vladić, Jelena; Vidović, Senka; Adamović, Dušan; Pavlić, Branimir

2016-10-01

Microwave-assisted extraction (MAE) of polyphenols from coriander seeds was optimized by simultaneous maximization of total phenolic (TP) and total flavonoid (TF) yields, as well as maximized antioxidant activity determined by 1,1-diphenyl-2-picrylhydrazyl and reducing power assays. Box-Behnken experimental design with response surface methodology (RSM) was used for optimization of MAE. Extraction time (X1 , 15-35 min), ethanol concentration (X2 , 50-90% w/w) and irradiation power (X3 , 400-800 W) were investigated as independent variables. Experimentally obtained values of investigated responses were fitted to a second-order polynomial model, and multiple regression analysis and analysis of variance were used to determine fitness of the model and optimal conditions. The optimal MAE conditions for simultaneous maximization of polyphenol yield and increased antioxidant activity were an extraction time of 19 min, an ethanol concentration of 63% and an irradiation power of 570 W, while predicted values of TP, TF, IC50 and EC50 at optimal MAE conditions were 311.23 mg gallic acid equivalent per 100 g dry weight (DW), 213.66 mg catechin equivalent per 100 g DW, 0.0315 mg mL(-1) and 0.1311 mg mL(-1) respectively. RSM was successfully used for multi-response optimization of coriander seed polyphenols. Comparison of optimized MAE with conventional extraction techniques confirmed that MAE provides significantly higher polyphenol yields and extracts with increased antioxidant activity. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Optimization of the preparation conditions of ceramic products using drinking water treatment sludges.

PubMed

Zamora, R M Ramirez; Ayala, F Espesel; Garcia, L Chavez; Moreno, A Duran; Schouwenaars, R

2008-11-01

The aim of this work is to optimize, via Response Surface Methodology, the values of the main process parameters for the production of ceramic products using sludges obtained from drinking water treatment in order to valorise them. In the first experimental stage, sludges were collected from a drinking water treatment plant for characterization. In the second stage, trials were carried out to elaborate thin cross-section specimens and fired bricks following an orthogonal central composite design of experiments with three factors (sludge composition, grain size and firing temperature) and five levels. The optimization parameters (Y(1)=shrinking by firing (%), Y(2)=water absorption (%), Y(3)=density (g/cm(3)) and Y(4)=compressive strength (kg/cm(2))) were determined according to standardized analytical methods. Two distinct physicochemical processes were active during firing at different conditions in the experimental design, preventing the determination of a full response surface, which would allow direct optimization of production parameters. Nevertheless, the temperature range for the production of classical red brick was closely delimitated by the results; above this temperature, a lightweight ceramic with surprisingly high strength was produced, opening possibilities for the valorisation of a product with considerably higher added value than what was originally envisioned.

Optimizing the Determination of Roughness Parameters for Model Urban Canopies

NASA Astrophysics Data System (ADS)

Huq, Pablo; Rahman, Auvi

2018-05-01

We present an objective optimization procedure to determine the roughness parameters for very rough boundary-layer flow over model urban canopies. For neutral stratification the mean velocity profile above a model urban canopy is described by the logarithmic law together with the set of roughness parameters of displacement height d, roughness length z_0 , and friction velocity u_* . Traditionally, values of these roughness parameters are obtained by fitting the logarithmic law through (all) the data points comprising the velocity profile. The new procedure generates unique velocity profiles from subsets or combinations of the data points of the original velocity profile, after which all possible profiles are examined. Each of the generated profiles is fitted to the logarithmic law for a sequence of values of d, with the representative value of d obtained from the minima of the summed least-squares errors for all the generated profiles. The representative values of z_0 and u_* are identified by the peak in the bivariate histogram of z_0 and u_* . The methodology has been verified against laboratory datasets of flow above model urban canopies.

A pragmatic approach to determine the optimal kVp in cone beam CT: balancing contrast-to-noise ratio and radiation dose

PubMed Central

Silkosessak, O; Jacobs, R; Bogaerts, R; Bosmans, H; Panmekiate, S

2014-01-01

Objectives: To determine the optimal kVp setting for a particular cone beam CT (CBCT) device by maximizing technical image quality at a fixed radiation dose. Methods: The 3D Accuitomo 170 (J. Morita Mfg. Corp., Kyoto, Japan) CBCT was used. The radiation dose as a function of kVp was measured in a cylindrical polymethyl methacrylate (PMMA) phantom using a small-volume ion chamber. Contrast-to-noise ratio (CNR) was measured using a PMMA phantom containing four materials (air, aluminium, polytetrafluoroethylene and low-density polyethylene), which was scanned using 180 combinations of kVp/mA, ranging from 60/1 to 90/8. The CNR was measured for each material using PMMA as background material. The pure effect of kVp and mAs on the CNR values was analysed. Using a polynomial fit for CNR as a function of mA for each kVp value, the optimal kVp was determined at five dose levels. Results: Absorbed doses ranged between 0.034 mGy mAs−1 (14 × 10 cm, 60 kVp) and 0.108 mGy mAs−1 (14 × 10 cm, 90 kVp). The relation between kVp and dose was quasilinear (R2 > 0.99). The effect of mA and kVp on CNR could be modelled using a second-degree polynomial. At a fixed dose, there was a tendency for higher CNR values at increasing kVp values, especially at low dose levels. A dose reduction through mA was more efficient than an equivalent reduction through kVp in terms of image quality deterioration. Conclusions: For the investigated CBCT model, the most optimal contrast at a fixed dose was found at the highest available kVp setting. There is great potential for dose reduction through mA with a minimal loss in image quality. PMID:24708447

Optimization of thermoelectric cooling regimes for heat-loaded elements taking into account the thermal resistance of the heat-spreading system

NASA Astrophysics Data System (ADS)

Vasil'ev, E. N.

2017-09-01

A mathematical model has been proposed for analyzing and optimizing thermoelectric cooling regimes for heat-loaded elements of engineering and electronic devices. The model based on analytic relations employs the working characteristics of thermoelectric modules as the initial data and makes it possible to determine the temperature regime and the optimal values of the feed current for the modules taking into account the thermal resistance of the heat-spreading system.

Defining a region of optimization based on engine usage data

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2015-08-04

Methods and systems for engine control optimization are provided. One or more operating conditions of a vehicle engine are detected. A value for each of a plurality of engine control parameters is determined based on the detected one or more operating conditions of the vehicle engine. A range of the most commonly detected operating conditions of the vehicle engine is identified and a region of optimization is defined based on the range of the most commonly detected operating conditions of the vehicle engine. The engine control optimization routine is initiated when the one or more operating conditions of the vehicle engine are within the defined region of optimization.

[Development of an optimal scheme for calculating results of the use of an immunoenzyme test-system for determining the antigenic activity of a cultured antirabies vaccine].

PubMed

Tsetlin, E M; Volkova, R A

1996-01-01

Ninety-eight lots of commercial antirabies vaccine manufactured by Immunopreparat Research and Production Amalgamation have been tested using enzyme immunoassay system for the detection of rabies virus antigens. Comparison of different variants of interpreting and expressing the results helped define the optimal method for assessment of vaccine titer and reference values: optical density value equal to 0.2 is taken as the cut-off. Antigenic activity of the vaccine may be expressed in international units, similarly as immunogenic activity.

A theoretical measure technique for determining 3D symmetric nearly optimal shapes with a given center of mass

NASA Astrophysics Data System (ADS)

Alimorad D., H.; Fakharzadeh J., A.

2017-07-01

In this paper, a new approach is proposed for designing the nearly-optimal three dimensional symmetric shapes with desired physical center of mass. Herein, the main goal is to find such a shape whose image in ( r, θ)-plane is a divided region into a fixed and variable part. The nearly optimal shape is characterized in two stages. Firstly, for each given domain, the nearly optimal surface is determined by changing the problem into a measure-theoretical one, replacing this with an equivalent infinite dimensional linear programming problem and approximating schemes; then, a suitable function that offers the optimal value of the objective function for any admissible given domain is defined. In the second stage, by applying a standard optimization method, the global minimizer surface and its related domain will be obtained whose smoothness is considered by applying outlier detection and smooth fitting methods. Finally, numerical examples are presented and the results are compared to show the advantages of the proposed approach.

Extraction of gelatin from salmon (Salmo salar) fish skin using trypsin-aided process: optimization by Plackett-Burman and response surface methodological approaches.

PubMed

Fan, HuiYin; Dumont, Marie-Josée; Simpson, Benjamin K

2017-11-01

Gelatin from salmon ( Salmo salar ) skin with high molecular weight protein chains ( α -chains) was extracted using trypsin-aided process. Response surface methodology was used to optimise the extraction parameters. Yield, hydroxyproline content and protein electrophoretic profile via sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of gelatin were used as responses in the optimization study. The optimum conditions were determined as: trypsin concentration at 1.49 U/g; extraction temperature at 45 °C; and extraction time at 6 h 16 min. This response surface optimized model was significant and produced an experimental value (202.04 ± 8.64%) in good agreement with the predicted value (204.19%). Twofold higher yields of gelatin with high molecular weight protein chains were achieved in the optimized process with trypsin treatment when compared to the process without trypsin.

Optimizing concentration of shifter additive for plastic scintillators of different size

NASA Astrophysics Data System (ADS)

Adadurov, A. F.; Zhmurin, P. N.; Lebedev, V. N.; Titskaya, V. D.

2009-02-01

This paper concerns the influence of wavelength shifting (secondary) luminescent additive (LA 2) on the light yield of polystyrene-based plastic scintillator (PS) taking self-absorption into account. Calculations of light yield dependence on concentration of 1.4-bis(2-(5-phenyloxazolyl)-benzene (POPOP) as LA 2 were made for various path lengths of photons in PS. It is shown that there is an optimal POPOP concentration ( Copt), which provides a maximum light yield for a given path length. This optimal concentration is determined by the competition of luminescence and self-reflection processes. Copt values were calculated for PS of different dimensions. For small PS, Copt≈0.02%, which agree with a common (standard) value of POPOP concentration. For higher PS dimensions, the optimal POPOP concentration is decreased (to Copt≈0.006% for 320×30×2 cm sample), reducing the light yield from PS by almost 35%.

NEMA NU 4-Optimized Reconstructions for Therapy Assessment in Cancer Research with the Inveon Small Animal PET/CT System.

PubMed

Lasnon, Charline; Dugue, Audrey Emmanuelle; Briand, Mélanie; Blanc-Fournier, Cécile; Dutoit, Soizic; Louis, Marie-Hélène; Aide, Nicolas

2015-06-01

We compared conventional filtered back-projection (FBP), two-dimensional-ordered subsets expectation maximization (OSEM) and maximum a posteriori (MAP) NEMA NU 4-optimized reconstructions for therapy assessment. Varying reconstruction settings were used to determine the parameters for optimal image quality with two NEMA NU 4 phantom acquisitions. Subsequently, data from two experiments in which nude rats bearing subcutaneous tumors had received a dual PI3K/mTOR inhibitor were reconstructed with the NEMA NU 4-optimized parameters. Mann-Whitney tests were used to compare mean standardized uptake value (SUV(mean)) variations among groups. All NEMA NU 4-optimized reconstructions showed the same 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) kinetic patterns and detected a significant difference in SUV(mean) relative to day 0 between controls and treated groups for all time points with comparable p values. In the framework of therapy assessment in rats bearing subcutaneous tumors, all algorithms available on the Inveon system performed equally.

Optimization of the omega-3 extraction as a functional food from flaxseed.

PubMed

Hassan-Zadeh, A; Sahari, M A; Barzegar, M

2008-09-01

The fatty acid content, total lipid, refractive index, peroxide, iodine, acid and saponification values of Iranian linseed oil (Linum usitatissimum) were studied. For optimization of extraction conditions, this oil was extracted by solvents (petroleum benzene and methanol-water-petroleum benzene) in 1:2, 1:3 and 1:4 ratios at 2, 5 and 8 h. Then its fatty acid content, omega-3 content and extraction yield were determined. According to the statistical analysis, petroleum benzene in a ratio of 1:3 at 5 h was chosen for the higher fatty acid, extraction yield, and economical feasibility. For preservation of omega-3 ingredients, oil with specified characters containing 46.8% omega-3 was kept under a nitrogen atmosphere at -30 degrees C during 0, 7, 30, 60 and 90 days and its peroxide value was determined. Statistical analysis showed a significant difference in the average amount of peroxide value only on the first 7 days of storage, and its increase (8.30%) conformed to the international standard.

Optimization of the Use of Selected Non-Phosphate Water Retention Additives in Minced Beef Using Response Surface Methodology

NASA Astrophysics Data System (ADS)

Shang, Xiaolan; Qiao, Jie; Liu, Yujie

2017-12-01

This study looked to determine what the optimum cooking loss for minced beef was when three different non-phosphate water retention additives (L-Arginine, sodium carbonate, and sodium citrate) were combined; the optimum value was determined using a Box-Behnken response surface design method. The optimum value was found to be 8.26%, and it was obtained when 0.29% L-Arginine, 0.45% sodium carbonate, and 0.24% sodium citrate were added to the beef.

Re-evaluation of the reported experimental values of the heat of vaporization of N-methylacetamide

PubMed Central

MacKerell, Alexander D.; Shim, Ji Hyun; Anisimov, Victor M.

2010-01-01

The accuracy of empirical force fields is inherently related to the quality of the target data used for optimization of the model. With the heat of vaporization (ΔHvap) of N-methylacetamide (NMA), a range of values have been reported as target data for optimization of the nonbond parameters associated with the peptide bond in proteins. In the present work, the original experimental data and Antoine constants used for the determination of the ΔHvap of NMA are reanalyzed. Based on this analysis, the wide range of ΔHvap values reported in the literature are shown to be due to incorrect reporting of the temperatures at which the original values were extracted and limitations in the quality of experimental vapor pressure-temperature data over a wide range of temperatures. Taking these problems into account, a consistent ΔHvap value is extracted from three studies for which experimental data are available. This analysis suggests that the most reliable value for ΔHvap is 13.0±0.1 at 410 K for use in force field optimization studies. The present results also indicate that similar analyses, including analysis of Antoine constants alone, may be of utility when reported ΔHvap values are not consistent for a given neat liquid. PMID:20445813

Shape optimization of road tunnel cross-section by simulated annealing

NASA Astrophysics Data System (ADS)

Sobótka, Maciej; Pachnicz, Michał

2016-06-01

The paper concerns shape optimization of a tunnel excavation cross-section. The study incorporates optimization procedure of the simulated annealing (SA). The form of a cost function derives from the energetic optimality condition, formulated in the authors' previous papers. The utilized algorithm takes advantage of the optimization procedure already published by the authors. Unlike other approaches presented in literature, the one introduced in this paper takes into consideration a practical requirement of preserving fixed clearance gauge. Itasca Flac software is utilized in numerical examples. The optimal excavation shapes are determined for five different in situ stress ratios. This factor significantly affects the optimal topology of excavation. The resulting shapes are elongated in the direction of a principal stress greater value. Moreover, the obtained optimal shapes have smooth contours circumscribing the gauge.

Applying complex models to poultry production in the future--economics and biology.

PubMed

Talpaz, H; Cohen, M; Fancher, B; Halley, J

2013-09-01

The ability to determine the optimal broiler feed nutrient density that maximizes margin over feeding cost (MOFC) has obvious economic value. To determine optimal feed nutrient density, one must consider ingredient prices, meat values, the product mix being marketed, and the projected biological performance. A series of 8 feeding trials was conducted to estimate biological responses to changes in ME and amino acid (AA) density. Eight different genotypes of sex-separate reared broilers were fed diets varying in ME (2,723-3,386 kcal of ME/kg) and AA (0.89-1.65% digestible lysine with all essential AA acids being indexed to lysine) levels. Broilers were processed to determine carcass component yield at many different BW (1.09-4.70 kg). Trial data generated were used in model constructed to discover the dietary levels of ME and AA that maximize MOFC on a per broiler or per broiler annualized basis (bird × number of cycles/year). The model was designed to estimate the effects of dietary nutrient concentration on broiler live weight, feed conversion, mortality, and carcass component yield. Estimated coefficients from the step-wise regression process are subsequently used to predict the optimal ME and AA concentrations that maximize MOFC. The effects of changing feed or meat prices across a wide spectrum on optimal ME and AA levels can be evaluated via parametric analysis. The model can rapidly compare both biological and economic implications of changing from current practice to the simulated optimal solution. The model can be exploited to enhance decision making under volatile market conditions.

Optimization of permeate flux produced by solar energy driven membrane distillation process using central composite design approach.

PubMed

Bouguecha, Salah T; Boubakri, Ali; Aly, Samir E; Al-Beirutty, Mohammad H; Hamdi, Mohamed M

2016-01-01

Membrane distillation (MD) is considered as a relatively high-energy requirement. To overcome this drawback, it is recommended to couple the MD process with solar energy as the renewable energy source in order to provide heat energy required to optimize its performance to produce permeate flux. In the present work, an original solar energy driven direct contact membrane distillation (DCMD) pilot plant was built and tested under actual weather conditions at Jeddah, KSA, in order to model and optimize permeate flux. The dependency of permeate flux on various operating parameters such as feed temperature (46.6-63.4°C), permeate temperature (6.6-23.4°C), feed flow rate (199-451L/h) and permeate flow rate (199-451L/h) was studied by response surface methodology based on central composite design approach. The analysis of variance (ANOVA) confirmed that all independent variables had significant influence on the model (where P-value <0.05). The high coefficient of determination (R(2) = 0.9644 and R(adj)(2) = 0.9261) obtained by ANOVA demonstrated good correlation between experimental and predicted values of the response. The optimized conditions, determined using desirability function, were T(f) = 63.4°C, Tp = 6.6°C, Q(f) = 451L/h and Q(p) = 451L/h. Under these conditions, the maximum permeate flux of 6.122 kg/m(2).h was achieved, which was close to the predicted value of 6.398 kg/m(2).h.

Development and validation of ultrasound-assisted solid-liquid extraction of phenolic compounds from waste spent coffee grounds.

PubMed

Al-Dhabi, Naif Abdullah; Ponmurugan, Karuppiah; Maran Jeganathan, Prakash

2017-01-01

In this current work, Box-Behnken statistical experimental design (BBD) was adopted to evaluate and optimize USLE (ultrasound-assisted solid-liquid extraction) of phytochemicals from spent coffee grounds. Factors employed in this study are ultrasonic power, temperature, time and solid-liquid (SL) ratio. Individual and interactive effect of independent variables over the extraction yield was depicted through mathematical models, which are generated from the experimental data. Determined optimum process conditions are 244W of ultrasonic power, 40°C of temperature, 34min of time and 1:17g/ml of SL ratio. The predicted values were in correlation with experimental values with 95% confidence level, under the determined optimal conditions. This indicates the significance of selected method for USLE of phytochemicals from SCG. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimization protocol for the extraction of 6-gingerol and 6-shogaol from Zingiber officinale var. rubrum Theilade and improving antioxidant and anticancer activity using response surface methodology.

PubMed

Ghasemzadeh, Ali; Jaafar, Hawa Z E; Rahmat, Asmah

2015-07-30

Analysis and extraction of plant matrices are important processes for the development, modernization, and quality control of herbal formulations. Response surface methodology is a collection of statistical and mathematical techniques that are used to optimize the range of variables in various experimental processes to reduce the number of experimental runs, cost , and time, compared to other methods. Response surface methodology was applied for optimizing reflux extraction conditions for achieving high 6-gingerol and 6-shogaol contents, and high antioxidant activity in Zingiber officinale var. rubrum Theilade . The two-factor central composite design was employed to determine the effects of two independent variables, namely extraction temperature (X1: 50-80 °C) and time (X2: 2-4 h), on the properties of the extracts. The 6-gingerol and 6-shogaol contents were measured using ultra-performance liquid chromatography. The antioxidant activity of the rhizome extracts was determined by means of the 1,1-diphenyl-2-picrylhydrazyl assay. Anticancer activity of optimized extracts against HeLa cancer cell lines was measured using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Increasing the extraction temperature and time induced significant response of the variables. The optimum extraction condition for all responses was at 76.9 °C for 3.4 h. Under the optimum condition, the corresponding predicted response values for 6-gingerol, 6-shogaol, and the antioxidant activity were 2.89 mg/g DW, 1.85 mg/g DW, and 84.3%, respectively. 6-gingerol and 6-shogaol were extracted under optimized condition to check the viability of the models. The values were 2.92 and 1.88 mg/g DW, and 84.0% for 6-gingerol, 6-shogaol, and the antioxidant activity respectively. The experimental values agreed with those predicted, thus indicating suitability of the models employed and the success of RSM in optimizing the extraction condition. With optimizing of reflux extraction anticancer activity of extracts against HeLa cancer cells enhanced about 16.8%. The half inhibition concentration (IC50) value of optimized and unoptimized extract was found at concentration of 20.9 and 38.4 μg/mL respectively. Optimized extract showed more distinct anticancer activities against HeLa cancer cells in a concentration of 40 μg/mL (P < 0.01) without toxicity to normal cells. The results indicated that the pharmaceutical quality of ginger could be improved significantly by optimizing of extraction process using response surface methodology.

Singular values behaviour optimization in the diagnosis of feed misalignments in radioastronomical reflectors

NASA Astrophysics Data System (ADS)

Capozzoli, Amedeo; Curcio, Claudio; Liseno, Angelo; Savarese, Salvatore; Schipani, Pietro

2016-07-01

The communication presents an innovative method for the diagnosis of reflector antennas in radio astronomical applications. The approach is based on the optimization of the number and the distribution of the far field sampling points exploited to retrieve the antenna status in terms of feed misalignments, this to drastically reduce the time length of the measurement process and minimize the effects of variable environmental conditions and simplifying the tracking process of the source. The feed misplacement is modeled in terms of an aberration function of the aperture field. The relationship between the unknowns and the far field pattern samples is linearized thanks to a Principal Component Analysis. The number and the position of the field samples are then determined by optimizing the Singular Values behaviour of the relevant operator.

Modeling and Optimization of NLDH/PVDF Ultrafiltration Nanocomposite Membrane Using Artificial Neural Network-Genetic Algorithm Hybrid.

PubMed

Arefi-Oskoui, Samira; Khataee, Alireza; Vatanpour, Vahid

2017-07-10

In this research, MgAl-CO 3 2- nanolayered double hydroxide (NLDH) was synthesized through a facile coprecipitation method, followed by a hydrothermal treatment. The prepared NLDHs were used as a hydrophilic nanofiller for improving the performance of the PVDF-based ultrafiltration membranes. The main objective of this research was to obtain the optimized formula of NLDH/PVDF nanocomposite membrane presenting the best performance using computational techniques as a cost-effective method. For this aim, an artificial neural network (ANN) model was developed for modeling and expressing the relationship between the performance of the nanocomposite membrane (pure water flux, protein flux and flux recovery ratio) and the affecting parameters including the NLDH, PVP 29000 and polymer concentrations. The effects of the mentioned parameters and the interaction between the parameters were investigated using the contour plot predicted with the developed model. Scanning electron microscopy (SEM), atomic force microscopy (AFM), and water contact angle techniques were applied to characterize the nanocomposite membranes and to interpret the predictions of the ANN model. The developed ANN model was introduced to genetic algorithm (GA) as a bioinspired optimizer to determine the optimum values of input parameters leading to high pure water flux, protein flux, and flux recovery ratio. The optimum values for NLDH, PVP 29000 and the PVDF concentration were determined to be 0.54, 1, and 18 wt %, respectively. The performance of the nanocomposite membrane prepared using the optimum values proposed by GA was investigated experimentally, in which the results were in good agreement with the values predicted by ANN model with error lower than 6%. This good agreement confirmed that the nanocomposite membranes prformance could be successfully modeled and optimized by ANN-GA system.

Transvesical Intra-Abdominal Pressure Measurement in Newborn: What Is the Optimal Saline Volume Instillation?

PubMed

Defontaine, Anne; Tirel, Olivier; Costet, Nathalie; Beuchée, Alain; Ozanne, Bruno; Gaillot, Théophile; Arnaud, Alexis Pierre; Wodey, Eric

2016-02-01

To determine the optimal saline volume bladder instillation to measure intravesical pressure in critically ill newborns weighing less than 4.5 kg, and to establish a reference of intra-abdominal pressure value in this population. Prospective monocentric study. Neonatal ICU and PICU. Newborns, premature or not, weighing less than 4.5 kg who required a urethral catheter. Patients were classified into two groups according to whether they presented a risk factor for intra-abdominal hypertension. Nine intravesical pressure measures per patient were performed after different volume saline instillation. The first one was done without saline instillation and then by increments of 0.5 mL/kg to a maximum of 4 mL/kg. Linear models for repeated measurements of intravesical pressure with unstructured covariance were used to analyze the variation of intravesical pressure measures according to the conditions of measurement (volume instilled). Pairwise comparisons of intravesical pressure adjusted mean values between instillation volumes were done using Tukey tests, corrected for multiple testing to determine an optimal instillation volume. Forty-seven patients with completed measures (nine instillations volumes) were included in the analysis. Mean intravesical pressure values were not significantly different when measured after instillation of 0.5, 1, or 1.5 mL/kg, whereas measures after instillation of 2 mL/kg or more were significantly higher. The median intravesical pressure value in the group without intra-abdominal hypertension risk factor after instillation of 1 mL/kg was 5 mm Hg (2-6 mm Hg). The optimal saline volume bladder instillation to measure intra-abdominal pressure in newborns weighing less than 4.5 kg was 1 mL/kg. Reference intra-abdominal pressure in this population was found to be 5 mm Hg (2-6 mm Hg).

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

A hydroeconomic modeling framework for optimal integrated management of forest and water

NASA Astrophysics Data System (ADS)

Garcia-Prats, Alberto; del Campo, Antonio D.; Pulido-Velazquez, Manuel

2016-10-01

Forests play a determinant role in the hydrologic cycle, with water being the most important ecosystem service they provide in semiarid regions. However, this contribution is usually neither quantified nor explicitly valued. The aim of this study is to develop a novel hydroeconomic modeling framework for assessing and designing the optimal integrated forest and water management for forested catchments. The optimization model explicitly integrates changes in water yield in the stands (increase in groundwater recharge) induced by forest management and the value of the additional water provided to the system. The model determines the optimal schedule of silvicultural interventions in the stands of the catchment in order to maximize the total net benefit in the system. Canopy cover and biomass evolution over time were simulated using growth and yield allometric equations specific for the species in Mediterranean conditions. Silvicultural operation costs according to stand density and canopy cover were modeled using local cost databases. Groundwater recharge was simulated using HYDRUS, calibrated and validated with data from the experimental plots. In order to illustrate the presented modeling framework, a case study was carried out in a planted pine forest (Pinus halepensis Mill.) located in south-western Valencia province (Spain). The optimized scenario increased groundwater recharge. This novel modeling framework can be used in the design of a "payment for environmental services" scheme in which water beneficiaries could contribute to fund and promote efficient forest management operations.

Optimization of Preparation of Antioxidative Peptides from Pumpkin Seeds Using Response Surface Method

PubMed Central

Fan, Sanhong; Hu, Yanan; Li, Chen; Liu, Yanrong

2014-01-01

Protein isolates of pumpkin (Cucurbita pepo L) seeds were hydrolyzed by acid protease to prepare antioxidative peptides. The hydrolysis conditions were optimized through Box-Behnken experimental design combined with response surface method (RSM). The second-order model, developed for the DPPH radical scavenging activity of pumpkin seed hydrolysates, showed good fit with the experiment data with a high value of coefficient of determination (0.9918). The optimal hydrolysis conditions were determined as follows: hydrolyzing temperature 50°C, pH 2.5, enzyme amount 6000 U/g, substrate concentration 0.05 g/ml and hydrolyzing time 5 h. Under the above conditions, the scavenging activity of DPPH radical was as high as 92.82%. PMID:24637721

Optimization of a pH-shift control strategy for producing monoclonal antibodies in Chinese hamster ovary cell cultures using a pH-dependent dynamic model.

PubMed

Hogiri, Tomoharu; Tamashima, Hiroshi; Nishizawa, Akitoshi; Okamoto, Masahiro

2018-02-01

To optimize monoclonal antibody (mAb) production in Chinese hamster ovary cell cultures, culture pH should be temporally controlled with high resolution. In this study, we propose a new pH-dependent dynamic model represented by simultaneous differential equations including a minimum of six system component, depending on pH value. All kinetic parameters in the dynamic model were estimated using an evolutionary numerical optimization (real-coded genetic algorithm) method based on experimental time-course data obtained at different pH values ranging from 6.6 to 7.2. We determined an optimal pH-shift schedule theoretically. We validated this optimal pH-shift schedule experimentally and mAb production increased by approximately 40% with this schedule. Throughout this study, it was suggested that the culture pH-shift optimization strategy using a pH-dependent dynamic model is suitable to optimize any pH-shift schedule for CHO cell lines used in mAb production projects. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Algorithms and analyses for stochastic optimization for turbofan noise reduction using parallel reduced-order modeling

NASA Astrophysics Data System (ADS)

Yang, Huanhuan; Gunzburger, Max

2017-06-01

Simulation-based optimization of acoustic liner design in a turbofan engine nacelle for noise reduction purposes can dramatically reduce the cost and time needed for experimental designs. Because uncertainties are inevitable in the design process, a stochastic optimization algorithm is posed based on the conditional value-at-risk measure so that an ideal acoustic liner impedance is determined that is robust in the presence of uncertainties. A parallel reduced-order modeling framework is developed that dramatically improves the computational efficiency of the stochastic optimization solver for a realistic nacelle geometry. The reduced stochastic optimization solver takes less than 500 seconds to execute. In addition, well-posedness and finite element error analyses of the state system and optimization problem are provided.

Determination of the optimal tolerance for MLC positioning in sliding window and VMAT techniques

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

Hernandez, V., E-mail: vhernandezmasgrau@gmail.com; Abella, R.; Calvo, J. F.

2015-04-15

Purpose: Several authors have recommended a 2 mm tolerance for multileaf collimator (MLC) positioning in sliding window treatments. In volumetric modulated arc therapy (VMAT) treatments, however, the optimal tolerance for MLC positioning remains unknown. In this paper, the authors present the results of a multicenter study to determine the optimal tolerance for both techniques. Methods: The procedure used is based on dynalog file analysis. The study was carried out using seven Varian linear accelerators from five different centers. Dynalogs were collected from over 100 000 clinical treatments and in-house software was used to compute the number of tolerance faults as amore » function of the user-defined tolerance. Thus, the optimal value for this tolerance, defined as the lowest achievable value, was investigated. Results: Dynalog files accurately predict the number of tolerance faults as a function of the tolerance value, especially for low fault incidences. All MLCs behaved similarly and the Millennium120 and the HD120 models yielded comparable results. In sliding window techniques, the number of beams with an incidence of hold-offs >1% rapidly decreases for a tolerance of 1.5 mm. In VMAT techniques, the number of tolerance faults sharply drops for tolerances around 2 mm. For a tolerance of 2.5 mm, less than 0.1% of the VMAT arcs presented tolerance faults. Conclusions: Dynalog analysis provides a feasible method for investigating the optimal tolerance for MLC positioning in dynamic fields. In sliding window treatments, the tolerance of 2 mm was found to be adequate, although it can be reduced to 1.5 mm. In VMAT treatments, the typically used 5 mm tolerance is excessively high. Instead, a tolerance of 2.5 mm is recommended.« less

Application of Box-Behnken design for ultrasonic-assisted extraction of polysaccharides from Paeonia emodi.

PubMed

Ahmad, Ajaz; Alkharfy, Khalid M; Wani, Tanveer A; Raish, Mohammad

2015-01-01

The objective of the present work was to study the ultrasonic assisted extraction and optimization of polysaccharides from Paeonia emodi and evaluation of its anti-inflammatory response. Specifically, the optimization of polysaccharides was carried out using Box-Behnken statistical experimental design. Response surface methodology (RSM) of three factors (extraction temperature, extraction time and liquid solid ratio) was employed to optimize the percentage yield of the polysaccharides. The experimental data were fitted to quadratic response surface models using multiple regression analysis with high coefficient of determination value (R) of 0.9906. The highest polysaccharide yield (8.69%) as per the Derringer's desirability prediction tool was obtained under the optimal extraction condition (extraction temperature 47.03 °C, extraction time 15.68 min, and liquid solid ratio 1.29 ml/g) with a desirability value of 0.98. These optimized values of tested parameters were validated under similar conditions (n = 6), an average of 8.13 ± 2.08% of polysaccharide yield was obtained in an optimized extraction conditions with 93.55% validity. The anti-inflammatory effect of polysaccharides of P. emodi were studied on carrageenan induced paw edema. In vivo results showed that the P. emodi 200mg/kg of polysaccharide extract exhibited strong potential against inflammatory response induced by 1% suspension of carrageenean in normal saline. Copyright © 2014 Elsevier B.V. All rights reserved.

A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters

PubMed Central

Wang, Zhihao; Yi, Jing

2016-01-01

For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result. PMID:28042291

Adaptive mass expulsion attitude control system

NASA Technical Reports Server (NTRS)

Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Carrou, Stephane (Inventor)

2001-01-01

An attitude control system and method operative with a thruster controls the attitude of a vehicle carrying the thruster, wherein the thruster has a valve enabling the formation of pulses of expelled gas from a source of compressed gas. Data of the attitude of the vehicle is gathered, wherein the vehicle is located within a force field tending to orient the vehicle in a first attitude different from a desired attitude. The attitude data is evaluated to determine a pattern of values of attitude of the vehicle in response to the gas pulses of the thruster and in response to the force field. The system and the method maintain the attitude within a predetermined band of values of attitude which includes the desired attitude. Computation circuitry establishes an optimal duration of each of the gas pulses based on the pattern of values of attitude, the optimal duration providing for a minimal number of opening and closure operations of the valve. The thruster is operated to provide gas pulses having the optimal duration.

Evaluation of orbits with incomplete knowledge of the mathematical expectancy and the matrix of covariation of errors

NASA Technical Reports Server (NTRS)

Bakhshiyan, B. T.; Nazirov, R. R.; Elyasberg, P. E.

1980-01-01

The problem of selecting the optimal algorithm of filtration and the optimal composition of the measurements is examined assuming that the precise values of the mathematical expectancy and the matrix of covariation of errors are unknown. It is demonstrated that the optimal algorithm of filtration may be utilized for making some parameters more precise (for example, the parameters of the gravitational fields) after preliminary determination of the elements of the orbit by a simpler method of processing (for example, the method of least squares).

Bio-inspired optimization algorithms for optical parameter extraction of dielectric materials: A comparative study

NASA Astrophysics Data System (ADS)

Ghulam Saber, Md; Arif Shahriar, Kh; Ahmed, Ashik; Hasan Sagor, Rakibul

2016-10-01

Particle swarm optimization (PSO) and invasive weed optimization (IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square (RMS) deviation is determined and compared.

Shape Optimization of Rubber Bushing Using Differential Evolution Algorithm

PubMed Central

2014-01-01

The objective of this study is to design rubber bushing at desired level of stiffness characteristics in order to achieve the ride quality of the vehicle. A differential evolution algorithm based approach is developed to optimize the rubber bushing through integrating a finite element code running in batch mode to compute the objective function values for each generation. Two case studies were given to illustrate the application of proposed approach. Optimum shape parameters of 2D bushing model were determined by shape optimization using differential evolution algorithm. PMID:25276848

Five Antiretroviral Drug Class-Resistant HIV-1 in a Treatment-Naïve Patient Successfully Suppressed with Optimized Antiretroviral Drug Selection.

PubMed

Volpe, Joseph M; Ward, Douglas J; Napolitano, Laura; Phung, Pham; Toma, Jonathan; Solberg, Owen; Petropoulos, Christos J; Walworth, Charles M

2015-01-01

Transmitted HIV-1 exhibiting reduced susceptibility to protease and reverse transcriptase inhibitors is well documented but limited for integrase inhibitors and enfuvirtide. We describe here a case of transmitted 5 drug class-resistance in an antiretroviral (ARV)-naïve patient who was successfully treated based on the optimized selection of an active ARV drug regimen. The value of baseline resistance testing to determine an optimal ARV treatment regimen is highlighted in this case report. © The Author(s) 2015.

The meaning of death: some simulations of a model of healthy and unhealthy consumption.

PubMed

Forster, M

2001-07-01

Simulations of a model of healthy and unhealthy consumption are used to investigate the impact of various terminal conditions on life-span, pathways of health-related consumption and health. A model in which life-span and the 'death' stock of health are fixed is compared to versions in which (i) the 'death' stock of health is freely chosen; (ii) life-span is freely chosen; (iii) both the 'death' stock of health and life-span are freely chosen. The choice of terminal conditions has a striking impact on optimal plans. Results are discussed with reference to the existing demand for health literature and illustrate the application of iterative processes to determine optimal life-span, the role played by the marginal value of health capital in determining optimal plans, and the importance of checking the second-order conditions for the optimal choice of life-span.

Economics of a nest-box program for the conservation of an endangered species: a reappraisal

Treesearch

Daniel A. Spring; Michael Bevers; John O.S. Kennedy; Dan Harley

2001-01-01

An optimization model is developed to identify timing and placement strategies for the installation of nest boxes and the harvesting of timber to meet joint timber–wildlife objectives. Optimal management regimes are determined on the basis of their impacts on the local abundance of a threatened species and net present value (NPV) and are identified for a range of NPV...

Establishment of quantitative retention-activity model by optimized microemulsion liquid chromatography.

PubMed

Xu, Liyuan; Gao, Haoshi; Li, Liangxing; Li, Yinnong; Wang, Liuyun; Gao, Chongkai; Li, Ning

2016-12-23

The effective permeability coefficient is of theoretical and practical importance in evaluation of the bioavailability of drug candidates. However, most methods currently used to measure this coefficient are expensive and time-consuming. In this paper, we addressed these problems by proposing a new measurement method which is based on the microemulsion liquid chromatography. First, the parallel artificial membrane permeability assays model was used to determine the effective permeability of drug so that quantitative retention-activity relationships could be established, which were used to optimize the microemulsion liquid chromatography. The most effective microemulsion system used a mobile phase of 6.0% (w/w) Brij35, 6.6% (w/w) butanol, 0.8% (w/w) octanol, and 86.6% (w/w) phosphate buffer (pH 7.4). Next, support vector machine and back-propagation neural networks are employed to develop a quantitative retention-activity relationships model associated with the optimal microemulsion system, and used to improve the prediction ability. Finally, an adequate correlation between experimental value and predicted value is computed to verify the performance of the optimal model. The results indicate that the microemulsion liquid chromatography can serve as a possible alternative to the PAMPA method for determination of high-throughput permeability and simulation of biological processes. Copyright © 2016. Published by Elsevier B.V.

Exploring the Pareto frontier using multisexual evolutionary algorithms: an application to a flexible manufacturing problem

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.; Subbu, Raj

2002-12-01

In multi-objective optimization (MOO) problems we need to optimize many possibly conflicting objectives. For instance, in manufacturing planning we might want to minimize the cost and production time while maximizing the product's quality. We propose the use of evolutionary algorithms (EAs) to solve these problems. Solutions are represented as individuals in a population and are assigned scores according to a fitness function that determines their relative quality. Strong solutions are selected for reproduction, and pass their genetic material to the next generation. Weak solutions are removed from the population. The fitness function evaluates each solution and returns a related score. In MOO problems, this fitness function is vector-valued, i.e. it returns a value for each objective. Therefore, instead of a global optimum, we try to find the Pareto-optimal or non-dominated frontier. We use multi-sexual EAs with as many genders as optimization criteria. We have created new crossover and gender assignment functions, and experimented with various parameters to determine the best setting (yielding the highest number of non-dominated solutions.) These experiments are conducted using a variety of fitness functions, and the algorithms are later evaluated on a flexible manufacturing problem with total cost and time minimization objectives.

Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Burt, Adam O.; Hull, Patrick V.

2014-01-01

This paper presents a design automation process using optimization via a genetic algorithm to design the conceptual structure of a Lunar Pallet Lander. The goal is to determine a design that will have the primary natural frequencies at or above a target value as well as minimize the total mass. Several iterations of the process are presented. First, a concept optimization is performed to determine what class of structure would produce suitable candidate designs. From this a stiffened sheet metal approach was selected leading to optimization of beam placement through generating a two-dimensional mesh and varying the physical location of reinforcing beams. Finally, the design space is reformulated as a binary problem using 1-dimensional beam elements to truncate the design space to allow faster convergence and additional mechanical failure criteria to be included in the optimization responses. Results are presented for each design space configuration. The final flight design was derived from these results.

Efficacy tests and determination of optimal spray timing values to control nantucket pine tip moth - (Lepidoptera: Tortricidae) infestation

Treesearch

John T. Nowak; Christopher J. Fettig; Kenneth W. McCravy; C. Wayne Berisford

2000-01-01

The Nantucket pine tip moth, Rhyaciona frustrana (Comstock), a common regeneration pest of loblolly pine, Pinus taeda L., has been shown to reduce tree volume yields through larval feeding. Chemical applications can be effective in protecting trees from the growth losses associated with this feeding and optimum spray timing values...

Optimization of lightweight structure and supporting bipod flexure for a space mirror.

PubMed

Chen, Yi-Cheng; Huang, Bo-Kai; You, Zhen-Ting; Chan, Chia-Yen; Huang, Ting-Ming

2016-12-20

This article presents an optimization process for integrated optomechanical design. The proposed optimization process for integrated optomechanical design comprises computer-aided drafting, finite element analysis (FEA), optomechanical transfer codes, and an optimization solver. The FEA was conducted to determine mirror surface deformation; then, deformed surface nodal data were transferred into Zernike polynomials through MATLAB optomechanical transfer codes to calculate the resulting optical path difference (OPD) and optical aberrations. To achieve an optimum design, the optimization iterations of the FEA, optomechanical transfer codes, and optimization solver were automatically connected through a self-developed Tcl script. Two examples of optimization design were illustrated in this research, namely, an optimum lightweight design of a Zerodur primary mirror with an outer diameter of 566 mm that is used in a spaceborne telescope and an optimum bipod flexure design that supports the optimum lightweight primary mirror. Finally, optimum designs were successfully accomplished in both examples, achieving a minimum peak-to-valley (PV) value for the OPD of the deformed optical surface. The simulated optimization results showed that (1) the lightweight ratio of the primary mirror increased from 56% to 66%; and (2) the PV value of the mirror supported by optimum bipod flexures in the horizontal position effectively decreased from 228 to 61 nm.

Design of experiments with four-factors for a PEM fuel cell optimization

NASA Astrophysics Data System (ADS)

Olteanu, V.; Pǎtularu, L.; Popescu, C. L.; Popescu, M. O.; Crǎciunescu, A.

2017-07-01

Nowadays, many research efforts are allocated for the development of fuel cells, since they constitute a carbon-free electrical energy generator which can be used for stationary, mobile and portable applications. The maximum value of the delivered power of a fuel cell depends on many factors as: the height of plates' channels, the stoichiometry level of the air flow, the air pressure for the cathode, and of the actual operating electric current density. In this paper, two levels, full four-factors factorial experiment has been designed in order to obtain the appropriate response surface which approximates the maximum delivered power dependence of the above-mentioned factors. The optimum set of the fuel-cell factors which determine the maximum value of the delivered power was determined and a comparison between simulated and measured optimal Power versus Current Density characteristics is given.

Optimality and oscillations near the edge of stability in the dynamics of autonomous vehicle platoons

NASA Astrophysics Data System (ADS)

Davis, L. C.

2013-09-01

A model that includes the mechanical response of a vehicle to a demanded change in acceleration is analyzed to determine the string stability of a platoon of autonomous vehicles. The response is characterized by a first-order time constant τ and an explicit delay td. The minimum value of the acceleration feedback control gain is found from calculations of the velocity of vehicles following a lead vehicle that decelerates sharply from high speed to low speed. Larger values of ξ (in the stable range) give larger values of deceleration for vehicles in the platoon. Optimal operation is attained close to the minimum value of ξ for stability. Small oscillations are found after the main peak in deceleration for ξ in the stable region but near the transition to instability. A theory for predicting the frequency and amplitude of the oscillations is presented.

Extraction optimization of mucilage from Basil (Ocimum basilicum L.) seeds using response surface methodology.

PubMed

Nazir, Sadaf; Wani, Idrees Ahmed; Masoodi, Farooq Ahmad

2017-05-01

Aqueous extraction of basil seed mucilage was optimized using response surface methodology. A Central Composite Rotatable Design (CCRD) for modeling of three independent variables: temperature (40-91 °C); extraction time (1.6-3.3 h) and water/seed ratio (18:1-77:1) was used to study the response for yield. Experimental values for extraction yield ranged from 7.86 to 20.5 g/100 g. Extraction yield was significantly ( P  < 0.05) affected by all the variables. Temperature and water/seed ratio were found to have pronounced effect while the extraction time was found to have minor possible effects. Graphical optimization determined the optimal conditions for the extraction of mucilage. The optimal condition predicted an extraction yield of 20.49 g/100 g at 56.7 °C, 1.6 h, and a water/seed ratio of 66.84:1. Optimal conditions were determined to obtain highest extraction yield. Results indicated that water/seed ratio was the most significant parameter, followed by temperature and time.

Design optimization of an axial-field eddy-current magnetic coupling based on magneto-thermal analytical model

NASA Astrophysics Data System (ADS)

Fontchastagner, Julien; Lubin, Thierry; Mezani, Smaïl; Takorabet, Noureddine

2018-03-01

This paper presents a design optimization of an axial-flux eddy-current magnetic coupling. The design procedure is based on a torque formula derived from a 3D analytical model and a population algorithm method. The main objective of this paper is to determine the best design in terms of magnets volume in order to transmit a torque between two movers, while ensuring a low slip speed and a good efficiency. The torque formula is very accurate and computationally efficient, and is valid for any slip speed values. Nevertheless, in order to solve more realistic problems, and then, take into account the thermal effects on the torque value, a thermal model based on convection heat transfer coefficients is also established and used in the design optimization procedure. Results show the effectiveness of the proposed methodology.

What is the optimal cutoff value of the axis-line-angle technique for evaluating trunk imbalance in coronal plane?

PubMed

Zhang, Rui-Fang; Fu, Yu-Chuan; Lu, Yi; Zhang, Xiao-Xia; Hu, Yu-Min; Zhou, Yong-Jin; Tian, Nai-Feng; He, Jia-Wei; Yan, Zhi-Han

2017-02-01

Accurately evaluating the extent of trunk imbalance in the coronal plane is significant for patients before and after treatment. We preliminarily practiced a new method, axis-line-angle technique (ALAT), for evaluating coronal trunk imbalance with excellent intra-observer and interobserver reliability. Radiologists and surgeons were encouraged to use this method in clinical practice. However, the optimal cutoff value of the ALAT for determination of the extent of coronal trunk imbalance has not been calculated up to now. The purpose of this study was to identify the cutoff value of the ALAT that best predicts a positive measurement point to assess coronal balance or imbalance. A retrospective study at a university affiliated hospital was carried out. A total of 130 patients with C7-central sacral vertical line (CSVL) >0 mm and aged 10-18 years were recruited in this study from September 2013 to December 2014. Data were analyzed to determine the optimal cutoff value of the ALAT measurement. The C7-CSVL and ALAT measurements were conducted respectively twice on plain film within a 2-week interval by two radiologists. The optimal cutoff value of the ALAT was analyzed via receiver operating characteristic (ROC) curve. Comparison variables were performed with chi-square test between the C7-CSVL and ALAT measurements for evaluating trunk imbalance. Kappa agreement coefficient method was used to test the intra-observer and interobserver agreement of C7-CSVL and ALAT. The ROC curve area for the ALAT was 0.82 (95% confidence interval: 0.753-0.894, p<.001). The maximum Youden index was 0.51, and the corresponding cutoff point was 2.59°. No statistical difference was found between the C7-CSVL and ALAT measurements for evaluating trunk imbalance (p>.05). Intra-observer agreement values for the C7-CSVL measurements by observers 1 and 2 were 0.79 and 0.91 (p<.001), respectively, whereas intra-observer agreement values for the ALAT measurements were both 0.89 by observers 1 and 2 (p<.001). The interobserver agreement values for the first and second measurements with the C7-CSVL were 0.78 and 0.85 (p<.001), respectively, whereas the interobserver agreement values for the first and second measurements with the ALAT were 0.91 and 0.88 (p<.001), respectively. The newly developed ALAT provided an acceptable optimal cutoff value for evaluating trunk imbalance in the coronal plane with a high level of intra-observer and interobserver agreement, which suggests that the ALAT is suitable for clinical use. Copyright © 2016 Elsevier Inc. All rights reserved.

Taguchi experimental design to determine the taste quality characteristic of candied carrot

NASA Astrophysics Data System (ADS)

Ekawati, Y.; Hapsari, A. A.

2018-03-01

Robust parameter design is used to design product that is robust to noise factors so the product’s performance fits the target and delivers a better quality. In the process of designing and developing the innovative product of candied carrot, robust parameter design is carried out using Taguchi Method. The method is used to determine an optimal quality design. The optimal quality design is based on the process and the composition of product ingredients that are in accordance with consumer needs and requirements. According to the identification of consumer needs from the previous research, quality dimensions that need to be assessed are the taste and texture of the product. The quality dimension assessed in this research is limited to the taste dimension. Organoleptic testing is used for this assessment, specifically hedonic testing that makes assessment based on consumer preferences. The data processing uses mean and signal to noise ratio calculation and optimal level setting to determine the optimal process/composition of product ingredients. The optimal value is analyzed using confirmation experiments to prove that proposed product match consumer needs and requirements. The result of this research is identification of factors that affect the product taste and the optimal quality of product according to Taguchi Method.

Tapping insertional torque allows prediction for better pedicle screw fixation and optimal screw size selection.

PubMed

Helgeson, Melvin D; Kang, Daniel G; Lehman, Ronald A; Dmitriev, Anton E; Luhmann, Scott J

2013-08-01

There is currently no reliable technique for intraoperative assessment of pedicle screw fixation strength and optimal screw size. Several studies have evaluated pedicle screw insertional torque (IT) and its direct correlation with pullout strength. However, there is limited clinical application with pedicle screw IT as it must be measured during screw placement and rarely causes the spine surgeon to change screw size. To date, no study has evaluated tapping IT, which precedes screw insertion, and its ability to predict pedicle screw pullout strength. The objective of this study was to investigate tapping IT and its ability to predict pedicle screw pullout strength and optimal screw size. In vitro human cadaveric biomechanical analysis. Twenty fresh-frozen human cadaveric thoracic vertebral levels were prepared and dual-energy radiographic absorptiometry scanned for bone mineral density (BMD). All specimens were osteoporotic with a mean BMD of 0.60 ± 0.07 g/cm(2). Five specimens (n=10) were used to perform a pilot study, as there were no previously established values for optimal tapping IT. Each pedicle during the pilot study was measured using a digital caliper as well as computed tomography measurements, and the optimal screw size was determined to be equal to or the first size smaller than the pedicle diameter. The optimal tap size was then selected as the tap diameter 1 mm smaller than the optimal screw size. During optimal tap size insertion, all peak tapping IT values were found to be between 2 in-lbs and 3 in-lbs. Therefore, the threshold tapping IT value for optimal pedicle screw and tap size was determined to be 2.5 in-lbs, and a comparison tapping IT value of 1.5 in-lbs was selected. Next, 15 test specimens (n=30) were measured with digital calipers, probed, tapped, and instrumented using a paired comparison between the two threshold tapping IT values (Group 1: 1.5 in-lbs; Group 2: 2.5 in-lbs), randomly assigned to the left or right pedicle on each specimen. Each pedicle was incrementally tapped to increasing size (3.75, 4.00, 4.50, and 5.50 mm) until the threshold value was reached based on the assigned group. Pedicle screw size was determined by adding 1 mm to the tap size that crossed the threshold torque value. Torque measurements were recorded with each revolution during tap and pedicle screw insertion. Each specimen was then individually potted and pedicle screws pulled out "in-line" with the screw axis at a rate of 0.25 mm/sec. Peak pullout strength (POS) was measured in Newtons (N). The peak tapping IT was significantly increased (50%) in Group 2 (3.23 ± 0.65 in-lbs) compared with Group 1 (2.15 ± 0.56 in-lbs) (p=.0005). The peak screw IT was also significantly increased (19%) in Group 2 (8.99 ± 2.27 in-lbs) compared with Group 1 (7.52 ± 2.96 in-lbs) (p=.02). The pedicle screw pullout strength was also significantly increased (23%) in Group 2 (877.9 ± 235.2 N) compared with Group 1 (712.3 ± 223.1 N) (p=.017). The mean pedicle screw diameter was significantly increased in Group 2 (5.70 ± 1.05 mm) compared with Group 1 (5.00 ± 0.80 mm) (p=.0002). There was also an increased rate of optimal pedicle screw size selection in Group 2 with 9 of 15 (60%) pedicle screws compared with Group 1 with 4 of 15 (26.7%) pedicle screws within 1 mm of the measured pedicle width. There was a moderate correlation for tapping IT with both screw IT (r=0.54; p=.002) and pedicle screw POS (r=0.55; p=.002). Our findings suggest that tapping IT directly correlates with pedicle screw IT, pedicle screw pullout strength, and optimal pedicle screw size. Therefore, tapping IT may be used during thoracic pedicle screw instrumentation as an adjunct to preoperative imaging and clinical experience to maximize fixation strength and optimize pedicle "fit and fill" with the largest screw possible. However, further prospective, in vivo studies are necessary to evaluate the intraoperative use of tapping IT to predict screw loosening/complications. Published by Elsevier Inc.

Optimal harvesting policy of predator-prey model with free fishing and reserve zones

NASA Astrophysics Data System (ADS)

Toaha, Syamsuddin; Rustam

2017-03-01

The present paper deals with an optimal harvesting of predator-prey model in an ecosystem that consists of two zones, namely the free fishing and prohibited zones. The dynamics of prey population in the ecosystem can migrate from the free fishing to the prohibited zone and vice versa. The predator and prey populations in the free fishing zone are then harvested with constant efforts. The existence of the interior equilibrium point is analyzed and its stability is determined using Routh-Hurwitz stability test. The stable interior equilibrium point is then related to the problem of maximum profit and the problem of present value of net revenue. We follow the Pontryagin's maximal principle to get the optimal harvesting policy of the present value of the net revenue. From the analysis, we found a critical point of the efforts that makes maximum profit. There also exists certain conditions of the efforts that makes the present value of net revenue becomes maximal. In addition, the interior equilibrium point is locally asymptotically stable which means that the optimal harvesting is reached and the unharvested prey, harvested prey, and harvested predator populations remain sustainable. Numerical examples are given to verify the analytical results.

Co-state initialization for the minimum-time low-thrust trajectory optimization

NASA Astrophysics Data System (ADS)

Taheri, Ehsan; Li, Nan I.; Kolmanovsky, Ilya

2017-05-01

This paper presents an approach for co-state initialization which is a critical step in solving minimum-time low-thrust trajectory optimization problems using indirect optimal control numerical methods. Indirect methods used in determining the optimal space trajectories typically result in two-point boundary-value problems and are solved by single- or multiple-shooting numerical methods. Accurate initialization of the co-state variables facilitates the numerical convergence of iterative boundary value problem solvers. In this paper, we propose a method which exploits the trajectory generated by the so-called pseudo-equinoctial and three-dimensional finite Fourier series shape-based methods to estimate the initial values of the co-states. The performance of the approach for two interplanetary rendezvous missions from Earth to Mars and from Earth to asteroid Dionysus is compared against three other approaches which, respectively, exploit random initialization of co-states, adjoint-control transformation and a standard genetic algorithm. The results indicate that by using our proposed approach the percent of the converged cases is higher for trajectories with higher number of revolutions while the computation time is lower. These features are advantageous for broad trajectory search in the preliminary phase of mission designs.

Central Composite Design Optimization of Zinc Removal from Contaminated Soil, Using Citric Acid as Biodegradable Chelant.

PubMed

Asadzadeh, Farrokh; Maleki-Kaklar, Mahdi; Soiltanalinejad, Nooshin; Shabani, Farzin

2018-02-08

Citric acid (CA) was evaluated in terms of its efficiency as a biodegradable chelating agent, in removing zinc (Zn) from heavily contaminated soil, using a soil washing process. To determine preliminary ranges of variables in the washing process, single factor experiments were carried out with different CA concentrations, pH levels and washing times. Optimization of batch washing conditions followed using a response surface methodology (RSM) based central composite design (CCD) approach. CCD predicted values and experimental results showed strong agreement, with an R 2 value of 0.966. Maximum removal of 92.8% occurred with a CA concentration of 167.6 mM, pH of 4.43, and washing time of 30 min as optimal variable values. A leaching column experiment followed, to examine the efficiency of the optimum conditions established by the CCD model. A comparison of two soil washing techniques indicated that the removal efficiency rate of the column experiment (85.8%) closely matching that of the batch experiment (92.8%). The methodology supporting the research experimentation for optimizing Zn removal may be useful in the design of protocols for practical engineering soil decontamination applications.

TH-CD-202-08: Feasibility Study of Planning Phase Optimization Using Patient Geometry-Driven Information for Better Dose Sparing of Organ at Risks

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

Kang, S; Kim, D; Kim, T

2016-06-15

Purpose: To propose a simple and effective cost value function to search optimal planning phase (gating window) and demonstrated its feasibility for respiratory correlated radiation therapy. Methods: We acquired 4DCT of 10 phases for 10 lung patients who have tumor located near OARs such as esophagus, heart, and spinal cord (i.e., central lung cancer patients). A simplified mathematical optimization function was established by using overlap volume histogram (OVH) between the target and organ at risk (OAR) at each phase and the tolerance dose of selected OARs to achieve surrounding OARs dose-sparing. For all patients and all phases, delineation of themore » target volume and selected OARs (esophagus, heart, and spinal cord) was performed (by one observer to avoid inter-observer variation), then cost values were calculated for all phases. After the breathing phases were ranked according to cost value function, the relationship between score and dose distribution at highest and lowest cost value phases were evaluated by comparing the mean/max dose. Results: A simplified mathematical cost value function showed noticeable difference from phase to phase, implying it is possible to find optimal phases for gating window. The lowest cost value which may result in lower mean/max dose to OARs was distributed at various phases for all patients. The mean doses of the OARs significantly decreased about 10% with statistical significance for all 3 OARs at the phase with the lowest cost value. Also, the max doses of the OARs were decreased about 2∼5% at the phase with the lowest cost value compared to the phase with the highest cost value. Conclusion: It is demonstrated that optimal phases (in dose distribution perspective) for gating window could exist differently through each patient and the proposed cost value function can be a useful tool for determining such phases without performing dose optimization calculations. This research was supported by the Mid-career Researcher Program through NRF funded by the Ministry of Science, ICT & Future Planning of Korea (NRF-2014R1A2A1A10050270) and by the Radiation Technology R&D program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (No. 2013M2A2A7038291)« less

A graphical approach to optimizing variable-kernel smoothing parameters for improved deformable registration of CT and cone beam CT images

NASA Astrophysics Data System (ADS)

Hart, Vern; Burrow, Damon; Li, X. Allen

2017-08-01

A systematic method is presented for determining optimal parameters in variable-kernel deformable image registration of cone beam CT and CT images, in order to improve accuracy and convergence for potential use in online adaptive radiotherapy. Assessed conditions included the noise constant (symmetric force demons), the kernel reduction rate, the kernel reduction percentage, and the kernel adjustment criteria. Four such parameters were tested in conjunction with reductions of 5, 10, 15, 20, 30, and 40%. Noise constants ranged from 1.0 to 1.9 for pelvic images in ten prostate cancer patients. A total of 516 tests were performed and assessed using the structural similarity index. Registration accuracy was plotted as a function of iteration number and a least-squares regression line was calculated, which implied an average improvement of 0.0236% per iteration. This baseline was used to determine if a given set of parameters under- or over-performed. The most accurate parameters within this range were applied to contoured images. The mean Dice similarity coefficient was calculated for bladder, prostate, and rectum with mean values of 98.26%, 97.58%, and 96.73%, respectively; corresponding to improvements of 2.3%, 9.8%, and 1.2% over previously reported values for the same organ contours. This graphical approach to registration analysis could aid in determining optimal parameters for Demons-based algorithms. It also establishes expectation values for convergence rates and could serve as an indicator of non-physical warping, which often occurred in cases  >0.6% from the regression line.

Finding the optimal lengths for three branches at a junction.

PubMed

Woldenberg, M J; Horsfield, K

1983-09-21

This paper presents an exact analytical solution to the problem of locating the junction point between three branches so that the sum of the total costs of the branches is minimized. When the cost per unit length of each branch is known the angles between each pair of branches can be deduced following reasoning first introduced to biology by Murray. Assuming the outer ends of each branch are fixed, the location of the junction and the length of each branch are then deduced using plane geometry and trigonometry. The model has applications in determining the optimal cost of a branch or branches at a junction. Comparing the optimal to the actual cost of a junction is a new way to compare cost models for goodness of fit to actual junction geometry. It is an unambiguous measure and is superior to comparing observed and optimal angles between each daughter and the parent branch. We present data for 199 junctions in the pulmonary arteries of two human lungs. For the branches at each junction we calculated the best fitting value of x from the relationship that flow alpha (radius)x. We found that the value of x determined whether a junction was best fitted by a surface, volume, drag or power minimization model. While economy of explanation casts doubt that four models operate simultaneously, we found that optimality may still operate, since the angle to the major daughter is less than the angle to the minor daughter. Perhaps optimality combined with a space filling branching pattern governs the branching geometry of the pulmonary artery.

Chinese version of the Optimism and Pessimism Scale: Psychometric properties in mainland China and development of a short form.

PubMed

Xia, Jie; Wu, Daxing; Zhang, Jibiao; Xu, Yuanchao; Xu, Yunxuan

2016-06-01

This study aimed to validate the Chinese version of the Optimism and Pessimism Scale in a sample of 730 adult Chinese individuals. Confirmatory factor analyses confirmed the bidimensionality of the scale with two factors, optimism and pessimism. The total scale and optimism and pessimism factors demonstrated satisfactory reliability and validity. Population-based normative data and mean values for gender, age, and education were determined. Furthermore, we developed a 20-item short form of the Chinese version of the Optimism and Pessimism Scale with structural validity comparable to the full form. In summary, the Chinese version of the Optimism and Pessimism Scale is an appropriate and practical tool for epidemiological research in mainland China. © The Author(s) 2014.

Research on Intelligent Control System of DC SQUID Magnetometer Parameters for Multi-channel System

NASA Astrophysics Data System (ADS)

Chen, Hua; Yang, Kang; Lu, Li; Kong, Xiangyan; Wang, Hai; Wu, Jun; Wang, Yongliang

2018-07-01

In a multi-channel SQUID measurement system, adjusting device parameters to optimal condition for all channels is time-consuming. In this paper, an intelligent control system is presented to determine the optimal working point of devices which is automatic and more efficient comparing to the manual one. An optimal working point searching algorithm is introduced as the core component of the control system. In this algorithm, the bias voltage V_bias is step scanned to obtain the maximal value of the peak-to-peak current value I_pp of the SQUID magnetometer modulation curve. We choose this point as the optimal one. Using the above control system, more than 30 weakly damped SQUID magnetometers with area of 5 × 5 mm^2 or 10 × 10 mm^2 are adjusted and a 36-channel magnetocardiography system perfectly worked in a magnetically shielded room. The average white flux noise is 15 {μ Φ }_0/Hz^{1/2}.

Research on Intelligent Control System of DC SQUID Magnetometer Parameters for Multi-channel System

NASA Astrophysics Data System (ADS)

Chen, Hua; Yang, Kang; Lu, Li; Kong, Xiangyan; Wang, Hai; Wu, Jun; Wang, Yongliang

2018-03-01

In a multi-channel SQUID measurement system, adjusting device parameters to optimal condition for all channels is time-consuming. In this paper, an intelligent control system is presented to determine the optimal working point of devices which is automatic and more efficient comparing to the manual one. An optimal working point searching algorithm is introduced as the core component of the control system. In this algorithm, the bias voltage V_bias is step scanned to obtain the maximal value of the peak-to-peak current value I_pp of the SQUID magnetometer modulation curve. We choose this point as the optimal one. Using the above control system, more than 30 weakly damped SQUID magnetometers with area of 5 × 5 mm^2 or 10 × 10 mm^2 are adjusted and a 36-channel magnetocardiography system perfectly worked in a magnetically shielded room. The average white flux noise is 15 μΦ_0/Hz^{1/2}.

Reward rate optimization in two-alternative decision making: empirical tests of theoretical predictions.

PubMed

Simen, Patrick; Contreras, David; Buck, Cara; Hu, Peter; Holmes, Philip; Cohen, Jonathan D

2009-12-01

The drift-diffusion model (DDM) implements an optimal decision procedure for stationary, 2-alternative forced-choice tasks. The height of a decision threshold applied to accumulating information on each trial determines a speed-accuracy tradeoff (SAT) for the DDM, thereby accounting for a ubiquitous feature of human performance in speeded response tasks. However, little is known about how participants settle on particular tradeoffs. One possibility is that they select SATs that maximize a subjective rate of reward earned for performance. For the DDM, there exist unique, reward-rate-maximizing values for its threshold and starting point parameters in free-response tasks that reward correct responses (R. Bogacz, E. Brown, J. Moehlis, P. Holmes, & J. D. Cohen, 2006). These optimal values vary as a function of response-stimulus interval, prior stimulus probability, and relative reward magnitude for correct responses. We tested the resulting quantitative predictions regarding response time, accuracy, and response bias under these task manipulations and found that grouped data conformed well to the predictions of an optimally parameterized DDM.

Antioxidant Compound Extraction from Maqui (Aristotelia chilensis [Mol] Stuntz) Berries: Optimization by Response Surface Methodology

PubMed Central

Quispe-Fuentes, Issis; Vega-Gálvez, Antonio; Campos-Requena, Víctor H.

2017-01-01

The optimum conditions for the antioxidant extraction from maqui berry were determined using a response surface methodology. A three level D-optimal design was used to investigate the effects of three independent variables namely, solvent type (methanol, acetone and ethanol), solvent concentration and extraction time over total antioxidant capacity by using the oxygen radical absorbance capacity (ORAC) method. The D-optimal design considered 42 experiments including 10 central point replicates. A second-order polynomial model showed that more than 89% of the variation is explained with a satisfactory prediction (78%). ORAC values are higher when acetone was used as a solvent at lower concentrations, and the extraction time range studied showed no significant influence on ORAC values. The optimal conditions for antioxidant extraction obtained were 29% of acetone for 159 min under agitation. From the results obtained it can be concluded that the given predictive model describes an antioxidant extraction process from maqui berry.

An extended heterogeneous car-following model accounting for anticipation driving behavior and mixed maximum speeds

NASA Astrophysics Data System (ADS)

Sun, Fengxin; Wang, Jufeng; Cheng, Rongjun; Ge, Hongxia

2018-02-01

The optimal driving speeds of the different vehicles may be different for the same headway. In the optimal velocity function of the optimal velocity (OV) model, the maximum speed vmax is an important parameter determining the optimal driving speed. A vehicle with higher maximum speed is more willing to drive faster than that with lower maximum speed in similar situation. By incorporating the anticipation driving behavior of relative velocity and mixed maximum speeds of different percentages into optimal velocity function, an extended heterogeneous car-following model is presented in this paper. The analytical linear stable condition for this extended heterogeneous traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulted from the cooperation between anticipation driving behavior and heterogeneous maximum speeds in the optimal velocity function. The analytical and numerical results all demonstrate that strengthening driver's anticipation effect can improve the stability of heterogeneous traffic flow, and increasing the lowest value in the mixed maximum speeds will result in more instability, but increasing the value or proportion of the part already having higher maximum speed will cause different stabilities at high or low traffic densities.

SU-E-T-367: Optimization of DLG Using TG-119 Test Cases and a Weighted Mean Approach

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

Sintay, B; Vanderstraeten, C; Terrell, J

2014-06-01

Purpose: Optimization of the dosimetric leaf gap (DLG) is an important step in commissioning the Eclipse treatment planning system for sliding window intensity-modulated radiation therapy (SW-IMRT) and RapidArc. Often the values needed for optimal dose delivery differ markedly from those measured at commissioning. We present a method to optimize this value using the AAPM TG-119 test cases. Methods: For SW-IMRT and RapidArc, TG-119 based test plans were created using a water-equivalent phantom. Dose distributions measured on film and ion chamber (IC) readings taken in low-gradient regions within the targets were analyzed separately. Since DLG is a single value per energy,more » SW-IMRT and RapidArc must be considered simultaneously. Plans were recalculated using a linear sweep from 0.02cm (the minimum DLG) to 0.3 cm. The calculated point doses were compared to the measured doses for each plan, and based on these comparisons an optimal DLG value was computed for each plan. TG-119 cases are designed to push the system in various ways, thus, a weighted mean of the DLG was computed where the relative importance of each type of plan was given a score from 0.0 to 1.0. Finally, SW-IMRT and RapidArc are assigned an overall weight based on clinical utilization. Our routine patient-QA (PQA) process was performed as independent validation. Results: For a Varian TrueBeam, the optimized DLG varied with σ = 0.044cm for SW-IMRT and σ = 0.035cm for RapidArc. The difference between the weighted mean SW-IMRT and RapidArc value was 0.038cm. We predicted utilization of 25% SW-IMRT and 75% RapidArc. The resulting DLG was ~1mm different than that found by commissioning and produced an average error of <1% for SW-IMRT and RapidArc PQA test cases separately. Conclusion: The weighted mean method presented is a useful tool for determining an optimal DLG value for commissioning Eclipse.« less

Optimal design of isotope labeling experiments.

PubMed

Yang, Hong; Mandy, Dominic E; Libourel, Igor G L

2014-01-01

Stable isotope labeling experiments (ILE) constitute a powerful methodology for estimating metabolic fluxes. An optimal label design for such an experiment is necessary to maximize the precision with which fluxes can be determined. But often, precision gained in the determination of one flux comes at the expense of the precision of other fluxes, and an appropriate label design therefore foremost depends on the question the investigator wants to address. One could liken ILE to shadows that metabolism casts on products. Optimal label design is the placement of the lamp; creating clear shadows for some parts of metabolism and obscuring others.An optimal isotope label design is influenced by: (1) the network structure; (2) the true flux values; (3) the available label measurements; and, (4) commercially available substrates. The first two aspects are dictated by nature and constrain any optimal design. The second two aspects are suitable design parameters. To create an optimal label design, an explicit optimization criterion needs to be formulated. This usually is a property of the flux covariance matrix, which can be augmented by weighting label substrate cost. An optimal design is found by using such a criterion as an objective function for an optimizer. This chapter uses a simple elementary metabolite units (EMU) representation of the TCA cycle to illustrate the process of experimental design of isotope labeled substrates.

Hierarchical optimization for neutron scattering problems

DOE PAGES

Bao, Feng; Archibald, Rick; Bansal, Dipanshu; ...

2016-03-14

In this study, we present a scalable optimization method for neutron scattering problems that determines confidence regions of simulation parameters in lattice dynamics models used to fit neutron scattering data for crystalline solids. The method uses physics-based hierarchical dimension reduction in both the computational simulation domain and the parameter space. We demonstrate for silicon that after a few iterations the method converges to parameters values (interatomic force-constants) computed with density functional theory simulations.

Hierarchical optimization for neutron scattering problems

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

Bao, Feng; Archibald, Rick; Bansal, Dipanshu

In this study, we present a scalable optimization method for neutron scattering problems that determines confidence regions of simulation parameters in lattice dynamics models used to fit neutron scattering data for crystalline solids. The method uses physics-based hierarchical dimension reduction in both the computational simulation domain and the parameter space. We demonstrate for silicon that after a few iterations the method converges to parameters values (interatomic force-constants) computed with density functional theory simulations.

Ultrasonic-assisted enzymatic extraction of phenolics from broccoli (Brassica oleracea L. var. italica) inflorescences and evaluation of antioxidant activity in vitro.

PubMed

Wu, Hao; Zhu, Junxiang; Yang, Long; Wang, Ran; Wang, Chengrong

2015-06-01

An efficient ultrasonic-assisted enzymatic extraction technique was applied to extracting phenolics from broccoli inflorescences without organic solvents. The synergistic model of enzymolysis and ultrasonication simultaneously was selected, and the enzyme combination was optimized by orthogonal test: cellulase 7.5 mg/g FW (fresh weight), pectinase 10 mg/g FW, and papain 1.0 mg/g FW. The operating parameters in ultrasonic-assisted enzymatic extraction were optimized with response surface methodology using Box-Behnken design. The optimal extraction conditions were as follows: ultrasonic power, 440 W; liquid to material ratio, 7.0:1 mL/g; pH value of 6.0 at 54.5 ℃ for 10 min. Under these conditions, the extraction yield of phenolics achieved 1.816 ± 0.0187 mg gallic acid equivalents/gram FW. The free radical scavenging activity of ultrasonic-assisted enzymatic extraction extracts was determined by 1,1-diphenyl-2-picrylhydrazyl·assay with EC50 values of 0.25, and total antioxidant activity was determined by ferric reducing antioxidant power assay with ferric reducing antioxidant power value of 0.998 mmol FeSO4/g compared with the referential ascorbic acid of 1.184 mmol FeSO4/g. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Value versus Accuracy: application of seasonal forecasts to a hydro-economic optimization model for the Sudanese Blue Nile

NASA Astrophysics Data System (ADS)

Satti, S.; Zaitchik, B. F.; Siddiqui, S.; Badr, H. S.; Shukla, S.; Peters-Lidard, C. D.

2015-12-01

The unpredictable nature of precipitation within the East African (EA) region makes it one of the most vulnerable, food insecure regions in the world. There is a vital need for forecasts to inform decision makers, both local and regional, and to help formulate the region's climate change adaptation strategies. Here, we present a suite of different seasonal forecast models, both statistical and dynamical, for the EA region. Objective regionalization is performed for EA on the basis of interannual variability in precipitation in both observations and models. This regionalization is applied as the basis for calculating a number of standard skill scores to evaluate each model's forecast accuracy. A dynamically linked Land Surface Model (LSM) is then applied to determine forecasted flows, which drive the Sudanese Hydroeconomic Optimization Model (SHOM). SHOM combines hydrologic, agronomic and economic inputs to determine the optimal decisions that maximize economic benefits along the Sudanese Blue Nile. This modeling sequence is designed to derive the potential added value of information of each forecasting model to agriculture and hydropower management. A rank of each model's forecasting skill score along with its added value of information is analyzed in order compare the performance of each forecast. This research aims to improve understanding of how characteristics of accuracy, lead time, and uncertainty of seasonal forecasts influence their utility to water resources decision makers who utilize them.

PubChem3D: Conformer generation

PubMed Central

2011-01-01

Background PubChem, an open archive for the biological activities of small molecules, provides search and analysis tools to assist users in locating desired information. Many of these tools focus on the notion of chemical structure similarity at some level. PubChem3D enables similarity of chemical structure 3-D conformers to augment the existing similarity of 2-D chemical structure graphs. It is also desirable to relate theoretical 3-D descriptions of chemical structures to experimental biological activity. As such, it is important to be assured that the theoretical conformer models can reproduce experimentally determined bioactive conformations. In the present study, we investigate the effects of three primary conformer generation parameters (the fragment sampling rate, the energy window size, and force field variant) upon the accuracy of theoretical conformer models, and determined optimal settings for PubChem3D conformer model generation and conformer sampling. Results Using the software package OMEGA from OpenEye Scientific Software, Inc., theoretical 3-D conformer models were generated for 25,972 small-molecule ligands, whose 3-D structures were experimentally determined. Different values for primary conformer generation parameters were systematically tested to find optimal settings. Employing a greater fragment sampling rate than the default did not improve the accuracy of the theoretical conformer model ensembles. An ever increasing energy window did increase the overall average accuracy, with rapid convergence observed at 10 kcal/mol and 15 kcal/mol for model building and torsion search, respectively; however, subsequent study showed that an energy threshold of 25 kcal/mol for torsion search resulted in slightly improved results for larger and more flexible structures. Exclusion of coulomb terms from the 94s variant of the Merck molecular force field (MMFF94s) in the torsion search stage gave more accurate conformer models at lower energy windows. Overall average accuracy of reproduction of bioactive conformations was remarkably linear with respect to both non-hydrogen atom count ("size") and effective rotor count ("flexibility"). Using these as independent variables, a regression equation was developed to predict the RMSD accuracy of a theoretical ensemble to reproduce bioactive conformations. The equation was modified to give a minimum RMSD conformer sampling value to help ensure that 90% of the sampled theoretical models should contain at least one conformer within the RMSD sampling value to a "bioactive" conformation. Conclusion Optimal parameters for conformer generation using OMEGA were explored and determined. An equation was developed that provides an RMSD sampling value to use that is based on the relative accuracy to reproduce bioactive conformations. The optimal conformer generation parameters and RMSD sampling values determined are used by the PubChem3D project to generate theoretical conformer models. PMID:21272340

Comparison of two microextraction methods based on solidification of floating organic droplet for the determination of multiclass analytes in river water samples by liquid chromatography tandem mass spectrometry using Central Composite Design.

PubMed

Asati, Ankita; Satyanarayana, G N V; Patel, Devendra K

2017-09-01

Two low density organic solvents based liquid-liquid microextraction methods, namely Vortex assisted liquid-liquid microextraction based on solidification of floating organic droplet (VALLME-SFO) and Dispersive liquid-liquid microextraction based on solidification of floating organic droplet(DLLME-SFO) have been compared for the determination of multiclass analytes (pesticides, plasticizers, pharmaceuticals and personal care products) in river water samples by using liquid chromatography tandem mass spectrometry (LC-MS/MS). The effect of various experimental parameters on the efficiency of the two methods and their optimum values were studied with the aid of Central Composite Design (CCD) and Response Surface Methodology(RSM). Under optimal conditions, VALLME-SFO was validated in terms of limit of detection, limit of quantification, dynamic linearity range, determination of coefficient, enrichment factor and extraction recovery for which the respective values were (0.011-0.219ngmL -1 ), (0.035-0.723ngmL -1 ), (0.050-0.500ngmL -1 ), (R 2 =0.992-0.999), (40-56), (80-106%). However, when the DLLME-SFO method was validated under optimal conditions, the range of values of limit of detection, limit of quantification, dynamic linearity range, determination of coefficient, enrichment factor and extraction recovery were (0.025-0.377ngmL -1 ), (0.083-1.256ngmL -1 ), (0.100-1.000ngmL -1 ), (R 2 =0.990-0.999), (35-49), (69-98%) respectively. Interday and intraday precisions were calculated as percent relative standard deviation (%RSD) and the values were ≤15% for VALLME-SFO and DLLME-SFO methods. Both methods were successfully applied for determining multiclass analytes in river water samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of culture conditions for penicilazaphilone C production by a marine-derived fungus Penicillium sclerotiorum M-22.

PubMed

Zhao, H-G; Wang, M; Lin, Y-Y; Zhou, S-L

2018-03-01

The aim of this study was to optimize the culture conditions of a marine-derived fungus Penicillium sclerotiorum M-22 for the production of penicilazaphilone C (PAC), a novel azaphilonidal derivative exhibiting broad cytotoxic and antibacterial effects. By single factor experiments, the effects to the production of PAC of aged seawater concentration, initial pH values, fermentation time, carbon sources, nitrogen sources and inorganic salt sources were investigated individually. Response surface methodology (RSM) analysis was adopted to investigate the interactions between variables and determine the optimal values for maximum PAC production. Evaluation of the experimental results signified that the optimum conditions for maximum production of PAC (19·85 mg l -1 ) in 250 ml Erlenmeyer flask were fermentation time 24·83 days, pH of 7·00, corn meal concentration of 10·72 g l -1 , yeast extract concentration of 4·58 g l -1 , crude sea salt concentration of 20·59 g l -1 . Production under optimized conditions increased to 1·344-fold comparing to its production prior to optimization. The higher PAC production and the penicilazaphilone C -producing marine fungus would be provide a promising alterative approach for industrial and commercial applications. Penicilazaphilone C (PAC) was a novel azaphilonidal derivative which had exhibited selective cytotoxicity and antibacterial activity. To further enhance production of PAC by optimizing fermentation conditions of Penicillium sclerotiorum M-22 would provide a promising alterative approach for industrial and commercial applications. We used the single factor test to determine the key factors which influence the PAC production. Then through the Response surface methodology and Box-Behnken design to determine the best fermentation condition for maximum production of PAC. Through these experimental designs and analysis will help us improve experimental efficiency and save time and materials. © 2017 The Society for Applied Microbiology.

Ability of High-Resolution Manometry to Determine Feeding Method and to Predict Aspiration Pneumonia in Patients With Dysphagia.

PubMed

Park, Chul-Hyun; Lee, Yong-Taek; Yi, Youbin; Lee, Jung-Sang; Park, Jung Ho; Yoon, Kyung Jae

2017-07-01

The introduction of high-resolution manometry (HRM) offered an improved method to objectively analyze the status of pharynx and esophagus. At present, HRM for patients with oropharyngeal dysphagia has been poorly studied. We aimed to determine feeding method and predict the development of aspiration pneumonia in patients with oropharyngeal dysphagia using HRM. We recruited 120 patients with dysphagia who underwent both HRM and videofluoroscopic swallow study. HRM was used to estimate pressure events from velopharynx (VP) to upper esophageal sphincter (UES). Feeding methods were determined to non-oral or oral feeding according to dysphagia severity. We prospectively followed patients to assess the development of aspiration pneumonia. VP maximal pressure and UES relaxation duration were independently associated with non-oral feeding. Non-oral feeding was determined based on optimal cutoff value of 105.0 mm Hg for VP maximal pressure (95.0% sensitivity and 70.0% specificity) and 0.45 s for UES relaxation duration (76.3% sensitivity and 57.5% specificity), respectively. During a mean follow-up of 18.8 months, 15.8% of patients developed aspiration pneumonia. On multivariate Cox regression analysis, VP maximal pressure (P<0.01) and UES relaxation duration (P<0.05) independently predicted the development of aspiration pneumonia. Cumulative incidence of aspiration pneumonia was significantly increased in patients with readings below optimal cutoff values for VP maximal pressure (P<0.01) and UES relaxation duration (P<0.01), individually. We first established the optimal thresholds for HRM parameters to determine feeding method and predict the development of aspiration pneumonia in patients with oropharyngeal dysphagia.

Simultaneous determination of macronutrients, micronutrients and trace elements in mineral fertilizers by inductively coupled plasma optical emission spectrometry

NASA Astrophysics Data System (ADS)

de Oliveira Souza, Sidnei; da Costa, Silvânio Silvério Lopes; Santos, Dayane Melo; dos Santos Pinto, Jéssica; Garcia, Carlos Alexandre Borges; Alves, José do Patrocínio Hora; Araujo, Rennan Geovanny Oliveira

2014-06-01

An analytical method for simultaneous determination of macronutrients (Ca, Mg, Na and P), micronutrients (Cu, Fe, Mn and Zn) and trace elements (Al, As, Cd, Pb and V) in mineral fertilizers was optimized. Two-level full factorial design was applied to evaluate the optimal proportions of reagents used in the sample digestion on hot plate. A Doehlert design for two variables was used to evaluate the operating conditions of the inductively coupled plasma optical emission spectrometer in order to accomplish the simultaneous determination of the analyte concentrations. The limits of quantification (LOQs) ranged from 2.0 mg kg- 1 for Mn to 77.3 mg kg- 1 for P. The accuracy and precision of the proposed method were evaluated by analysis of standard reference materials (SRMs) of Western phosphate rock (NIST 694), Florida phosphate rock (NIST 120C) and Trace elements in multi-nutrient fertilizer (NIST 695), considered to be adequate for simultaneous determination. Twenty-one samples of mineral fertilizers collected in Sergipe State, Brazil, were analyzed. For all samples, the As, Ca, Cd and Pb concentrations were below the LOQ values of the analytical method. For As, Cd and Pb the obtained LOQ values were below the maximum limit allowed by the Brazilian Ministry of Agriculture, Livestock and Food Supply (Ministério da Agricultura, Pecuária e Abastecimento - MAPA). The optimized method presented good accuracy and was effectively applied to quantitative simultaneous determination of the analytes in mineral fertilizers by inductively coupled plasma optical emission spectrometry (ICP OES).

Evaluating data worth for ground-water management under uncertainty

USGS Publications Warehouse

Wagner, B.J.

1999-01-01

A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models-a chance-constrained ground-water management model and an integer-programing sampling network design model-to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information-i.e., the projected reduction in management costs-with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models - a chance-constrained ground-water management model and an integer-programming sampling network design model - to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information - i.e., the projected reduction in management costs - with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.

Optimal deployment of thermal energy storage under diverse economic and climate conditions

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

DeForest, Nicholas; Mendes, Gonçalo; Stadler, Michael

2014-04-01

This paper presents an investigation of the economic benefit of thermal energy storage (TES) for cooling, across a range of economic and climate conditions. Chilled water TES systems are simulated for a large office building in four distinct locations, Miami in the U.S.; Lisbon, Portugal; Shanghai, China; and Mumbai, India. Optimal system size and operating schedules are determined using the optimization model DER-CAM, such that total cost, including electricity and amortized capital costs are minimized. The economic impacts of each optimized TES system is then compared to systems sized using a simple heuristic method, which bases system size as fractionmore » (50percent and 100percent) of total on-peak summer cooling loads. Results indicate that TES systems of all sizes can be effective in reducing annual electricity costs (5percent-15percent) and peak electricity consumption (13percent-33percent). The investigation also indentifies a number of criteria which drive TES investment, including low capital costs, electricity tariffs with high power demand charges and prolonged cooling seasons. In locations where these drivers clearly exist, the heuristically sized systems capture much of the value of optimally sized systems; between 60percent and 100percent in terms of net present value. However, in instances where these drivers are less pronounced, the heuristic tends to oversize systems, and optimization becomes crucial to ensure economically beneficial deployment of TES, increasing the net present value of heuristically sized systems by as much as 10 times in some instances.« less

Genetic Algorithm for Initial Orbit Determination with Too Short Arc

NASA Astrophysics Data System (ADS)

Li, Xin-ran; Wang, Xin

2017-01-01

A huge quantity of too-short-arc (TSA) observational data have been obtained in sky surveys of space objects. However, reasonable results for the TSAs can hardly be obtained with the classical methods of initial orbit determination (IOD). In this paper, the IOD is reduced to a two-stage hierarchical optimization problem containing three variables for each stage. Using the genetic algorithm, a new method of the IOD for TSAs is established, through the selections of the optimized variables and the corresponding genetic operators for specific problems. Numerical experiments based on the real measurements show that the method can provide valid initial values for the follow-up work.

Genetic Algorithm for Initial Orbit Determination with Too Short Arc

NASA Astrophysics Data System (ADS)

Li, X. R.; Wang, X.

2016-01-01

The sky surveys of space objects have obtained a huge quantity of too-short-arc (TSA) observation data. However, the classical method of initial orbit determination (IOD) can hardly get reasonable results for the TSAs. The IOD is reduced to a two-stage hierarchical optimization problem containing three variables for each stage. Using the genetic algorithm, a new method of the IOD for TSAs is established, through the selection of optimizing variables as well as the corresponding genetic operator for specific problems. Numerical experiments based on the real measurements show that the method can provide valid initial values for the follow-up work.

Quantitative determination of limonin in citrus juices by HPLC using computerized solvent optimization.

PubMed

Shaw, P E; Wilson, C W

1988-09-01

The commercially available computer program, Drylab, for optimization of separations by high-performance liquid chromatography (HPLC) using binary solvent mixtures is used to improve an HPLC method for separation of the bitter principle, limonin, in grapefruit and navel orange juices. Best conditions for separation of limonin in a reasonable time are 30 to 32% acetonitrile in water at 0.9 mL/min using a 5-micron C18 column 10 cm long. These conditions are used to analyze grapefruit and navel orange juice samples, and these HPLC results are compared with values determined by enzyme immunoassay or thin-layer chromatography (TLC) on the same samples.

An Energy Storage Assessment: Using Optimal Control Strategies to Capture Multiple Services

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

Wu, Di; Jin, Chunlian; Balducci, Patrick J.

2015-09-01

This paper presents a methodology for evaluating benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. In the proposed method, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This methodology is used to assess energy storage alternatives in Puget Sound Energy System. Different battery storage candidates are simulated for a period of one year to assess different value streams and overall benefits, as partmore » of a financial feasibility evaluation of battery storage projects.« less

A computerized bucking trainer for optimally bucking hardwoods

Treesearch

Scott Noble; Blair Orr; Philip A. Araman; John Baumgras; James B. Pickens

2000-01-01

The bucking of hardwood stems constitutes the initial manufacturing decision for hardwood lumber production. Each bucking cut creates a log of fixed grade and scale. The grade and scale of each log created by the bucker determines the quantity and quality of potential lumber, which determines the value of the log within a given market. As a result, bucking decisions...

Future contingencies and photovoltaic system worth

NASA Astrophysics Data System (ADS)

Jones, G. J.; Thomas, M. G.; Bonk, G. J.

1982-09-01

The value of dispersed photovoltaic systems connected to the utility grid was calculated using the optimized generation planning program. The 1986 to 2001 time period was used for this study. Photovoltaic systems were dynamically integrated, up to 5% total capacity, into 9 NERC based regions under a range of future fuel and economic contingencies. Value was determined by the change in revenue requirements due to the photovoltaic additions. Displacement of high cost fuel was paramount to value, while capacity displacement was highly variable and dependent upon regional fuel mix.

Optimization of ecosystem model parameters with different temporal variabilities using tower flux data and an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

He, L.; Chen, J. M.; Liu, J.; Mo, G.; Zhen, T.; Chen, B.; Wang, R.; Arain, M.

2013-12-01

Terrestrial ecosystem models have been widely used to simulate carbon, water and energy fluxes and climate-ecosystem interactions. In these models, some vegetation and soil parameters are determined based on limited studies from literatures without consideration of their seasonal variations. Data assimilation (DA) provides an effective way to optimize these parameters at different time scales . In this study, an ensemble Kalman filter (EnKF) is developed and applied to optimize two key parameters of an ecosystem model, namely the Boreal Ecosystem Productivity Simulator (BEPS): (1) the maximum photosynthetic carboxylation rate (Vcmax) at 25 °C, and (2) the soil water stress factor (fw) for stomatal conductance formulation. These parameters are optimized through assimilating observations of gross primary productivity (GPP) and latent heat (LE) fluxes measured in a 74 year-old pine forest, which is part of the Turkey Point Flux Station's age-sequence sites. Vcmax is related to leaf nitrogen concentration and varies slowly over the season and from year to year. In contrast, fw varies rapidly in response to soil moisture dynamics in the root-zone. Earlier studies suggested that DA of vegetation parameters at daily time steps leads to Vcmax values that are unrealistic. To overcome the problem, we developed a three-step scheme to optimize Vcmax and fw. First, the EnKF is applied daily to obtain precursor estimates of Vcmax and fw. Then Vcmax is optimized at different time scales assuming fw is unchanged from first step. The best temporal period or window size is then determined by analyzing the magnitude of the minimized cost-function, and the coefficient of determination (R2) and Root-mean-square deviation (RMSE) of GPP and LE between simulation and observation. Finally, the daily fw value is optimized for rain free days corresponding to the Vcmax curve from the best window size. The optimized fw is then used to model its relationship with soil moisture. We found that the optimized fw is best correlated linearly to soil water content at 5 to 10 cm depth. We also found that both the temporal scale or window size and the priori uncertainty of Vcmax (given as its standard deviation) are important in determining the seasonal trajectory of Vcmax. During the leaf expansion stage, an appropriate window size leads to reasonable estimate of Vcmax. In the summer, the fluctuation of optimized Vcmax is mainly caused by the uncertainties in Vcmax but not the window size. Our study suggests that a smooth Vcmax curve optimized from an optimal time window size is close to the reality though the RMSE of GPP at this window is not the minimum. It also suggests that for the accurate optimization of Vcmax, it is necessary to set appropriate levels of uncertainty of Vcmax in the spring and summer because the rate of leaf nitrogen concentration change is different over the season. Parameter optimizations for more sites and multi-years are in progress.

Spectrophotometric determination of gold(III) in forensic and pharmaceutical samples and results complemented with ICP AES and EDXRF analysis

NASA Astrophysics Data System (ADS)

Nagaraja, Vani; Kumar, M. Kiran; Giddappa, Nagendrappa

2017-02-01

Spectrophotometric method with three systems were developed here for the determination of gold(III) using o-dianisidine, aniline sulphate and catechol. Gold(III),in the system 1 it oxidizes o-dianisidine, in the system 2 it oxidizes catechol followed by its coupling with o-dianisidine, in the system 3 it oxidizes catechol followed by its coupling with aniline sulphate forming dye products with respective λmax 446 nm, 540 nm, and 505 nm. All the three systems were optimized and analytical parameters were calculated. The molar absorptivity values were 9.27 × 104, 1.97 × 104 and 1.62 × 104 respectively for the systems 1, 2 and 3 with the corresponding Sandell sensitivity values (μg cm- 2), 0.0021, 0.0096 and 0.011. The optimized systems were used for the determination of gold present in some forensic jewellery and pharmaceutical samples and the results obtained were compared with the results of all samples determined by Inductively Coupled Plasma - Atomic Emission Spectrometric method and a few of them were also complemented by Energy Dispersive X-Ray Fluorescent spectral analysis.

Spectrophotometric determination of gold(III) in forensic and pharmaceutical samples and results complemented with ICP AES and EDXRF analysis.

PubMed

Nagaraja, Vani; Kumar, M Kiran; Giddappa, Nagendrappa

2017-02-15

Spectrophotometric method with three systems were developed here for the determination of gold(III) using o-dianisidine, aniline sulphate and catechol. Gold(III),in the system 1 it oxidizes o-dianisidine, in the system 2 it oxidizes catechol followed by its coupling with o-dianisidine, in the system 3 it oxidizes catechol followed by its coupling with aniline sulphate forming dye products with respective λ max 446nm, 540nm, and 505nm. All the three systems were optimized and analytical parameters were calculated. The molar absorptivity values were 9.27×10 4 , 1.97×10 4 and 1.62×10 4 respectively for the systems 1, 2 and 3 with the corresponding Sandell sensitivity values (μgcm -2 ), 0.0021, 0.0096 and 0.011. The optimized systems were used for the determination of gold present in some forensic jewellery and pharmaceutical samples and the results obtained were compared with the results of all samples determined by Inductively Coupled Plasma - Atomic Emission Spectrometric method and a few of them were also complemented by Energy Dispersive X-Ray Fluorescent spectral analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Current evidence and future perspectives on the effective practice of patient-centered laboratory medicine.

PubMed

Hallworth, Mike J; Epner, Paul L; Ebert, Christoph; Fantz, Corinne R; Faye, Sherry A; Higgins, Trefor N; Kilpatrick, Eric S; Li, Wenzhe; Rana, S V; Vanstapel, Florent

2015-04-01

Systematic evidence of the contribution made by laboratory medicine to patient outcomes and the overall process of healthcare is difficult to find. An understanding of the value of laboratory medicine, how it can be determined, and the various factors that influence it is vital to ensuring that the service is provided and used optimally. This review summarizes existing evidence supporting the impact of laboratory medicine in healthcare and indicates the gaps in our understanding. It also identifies deficiencies in current utilization, suggests potential solutions, and offers a vision of a future in which laboratory medicine is used optimally to support patient care. To maximize the value of laboratory medicine, work is required in 5 areas: (a) improved utilization of existing and new tests; (b) definition of new roles for laboratory professionals that are focused on optimizing patient outcomes by adding value at all points of the diagnostic brain-to-brain cycle; (c) development of standardized protocols for prospective patient-centered studies of biomarker clinical effectiveness or extraanalytical process effectiveness; (d) benchmarking of existing and new tests in specified situations with commonly accepted measures of effectiveness; (e) agreed definition and validation of effectiveness measures and use of checklists for articles submitted for publication. Progress in these areas is essential if we are to demonstrate and enhance the value of laboratory medicine and prevent valuable information being lost in meaningless data. This requires effective collaboration with clinicians, and a determination to accept patient outcome and patient experience as the primary measure of laboratory effectiveness. © 2014 American Association for Clinical Chemistry.

Normal and abnormal tissue identification system and method for medical images such as digital mammograms

NASA Technical Reports Server (NTRS)

Heine, John J. (Inventor); Clarke, Laurence P. (Inventor); Deans, Stanley R. (Inventor); Stauduhar, Richard Paul (Inventor); Cullers, David Kent (Inventor)

2001-01-01

A system and method for analyzing a medical image to determine whether an abnormality is present, for example, in digital mammograms, includes the application of a wavelet expansion to a raw image to obtain subspace images of varying resolution. At least one subspace image is selected that has a resolution commensurate with a desired predetermined detection resolution range. A functional form of a probability distribution function is determined for each selected subspace image, and an optimal statistical normal image region test is determined for each selected subspace image. A threshold level for the probability distribution function is established from the optimal statistical normal image region test for each selected subspace image. A region size comprising at least one sector is defined, and an output image is created that includes a combination of all regions for each selected subspace image. Each region has a first value when the region intensity level is above the threshold and a second value when the region intensity level is below the threshold. This permits the localization of a potential abnormality within the image.

Development of a Method for the Determination of Chromium and Cadmium in Tannery Wastewater Using Laser-Induced Breakdown Spectroscopy

PubMed Central

Bukhari, Mahwish; Awan, M. Ali; Qazi, Ishtiaq A.; Baig, M. Anwar

2012-01-01

This paper illustrates systematic development of a convenient analytical method for the determination of chromium and cadmium in tannery wastewater using laser-induced breakdown spectroscopy (LIBS). A new approach was developed by which liquid was converted into solid phase sample surface using absorption paper for subsequent LIBS analysis. The optimized values of LIBS parameters were 146.7 mJ for chromium and 89.5 mJ for cadmium (laser pulse energy), 4.5 μs (delay time), 70 mm (lens to sample surface distance), and 7 mm (light collection system to sample surface distance). Optimized values of LIBS parameters demonstrated strong spectrum lines for each metal keeping the background noise at minimum level. The new method of preparing metal standards on absorption papers exhibited calibration curves with good linearity with correlation coefficients, R2 in the range of 0.992 to 0.998. The developed method was tested on real tannery wastewater samples for determination of chromium and cadmium. PMID:22567570

Determining optimal parameters in magnetic spacecraft stabilization via attitude feedback

NASA Astrophysics Data System (ADS)

Bruni, Renato; Celani, Fabio

2016-10-01

The attitude control of a spacecraft using magnetorquers can be achieved by a feedback control law which has four design parameters. However, the practical determination of appropriate values for these parameters is a critical open issue. We propose here an innovative systematic approach for finding these values: they should be those that minimize the convergence time to the desired attitude. This a particularly diffcult optimization problem, for several reasons: 1) such time cannot be expressed in analytical form as a function of parameters and initial conditions; 2) design parameters may range over very wide intervals; 3) convergence time depends also on the initial conditions of the spacecraft, which are not known in advance. To overcome these diffculties, we present a solution approach based on derivative-free optimization. These algorithms do not need to write analytically the objective function: they only need to compute it in a number of points. We also propose a fast probing technique to identify which regions of the search space have to be explored densely. Finally, we formulate a min-max model to find robust parameters, namely design parameters that minimize convergence time under the worst initial conditions. Results are very promising.

Multi-objective optimization on laser solder jet bonding process in head gimbal assembly using the response surface methodology

NASA Astrophysics Data System (ADS)

Deeying, J.; Asawarungsaengkul, K.; Chutima, P.

2018-01-01

This paper aims to investigate the effect of laser solder jet bonding parameters to the solder joints in Head Gimbal Assembly. Laser solder jet bonding utilizes the fiber laser to melt solder ball in capillary. The molten solder is transferred to two bonding pads by nitrogen gas. The response surface methodology have been used to investigate the effects of laser energy, wait time, nitrogen gas pressure, and focal position on the shear strength of solder joints and the change of pitch static attitude (PSA). The response surface methodology is employed to establish the reliable mathematical relationships between the laser soldering parameters and desired responses. Then, multi-objective optimization is conducted to determine the optimal process parameters that can enhance the joint shear strength and minimize the change of PSA. The validation test confirms that the predicted value has good agreement with the actual value.

Aerodynamic configuration design using response surface methodology analysis

NASA Technical Reports Server (NTRS)

Engelund, Walter C.; Stanley, Douglas O.; Lepsch, Roger A.; Mcmillin, Mark M.; Unal, Resit

1993-01-01

An investigation has been conducted to determine a set of optimal design parameters for a single-stage-to-orbit reentry vehicle. Several configuration geometry parameters which had a large impact on the entry vehicle flying characteristics were selected as design variables: the fuselage fineness ratio, the nose to body length ratio, the nose camber value, the wing planform area scale factor, and the wing location. The optimal geometry parameter values were chosen using a response surface methodology (RSM) technique which allowed for a minimum dry weight configuration design that met a set of aerodynamic performance constraints on the landing speed, and on the subsonic, supersonic, and hypersonic trim and stability levels. The RSM technique utilized, specifically the central composite design method, is presented, along with the general vehicle conceptual design process. Results are presented for an optimized configuration along with several design trade cases.

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

Automatic Sleep Stage Determination by Multi-Valued Decision Making Based on Conditional Probability with Optimal Parameters

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Wang, Xingyu; Nakamura, Masatoshi

Data for human sleep study may be affected by internal and external influences. The recorded sleep data contains complex and stochastic factors, which increase the difficulties for the computerized sleep stage determination techniques to be applied for clinical practice. The aim of this study is to develop an automatic sleep stage determination system which is optimized for variable sleep data. The main methodology includes two modules: expert knowledge database construction and automatic sleep stage determination. Visual inspection by a qualified clinician is utilized to obtain the probability density function of parameters during the learning process of expert knowledge database construction. Parameter selection is introduced in order to make the algorithm flexible. Automatic sleep stage determination is manipulated based on conditional probability. The result showed close agreement comparing with the visual inspection by clinician. The developed system can meet the customized requirements in hospitals and institutions.

Optimization of seismic isolation systems via harmony search

NASA Astrophysics Data System (ADS)

Melih Nigdeli, Sinan; Bekdaş, Gebrail; Alhan, Cenk

2014-11-01

In this article, the optimization of isolation system parameters via the harmony search (HS) optimization method is proposed for seismically isolated buildings subjected to both near-fault and far-fault earthquakes. To obtain optimum values of isolation system parameters, an optimization program was developed in Matlab/Simulink employing the HS algorithm. The objective was to obtain a set of isolation system parameters within a defined range that minimizes the acceleration response of a seismically isolated structure subjected to various earthquakes without exceeding a peak isolation system displacement limit. Several cases were investigated for different isolation system damping ratios and peak displacement limitations of seismic isolation devices. Time history analyses were repeated for the neighbouring parameters of optimum values and the results proved that the parameters determined via HS were true optima. The performance of the optimum isolation system was tested under a second set of earthquakes that was different from the first set used in the optimization process. The proposed optimization approach is applicable to linear isolation systems. Isolation systems composed of isolation elements that are inherently nonlinear are the subject of a future study. Investigation of the optimum isolation system parameters has been considered in parametric studies. However, obtaining the best performance of a seismic isolation system requires a true optimization by taking the possibility of both near-fault and far-fault earthquakes into account. HS optimization is proposed here as a viable solution to this problem.

Ring rolling process simulation for microstructure optimization

NASA Astrophysics Data System (ADS)

Franchi, Rodolfo; Del Prete, Antonio; Donatiello, Iolanda; Calabrese, Maurizio

2017-10-01

Metal undergoes complicated microstructural evolution during Hot Ring Rolling (HRR), which determines the quality, mechanical properties and life of the ring formed. One of the principal microstructure properties which mostly influences the structural performances of forged components, is the value of the average grain size. In the present paper a ring rolling process has been studied and optimized in order to obtain anular components to be used in aerospace applications. In particular, the influence of process input parameters (feed rate of the mandrel and angular velocity of driver roll) on microstructural and on geometrical features of the final ring has been evaluated. For this purpose, a three-dimensional finite element model for HRR has been developed in SFTC DEFORM V11, taking into account also microstructural development of the material used (the nickel superalloy Waspalloy). The Finite Element (FE) model has been used to formulate a proper optimization problem. The optimization procedure has been developed in order to find the combination of process parameters which allows to minimize the average grain size. The Response Surface Methodology (RSM) has been used to find the relationship between input and output parameters, by using the exact values of output parameters in the control points of a design space explored through FEM simulation. Once this relationship is known, the values of the output parameters can be calculated for each combination of the input parameters. Then, an optimization procedure based on Genetic Algorithms has been applied. At the end, the minimum value of average grain size with respect to the input parameters has been found.

Modeling and optimization of trihalomethanes formation potential of surface water (a drinking water source) using Box-Behnken design.

PubMed

Singh, Kunwar P; Rai, Premanjali; Pandey, Priyanka; Sinha, Sarita

2012-01-01

The present research aims to investigate the individual and interactive effects of chlorine dose/dissolved organic carbon ratio, pH, temperature, bromide concentration, and reaction time on trihalomethanes (THMs) formation in surface water (a drinking water source) during disinfection by chlorination in a prototype laboratory-scale simulation and to develop a model for the prediction and optimization of THMs levels in chlorinated water for their effective control. A five-factor Box-Behnken experimental design combined with response surface and optimization modeling was used for predicting the THMs levels in chlorinated water. The adequacy of the selected model and statistical significance of the regression coefficients, independent variables, and their interactions were tested by the analysis of variance and t test statistics. The THMs levels predicted by the model were very close to the experimental values (R(2) = 0.95). Optimization modeling predicted maximum (192 μg/l) TMHs formation (highest risk) level in water during chlorination was very close to the experimental value (186.8 ± 1.72 μg/l) determined in laboratory experiments. The pH of water followed by reaction time and temperature were the most significant factors that affect the THMs formation during chlorination. The developed model can be used to determine the optimum characteristics of raw water and chlorination conditions for maintaining the THMs levels within the safe limit.

Early Recurrence After Hepatectomy for Colorectal Liver Metastases: What Optimal Definition and What Predictive Factors?

PubMed Central

Imai, Katsunori; Allard, Marc-Antoine; Benitez, Carlos Castro; Vibert, Eric; Sa Cunha, Antonio; Cherqui, Daniel; Castaing, Denis; Bismuth, Henri; Baba, Hideo

2016-01-01

Background. The purpose of this study was to determine the optimal definition and elucidate the predictive factors of early recurrence after surgery for colorectal liver metastases (CRLM). Methods. Among 987 patients who underwent curative surgery for CRLM from 1990 to 2012, 846 with a minimum follow-up period of 24 months were eligible for this study. The minimum p value approach of survival after initial recurrence was used to determine the optimal cutoff for the definition of early recurrence. The predictive factors of early recurrence and prognostic factors of survival were analyzed. Results. For 667 patients (79%) who developed recurrence, the optimal cutoff point of early recurrence was determined to be 8 months after surgery. The impact of early recurrence on survival was demonstrated mainly in patients who received preoperative chemotherapy. Among the 691 patients who received preoperative chemotherapy, recurrence was observed in 562 (81%), and survival in patients with early recurrence was significantly worse than in those with late recurrence (5-year survival 18.5% vs. 53.4%, p < .0001). Multivariate logistic analysis identified age ≤57 years (p = .0022), >1 chemotherapy line (p = .03), disease progression during last-line chemotherapy (p = .024), >3 tumors (p = .0014), and carbohydrate antigen 19-9 >60 U/mL (p = .0003) as independent predictors of early recurrence. Salvage surgery for recurrence significantly improved survival, even in patients with early recurrence. Conclusion. The optimal cutoff point of early recurrence was determined to be 8 months. The preoperative prediction of early recurrence is possible and crucial for designing effective perioperative chemotherapy regimens. Implications for Practice: In this study, the optimal cutoff point of early recurrence was determined to be 8 months after surgery based on the minimum p value approach, and its prognostic impact was demonstrated mainly in patients who received preoperative chemotherapy. Five factors, including age, number of preoperative chemotherapy lines, response to last-line chemotherapy, number of tumors, and carbohydrate antigen 19-9 concentrations, were identified as predictors of early recurrence. Salvage surgery for recurrence significantly improved survival, even in patients with early recurrence. For better selection of patients who could truly benefit from surgery and should also receive strong postoperative chemotherapy, the accurate preoperative prediction of early recurrence is crucial. PMID:27125753

Economic-Oriented Stochastic Optimization in Advanced Process Control of Chemical Processes

PubMed Central

Dobos, László; Király, András; Abonyi, János

2012-01-01

Finding the optimal operating region of chemical processes is an inevitable step toward improving economic performance. Usually the optimal operating region is situated close to process constraints related to product quality or process safety requirements. Higher profit can be realized only by assuring a relatively low frequency of violation of these constraints. A multilevel stochastic optimization framework is proposed to determine the optimal setpoint values of control loops with respect to predetermined risk levels, uncertainties, and costs of violation of process constraints. The proposed framework is realized as direct search-type optimization of Monte-Carlo simulation of the controlled process. The concept is illustrated throughout by a well-known benchmark problem related to the control of a linear dynamical system and the model predictive control of a more complex nonlinear polymerization process. PMID:23213298

Mathematical modeling of a thermovoltaic cell

NASA Technical Reports Server (NTRS)

White, Ralph E.; Kawanami, Makoto

1992-01-01

A new type of battery named 'Vaporvolt' cell is in the early stage of its development. A mathematical model of a CuO/Cu 'Vaporvolt' cell is presented that can be used to predict the potential and the transport behavior of the cell during discharge. A sensitivity analysis of the various transport and electrokinetic parameters indicates which parameters have the most influence on the predicted energy and power density of the 'Vaporvolt' cell. This information can be used to decide which parameters should be optimized or determined more accurately through further modeling or experimental studies. The optimal thicknesses of electrodes and separator, the concentration of the electrolyte, and the current density are determined by maximizing the power density. These parameter sensitivities and optimal design parameter values will help in the development of a better CuO/Cu 'Vaporvolt' cell.

Determination of optimal environmental policy for reclamation of land unearthed in lignite mines - Strategy and tactics

NASA Astrophysics Data System (ADS)

Batzias, Dimitris F.; Pollalis, Yannis A.

2012-12-01

In this paper, optimal environmental policy for reclamation of land unearthed in lignite mines is defined as a strategic target. The tactics concerning the achievement of this target, includes estimation of optimal time lag between each lignite site (which is a segment of the whole lignite field) complete exploitation and its reclamation. Subsidizing of reclamation has been determined as a function of this time lag and relevant implementation is presented for parameter values valid for the Greek economy. We proved that the methodology we have developed gives reasonable quantitative results within the norms imposed by legislation. Moreover, the interconnection between strategy and tactics becomes evident, since the former causes the latter by deduction and the latter revises the former by induction in the time course of land reclamation.

Tumor invasiveness defined by IASLC/ATS/ERS classification of ground-glass nodules can be predicted by quantitative CT parameters.

PubMed

Zhou, Qian-Jun; Zheng, Zhi-Chun; Zhu, Yong-Qiao; Lu, Pei-Ji; Huang, Jia; Ye, Jian-Ding; Zhang, Jie; Lu, Shun; Luo, Qing-Quan

2017-05-01

To investigate the potential value of CT parameters to differentiate ground-glass nodules between noninvasive adenocarcinoma and invasive pulmonary adenocarcinoma (IPA) as defined by IASLC/ATS/ERS classification. We retrospectively reviewed 211 patients with pathologically proved stage 0-IA lung adenocarcinoma which appeared as subsolid nodules, from January 2012 to January 2013 including 137 pure ground glass nodules (pGGNs) and 74 part-solid nodules (PSNs). Pathological data was classified under the 2011 IASLC/ATS/ERS classification. Both quantitative and qualitative CT parameters were used to determine the tumor invasiveness between noninvasive adenocarcinomas and IPAs. There were 154 noninvasive adenocarcinomas and 57 IPAs. In pGGNs, CT size and area, one-dimensional mean CT value and bubble lucency were significantly different between noninvasive adenocarcinomas and IPAs on univariate analysis. Multivariate regression and ROC analysis revealed that CT size and one-dimensional mean CT value were predictive of noninvasive adenocarcinomas compared to IPAs. Optimal cutoff value was 13.60 mm (sensitivity, 75.0%; specificity, 99.6%), and -583.60 HU (sensitivity, 68.8%; specificity, 66.9%). In PSNs, there were significant differences in CT size and area, solid component area, solid proportion, one-dimensional mean and maximum CT value, three-dimensional (3D) mean CT value between noninvasive adenocarcinomas and IPAs on univariate analysis. Multivariate and ROC analysis showed that CT size and 3D mean CT value were significantly differentiators. Optimal cutoff value was 19.64 mm (sensitivity, 53.7%; specificity, 93.9%), -571.63 HU (sensitivity, 85.4%; specificity, 75.8%). For pGGNs, CT size and one-dimensional mean CT value are determinants for tumor invasiveness. For PSNs, tumor invasiveness can be predicted by CT size and 3D mean CT value.

Optimal exploration systems

NASA Astrophysics Data System (ADS)

Klesh, Andrew T.

This dissertation studies optimal exploration, defined as the collection of information about given objects of interest by a mobile agent (the explorer) using imperfect sensors. The key aspects of exploration are kinematics (which determine how the explorer moves in response to steering commands), energetics (which determine how much energy is consumed by motion and maneuvers), informatics (which determine the rate at which information is collected) and estimation (which determines the states of the objects). These aspects are coupled by the steering decisions of the explorer. We seek to improve exploration by finding trade-offs amongst these couplings and the components of exploration: the Mission, the Path and the Agent. A comprehensive model of exploration is presented that, on one hand, accounts for these couplings and on the other hand is simple enough to allow analysis. This model is utilized to pose and solve several exploration problems where an objective function is to be minimized. Specific functions to be considered are the mission duration and the total energy. These exploration problems are formulated as optimal control problems and necessary conditions for optimality are obtained in the form of two-point boundary value problems. An analysis of these problems reveals characteristics of optimal exploration paths. Several regimes are identified for the optimal paths including the Watchtower, Solar and Drag regime, and several non-dimensional parameters are derived that determine the appropriate regime of travel. The so-called Power Ratio is shown to predict the qualitative features of the optimal paths, provide a metric to evaluate an aircrafts design and determine an aircrafts capability for flying perpetually. Optimal exploration system drivers are identified that provide perspective as to the importance of these various regimes of flight. A bank-to-turn solar-powered aircraft flying at constant altitude on Mars is used as a specific platform for analysis using the coupled model. Flight-paths found with this platform are presented that display the optimal exploration problem characteristics. These characteristics are used to form heuristics, such as a Generalized Traveling Salesman Problem solver, to simplify the exploration problem. These heuristics are used to empirically show the successful completion of an exploration mission by a physical explorer.

Response surface optimization of medium components for naringinase production from Staphylococcus xylosus MAK2.

PubMed

Puri, Munish; Kaur, Aneet; Singh, Ram Sarup; Singh, Anubhav

2010-09-01

Response surface methodology was used to optimize the fermentation medium for enhancing naringinase production by Staphylococcus xylosus. The first step of this process involved the individual adjustment and optimization of various medium components at shake flask level. Sources of carbon (sucrose) and nitrogen (sodium nitrate), as well as an inducer (naringin) and pH levels were all found to be the important factors significantly affecting naringinase production. In the second step, a 22 full factorial central composite design was applied to determine the optimal levels of each of the significant variables. A second-order polynomial was derived by multiple regression analysis on the experimental data. Using this methodology, the optimum values for the critical components were obtained as follows: sucrose, 10.0%; sodium nitrate, 10.0%; pH 5.6; biomass concentration, 1.58%; and naringin, 0.50% (w/v), respectively. Under optimal conditions, the experimental naringinase production was 8.45 U/mL. The determination coefficients (R(2)) were 0.9908 and 0.9950 for naringinase activity and biomass production, respectively, indicating an adequate degree of reliability in the model.

Optimization of ultrasonic emulsification conditions for the production of orange peel essential oil nanoemulsions.

PubMed

Hashtjin, Adel Mirmajidi; Abbasi, Soleiman

2015-05-01

The aim of the present study was to investigate the influence of emulsifying conditions on some physical and rheological properties of orange peel essential oil (OPEO) in water nanoemulsions. In this regard, using the response surface methodology, the influence of ultrasonication conditions including sonication amplitude (70-100 %), sonication time (90-150 s) and process temperature (5-45 °C) on the mean droplets diameter (Z-average value), polydispersity index (PDI), and viscosity of the OPEO nanoemulsions was evaluated. In addition, the flow behavior and stability of selected nanoemulsions was evaluated during storage (up to 3 months) at different temperatures (5, 25 and 45 °C). Based on the results of the optimization, the optimum conditions for producing OPEO nanoemulsions (Z-average value 18.16 nm) were determined as 94 % (sonication amplitude), 138 s (sonication time) and 37 °C (process temperature). Moreover, analysis of variance (ANOVA) showed high coefficients of determination values (R (2) > 0.95) for the response surface models of the energy input and Z-average. In addition, the flow behavior of produced nanoemulsions was Newtonian, and the effect of time and storage temperature as well as their interactions on the Z-average value was highly significant (P < 0.0001).

Optimization of hyaluronic acid production and its cytotoxicity and degradability characteristics.

PubMed

Gedikli, Serap; Güngör, Gökhan; Toptaş, Yağmur; Sezgin, Dilber Ece; Demirbilek, Murat; Yazıhan, Nuray; Aytar Çelik, Pınar; Denkbaş, Emir Baki; Bütün, Vural; Çabuk, Ahmet

2018-06-14

In the present study, culture conditions of Streptococcus equi was optimized through Box-Behnken experimental design for hyaluronic acid production. About 0.87 gL -1 of hyaluronic acid was produced under the determined conditions and optimal conditions were found as 38.42 °C, 24 hr and 250 rpm. The validity and practicability of this statistical optimization strategy were confirmed relation between predicted and experimental values. The hyaluronic acid obtained under optimal conditions was characterized. The effects of different conditions such as ultraviolet light, temperature and enzymatic degradation on hyaluronic acid produced under optimal conditions were determined. 118 °C for 32 min of autoclaved HA sample included 63.09 µg mL -1 of d-glucuronic acid, which is about two-fold of enzymatic effect. Cytotoxicity of hyaluronic acid on human dermal cells (HUVEC, HaCaT), L929 and THP-1 cells was studied. In vitro effect on pro or anti-inflammatory cytokine release of THP-1 cells was determined. Although it varies depending on the concentration, cytotoxicity of hyaluronic acid is between 5 and 30%. However, it varies depending on the concentration of hyaluronic acid, TNF-α release was not much increased compared to control study. Consequently, purification procedure is necessary to develop and it is worth developing the bacterial hyaluronic acid.

Open pit mining profit maximization considering selling stage and waste rehabilitation cost

NASA Astrophysics Data System (ADS)

Muttaqin, B. I. A.; Rosyidi, C. N.

2017-11-01

In open pit mining activities, determination of the cut-off grade becomes crucial for the company since the cut-off grade affects how much profit will be earned for the mining company. In this study, we developed a cut-off grade determination mode for the open pit mining industry considering the cost of mining, waste removal (rehabilitation) cost, processing cost, fixed cost, and selling stage cost. The main goal of this study is to develop a model of cut-off grade determination to get the maximum total profit. Secondly, this study is also developed to observe the model of sensitivity based on changes in the cost components. The optimization results show that the models can help mining company managers to determine the optimal cut-off grade and also estimate how much profit that can be earned by the mining company. To illustrate the application of the models, a numerical example and a set of sensitivity analysis are presented. From the results of sensitivity analysis, we conclude that the changes in the sales price greatly affects the optimal cut-off value and the total profit.

Stepped MS(All) Relied Transition (SMART): An approach to rapidly determine optimal multiple reaction monitoring mass spectrometry parameters for small molecules.

PubMed

Ye, Hui; Zhu, Lin; Wang, Lin; Liu, Huiying; Zhang, Jun; Wu, Mengqiu; Wang, Guangji; Hao, Haiping

2016-02-11

Multiple reaction monitoring (MRM) is a universal approach for quantitative analysis because of its high specificity and sensitivity. Nevertheless, optimization of MRM parameters remains as a time and labor-intensive task particularly in multiplexed quantitative analysis of small molecules in complex mixtures. In this study, we have developed an approach named Stepped MS(All) Relied Transition (SMART) to predict the optimal MRM parameters of small molecules. SMART requires firstly a rapid and high-throughput analysis of samples using a Stepped MS(All) technique (sMS(All)) on a Q-TOF, which consists of serial MS(All) events acquired from low CE to gradually stepped-up CE values in a cycle. The optimal CE values can then be determined by comparing the extracted ion chromatograms for the ion pairs of interest among serial scans. The SMART-predicted parameters were found to agree well with the parameters optimized on a triple quadrupole from the same vendor using a mixture of standards. The parameters optimized on a triple quadrupole from a different vendor was also employed for comparison, and found to be linearly correlated with the SMART-predicted parameters, suggesting the potential applications of the SMART approach among different instrumental platforms. This approach was further validated by applying to simultaneous quantification of 31 herbal components in the plasma of rats treated with a herbal prescription. Because the sMS(All) acquisition can be accomplished in a single run for multiple components independent of standards, the SMART approach are expected to find its wide application in the multiplexed quantitative analysis of complex mixtures. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimal shapes of surface-slip driven self-propelled swimmers

NASA Astrophysics Data System (ADS)

Vilfan, Andrej; Osterman, Natan

2012-11-01

If one defines the swimming efficiency of a microorganism as the power needed to move it against viscous drag, divided by the total dissipated power, one usually finds values no better than 1%. In order to find out how close this is to the theoretically achievable optimum, we first introduced a new efficiency measure at the level of a single cilium or an infinite ciliated surface and numerically determined the optimal beating patterns according to this criterion. In the following we also determined the optimal shape of a swimmer such that the total power is minimal while maintaining the volume and the swimming speed. The resulting shape depends strongly on the allowed maximum curvature. When sufficient curvature is allowed the optimal swimmer exhibits two protrusions along the symmetry axis. The results show that prolate swimmers such as Paramecium have an efficiency that is ~ 20% higher than that of a spherical body, whereas some microorganisms have shapes that allow even higher efficiency.

Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

NASA Astrophysics Data System (ADS)

Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

2018-04-01

Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

The analytical representation of viscoelastic material properties using optimization techniques

NASA Technical Reports Server (NTRS)

Hill, S. A.

1993-01-01

This report presents a technique to model viscoelastic material properties with a function of the form of the Prony series. Generally, the method employed to determine the function constants requires assuming values for the exponential constants of the function and then resolving the remaining constants through linear least-squares techniques. The technique presented here allows all the constants to be analytically determined through optimization techniques. This technique is employed in a computer program named PRONY and makes use of commercially available optimization tool developed by VMA Engineering, Inc. The PRONY program was utilized to compare the technique against previously determined models for solid rocket motor TP-H1148 propellant and V747-75 Viton fluoroelastomer. In both cases, the optimization technique generated functions that modeled the test data with at least an order of magnitude better correlation. This technique has demonstrated the capability to use small or large data sets and to use data sets that have uniformly or nonuniformly spaced data pairs. The reduction of experimental data to accurate mathematical models is a vital part of most scientific and engineering research. This technique of regression through optimization can be applied to other mathematical models that are difficult to fit to experimental data through traditional regression techniques.

Multicomponent Therapeutics of Berberine Alkaloids

PubMed Central

Luo, Jiaoyang; Yan, Dan; Yang, Meihua; Dong, Xiaoping; Xiao, Xiaohe

2013-01-01

Although berberine alkaloids (BAs) are reported to be with broad-spectrum antibacterial and antiviral activities, the interactions among BAs have not been elucidated. In the present study, methicillin-resistant Staphylococcus aureus (MRSA) was chosen as a model organism, and modified broth microdilution was applied for the determination of the fluorescence absorption values to calculate the anti-MRSA activity of BAs. We have initiated four steps to seek the optimal combination of BAs that are (1) determining the anti-MRSA activity of single BA, (2) investigating the two-component combination to clarify the interactions among BAs by checkerboard assay, (3) investigating the multicomponent combination to determine the optimal ratio by quadratic rotation-orthogonal combination design, and (4) in vivo and in vitro validation of the optimal combination. The results showed that the interactions among BAs are related to their concentrations. The synergetic combinations included “berberine and epiberberine,” “jatrorrhizine and palmatine” and “jatrorrhizine and coptisine”; the antagonistic combinations included “coptisine and epiberberine”. The optimal combination was berberine : coptisine : jatrorrhizine : palmatine : epiberberine = 0.702 : 0.863 : 1 : 0.491 : 0.526, and the potency of the optimal combination on cyclophosphamide-immunocompromised mouse model was better than the natural combinations of herbs containing BAs. PMID:23634170

Game theory and risk-based leveed river system planning with noncooperation

NASA Astrophysics Data System (ADS)

Hui, Rui; Lund, Jay R.; Madani, Kaveh

2016-01-01

Optimal risk-based levee designs are usually developed for economic efficiency. However, in river systems with multiple levees, the planning and maintenance of different levees are controlled by different agencies or groups. For example, along many rivers, levees on opposite riverbanks constitute a simple leveed river system with each levee designed and controlled separately. Collaborative planning of the two levees can be economically optimal for the whole system. Independent and self-interested landholders on opposite riversides often are willing to separately determine their individual optimal levee plans, resulting in a less efficient leveed river system from an overall society-wide perspective (the tragedy of commons). We apply game theory to simple leveed river system planning where landholders on each riverside independently determine their optimal risk-based levee plans. Outcomes from noncooperative games are analyzed and compared with the overall economically optimal outcome, which minimizes net flood cost system-wide. The system-wide economically optimal solution generally transfers residual flood risk to the lower-valued side of the river, but is often impractical without compensating for flood risk transfer to improve outcomes for all individuals involved. Such compensation can be determined and implemented with landholders' agreements on collaboration to develop an economically optimal plan. By examining iterative multiple-shot noncooperative games with reversible and irreversible decisions, the costs of myopia for the future in making levee planning decisions show the significance of considering the externalities and evolution path of dynamic water resource problems to improve decision-making.

Development of a direct competitive enzyme-linked immunosorbent assay for parathion residue in food samples.

PubMed

Gui, Wen-Jun; Liu, Yi-Hua; Wang, Chun-Mei; Liang, Xiao; Zhu, Guo-Nian

2009-10-01

A heterologous direct competitive enzyme-linked immunosorbent assay (ELISA) for parathion residue determination is described based on a monoclonal antibody and a new competitor. The effects of several physicochemical factors, such as methanol concentration, ionic strength, pH value, and sample matrix, on the performance of the ELISA were optimized for the sake of obtaining a satisfactory assay sensitivity. Results showed that when the assay medium was in the optimized condition (phosphate buffer solution [PBS] containing 10% [v/v] methanol and 0.2 mol/L NaCl at a pH value of 5.0), the sensitivity (estimated as the IC(50) value) and the limit of detection (LOD, estimated as the IC(10) value) were 1.19 and 0.08 ng/ml, respectively. The precision investigation indicated that the intraassay precision values all were below 10% and that the interassay precision values ranged from 4.89 to 19.12%. In addition, the developed ELISA showed a good linear correlation (r(2)=0.9962) to gas chromatography within the analyte's concentration range of 0.1 to 16 ng/ml. When applied to the fortified samples (parathion adding level: 5-15 microg/kg), the developed ELISA presented mean recoveries of 127.46, 122.52, 91.92, 124.01, 129.72, 99.37, and 87.17% for tomato, cucumber, banana, apple, orange, pear, and sugarcane, respectively. Results indicated that the established ELISA is a potential tool for parathion residue determination.

Thermal and energy battery management optimization in electric vehicles using Pontryagin's maximum principle

NASA Astrophysics Data System (ADS)

Bauer, Sebastian; Suchaneck, Andre; Puente León, Fernando

2014-01-01

Depending on the actual battery temperature, electrical power demands in general have a varying impact on the life span of a battery. As electrical energy provided by the battery is needed to temper it, the question arises at which temperature which amount of energy optimally should be utilized for tempering. Therefore, the objective function that has to be optimized contains both the goal to maximize life expectancy and to minimize the amount of energy used for obtaining the first goal. In this paper, Pontryagin's maximum principle is used to derive a causal control strategy from such an objective function. The derivation of the causal strategy includes the determination of major factors that rule the optimal solution calculated with the maximum principle. The optimization is calculated offline on a desktop computer for all possible vehicle parameters and major factors. For the practical implementation in the vehicle, it is sufficient to have the values of the major factors determined only roughly in advance and the offline calculation results available. This feature sidesteps the drawback of several optimization strategies that require the exact knowledge of the future power demand. The resulting strategy's application is not limited to batteries in electric vehicles.

Structured decision making as a conceptual framework to identify thresholds for conservation and management

USGS Publications Warehouse

Martin, J.; Runge, M.C.; Nichols, J.D.; Lubow, B.C.; Kendall, W.L.

2009-01-01

Thresholds and their relevance to conservation have become a major topic of discussion in the ecological literature. Unfortunately, in many cases the lack of a clear conceptual framework for thinking about thresholds may have led to confusion in attempts to apply the concept of thresholds to conservation decisions. Here, we advocate a framework for thinking about thresholds in terms of a structured decision making process. The purpose of this framework is to promote a logical and transparent process for making informed decisions for conservation. Specification of such a framework leads naturally to consideration of definitions and roles of different kinds of thresholds in the process. We distinguish among three categories of thresholds. Ecological thresholds are values of system state variables at which small changes bring about substantial changes in system dynamics. Utility thresholds are components of management objectives (determined by human values) and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. The approach that we present focuses directly on the objectives of management, with an aim to providing decisions that are optimal with respect to those objectives. This approach clearly distinguishes the components of the decision process that are inherently subjective (management objectives, potential management actions) from those that are more objective (system models, estimates of system state). Optimization based on these components then leads to decision matrices specifying optimal actions to be taken at various values of system state variables. Values of state variables separating different actions in such matrices are viewed as decision thresholds. Utility thresholds are included in the objectives component, and ecological thresholds may be embedded in models projecting consequences of management actions. Decision thresholds are determined by the above-listed components of a structured decision process. These components may themselves vary over time, inducing variation in the decision thresholds inherited from them. These dynamic decision thresholds can then be determined using adaptive management. We provide numerical examples (that are based on patch occupancy models) of structured decision processes that include all three kinds of thresholds. ?? 2009 by the Ecological Society of America.

Evaluation of the prognostic value of neutrophil to lymphocyte ratio in patients with hypertriglyceridemia-induced acute pancreatitis.

PubMed

Wang, Yuchen; Fuentes, Harry E; Attar, Bashar M; Jaiswal, Palash; Demetria, Melchor

Recent studies attribute promising prognostic values to various inflammatory biomarkers in acute pancreatitis, including the following: the neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and red cell distribution width (RDW). We aimed to determine the performance of these biomarkers for detecting disease severity in patients with hypertriglyceridemia-induced acute pancreatitis (HTG-AP). We retrospectively reviewed 110 patients with HTG-AP and compared the NLR, PLR, and RDW in different severity groups. We performed receiver-operating characteristic (ROC) analysis to identify the optimal cut-off value for NLR to predict severe AP. NLR was significantly higher in patients with severe AP than mild and moderately severe AP (14.6 vs. 6.9, p < 0.001), and higher with organ failure upon presentation (9.1 vs. 7.1, p = 0.026). After dichotomization by the optimal cut-off value of 10 as determined by the ROC curve, the high-NLR group had a significantly longer length of stay (9.1 vs. 6.6 days, p = 0.001), duration of nil per os (4.9 vs. 3.7 days, p = 0.007), and higher rates of complications, including systemic inflammatory response syndrome (81.5% vs. 44.6%, p = 0.001) and persistent acute kidney injury (25.9% vs. 3.6%, p < 0.001). High NLR independently predicted severe acute pancreatitis in multivariate analysis (Odds ratio 6.71, p = 0.019). NLR represents an inexpensive, readily available test with a promising value to predict disease severity in HTG-AP. Among the three inflammatory biomarkers, NLR has the highest discriminatory capacity for severe HTG-AP, with an optimal cut-off value of 10. Copyright © 2017 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Optimal Waist-to-Height Ratio Values for Cardiometabolic Risk Screening in an Ethnically Diverse Sample of South African Urban and Rural School Boys and Girls

PubMed Central

Matsha, Tandi E.; Kengne, Andre-Pascal; Yako, Yandiswa Y.; Hon, Gloudina M.; Hassan, Mogamat S.; Erasmus, Rajiv T.

2013-01-01

Background The proposed waist-to-height ratio (WHtR) cut-off of 0.5 is less optimal for cardiometabolic risk screening in children in many settings. The purpose of this study was to determine the optimal WHtR for children from South Africa, and investigate variations by gender, ethnicity and residence in the achieved value. Methods Metabolic syndrome (MetS) components were measured in 1272 randomly selected learners, aged 10–16 years, comprising of 446 black Africans, 696 mixed-ancestry and 130 Caucasians. The Youden’s index and the closest-top-left (CTL) point approaches were used to derive WHtR cut-offs for diagnosing any two MetS components, excluding the waist circumference. Results The two approaches yielded similar cut-off in girls, 0.465 (sensitivity 50.0, specificity 69.5), but two different values in boys, 0.455 (42.9, 88.4) and 0.425 (60.3, 67.7) based on the Youden’s index and the CTL point, respectively. Furthermore, WHtR cut-off values derived differed substantially amongst the regions and ethnic groups investigated, whereby the highest cut-off was observed in semi-rural and white children, respectively, Youden’s index0.505 (31.6, 87.1) and CTL point 0.475 (44.4, 75.9). Conclusion The WHtR cut-off of 0.5 is less accurate for screening cardiovascular risk in South African children. The optimal value in this setting is likely gender and ethnicity-specific and sensitive to urbanization. PMID:23967160

Optimal Parameters to Determine the Apparent Diffusion Coefficient in Diffusion Weighted Imaging via Simulation

NASA Astrophysics Data System (ADS)

Perera, Dimuthu

Diffusion weighted (DW) Imaging is a non-invasive MR technique that provides information about the tissue microstructure using the diffusion of water molecules. The diffusion is generally characterized by the apparent diffusion coefficient (ADC) parametric map. The purpose of this study is to investigate in silico how the calculation of ADC is affected by image SNR, b-values, and the true tissue ADC. Also, to provide optimal parameter combination depending on the percentage accuracy and precision for prostate peripheral region cancer application. Moreover, to suggest parameter choices for any type of tissue, while providing the expected accuracy and precision. In this research DW images were generated assuming a mono-exponential signal model at two different b-values and for known true ADC values. Rician noise of different levels was added to the DWI images to adjust the image SNR. Using the two DWI images, ADC was calculated using a mono-exponential model for each set of b-values, SNR, and true ADC. 40,000 ADC data were collected for each parameter setting to determine the mean and the standard-deviation of the calculated ADC, as well as the percentage accuracy and precision with respect to the true ADC. The accuracy was calculated using the difference between known and calculated ADC. The precision was calculated using the standard-deviation of calculated ADC. The optimal parameters for a specific study was determined when both the percentage accuracy and precision were minimized. In our study, we simulated two true ADCs (ADC 0.00102 for tumor and 0.00180 mm2/s for normal prostate peripheral region tissue). Image SNR was varied from 2 to 100 and b-values were varied from 0 to 2000s/mm2. The results show that the percentage accuracy and percentage precision were minimized with image SNR. To increase SNR, 10 signal-averagings (NEX) were used considering the limitation in total scan time. The optimal NEX combination for tumor and normal tissue for prostate peripheral region was 1: 9. Also, the minimum percentage accuracy and percentage precision were obtained when low b-value is 0 and high b-value is 800 mm2/s for normal tissue and 1400 mm2/s for tumor tissue. Results also showed that for tissues with 1 x 10-3 < ADC < 2.1 x 10-3 mm 2/s the parameter combination at SNR = 20, b-value pair 0, 800 mm 2/s with NEX = 1:9 can calculate ADC with a percentage accuracy of less than 2% and percentage precision of 6-8%. Also, for tissues with 0.6 x 10-3 < ADC < 1.25 x 10-3 mm2 /s the parameter combination at SNR = 20, b-value pair 0, 1400 mm 2/s with NEX =1:9 can calculate ADC with a percentage accuracy of less than 2% and percentage precision of 6-8%.

Optimization strategies for radiation induced grafting of 4-vinylpyridine onto poly(ethylene-co-tetraflouroethene) film using Box-Behnken design

NASA Astrophysics Data System (ADS)

Mahmoud Nasef, Mohamed; Shamsaei, Ezzatollah; Ghassemi, Payman; Ahmed Aly, Amgad; Hamid Yahaya, Abdul

2012-04-01

The radiation induced grafting of 4-vinylpyridine (4-VP) onto poly(ethylene-co-tetrafluoroethene) (ETFE) was optimized using the Box-Behnken factorial design available in the response surface method (RSM). The optimized grafting parameters; absorbed dose, monomer concentration, grafting time and reaction temperature were varied in four levels to quantify their effect on the grafting yield (GY). The validity of the statistical model was supported by the small deviation between the predicted (GY=61%) and experimental (GY=57%) values. The optimum conditions for enhancing GY were determined at the following values: monomer concentration of 48 vol%, absorbed dose of 64 kGy, reaction time of 4 h and temperature of 68 °C. A comparison was made between the optimization model developed for the present grafting system and that for grafting of 1-vinylimidazole (1-VIm) onto ETFE to confirm the validly and reliability of the Box-Behnken for the optimization of various radiation induced grafting reactions. Fourier transform infrared (FTIR), thermogravimetric analysis (TGA) and X-ray diffraction (XRD) were used to investigate the properties of the obtained films and provide evidence for grafting.

Liver Stiffness Measured by Two-Dimensional Shear-Wave Elastography: Prognostic Value after Radiofrequency Ablation for Hepatocellular Carcinoma.

PubMed

Lee, Dong Ho; Lee, Jeong Min; Yoon, Jung-Hwan; Kim, Yoon Jun; Lee, Jeong-Hoon; Yu, Su Jong; Han, Joon Koo

2018-03-01

To evaluate the prognostic value of liver stiffness (LS) measured using two-dimensional (2D) shear-wave elastography (SWE) in patients with hepatocellular carcinoma (HCC) treated by radiofrequency ablation (RFA). The Institutional Review Board approved this retrospective study and informed consent was obtained from all patients. A total of 134 patients with up to 3 HCCs ≤5 cm who had undergone pre-procedural 2D-SWE prior to RFA treatment between January 2012 and December 2013 were enrolled. LS values were measured using real-time 2D-SWE before RFA on the procedural day. After a mean follow-up of 33.8 ± 9.9 months, we analyzed the overall survival after RFA using the Kaplan-Meier method and Cox proportional hazard regression model. The optimal cutoff LS value to predict overall survival was determined using the minimal p value approach. During the follow-up period, 22 patients died, and the estimated 1- and 3-year overall survival rates were 96.4 and 85.8%, respectively. LS measured by 2D-SWE was found to be a significant predictive factor for overall survival after RFA of HCCs, as was the presence of extrahepatic metastases. As for the optimal cutoff LS value for the prediction of overall survival, it was determined to be 13.3 kPa. In our study, 71 patients had LS values ≥13.3 kPa, and the estimated 3-year overall survival was 76.8% compared to 96.3% in 63 patients with LS values <13.3 kPa. This difference was statistically significant (hazard ratio = 4.30 [1.26-14.7]; p = 0.020). LS values measured by 2D-SWE was a significant predictive factor for overall survival after RFA for HCC.

An inverse problem of determining the implied volatility in option pricing

NASA Astrophysics Data System (ADS)

Deng, Zui-Cha; Yu, Jian-Ning; Yang, Liu

2008-04-01

In the Black-Scholes world there is the important quantity of volatility which cannot be observed directly but has a major impact on the option value. In practice, traders usually work with what is known as implied volatility which is implied by option prices observed in the market. In this paper, we use an optimal control framework to discuss an inverse problem of determining the implied volatility when the average option premium, namely the average value of option premium corresponding with a fixed strike price and all possible maturities from the current time to a chosen future time, is known. The issue is converted into a terminal control problem by Green function method. The existence and uniqueness of the minimum of the control functional are addressed by the optimal control method, and the necessary condition which must be satisfied by the minimum is also given. The results obtained in the paper may be useful for those who engage in risk management or volatility trading.

Approximating the Basset force by optimizing the method of van Hinsberg et al.

NASA Astrophysics Data System (ADS)

Casas, G.; Ferrer, A.; Oñate, E.

2018-01-01

In this work we put the method proposed by van Hinsberg et al. [29] to the test, highlighting its accuracy and efficiency in a sequence of benchmarks of increasing complexity. Furthermore, we explore the possibility of systematizing the way in which the method's free parameters are determined by generalizing the optimization problem that was considered originally. Finally, we provide a list of worked-out values, ready for implementation in large-scale particle-laden flow simulations.

Optimal convergence in naming game with geography-based negotiation on small-world networks

NASA Astrophysics Data System (ADS)

Liu, Run-Ran; Wang, Wen-Xu; Lai, Ying-Cheng; Chen, Guanrong; Wang, Bing-Hong

2011-01-01

We propose a negotiation strategy to address the effect of geography on the dynamics of naming games over small-world networks. Communication and negotiation frequencies between two agents are determined by their geographical distance in terms of a parameter characterizing the correlation between interaction strength and the distance. A finding is that there exists an optimal parameter value leading to fastest convergence to global consensus on naming. Numerical computations and a theoretical analysis are provided to substantiate our findings.

Pharmacokinetic design optimization in children and estimation of maturation parameters: example of cytochrome P450 3A4.

PubMed

Bouillon-Pichault, Marion; Jullien, Vincent; Bazzoli, Caroline; Pons, Gérard; Tod, Michel

2011-02-01

The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochrome P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, while taking into account age- and weight-related changes. A linear monocompartmental model with first-order absorption was used successively with three different residual error models and previously published pharmacokinetic parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases." The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse sampling databases." We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modeled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values. The established optimal design comprised four age ranges: 0.008 years old (i.e., around 3 days), 0.192 years old (i.e., around 2 months), 1.325 years old, and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population pharmacokinetic parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance and distribution volume and less than 18% for k(a)), whereas the maturation parameters were unbiased but less precise (MPE < 6% and RMSE < 37%). Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However, it requires that very early ages be included in studies, which may present an obstacle to the use of this approach. First-pass effects, alternative elimination routes, and combined elimination pathways should also be investigated.

Hot and cold body reference noise generators from 0 to 40 GHz

NASA Technical Reports Server (NTRS)

Hornbostel, D. H.

1974-01-01

This article describes the design, development, and analysis of exceptionally accurate radiometric noise generators from 0-40 GHz to serve as standard references. Size, weight, power, and reliability are optimized to meet the requirements of NASA air- and space-borne radiometers. The radiometric noise temperature of these noise generators is, unavoidably, calculated from measured values rather than measured directly. The absolute accuracy and stability are equal to or better than those of reliable standards available for comparison. A noise generator has been developed whose measurable properties (VSWR, line loss, thermometric temperatures) have been optimized in order to minimize the effects of the uncertainty in the calculated radiometric noise temperatures. Each measurable property is evaluated and analyzed to determine the effects of the uncertainty of the measured value. Unmeasurable properties (primarily temperature gradients) are analyzed, and reasonable precautions are designed into the noise generator to guarantee that the uncertainty of the value remains within tolerable limits.

Probing the microscopic environment of 23 Na ions in brain tissue by MRI: On the accuracy of different sampling schemes for the determination of rapid, biexponential T2* decay at low signal-to-noise ratio.

PubMed

Lommen, Jonathan M; Flassbeck, Sebastian; Behl, Nicolas G R; Niesporek, Sebastian; Bachert, Peter; Ladd, Mark E; Nagel, Armin M

2018-08-01

To investigate and to reduce influences on the determination of the short and long apparent transverse relaxation times ( T2,s*, T2,l*) of 23 Na in vivo with respect to signal sampling. The accuracy of T2* determination was analyzed in simulations for five different sampling schemes. The influence of noise in the parameter fit was investigated for three different models. A dedicated sampling scheme was developed for brain parenchyma by numerically optimizing the parameter estimation. This scheme was compared in vivo to linear sampling at 7T. For the considered sampling schemes, T2,s* / T2,l* exhibit an average bias of 3% / 4% with a variation of 25% / 15% based on simulations with previously published T2* values. The accuracy could be improved with the optimized sampling scheme by strongly averaging the earliest sample. A fitting model with constant noise floor can increase accuracy while additional fitting of a noise term is only beneficial in case of sampling until late echo time > 80 ms. T2* values in white matter were determined to be T2,s* = 5.1 ± 0.8 / 4.2 ± 0.4 ms and T2,l* = 35.7 ± 2.4 / 34.4 ± 1.5 ms using linear/optimized sampling. Voxel-wise T2* determination of 23 Na is feasible in vivo. However, sampling and fitting methods have to be chosen carefully to retrieve accurate results. Magn Reson Med 80:571-584, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Lipid-anthropometric index optimization for insulin sensitivity estimation

NASA Astrophysics Data System (ADS)

Velásquez, J.; Wong, S.; Encalada, L.; Herrera, H.; Severeyn, E.

2015-12-01

Insulin sensitivity (IS) is the ability of cells to react due to insulińs presence; when this ability is diminished, low insulin sensitivity or insulin resistance (IR) is considered. IR had been related to other metabolic disorders as metabolic syndrome (MS), obesity, dyslipidemia and diabetes. IS can be determined using direct or indirect methods. The indirect methods are less accurate and invasive than direct and they use glucose and insulin values from oral glucose tolerance test (OGTT). The accuracy is established by comparison using spearman rank correlation coefficient between direct and indirect method. This paper aims to propose a lipid-anthropometric index which offers acceptable correlation to insulin sensitivity index for different populations (DB1=MS subjects, DB2=sedentary without MS subjects and DB3=marathoners subjects) without to use OGTT glucose and insulin values. The proposed method is parametrically optimized through a random cross-validation, using the spearman rank correlation as comparator with CAUMO method. CAUMO is an indirect method designed from a simplification of the minimal model intravenous glucose tolerance test direct method (MINMOD-IGTT) and with acceptable correlation (0.89). The results show that the proposed optimized method got a better correlation with CAUMO in all populations compared to non-optimized. On the other hand, it was observed that the optimized method has better correlation with CAUMO in DB2 and DB3 groups than HOMA-IR method, which is the most widely used for diagnosing insulin resistance. The optimized propose method could detect incipient insulin resistance, when classify as insulin resistant subjects that present impaired postprandial insulin and glucose values.

Real option valuation of a decremental regulation service provided by electricity storage.

PubMed

Szabó, Dávid Zoltán; Martyr, Randall

2017-08-13

This paper is a quantitative study of a reserve contract for real-time balancing of a power system. Under this contract, the owner of a storage device, such as a battery, helps smooth fluctuations in electricity demand and supply by using the device to increase electricity consumption. The battery owner must be able to provide immediate physical cover, and should therefore have sufficient storage available in the battery before entering the contract. Accordingly, the following problem can be formulated for the battery owner: determine the optimal time to enter the contract and, if necessary, the optimal time to discharge electricity before entering the contract. This problem is formulated as one of optimal stopping, and is solved explicitly in terms of the model parameters and instantaneous values of the power system imbalance. The optimal operational strategies thus obtained ensure that the battery owner has positive expected economic profit from the contract. Furthermore, they provide explicit conditions under which the optimal discharge time is consistent with the overall objective of power system balancing. This paper also carries out a preliminary investigation of the 'lifetime value' aggregated from an infinite sequence of these balancing reserve contracts. This lifetime value, which can be viewed as a single project valuation of the battery, is shown to be positive and bounded. Therefore, in the long run such reserve contracts can be beneficial to commercial operators of electricity storage, while reducing some of the financial and operational risks in power system balancing.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Reliability Constrained Priority Load Shedding for Aerospace Power System Automation

NASA Technical Reports Server (NTRS)

Momoh, James A.; Zhu, Jizhong; Kaddah, Sahar S.; Dolce, James L. (Technical Monitor)

2000-01-01

The need for improving load shedding on board the space station is one of the goals of aerospace power system automation. To accelerate the optimum load-shedding functions, several constraints must be involved. These constraints include congestion margin determined by weighted probability contingency, component/system reliability index, generation rescheduling. The impact of different faults and indices for computing reliability were defined before optimization. The optimum load schedule is done based on priority, value and location of loads. An optimization strategy capable of handling discrete decision making, such as Everett optimization, is proposed. We extended Everett method to handle expected congestion margin and reliability index as constraints. To make it effective for real time load dispatch process, a rule-based scheme is presented in the optimization method. It assists in selecting which feeder load to be shed, the location of the load, the value, priority of the load and cost benefit analysis of the load profile is included in the scheme. The scheme is tested using a benchmark NASA system consisting of generators, loads and network.

Enzymatically catalyzed synthesis of low-calorie structured lipid in a solvent-free system: optimization by response surface methodology.

PubMed

Han, Lu; Xu, Zijian; Huang, Jianhua; Meng, Zong; Liu, Yuanfa; Wang, Xingguo

2011-12-14

A kind of low-calorie structured lipid (LCSL) was obtained by interesterification of tributyrin (TB) and methyl stearate (St-ME), catalyzed by a commercially immobilized 1,3-specific lipase, Lipozyme RM IM from Rhizomucor miehei . The condition optimization of the process was conducted by using response surface methodology (RSM). The optimal conditions for highest conversion of St-ME and lowest content LLL-TAG (SSS and SSP; S, stearic acid; P, palmitic acid) were determined to be a reaction time 6.52 h, a substrate molar ratio (St-ME:TB) of 1.77:1, and an enzyme amount of 10.34% at a reaction temperature of 65 °C; under these conditions, the actually measured conversion of St-ME and content of LLL-TAG were 78.47 and 4.89% respectively, in good agreement with predicted values. The target product under optimal conditions after short-range molecular distillation showed solid fat content (SFC) values similar to those of cocoa butter substitutes (CBS), cocoa butter equivalent (CBE), and cocoa butters (CB), indicating its application for inclusion with other fats as cocoa butter substitutes.

Virtual Monoenergetic Images From a Novel Dual-Layer Spectral Detector Computed Tomography Scanner in Portal Venous Phase: Adjusted Window Settings Depending on Assessment Focus Are Essential for Image Interpretation.

PubMed

Hickethier, Tilman; Iuga, Andra-Iza; Lennartz, Simon; Hauger, Myriam; Byrtus, Jonathan; Luetkens, Julian A; Haneder, Stefan; Maintz, David; Doerner, Jonas

We aimed to determine optimal window settings for conventional polyenergetic (PolyE) and virtual monoenergetic images (MonoE) derived from abdominal portal venous phase computed tomography (CT) examinations on a novel dual-layer spectral-detector CT (SDCT). From 50 patients, SDCT data sets MonoE at 40 kiloelectron volt as well as PolyE were reconstructed and best individual window width and level values manually were assessed separately for evaluation of abdominal arteries as well as for liver lesions. Via regression analysis, optimized individual values were mathematically calculated. Subjective image quality parameters, vessel, and liver lesion diameters were measured to determine influences of different W/L settings. Attenuation and contrast-to-noise values were significantly higher in MonoE compared with PolyE. Compared with standard settings, almost all adjusted W/L settings varied significantly and yielded higher subjective scoring. No differences were found between manually adjusted and mathematically calculated W/L settings. PolyE and MonoE from abdominal portal venous phase SDCT examinations require appropriate W/L settings depending on reconstruction technique and assessment focus.

Use of hyperspectral imaging technology to develop a diagnostic support system for gastric cancer

NASA Astrophysics Data System (ADS)

Goto, Atsushi; Nishikawa, Jun; Kiyotoki, Shu; Nakamura, Munetaka; Nishimura, Junichi; Okamoto, Takeshi; Ogihara, Hiroyuki; Fujita, Yusuke; Hamamoto, Yoshihiko; Sakaida, Isao

2015-01-01

Hyperspectral imaging (HSI) is a new technology that obtains spectroscopic information and renders it in image form. This study examined the difference in the spectral reflectance (SR) of gastric tumors and normal mucosa recorded with a hyperspectral camera equipped with HSI technology and attempted to determine the specific wavelength that is useful for the diagnosis of gastric cancer. A total of 104 gastric tumors removed by endoscopic submucosal dissection from 96 patients at Yamaguchi University Hospital were recorded using a hyperspectral camera. We determined the optimal wavelength and the cut-off value for differentiating tumors from normal mucosa to establish a diagnostic algorithm. We also attempted to highlight tumors by image processing using the hyperspectral camera's analysis software. A wavelength of 770 nm and a cut-off value of 1/4 the corrected SR were selected as the respective optimal wavelength and cut-off values. The rates of sensitivity, specificity, and accuracy of the algorithm's diagnostic capability were 71%, 98%, and 85%, respectively. It was possible to enhance tumors by image processing at the 770-nm wavelength. HSI can be used to measure the SR in gastric tumors and to differentiate between tumorous and normal mucosa.

Modern control techniques in active flutter suppression using a control moment gyro

NASA Technical Reports Server (NTRS)

Buchek, P. M.

1974-01-01

Development of organized synthesis techniques, using concepts of modern control theory was studied for the design of active flutter suppression systems for two and three-dimensional lifting surfaces, utilizing a control moment gyro (CMG) to generate the required control torques. Incompressible flow theory is assumed, with the unsteady aerodynamic forces and moments for arbitrary airfoil motion obtained by using the convolution integral based on Wagner's indicial lift function. Linear optimal control theory is applied to find particular optimal sets of gain values which minimize a quadratic performance function. The closed loop system's response to impulsive gust disturbances and the resulting control power requirements are investigated, and the system eigenvalues necessary to minimize the maximum value of control power are determined.

Design of dry-friction dampers for turbine blades

NASA Technical Reports Server (NTRS)

Ancona, W.; Dowell, E. H.

1983-01-01

A study is conducted of turbine blade forced response, where the blade has been modeled as a cantilever beam with a generally dry friction damper attached, and where the minimization of blade root strain as the excitation frequency is varied over a given range is the criterion for the evaluation of the effectiveness of the dry friction damper. Attempts are made to determine the location of the damper configuration best satisfying the design criterion, together with the best damping force (assuming that the damper location has been fixed). Results suggest that there need not be an optimal value for the damping force, or an optimal location for the dry friction damper, although there is a range of values which should be avoided.

Comparison of Genetic Algorithm and Hill Climbing for Shortest Path Optimization Mapping

NASA Astrophysics Data System (ADS)

Fronita, Mona; Gernowo, Rahmat; Gunawan, Vincencius

2018-02-01

Traveling Salesman Problem (TSP) is an optimization to find the shortest path to reach several destinations in one trip without passing through the same city and back again to the early departure city, the process is applied to the delivery systems. This comparison is done using two methods, namely optimization genetic algorithm and hill climbing. Hill Climbing works by directly selecting a new path that is exchanged with the neighbour's to get the track distance smaller than the previous track, without testing. Genetic algorithms depend on the input parameters, they are the number of population, the probability of crossover, mutation probability and the number of generations. To simplify the process of determining the shortest path supported by the development of software that uses the google map API. Tests carried out as much as 20 times with the number of city 8, 16, 24 and 32 to see which method is optimal in terms of distance and time computation. Based on experiments conducted with a number of cities 3, 4, 5 and 6 producing the same value and optimal distance for the genetic algorithm and hill climbing, the value of this distance begins to differ with the number of city 7. The overall results shows that these tests, hill climbing are more optimal to number of small cities and the number of cities over 30 optimized using genetic algorithms.

Quantum dot ternary-valued full-adder: Logic synthesis by a multiobjective design optimization based on a genetic algorithm

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

Klymenko, M. V.; Remacle, F., E-mail: fremacle@ulg.ac.be

2014-10-28

A methodology is proposed for designing a low-energy consuming ternary-valued full adder based on a quantum dot (QD) electrostatically coupled with a single electron transistor operating as a charge sensor. The methodology is based on design optimization: the values of the physical parameters of the system required for implementing the logic operations are optimized using a multiobjective genetic algorithm. The searching space is determined by elements of the capacitance matrix describing the electrostatic couplings in the entire device. The objective functions are defined as the maximal absolute error over actual device logic outputs relative to the ideal truth tables formore » the sum and the carry-out in base 3. The logic units are implemented on the same device: a single dual-gate quantum dot and a charge sensor. Their physical parameters are optimized to compute either the sum or the carry out outputs and are compatible with current experimental capabilities. The outputs are encoded in the value of the electric current passing through the charge sensor, while the logic inputs are supplied by the voltage levels on the two gate electrodes attached to the QD. The complex logic ternary operations are directly implemented on an extremely simple device, characterized by small sizes and low-energy consumption compared to devices based on switching single-electron transistors. The design methodology is general and provides a rational approach for realizing non-switching logic operations on QD devices.« less

An Optimization System with Parallel Processing for Reducing Common-Mode Current on Electronic Control Unit

NASA Astrophysics Data System (ADS)

Okazaki, Yuji; Uno, Takanori; Asai, Hideki

In this paper, we propose an optimization system with parallel processing for reducing electromagnetic interference (EMI) on electronic control unit (ECU). We adopt simulated annealing (SA), genetic algorithm (GA) and taboo search (TS) to seek optimal solutions, and a Spice-like circuit simulator to analyze common-mode current. Therefore, the proposed system can determine the adequate combinations of the parasitic inductance and capacitance values on printed circuit board (PCB) efficiently and practically, to reduce EMI caused by the common-mode current. Finally, we apply the proposed system to an example circuit to verify the validity and efficiency of the system.

Genetic Algorithm for Optimization: Preprocessing with n Dimensional Bisection and Error Estimation

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam Ali

2006-01-01

A knowledge of the appropriate values of the parameters of a genetic algorithm (GA) such as the population size, the shrunk search space containing the solution, crossover and mutation probabilities is not available a priori for a general optimization problem. Recommended here is a polynomial-time preprocessing scheme that includes an n-dimensional bisection and that determines the foregoing parameters before deciding upon an appropriate GA for all problems of similar nature and type. Such a preprocessing is not only fast but also enables us to get the global optimal solution and its reasonably narrow error bounds with a high degree of confidence.

Data Transfer Advisor with Transport Profiling Optimization

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

Rao, Nageswara S.; Liu, Qiang; Yun, Daqing

The network infrastructures have been rapidly upgraded in many high-performance networks (HPNs). However, such infrastructure investment has not led to corresponding performance improvement in big data transfer, especially at the application layer, largely due to the complexity of optimizing transport control on end hosts. We design and implement ProbData, a PRofiling Optimization Based DAta Transfer Advisor, to help users determine the most effective data transfer method with the most appropriate control parameter values to achieve the best data transfer performance. ProbData employs a profiling optimization based approach to exploit the optimal operational zone of various data transfer methods in supportmore » of big data transfer in extreme scale scientific applications. We present a theoretical framework of the optimized profiling approach employed in ProbData as wellas its detailed design and implementation. The advising procedure and performance benefits of ProbData are illustrated and evaluated by proof-of-concept experiments in real-life networks.« less

Graphical representation of robot grasping quality measures

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

Varma, V.; Tasch, U.

1993-11-01

When an object is held by a multi-fingered hand, the values of the contact forces can be multivalued. An objective function, when used in conjunction with the frictional and geometric constraints of the grasp, can however, give a unique set of finger force values. The selection of the objective function in determining the finger forces is dependent on the type of grasp required, the material properties of the object, and the limitations of the robot fingers. In this paper several optimization functions are studied and their merits highlighted. A graphical representation of the finger force values and the objective functionmore » is introduced that enable one in selecting and comparing various grasping configurations. The impending motion of the object at different torque and finger force values are determined by observing the normalized coefficient of friction plots.« less

Optimization of a sensor cluster for determination of trajectories and velocities of supersonic objects

NASA Astrophysics Data System (ADS)

Cannella, Marco; Sciuto, Salvatore Andrea

2001-04-01

An evaluation of errors for a method for determination of trajectories and velocities of supersonic objects is conducted. The analytical study of a cluster, composed of three pressure transducers and generally used as an apparatus for cinematic determination of parameters of supersonic objects, is developed. Furthermore, detailed investigation into the accuracy of this cluster on determination of the slope of an incoming shock wave is carried out for optimization of the device. In particular, a specific non-dimensional parameter is proposed in order to evaluate accuracies for various values of parameters and reference graphs are provided in order to properly design the sensor cluster. Finally, on the basis of the error analysis conducted, a discussion on the best estimation of the relative distance for the sensor as a function of temporal resolution of the measuring system is presented.

Optimization of DSC MRI Echo Times for CBV Measurements Using Error Analysis in a Pilot Study of High-Grade Gliomas.

PubMed

Bell, L C; Does, M D; Stokes, A M; Baxter, L C; Schmainda, K M; Dueck, A C; Quarles, C C

2017-09-01

The optimal TE must be calculated to minimize the variance in CBV measurements made with DSC MR imaging. Simulations can be used to determine the influence of the TE on CBV, but they may not adequately recapitulate the in vivo heterogeneity of precontrast T2*, contrast agent kinetics, and the biophysical basis of contrast agent-induced T2* changes. The purpose of this study was to combine quantitative multiecho DSC MRI T2* time curves with error analysis in order to compute the optimal TE for a traditional single-echo acquisition. Eleven subjects with high-grade gliomas were scanned at 3T with a dual-echo DSC MR imaging sequence to quantify contrast agent-induced T2* changes in this retrospective study. Optimized TEs were calculated with propagation of error analysis for high-grade glial tumors, normal-appearing white matter, and arterial input function estimation. The optimal TE is a weighted average of the T2* values that occur as a contrast agent bolus transverses a voxel. The mean optimal TEs were 30.0 ± 7.4 ms for high-grade glial tumors, 36.3 ± 4.6 ms for normal-appearing white matter, and 11.8 ± 1.4 ms for arterial input function estimation (repeated-measures ANOVA, P < .001). Greater heterogeneity was observed in the optimal TE values for high-grade gliomas, and mean values of all 3 ROIs were statistically significant. The optimal TE for the arterial input function estimation is much shorter; this finding implies that quantitative DSC MR imaging acquisitions would benefit from multiecho acquisitions. In the case of a single-echo acquisition, the optimal TE prescribed should be 30-35 ms (without a preload) and 20-30 ms (with a standard full-dose preload). © 2017 by American Journal of Neuroradiology.

Capacity Expansion Modeling for Storage Technologies

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

Hale, Elaine; Stoll, Brady; Mai, Trieu

2017-04-03

The Resource Planning Model (RPM) is a capacity expansion model designed for regional power systems and high levels of renewable generation. Recent extensions capture value-stacking for storage technologies, including batteries and concentrating solar power with storage. After estimating per-unit capacity value and curtailment reduction potential, RPM co-optimizes investment decisions and reduced-form dispatch, accounting for planning reserves; energy value, including arbitrage and curtailment reduction; and three types of operating reserves. Multiple technology cost scenarios are analyzed to determine level of deployment in the Western Interconnection under various conditions.

Accuracy of Pulse Oximeters in Detecting Hypoxemia in Patients with Chronic Thromboembolic Pulmonary Hypertension

PubMed Central

Kohyama, Tomoki; Moriyama, Kiyoshi; Kanai, Riichiro; Kotani, Mariko; Uzawa, Kohji; Satoh, Toru; Yorozu, Tomoko

2015-01-01

Purpose Pulse oximetry is routinely used to continuously and non-invasively monitor arterial oxygen saturation (SaO2). When oxygen saturation by pulse oximeter (SpO2) overestimates SaO2, hypoxemia may be overlooked. We compared the SpO2 - SaO2 differences among three pulse oximeters in patients with chronic thromboembolic pulmonary hypertension (CTEPH) who spent their daily lives in a poor oxygen state. Material and Method This prospective observational study recruited 32 patients with CTEPH undergoing elective cardiac catheterization. As we collected arterial blood samples in the catheter laboratory, SpO2 values were simultaneously recorded. Three pulse oximeters were used on each patient, and SpO2 values were compared with oximetry readings using a blood gas analyzer. To determine the optimal SpO2 value by which to detect hypoxemia (SaO2≦90%), we generated receiver operating characteristic (ROC) curves for each pulse oximeter. Result The root mean square of each pulse oximeter was 1.79 (OLV-3100), 1.64 (N-BS), and 2.50 (Masimo Radical). The mean bias (SpO2 - SaO2) for the 90%–95% saturation range was significantly higher for Masimo Radical (0.19 +/- 1.78% [OLV-3100], 0.18 +/- 1.63% [N-BS], and 1.61 +/- 1.91% [Masimo Radical]; p<0.0001). The optimal SpO2 value to detect hypoxemia (SaO2≦90%) was 89% for OLV-3100, 90% for N-BS, and 92% for Masimo Radical. Conclusion We found that the biases and precision with which to detect hypoxemia differed among the three pulse oximeters. To avoid hypoxemia, the optimal SpO2 should be determined for each pulse oximeter. PMID:25978517

Airway hyperresponsiveness to methacholine in 7-year-old children: sensitivity and specificity for pediatric allergist-diagnosed asthma.

PubMed

Carlsten, Chris; Dimich-Ward, Helen; Ferguson, Alexander; Becker, Allan; Dybuncio, Anne; Chan-Yeung, Moira

2011-02-01

The operating characteristics of PC(20) values used as cut-offs to define airway hyperresponsiveness, as it informs the diagnosis of asthma in children, are poorly understood. We examine data from a unique cohort to inform this concern. Determine the sensitivity and specificity of incremental PC(20) cut-offs for allergist-diagnosed asthma. Airway reactivity at age 7 was assessed in children within a birth cohort at high risk for asthma; PC(20) for methacholine was determined by standard technique including interpolation. The diagnosis of asthma was considered by the pediatric allergist without knowledge of the methacholine challenge results. Sensitivity and specificity were calculated using a cross-tabulation of asthma diagnosis with incremental PC(20) cut-off values, from 1.0 to 8.0 mg/ml, and plotted as receiver operator characteristic (ROC) curves. The "optimal" cut-off was defined as that PC(20) conferring maximal value for sensitivity plus specificity while the "balanced" cut-off was defined as that PC(20) at which sensitivity and specificity were most equal. 70/348 children (20.1%) were diagnosed with asthma. The optimal and balanced PC(20) cut-offs, both for all children and for females alone, were respectively 3 mg/ml (sensitivity 80.0%, specificity 49.1%) and 2 mg/ml (sensitivity 63.1%, specificity 64.7%). For males alone, the "optimal" and "balanced" PC(20) cut-offs were both 2 mg/ml. For this cohort of 7-year olds at high risk for asthma, methacholine challenge testing using a cut-off value of PC(20) 3 mg/ml conferred the maximal sum of specificity plus sensitivity. For contexts in which higher sensitivity or specificity is desired, other cut-offs may be preferred. Copyright © 2011 Wiley-Liss, Inc.

Accuracy of pulse oximeters in detecting hypoxemia in patients with chronic thromboembolic pulmonary hypertension.

PubMed

Kohyama, Tomoki; Moriyama, Kiyoshi; Kanai, Riichiro; Kotani, Mariko; Uzawa, Kohji; Satoh, Toru; Yorozu, Tomoko

2015-01-01

Pulse oximetry is routinely used to continuously and non-invasively monitor arterial oxygen saturation (SaO2). When oxygen saturation by pulse oximeter (SpO2) overestimates SaO2, hypoxemia may be overlooked. We compared the SpO2 - SaO2 differences among three pulse oximeters in patients with chronic thromboembolic pulmonary hypertension (CTEPH) who spent their daily lives in a poor oxygen state. This prospective observational study recruited 32 patients with CTEPH undergoing elective cardiac catheterization. As we collected arterial blood samples in the catheter laboratory, SpO2 values were simultaneously recorded. Three pulse oximeters were used on each patient, and SpO2 values were compared with oximetry readings using a blood gas analyzer. To determine the optimal SpO2 value by which to detect hypoxemia (SaO2≦90%), we generated receiver operating characteristic (ROC) curves for each pulse oximeter. The root mean square of each pulse oximeter was 1.79 (OLV-3100), 1.64 (N-BS), and 2.50 (Masimo Radical). The mean bias (SpO2 - SaO2) for the 90%-95% saturation range was significantly higher for Masimo Radical (0.19 +/- 1.78% [OLV-3100], 0.18 +/- 1.63% [N-BS], and 1.61 +/- 1.91% [Masimo Radical]; p<0.0001). The optimal SpO2 value to detect hypoxemia (SaO2≦90%) was 89% for OLV-3100, 90% for N-BS, and 92% for Masimo Radical. We found that the biases and precision with which to detect hypoxemia differed among the three pulse oximeters. To avoid hypoxemia, the optimal SpO2 should be determined for each pulse oximeter.

Determination of dosimetric quantities in pediatric abdominal computed tomography scans*

PubMed Central

Jornada, Tiago da Silva; da Silva, Teógenes Augusto

2014-01-01

Objective Aiming at contributing to the knowledge on doses in computed tomography (CT), this study has the objective of determining dosimetric quantities associated with pediatric abdominal CT scans, comparing the data with diagnostic reference levels (DRL). Materials and methods The study was developed with a Toshiba Asteion single-slice CT scanner and a GE BrightSpeed multi-slice CT unit in two hospitals. Measurements were performed with a pencil-type ionization chamber and a 16 cm-diameter polymethylmethacrylate trunk phantom. Results No significant difference was observed in the values for weighted air kerma index (CW), but the differences were relevant in values for volumetric air kerma index (CVOL), air kerma-length product (PKL,CT) and effective dose. Conclusion Only the CW values were lower than the DRL, suggesting that dose optimization might not be necessary. However, PKL,CT and effective dose values stressed that there still is room for reducing pediatric radiation doses. The present study emphasizes the importance of determining all dosimetric quantities associated with CT scans. PMID:25741103

Extrinsic and intrinsic index finger muscle attachments in an OpenSim upper-extremity model.

PubMed

Lee, Jong Hwa; Asakawa, Deanna S; Dennerlein, Jack T; Jindrich, Devin L

2015-04-01

Musculoskeletal models allow estimation of muscle function during complex tasks. We used objective methods to determine possible attachment locations for index finger muscles in an OpenSim upper-extremity model. Data-driven optimization algorithms, Simulated Annealing and Hook-Jeeves, estimated tendon locations crossing the metacarpophalangeal (MCP), proximal interphalangeal (PIP) and distal interphalangeal (DIP) joints by minimizing the difference between model-estimated and experimentally-measured moment arms. Sensitivity analysis revealed that multiple sets of muscle attachments with similar optimized moment arms are possible, requiring additional assumptions or data to select a single set of values. The most smooth muscle paths were assumed to be biologically reasonable. Estimated tendon attachments resulted in variance accounted for (VAF) between calculated moment arms and measured values of 78% for flex/extension and 81% for ab/adduction at the MCP joint. VAF averaged 67% at the PIP joint and 54% at the DIP joint. VAF values at PIP and DIP joints partially reflected the constant moment arms reported for muscles about these joints. However, all moment arm values found through optimization were non-linear and non-constant. Relationships between moment arms and joint angles were best described with quadratic equations for tendons at the PIP and DIP joints.

Minimizing metastatic risk in radiotherapy fractionation schedules

NASA Astrophysics Data System (ADS)

Badri, Hamidreza; Ramakrishnan, Jagdish; Leder, Kevin

2015-11-01

Metastasis is the process by which cells from a primary tumor disperse and form new tumors at distant anatomical locations. The treatment and prevention of metastatic cancer remains an extremely challenging problem. This work introduces a novel biologically motivated objective function to the radiation optimization community that takes into account metastatic risk instead of the status of the primary tumor. In this work, we consider the problem of developing fractionated irradiation schedules that minimize production of metastatic cancer cells while keeping normal tissue damage below an acceptable level. A dynamic programming framework is utilized to determine the optimal fractionation scheme. We evaluated our approach on a breast cancer case using the heart and the lung as organs-at-risk (OAR). For small tumor α /β values, hypo-fractionated schedules were optimal, which is consistent with standard models. However, for relatively larger α /β values, we found the type of schedule depended on various parameters such as the time when metastatic risk was evaluated, the α /β values of the OARs, and the normal tissue sparing factors. Interestingly, in contrast to standard models, hypo-fractionated and semi-hypo-fractionated schedules (large initial doses with doses tapering off with time) were suggested even with large tumor α/β values. Numerical results indicate the potential for significant reduction in metastatic risk.

Optimizing isothiocyanate formation during enzymatic glucosinolate breakdown by adjusting pH value, temperature and dilution in Brassica vegetables and Arabidopsis thaliana

NASA Astrophysics Data System (ADS)

Hanschen, Franziska S.; Klopsch, Rebecca; Oliviero, Teresa; Schreiner, Monika; Verkerk, Ruud; Dekker, Matthijs

2017-01-01

Consumption of glucosinolate-rich Brassicales vegetables is associated with a decreased risk of cancer with enzymatic hydrolysis of glucosinolates playing a key role. However, formation of health-promoting isothiocyanates is inhibited by the epithiospecifier protein in favour of nitriles and epithionitriles. Domestic processing conditions, such as changes in pH value, temperature or dilution, might also affect isothiocyanate formation. Therefore, the influences of these three factors were evaluated in accessions of Brassica rapa, Brassica oleracea, and Arabidopsis thaliana. Mathematical modelling was performed to determine optimal isothiocyanate formation conditions and to obtain knowledge on the kinetics of the reactions. At 22 °C and endogenous plant pH, nearly all investigated plants formed nitriles and epithionitriles instead of health-promoting isothiocyanates. Response surface models, however, clearly demonstrated that upon change in pH to domestic acidic (pH 4) or basic pH values (pH 8), isothiocyanate formation considerably increases. While temperature also affects this process, the pH value has the greatest impact. Further, a kinetic model showed that isothiocyanate formation strongly increases due to dilution. Finally, the results show that isothiocyanate intake can be strongly increased by optimizing the conditions of preparation of Brassicales vegetables.

The fully actuated traffic control problem solved by global optimization and complementarity

NASA Astrophysics Data System (ADS)

Ribeiro, Isabel M.; de Lurdes de Oliveira Simões, Maria

2016-02-01

Global optimization and complementarity are used to determine the signal timing for fully actuated traffic control, regarding effective green and red times on each cycle. The average values of these parameters can be used to estimate the control delay of vehicles. In this article, a two-phase queuing system for a signalized intersection is outlined, based on the principle of minimization of the total waiting time for the vehicles. The underlying model results in a linear program with linear complementarity constraints, solved by a sequential complementarity algorithm. Departure rates of vehicles during green and yellow periods were treated as deterministic, while arrival rates of vehicles were assumed to follow a Poisson distribution. Several traffic scenarios were created and solved. The numerical results reveal that it is possible to use global optimization and complementarity over a reasonable number of cycles and determine with efficiency effective green and red times for a signalized intersection.

An optimizing start-up strategy for a bio-methanator.

PubMed

Sbarciog, Mihaela; Loccufier, Mia; Vande Wouwer, Alain

2012-05-01

This paper presents an optimizing start-up strategy for a bio-methanator. The goal of the control strategy is to maximize the outflow rate of methane in anaerobic digestion processes, which can be described by a two-population model. The methodology relies on a thorough analysis of the system dynamics and involves the solution of two optimization problems: steady-state optimization for determining the optimal operating point and transient optimization. The latter is a classical optimal control problem, which can be solved using the maximum principle of Pontryagin. The proposed control law is of the bang-bang type. The process is driven from an initial state to a small neighborhood of the optimal steady state by switching the manipulated variable (dilution rate) from the minimum to the maximum value at a certain time instant. Then the dilution rate is set to the optimal value and the system settles down in the optimal steady state. This control law ensures the convergence of the system to the optimal steady state and substantially increases its stability region. The region of attraction of the steady state corresponding to maximum production of methane is considerably enlarged. In some cases, which are related to the possibility of selecting the minimum dilution rate below a certain level, the stability region of the optimal steady state equals the interior of the state space. Aside its efficiency, which is evaluated not only in terms of biogas production but also from the perspective of treatment of the organic load, the strategy is also characterized by simplicity, being thus appropriate for implementation in real-life systems. Another important advantage is its generality: this technique may be applied to any anaerobic digestion process, for which the acidogenesis and methanogenesis are, respectively, characterized by Monod and Haldane kinetics.

Sensitivity Analysis of Genetic Algorithm Parameters for Optimal Groundwater Monitoring Network Design

NASA Astrophysics Data System (ADS)

Abdeh-Kolahchi, A.; Satish, M.; Datta, B.

2004-05-01

A state art groundwater monitoring network design is introduced. The method combines groundwater flow and transport results with optimization Genetic Algorithm (GA) to identify optimal monitoring well locations. Optimization theory uses different techniques to find a set of parameter values that minimize or maximize objective functions. The suggested groundwater optimal monitoring network design is based on the objective of maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. The MODFLOW and MT3DMS models included as separate modules within the Groundwater Modeling System (GMS) are used to develop three dimensional groundwater flow and contamination transport simulation. The groundwater flow and contamination simulation results are introduced as input to the optimization model, using Genetic Algorithm (GA) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations. The groundwater monitoring network design model is used Genetic Algorithms with binary variables representing potential monitoring location. As the number of decision variables and constraints increase, the non-linearity of the objective function also increases which make difficulty to obtain optimal solutions. The genetic algorithm is an evolutionary global optimization technique, which is capable of finding the optimal solution for many complex problems. In this study, the GA approach capable of finding the global optimal solution to a groundwater monitoring network design problem involving 18.4X 1018 feasible solutions will be discussed. However, to ensure the efficiency of the solution process and global optimality of the solution obtained using GA, it is necessary that appropriate GA parameter values be specified. The sensitivity analysis of genetic algorithms parameters such as random number, crossover probability, mutation probability, and elitism are discussed for solution of monitoring network design.

Discrimination and prediction of the origin of Chinese and Korean soybeans using Fourier transform infrared spectrometry (FT-IR) with multivariate statistical analysis

PubMed Central

Lee, Byeong-Ju; Zhou, Yaoyao; Lee, Jae Soung; Shin, Byeung Kon; Seo, Jeong-Ah; Lee, Doyup; Kim, Young-Suk

2018-01-01

The ability to determine the origin of soybeans is an important issue following the inclusion of this information in the labeling of agricultural food products becoming mandatory in South Korea in 2017. This study was carried out to construct a prediction model for discriminating Chinese and Korean soybeans using Fourier-transform infrared (FT-IR) spectroscopy and multivariate statistical analysis. The optimal prediction models for discriminating soybean samples were obtained by selecting appropriate scaling methods, normalization methods, variable influence on projection (VIP) cutoff values, and wave-number regions. The factors for constructing the optimal partial-least-squares regression (PLSR) prediction model were using second derivatives, vector normalization, unit variance scaling, and the 4000–400 cm–1 region (excluding water vapor and carbon dioxide). The PLSR model for discriminating Chinese and Korean soybean samples had the best predictability when a VIP cutoff value was not applied. When Chinese soybean samples were identified, a PLSR model that has the lowest root-mean-square error of the prediction value was obtained using a VIP cutoff value of 1.5. The optimal PLSR prediction model for discriminating Korean soybean samples was also obtained using a VIP cutoff value of 1.5. This is the first study that has combined FT-IR spectroscopy with normalization methods, VIP cutoff values, and selected wave-number regions for discriminating Chinese and Korean soybeans. PMID:29689113

Optimization of processing parameters for the preparation of phytosterol microemulsions by the solvent displacement method.

PubMed

Leong, Wai Fun; Che Man, Yaakob B; Lai, Oi Ming; Long, Kamariah; Misran, Misni; Tan, Chin Ping

2009-09-23

The purpose of this study was to optimize the parameters involved in the production of water-soluble phytosterol microemulsions for use in the food industry. In this study, response surface methodology (RSM) was employed to model and optimize four of the processing parameters, namely, the number of cycles of high-pressure homogenization (1-9 cycles), the pressure used for high-pressure homogenization (100-500 bar), the evaporation temperature (30-70 degrees C), and the concentration ratio of microemulsions (1-5). All responses-particle size (PS), polydispersity index (PDI), and percent ethanol residual (%ER)-were well fit by a reduced cubic model obtained by multiple regression after manual elimination. The coefficient of determination (R(2)) and absolute average deviation (AAD) value for PS, PDI, and %ER were 0.9628 and 0.5398%, 0.9953 and 0.7077%, and 0.9989 and 1.0457%, respectively. The optimized processing parameters were 4.88 (approximately 5) homogenization cycles, homogenization pressure of 400 bar, evaporation temperature of 44.5 degrees C, and concentration ratio of microemulsions of 2.34 cycles (approximately 2 cycles) of high-pressure homogenization. The corresponding responses for the optimized preparation condition were a minimal particle size of 328 nm, minimal polydispersity index of 0.159, and <0.1% of ethanol residual. The chi-square test verified the model, whereby the experimental values of PS, PDI, and %ER agreed with the predicted values at a 0.05 level of significance.

Development and validation of optimal cut-off value in inter-arm systolic blood pressure difference for prediction of cardiovascular events.

PubMed

Hirono, Akira; Kusunose, Kenya; Kageyama, Norihito; Sumitomo, Masayuki; Abe, Masahiro; Fujinaga, Hiroyuki; Sata, Masataka

2018-01-01

An inter-arm systolic blood pressure difference (IAD) is associated with cardiovascular disease. The aim of this study was to develop and validate the optimal cut-off value of IAD as a predictor of major adverse cardiac events in patients with arteriosclerosis risk factors. From 2009 to 2014, 1076 patients who had at least one cardiovascular risk factor were included in the analysis. We defined 700 randomly selected patients as a development cohort to confirm that IAD was the predictor of cardiovascular events and to determine optimal cut-off value of IAD. Next, we validated outcomes in the remaining 376 patients as a validation cohort. The blood pressure (BP) of both arms measurements were done simultaneously using the ankle-brachial blood pressure index (ABI) form of automatic device. The primary endpoint was the cardiovascular event and secondary endpoint was the all-cause mortality. During a median period of 2.8 years, 143 patients reached the primary endpoint in the development cohort. In the multivariate Cox proportional hazards analysis, IAD was the strong predictor of cardiovascular events (hazard ratio: 1.03, 95% confidence interval: 1.01-1.05, p=0.005). The receiver operating characteristic curve revealed that 5mmHg was the optimal cut-off point of IAD to predict cardiovascular events (p<0.001). In the validation cohort, the presence of a large IAD (IAD ≥5mmHg) was significantly associated with the primary endpoint (p=0.021). IAD is significantly associated with future cardiovascular events in patients with arteriosclerosis risk factors. The optimal cut-off value of IAD is 5mmHg. Copyright © 2017 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks

NASA Astrophysics Data System (ADS)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2011-01-01

In this paper, we propose a scheme for the optimal allocation of power, source coding rate, and channel coding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower source coding rate, so they will be able to allocate a greater portion of the total available bit rate to channel coding. Stronger channel coding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channel coding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, source coding rate and channel coding rate for the nodes of the visual sensor network.

Optimal policy for profit maximising in an EOQ model under non-linear holding cost and stock-dependent demand rate

NASA Astrophysics Data System (ADS)

Pando, V.; García-Laguna, J.; San-José, L. A.

2012-11-01

In this article, we integrate a non-linear holding cost with a stock-dependent demand rate in a maximising profit per unit time model, extending several inventory models studied by other authors. After giving the mathematical formulation of the inventory system, we prove the existence and uniqueness of the optimal policy. Relying on this result, we can obtain the optimal solution using different numerical algorithms. Moreover, we provide a necessary and sufficient condition to determine whether a system is profitable, and we establish a rule to check when a given order quantity is the optimal lot size of the inventory model. The results are illustrated through numerical examples and the sensitivity of the optimal solution with respect to changes in some values of the parameters is assessed.

A Computationally Inexpensive Optimal Guidance via Radial-Basis-Function Neural Network for Autonomous Soft Landing on Asteroids

PubMed Central

Zhang, Peng; Liu, Keping; Zhao, Bo; Li, Yuanchun

2015-01-01

Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN) is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP). Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm. PMID:26367382

Applying a Dynamic Stomatal Optimization to Predict Shifts in the Functional Composition of Tropical Forests Under Increased Drought And CO2

NASA Astrophysics Data System (ADS)

Bartlett, M. K.; Detto, M.; Pacala, S. W.

2017-12-01

The accurate prediction of tropical forest carbon fluxes is key to forecasting global climate, but forest responses to projected increases in CO2 and drought are highly uncertain. Here we present a dynamic optimization that derives the trajectory of stomatal conductance (gs) during drought, a key source of model uncertainty, from plant and soil water relations and the carbon economy of the plant hydraulic system. This optimization scheme is novel in two ways. First, by accounting for the ability of capacitance (i.e., the release of water from plant storage tissue; C) to buffer evaporative water loss and maintain gs during drought, this optimization captures both drought tolerant and avoidant hydraulic strategies. Second, by determining the optimal trajectory of plant and soil water potentials, this optimization quantifies species' impacts on the water available to competing plants. These advances allowed us to apply this optimization across the range of physiology trait values observed in tropical species to evaluate shifts in the competitively optimal trait values, or evolutionarily stable hydraulic strategy (ESS), under increased drought and CO2. Increasing the length of the dry season shifted the ESS towards more drought tolerant, rather than avoidant, trait values, and these shifts were larger for longer individual drought periods (i.e., more consecutive days without rainfall), even if the total time spent in drought was the same. Concurrently doubling the CO2 level reduced the magnitude of these shifts and slightly favored drought avoidant strategies under wet conditions. Overall, these analyses predicted that short, frequent droughts would allow elevated CO2 to shift the functional composition in tropical forests towards more drought avoidant species, while infrequent but long drought periods would shift the ESS to more drought tolerant trait values, despite increased CO2. Overall, these analyses quantified the impact of physiology traits on plant performance and competitive ability, and provide a mechanistic, trait-based approach to predict shifts in the functional composition of tropical forests under projected climatic conditions.

Extreme Learning Machine and Particle Swarm Optimization in optimizing CNC turning operation

NASA Astrophysics Data System (ADS)

Janahiraman, Tiagrajah V.; Ahmad, Nooraziah; Hani Nordin, Farah

2018-04-01

The CNC machine is controlled by manipulating cutting parameters that could directly influence the process performance. Many optimization methods has been applied to obtain the optimal cutting parameters for the desired performance function. Nonetheless, the industry still uses the traditional technique to obtain those values. Lack of knowledge on optimization techniques is the main reason for this issue to be prolonged. Therefore, the simple yet easy to implement, Optimal Cutting Parameters Selection System is introduced to help the manufacturer to easily understand and determine the best optimal parameters for their turning operation. This new system consists of two stages which are modelling and optimization. In modelling of input-output and in-process parameters, the hybrid of Extreme Learning Machine and Particle Swarm Optimization is applied. This modelling technique tend to converge faster than other artificial intelligent technique and give accurate result. For the optimization stage, again the Particle Swarm Optimization is used to get the optimal cutting parameters based on the performance function preferred by the manufacturer. Overall, the system can reduce the gap between academic world and the industry by introducing a simple yet easy to implement optimization technique. This novel optimization technique can give accurate result besides being the fastest technique.

Development of genetic algorithm-based optimization module in WHAT system for hydrograph analysis and model application

NASA Astrophysics Data System (ADS)

Lim, Kyoung Jae; Park, Youn Shik; Kim, Jonggun; Shin, Yong-Chul; Kim, Nam Won; Kim, Seong Joon; Jeon, Ji-Hong; Engel, Bernard A.

2010-07-01

Many hydrologic and water quality computer models have been developed and applied to assess hydrologic and water quality impacts of land use changes. These models are typically calibrated and validated prior to their application. The Long-Term Hydrologic Impact Assessment (L-THIA) model was applied to the Little Eagle Creek (LEC) watershed and compared with the filtered direct runoff using BFLOW and the Eckhardt digital filter (with a default BFI max value of 0.80 and filter parameter value of 0.98), both available in the Web GIS-based Hydrograph Analysis Tool, called WHAT. The R2 value and the Nash-Sutcliffe coefficient values were 0.68 and 0.64 with BFLOW, and 0.66 and 0.63 with the Eckhardt digital filter. Although these results indicate that the L-THIA model estimates direct runoff reasonably well, the filtered direct runoff values using BFLOW and Eckhardt digital filter with the default BFI max and filter parameter values do not reflect hydrological and hydrogeological situations in the LEC watershed. Thus, a BFI max GA-Analyzer module (BFI max Genetic Algorithm-Analyzer module) was developed and integrated into the WHAT system for determination of the optimum BFI max parameter and filter parameter of the Eckhardt digital filter. With the automated recession curve analysis method and BFI max GA-Analyzer module of the WHAT system, the optimum BFI max value of 0.491 and filter parameter value of 0.987 were determined for the LEC watershed. The comparison of L-THIA estimates with filtered direct runoff using an optimized BFI max and filter parameter resulted in an R2 value of 0.66 and the Nash-Sutcliffe coefficient value of 0.63. However, L-THIA estimates calibrated with the optimized BFI max and filter parameter increased by 33% and estimated NPS pollutant loadings increased by more than 20%. This indicates L-THIA model direct runoff estimates can be incorrect by 33% and NPS pollutant loading estimation by more than 20%, if the accuracy of the baseflow separation method is not validated for the study watershed prior to model comparison. This study shows the importance of baseflow separation in hydrologic and water quality modeling using the L-THIA model.

Determination of the optimal area of waste incineration in a rotary kiln using a simulation model.

PubMed

Bujak, J

2015-08-01

The article presents a mathematical model to determine the flux of incinerated waste in terms of its calorific values. The model is applicable in waste incineration systems equipped with rotary kilns. It is based on the known and proven energy flux balances and equations that describe the specific losses of energy flux while considering the specificity of waste incineration systems. The model is universal as it can be used both for the analysis and testing of systems burning different types of waste (municipal, medical, animal, etc.) and for allowing the use of any kind of additional fuel. Types of waste incinerated and additional fuel are identified by a determination of their elemental composition. The computational model has been verified in three existing industrial-scale plants. Each system incinerated a different type of waste. Each waste type was selected in terms of a different calorific value. This allowed the full verification of the model. Therefore the model can be used to optimize the operation of waste incineration system both at the design stage and during its lifetime. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of the prognostic value of platelet to lymphocyte ratio in patients with hepatocellular carcinoma.

PubMed

Wang, Yuchen; Attar, Bashar M; Fuentes, Harry E; Jaiswal, Palashkumar; Tafur, Alfonso J

2017-12-01

Hepatocellular carcinoma (HCC) is increasingly common, potentially fatal cancer type globally. Platelet-lymphocyte ratio (PLR) as a biomarker for systemic inflammation has recently been recognized as a valuable prognostic marker in multiple cancer types. The aim of the present study was to assess the prognostic value of PLR in HCC patients and determine the optimal cut-off value for risk stratification. We retrospectively analyzed patients with diagnosis of HCC (screened by ICD-9 code, confirmed with radiographic examination and/or biopsy) at a large public hospital during 15 years (Jan 2000 through July 2015). PLR, among other serology laboratory values were collected at diagnosis of HCC. Its association with overall survival was evaluated with Cox proportional hazard model. Among 270 patients with HCC, 57 (21.1%) patients died within an average follow-up of 11.9 months. PLR at diagnosis was significantly different between survivors and deceased (128.9 vs. 186.7; P=0.003). In multivariate analysis, aspartate transaminase (AST) (HR 2.022, P<0.001) and PLR (HR 1.768, P=0.004) independently predicted mortality. The optimal cut-off value for PLR was determined to be 220 by receiver-operating characteristics curve, and high PLR group had significantly higher mortality (HR 3.42, P<0.001). Our results indicated that elevated PLR at diagnosis above 220 predicted poor prognosis in HCC patients. PLR is a low-cost and convenient tool, which may serve as a useful prognostic marker for HCC.

Non-invasive assessment of liver fibrosis using two-dimensional shear wave elastography in patients with autoimmune liver diseases

PubMed Central

Zeng, Jie; Huang, Ze-Ping; Zheng, Jian; Wu, Tao; Zheng, Rong-Qin

2017-01-01

AIM To determine the diagnostic accuracy of two-dimensional shear wave elastography (2D-SWE) for the non-invasive assessment of liver fibrosis in patients with autoimmune liver diseases (AILD) using liver biopsy as the reference standard. METHODS Patients with AILD who underwent liver biopsy and 2D-SWE were consecutively enrolled. Receiver operating characteristic (ROC) curves were constructed to assess the overall accuracy and to identify optimal cut-off values. RESULTS The characteristics of the diagnostic performance were determined for 114 patients with AILD. The areas under the ROC curves for significant fibrosis, severe fibrosis, and cirrhosis were 0.85, 0.85, and 0.86, respectively, and the optimal cut-off values associated with significant fibrosis (≥ F2), severe fibrosis (≥ F3), and cirrhosis (F4) were 9.7 kPa, 13.2 kPa and 16.3 kPa, respectively. 2D-SWE showed sensitivity values of 81.7% for significant fibrosis, 83.0% for severe fibrosis, and 87.0% for cirrhosis, and the respective specificity values were 81.3%, 74.6%, and 80.2%. The overall concordance rate of the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages was 53.5%. CONCLUSION 2D-SWE showed promising diagnostic performance for assessing liver fibrosis stages and exhibited high cut-off values in patients with AILD. Low overall concordance rate was observed in the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages. PMID:28765706

Non-invasive assessment of liver fibrosis using two-dimensional shear wave elastography in patients with autoimmune liver diseases.

PubMed

Zeng, Jie; Huang, Ze-Ping; Zheng, Jian; Wu, Tao; Zheng, Rong-Qin

2017-07-14

To determine the diagnostic accuracy of two-dimensional shear wave elastography (2D-SWE) for the non-invasive assessment of liver fibrosis in patients with autoimmune liver diseases (AILD) using liver biopsy as the reference standard. Patients with AILD who underwent liver biopsy and 2D-SWE were consecutively enrolled. Receiver operating characteristic (ROC) curves were constructed to assess the overall accuracy and to identify optimal cut-off values. The characteristics of the diagnostic performance were determined for 114 patients with AILD. The areas under the ROC curves for significant fibrosis, severe fibrosis, and cirrhosis were 0.85, 0.85, and 0.86, respectively, and the optimal cut-off values associated with significant fibrosis (≥ F2), severe fibrosis (≥ F3), and cirrhosis (F4) were 9.7 kPa, 13.2 kPa and 16.3 kPa, respectively. 2D-SWE showed sensitivity values of 81.7% for significant fibrosis, 83.0% for severe fibrosis, and 87.0% for cirrhosis, and the respective specificity values were 81.3%, 74.6%, and 80.2%. The overall concordance rate of the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages was 53.5%. 2D-SWE showed promising diagnostic performance for assessing liver fibrosis stages and exhibited high cut-off values in patients with AILD. Low overall concordance rate was observed in the liver stiffness measurements obtained using 2D-SWE vs fibrosis stages.

Newborn screening of glucose-6-phosphate dehydrogenase deficiency in Guangxi, China: determination of optimal cutoff value to identify heterozygous female neonates.

PubMed

Fu, Chunyun; Luo, Shiyu; Li, Qifei; Xie, Bobo; Yang, Qi; Geng, Guoxing; Lin, Caijuan; Su, Jiasun; Zhang, Yue; Wang, Jin; Qin, Zailong; Luo, Jingsi; Chen, Shaoke; Fan, Xin

2018-01-16

The aim of this study is to assess the disease incidence and mutation spectrum of glucose-6-phosphate dehydrogenase (G6PD) deficiency in Guangxi, China, and to determine an optimal cutoff value to identify heterozygous female neonates. A total of 130, 635 neonates were screened from the year of 2013 to 2017. Neonates suspected for G6PD deficiency were further analyzed by quantitatively enzymatic assay and G6PD mutation analysis. The overall incidence of G6PD deficiency was 7.28%. A total of 14 G6PD mutations were identified, and different mutations lead to varying levels of G6PD enzymatic activities. The best cut-off value of G6PD activity in male subjects is 2.2 U/g Hb, same as conventional setting. In female population, however, the cut-off value is found to be 2.8 U/g Hb (sensitivity: 97.5%, specificity: 87.7%, AUC: 0.964) to best discriminate between normal and heterozygotes, and 1.6 U/g Hb (sensitivity: 82.2%, specificity: 85.9%, AUC: 0.871) between heterozygotes and deficient subjects. In conclusion, we have conducted a comprehensive newborn screening of G6PD deficiency in a large cohort of population from Guangxi, China, and first established a reliable cut-off value of G6PD activity to distinguish heterozygous females from either normal or deficient subjects.

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.

Complex wave fields in the interacting one-dimensional Bose gas

NASA Astrophysics Data System (ADS)

Pietraszewicz, J.; Deuar, P.

2018-05-01

We study the temperature regimes of the one-dimensional interacting gas to determine when the matter wave (c-field) theory is, in fact, correct and usable. The judgment is made by investigating the level of discrepancy in many observables at once in comparison to the exact Yang-Yang theory. We also determine what cutoff maximizes the accuracy of such an approach. Results are given in terms of a bound on accuracy, as well as an optimal cutoff prescription. For a wide range of temperatures the optimal cutoff is independent of density or interaction strength and so its temperature-dependent form is suitable for many cloud shapes and, possibly, basis choices. However, this best global choice is higher in energy than most prior determinations. The high value is needed to obtain the correct kinetic energy, but does not detrimentally affect other observables.

Optimal Experimental Design for Model Discrimination

ERIC Educational Resources Information Center

Myung, Jay I.; Pitt, Mark A.

2009-01-01

Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it…

The Optimal Cut-Off Value of Neutrophil-to-Lymphocyte Ratio for Predicting Prognosis in Adult Patients with Henoch–Schönlein Purpura

PubMed Central

Park, Chan Hyuk; Han, Dong Soo; Jeong, Jae Yoon; Eun, Chang Soo; Yoo, Kyo-Sang; Jeon, Yong Cheol; Sohn, Joo Hyun

2016-01-01

Background The development of gastrointestinal (GI) bleeding and end-stage renal disease (ESRD) can be a concern in the management of Henoch–Schönlein purpura (HSP). We aimed to evaluate whether the neutrophil-to-lymphocyte ratio (NLR) is associated with the prognosis of adult patients with HSP. Methods Clinical data including the NLR of adult patients with HSP were retrospectively analyzed. Patients were classified into three groups as follows: (a) simple recovery, (b) wax & wane without GI bleeding, and (c) development of GI bleeding. The optimal cut-off value was determined using a receiver operating characteristics curve and the Youden index. Results A total of 66 adult patients were enrolled. The NLR was higher in the GI bleeding group than in the simple recovery or wax & wane group (simple recovery vs. wax & wane vs. GI bleeding; median [IQR], 2.32 [1.61–3.11] vs. 3.18 [2.16–3.71] vs. 7.52 [4.91–10.23], P<0.001). For the purpose of predicting simple recovery, the optimal cut-off value of NLR was 3.18, and the sensitivity and specificity were 74.1% and 75.0%, respectively. For predicting development of GI bleeding, the optimal cut-off value was 3.90 and the sensitivity and specificity were 87.5% and 88.6%, respectively. Conclusions The NLR is useful for predicting development of GI bleeding as well as simple recovery without symptom relapse. Two different cut-off values of NLR, 3.18 for predicting an easy recovery without symptom relapse and 3.90 for predicting GI bleeding can be used in adult patients with HSP. PMID:27073884

Artificial neural network modeling and optimization of ultrahigh pressure extraction of green tea polyphenols.

PubMed

Xi, Jun; Xue, Yujing; Xu, Yinxiang; Shen, Yuhong

2013-11-01

In this study, the ultrahigh pressure extraction of green tea polyphenols was modeled and optimized by a three-layer artificial neural network. A feed-forward neural network trained with an error back-propagation algorithm was used to evaluate the effects of pressure, liquid/solid ratio and ethanol concentration on the total phenolic content of green tea extracts. The neural network coupled with genetic algorithms was also used to optimize the conditions needed to obtain the highest yield of tea polyphenols. The obtained optimal architecture of artificial neural network model involved a feed-forward neural network with three input neurons, one hidden layer with eight neurons and one output layer including single neuron. The trained network gave the minimum value in the MSE of 0.03 and the maximum value in the R(2) of 0.9571, which implied a good agreement between the predicted value and the actual value, and confirmed a good generalization of the network. Based on the combination of neural network and genetic algorithms, the optimum extraction conditions for the highest yield of green tea polyphenols were determined as follows: 498.8 MPa for pressure, 20.8 mL/g for liquid/solid ratio and 53.6% for ethanol concentration. The total phenolic content of the actual measurement under the optimum predicated extraction conditions was 582.4 ± 0.63 mg/g DW, which was well matched with the predicted value (597.2mg/g DW). This suggests that the artificial neural network model described in this work is an efficient quantitative tool to predict the extraction efficiency of green tea polyphenols. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Multi-Objective Trajectory Optimization of a Hypersonic Reconnaissance Vehicle with Temperature Constraints

NASA Astrophysics Data System (ADS)

Masternak, Tadeusz J.

This research determines temperature-constrained optimal trajectories for a scramjet-based hypersonic reconnaissance vehicle by developing an optimal control formulation and solving it using a variable order Gauss-Radau quadrature collocation method with a Non-Linear Programming (NLP) solver. The vehicle is assumed to be an air-breathing reconnaissance aircraft that has specified takeoff/landing locations, airborne refueling constraints, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom scramjet aircraft model is adapted from previous work and includes flight dynamics, aerodynamics, and thermal constraints. Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and coverage of high-value targets. To solve the optimal control formulation, a MATLAB-based package called General Pseudospectral Optimal Control Software (GPOPS-II) is used, which transcribes continuous time optimal control problems into an NLP problem. In addition, since a mission profile can have varying vehicle dynamics and en-route imposed constraints, the optimal control problem formulation can be broken up into several "phases" with differing dynamics and/or varying initial/final constraints. Optimal trajectories are developed using several different performance costs in the optimal control formulation: minimum time, minimum time with control penalties, and maximum range. The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for larger-scale operational and campaign planning and execution.

C-tactile afferent stimulating touch carries a positive affective value.

PubMed

Pawling, Ralph; Cannon, Peter R; McGlone, Francis P; Walker, Susannah C

2017-01-01

The rewarding sensation of touch in affiliative interactions is hypothesized to be underpinned by a specialized system of nerve fibers called C-Tactile afferents (CTs), which respond optimally to slowly moving, gentle touch, typical of a caress. However, empirical evidence to support the theory that CTs encode socially relevant, rewarding tactile information in humans is currently limited. While in healthy participants, touch applied at CT optimal velocities (1-10cm/sec) is reliably rated as subjectively pleasant, neuronopathy patients lacking large myelinated afferents, but with intact C-fibres, report that the conscious sensation elicited by stimulation of CTs is rather vague. Given this weak perceptual impact the value of self-report measures for assessing the specific affective value of CT activating touch appears limited. Therefore, we combined subjective ratings of touch pleasantness with implicit measures of affective state (facial electromyography) and autonomic arousal (heart rate) to determine whether CT activation carries a positive affective value. We recorded the activity of two key emotion-relevant facial muscle sites (zygomaticus major-smile muscle, positive affect & corrugator supercilii-frown muscle, negative affect) while participants evaluated the pleasantness of experimenter administered stroking touch, delivered using a soft brush, at two velocities (CT optimal 3cm/sec & CT non-optimal 30cm/sec), on two skin sites (CT innervated forearm & non-CT innervated palm). On both sites, 3cm/sec stroking touch was rated as more pleasant and produced greater heart rate deceleration than 30cm/sec stimulation. However, neither self-report ratings nor heart rate responses discriminated stimulation on the CT innervated arm from stroking of the non-CT innervated palm. In contrast, significantly greater activation of the zygomaticus major (smiling muscle) was seen specifically to CT optimal, 3cm/sec, stroking on the forearm in comparison to all other stimuli. These results offer the first empirical evidence in humans that tactile stimulation that optimally activates CTs carries a positive affective valence that can be measured implicitly.

Standardization and validation of a cytometric bead assay to assess antibodies to multiple Plasmodium falciparum recombinant antigens.

PubMed

Ondigo, Bartholomew N; Park, Gregory S; Gose, Severin O; Ho, Benjamin M; Ochola, Lyticia A; Ayodo, George O; Ofulla, Ayub V; John, Chandy C

2012-12-21

Multiplex cytometric bead assay (CBA) have a number of advantages over ELISA for antibody testing, but little information is available on standardization and validation of antibody CBA to multiple Plasmodium falciparum antigens. The present study was set to determine optimal parameters for multiplex testing of antibodies to P. falciparum antigens, and to compare results of multiplex CBA to ELISA. Antibodies to ten recombinant P. falciparum antigens were measured by CBA and ELISA in samples from 30 individuals from a malaria endemic area of Kenya and compared to known positive and negative control plasma samples. Optimal antigen amounts, monoplex vs multiplex testing, plasma dilution, optimal buffer, number of beads required were assessed for CBA testing, and results from CBA vs. ELISA testing were compared. Optimal amounts for CBA antibody testing differed according to antigen. Results for monoplex CBA testing correlated strongly with multiplex testing for all antigens (r = 0.88-0.99, P values from <0.0001 - 0.004), and antibodies to variants of the same antigen were accurately distinguished within a multiplex reaction. Plasma dilutions of 1:100 or 1:200 were optimal for all antigens for CBA testing. Plasma diluted in a buffer containing 0.05% sodium azide, 0.5% polyvinylalcohol, and 0.8% polyvinylpyrrolidone had the lowest background activity. CBA median fluorescence intensity (MFI) values with 1,000 antigen-conjugated beads/well did not differ significantly from MFI with 5,000 beads/well. CBA and ELISA results correlated well for all antigens except apical membrane antigen-1 (AMA-1). CBA testing produced a greater range of values in samples from malaria endemic areas and less background reactivity for blank samples than ELISA. With optimization, CBA may be the preferred method of testing for antibodies to P. falciparum antigens, as CBA can test for antibodies to multiple recombinant antigens from a single plasma sample and produces a greater range of values in positive samples and lower background readings for blank samples than ELISA.

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

Firestone, Ryan; Marnay, Chris

The on-site generation of electricity can offer buildingowners and occupiers financial benefits as well as social benefits suchas reduced grid congestion, improved energy efficiency, and reducedgreenhouse gas emissions. Combined heat and power (CHP), or cogeneration,systems make use of the waste heat from the generator for site heatingneeds. Real-time optimal dispatch of CHP systems is difficult todetermine because of complicated electricity tariffs and uncertainty inCHP equipment availability, energy prices, and system loads. Typically,CHP systems use simple heuristic control strategies. This paper describesa method of determining optimal control in real-time and applies it to alight industrial site in San Diego, California, tomore » examine: 1) the addedbenefit of optimal over heuristic controls, 2) the price elasticity ofthe system, and 3) the site-attributable greenhouse gas emissions, allunder three different tariff structures. Results suggest that heuristiccontrols are adequate under the current tariff structure and relativelyhigh electricity prices, capturing 97 percent of the value of thedistributed generation system. Even more value could be captured bysimply not running the CHP system during times of unusually high naturalgas prices. Under hypothetical real-time pricing of electricity,heuristic controls would capture only 70 percent of the value ofdistributed generation.« less

GOCI image enhancement using an MTF compensation technique for coastal water applications.

PubMed

Oh, Eunsong; Choi, Jong-Kuk

2014-11-03

The Geostationary Ocean Color Imager (GOCI) is the first optical sensor in geostationary orbit for monitoring the ocean environment around the Korean Peninsula. This paper discusses on-orbit modulation transfer function (MTF) estimation with the pulse-source method and its compensation results for the GOCI. Additionally, by analyzing the relationship between the MTF compensation effect and the accuracy of the secondary ocean product, we confirmed the optimal MTF compensation parameter for enhancing image quality without variation in the accuracy. In this study, MTF assessment was performed using a natural target because the GOCI system has a spatial resolution of 500 m. For MTF compensation with the Wiener filter, we fitted a point spread function with a Gaussian curve controlled by a standard deviation value (σ). After a parametric analysis for finding the optimal degradation model, the σ value of 0.4 was determined to be an optimal indicator. Finally, the MTF value was enhanced from 0.1645 to 0.2152 without degradation of the accuracy of the ocean color product. Enhanced GOCI images by MTF compensation are expected to recognize small-scale ocean products in coastal areas with sharpened geometric performance.

A batch sliding window method for local singularity mapping and its application for geochemical anomaly identification

NASA Astrophysics Data System (ADS)

Xiao, Fan; Chen, Zhijun; Chen, Jianguo; Zhou, Yongzhang

2016-05-01

In this study, a novel batch sliding window (BSW) based singularity mapping approach was proposed. Compared to the traditional sliding window (SW) technique with disadvantages of the empirical predetermination of a fixed maximum window size and outliers sensitivity of least-squares (LS) linear regression method, the BSW based singularity mapping approach can automatically determine the optimal size of the largest window for each estimated position, and utilizes robust linear regression (RLR) which is insensitive to outlier values. In the case study, tin geochemical data in Gejiu, Yunnan, have been processed by BSW based singularity mapping approach. The results show that the BSW approach can improve the accuracy of the calculation of singularity exponent values due to the determination of the optimal maximum window size. The utilization of RLR method in the BSW approach can smoothen the distribution of singularity index values with few or even without much high fluctuate values looking like noise points that usually make a singularity map much roughly and discontinuously. Furthermore, the student's t-statistic diagram indicates a strong spatial correlation between high geochemical anomaly and known tin polymetallic deposits. The target areas within high tin geochemical anomaly could probably have much higher potential for the exploration of new tin polymetallic deposits than other areas, particularly for the areas that show strong tin geochemical anomalies whereas no tin polymetallic deposits have been found in them.

Optimal Energy Extraction From a Hot Water Geothermal Reservoir

NASA Astrophysics Data System (ADS)

Golabi, Kamal; Scherer, Charles R.; Tsang, Chin Fu; Mozumder, Sashi

1981-01-01

An analytical decision model is presented for determining optimal energy extraction rates from hot water geothermal reservoirs when cooled brine is reinjected into the hot water aquifer. This applied economic management model computes the optimal fluid pumping rate and reinjection temperature and the project (reservoir) life consistent with maximum present worth of the net revenues from sales of energy for space heating. The real value of product energy is assumed to increase with time, as is the cost of energy used in pumping the aquifer. The economic model is implemented by using a hydrothermal model that relates hydraulic pumping rate to the quality (temperature) of remaining heat energy in the aquifer. The results of a numerical application to space heating show that profit-maximizing extraction rate increases with interest (discount) rate and decreases as the rate of rise of real energy value increases. The economic life of the reservoir generally varies inversely with extraction rate. Results were shown to be sensitive to permeability, initial equilibrium temperature, well cost, and well life.

Application of response surface methodology for optimization of polygalacturonase production by Aspergillus niger.

PubMed

Yadav, Kaushlesh K; Garg, Neelima; Kumar, Devendra; Kumar, Sanjay; Singh, Achal; Muthukumar, M

2015-01-01

Polygalacturonase (PG) degrades pectin into D-galacturonic acid monomers and is used widely in food industry especially for juice clarification. In the present study,. fermentation conditions for polygalacturonase production by Asgergillus niger NAIMCCF-02958, using mango peel as substrate, were optimized using the 2(3) factorial design with central composite rotatable experimental design (CCRD) of response surface methodology (RSM). The maximum PG activity 723.66 U g(-1) was achieved under pH 4.0, temperature 30 degrees C and 2% inoculum by response surface curve. The experimental value of PG activity wkas higher 607.65 U g(-1) than the predicted value 511.75 U g(-1). Under the proposed optimized conditions, the determination coefficient (R2) was equal to 0.66 indicating that the model could explain 66% of the total variation as well as establish the relationship between the variables and the responses. ANOVA analysis and the three dimensional plots also confirmed interactions among the parameters.

Infinite capacity multi-server queue with second optional service channel

NASA Astrophysics Data System (ADS)

Ke, Jau-Chuan; Wu, Chia-Huang; Pearn, Wen Lea

2013-02-01

This paper deals with an infinite-capacity multi-server queueing system with a second optional service (SOS) channel. The inter-arrival times of arriving customers, the service times of the first essential service (FES) and the SOS channel are all exponentially distributed. A customer may leave the system after the FES channel with probability (1-θ), or at the completion of the FES may immediately require a SOS with probability θ (0 <= θ <= 1). The formulae for computing the rate matrix and stationary probabilities are derived by means of a matrix analytical approach. A cost model is developed to determine the optimal values of the number of servers and the two service rates, simultaneously, at the minimal total expected cost per unit time. Quasi-Newton method are employed to deal with the optimization problem. Under optimal operating conditions, numerical results are provided in which several system performance measures are calculated based on assumed numerical values of the system parameters.

The Contribution of Particle Swarm Optimization to Three-Dimensional Slope Stability Analysis

PubMed Central

A Rashid, Ahmad Safuan; Ali, Nazri

2014-01-01

Over the last few years, particle swarm optimization (PSO) has been extensively applied in various geotechnical engineering including slope stability analysis. However, this contribution was limited to two-dimensional (2D) slope stability analysis. This paper applied PSO in three-dimensional (3D) slope stability problem to determine the critical slip surface (CSS) of soil slopes. A detailed description of adopted PSO was presented to provide a good basis for more contribution of this technique to the field of 3D slope stability problems. A general rotating ellipsoid shape was introduced as the specific particle for 3D slope stability analysis. A detailed sensitivity analysis was designed and performed to find the optimum values of parameters of PSO. Example problems were used to evaluate the applicability of PSO in determining the CSS of 3D slopes. The first example presented a comparison between the results of PSO and PLAXI-3D finite element software and the second example compared the ability of PSO to determine the CSS of 3D slopes with other optimization methods from the literature. The results demonstrated the efficiency and effectiveness of PSO in determining the CSS of 3D soil slopes. PMID:24991652

The contribution of particle swarm optimization to three-dimensional slope stability analysis.

PubMed

Kalatehjari, Roohollah; Rashid, Ahmad Safuan A; Ali, Nazri; Hajihassani, Mohsen

2014-01-01

Over the last few years, particle swarm optimization (PSO) has been extensively applied in various geotechnical engineering including slope stability analysis. However, this contribution was limited to two-dimensional (2D) slope stability analysis. This paper applied PSO in three-dimensional (3D) slope stability problem to determine the critical slip surface (CSS) of soil slopes. A detailed description of adopted PSO was presented to provide a good basis for more contribution of this technique to the field of 3D slope stability problems. A general rotating ellipsoid shape was introduced as the specific particle for 3D slope stability analysis. A detailed sensitivity analysis was designed and performed to find the optimum values of parameters of PSO. Example problems were used to evaluate the applicability of PSO in determining the CSS of 3D slopes. The first example presented a comparison between the results of PSO and PLAXI-3D finite element software and the second example compared the ability of PSO to determine the CSS of 3D slopes with other optimization methods from the literature. The results demonstrated the efficiency and effectiveness of PSO in determining the CSS of 3D soil slopes.

Optimizing Extraction Conditions of Free and Bound Phenolic Compounds from Rice By-Products and Their Antioxidant Effects.

PubMed

Irakli, Maria; Kleisiaris, Fotis; Kadoglidou, Kalliopi; Katsantonis, Dimitrios

2018-06-13

Rice by-products are extensively abundant agricultural wastes from the rice industry. This study was designed to optimize experimental conditions for maximum recovery of free and bound phenolic compounds from rice by-products. Optimized conditions were determined using response surface methodology based on total phenolic content (TPC), ABTS radical scavenging activity and ferric reducing power (FRAP). A Box-Behnken design was used to investigate the effects of ethanol concentration, extraction time and temperature, and NaOH concentration, hydrolysis time and temperature for free and bound fractions, respectively. The optimal conditions for the free phenolics were 41⁻56%, 40 °C, 10 min, whereas for bound phenolics were 2.5⁻3.6 M, 80 °C, 120 min. Under these conditions free TPC, ABTS and FRAP values in the bran were approximately 2-times higher than in the husk. However, bound TPC and FRAP values in the husk were 1.9- and 1.2-times higher than those in the bran, respectively, while bran fraction observed the highest ABTS value. Ferulic acid was most evident in the bran, whereas p -coumaric acid was mostly found in the husk. Findings from this study demonstrates that rice by-products could be exploited as valuable sources of bioactive components that could be used as ingredients of functional food and nutraceuticals.

Dual-mode nested search method for categorical uncertain multi-objective optimization

NASA Astrophysics Data System (ADS)

Tang, Long; Wang, Hu

2016-10-01

Categorical multi-objective optimization is an important issue involved in many matching design problems. Non-numerical variables and their uncertainty are the major challenges of such optimizations. Therefore, this article proposes a dual-mode nested search (DMNS) method. In the outer layer, kriging metamodels are established using standard regular simplex mapping (SRSM) from categorical candidates to numerical values. Assisted by the metamodels, a k-cluster-based intelligent sampling strategy is developed to search Pareto frontier points. The inner layer uses an interval number method to model the uncertainty of categorical candidates. To improve the efficiency, a multi-feature convergent optimization via most-promising-area stochastic search (MFCOMPASS) is proposed to determine the bounds of objectives. Finally, typical numerical examples are employed to demonstrate the effectiveness of the proposed DMNS method.

Optimizing the Compressive Strength of Strain-Hardenable Stretch-Formed Microtruss Architectures

NASA Astrophysics Data System (ADS)

Yu, Bosco; Abu Samk, Khaled; Hibbard, Glenn D.

2015-05-01

The mechanical performance of stretch-formed microtrusses is determined by both the internal strut architecture and the accumulated plastic strain during fabrication. The current study addresses the question of optimization, by taking into consideration the interdependency between fabrication path, material properties and architecture. Low carbon steel (AISI1006) and aluminum (AA3003) material systems were investigated experimentally, with good agreement between measured values and the analytical model. The compressive performance of the microtrusses was then optimized on a minimum weight basis under design constraints such as fixed starting sheet thickness and final microtruss height by satisfying the Karush-Kuhn-Tucker condition. The optimization results were summarized as carpet plots in order to meaningfully visualize the interdependency between architecture, microstructural state, and mechanical performance, enabling material and processing path selection.

Fabrication of Thermoplastic Composite Laminates Having Film Interleaves By Automated Fiber Placement

NASA Technical Reports Server (NTRS)

Hulcher, A. B.; Tiwari, S. N.; Marchello, J. M.; Johnston, Norman J. (Technical Monitor)

2001-01-01

Experiments were carried out at the NASA Langley Research Center automated Fiber placement facility to determine an optimal process for the fabrication of composite materials having polymer film interleaves. A series of experiments was conducted to determine an optimal process for the composite prior to investigation of a process to fabricate laminates with polymer films. The results of the composite tests indicated that a well-consolidated, void-free laminate could be attained. Preliminary interleaf processing trials were then conducted to establish some broad guidelines for film processing. The primary finding of these initial studies was that a two-stage process was necessary in order to process these materials adequately. A screening experiment was then performed to determine the relative influence of the process variables on the quality of the film interface as determined by the wedge peel test method. Parameters that were found to be of minor influence on specimen quality were subsequently held at fixed values enabling a more rapid determination of an optimal process. Optimization studies were then performed by varying the remaining parameters at three film melt processing rates. The resulting peel data were fitted with quadratic response surfaces. Additional specimens were fabricated at levels of high peel strength as predicted by the regression models in an attempt to gage the accuracy of the predicted response and to assess the repeatability of the process. The overall results indicate that quality laminates having film interleaves can be successfully and repeatably fabricated by automated fiber placement.

Enhanced Production of Gamma-Aminobutyric Acid by Optimizing Culture Conditions of Lactobacillus brevis HYE1 Isolated from Kimchi, a Korean Fermented Food.

PubMed

Lim, Hee Seon; Cha, In-Tae; Roh, Seong Woon; Shin, Hae-Hun; Seo, Myung-Ji

2017-03-28

This study evaluated the effects of culture conditions, including carbon and nitrogen sources, L-monosodium glutamate (MSG), and initial pH, on gamma-aminobutyric acid (GABA) production by Lactobacillus brevis HYE1 isolated from kimchi, a Korean traditional fermented food. L. brevis HYE1 was screened by the production analysis of GABA and genetic analysis of the glutamate decarboxylase gene, resulting in 14.64 mM GABA after 48 h of cultivation in MRS medium containing 1% (w/v) MSG. In order to increase GABA production by L. brevis HYE1, the effects of carbon and nitrogen sources on GABA production were preliminarily investigated via one-factor-at-a-time optimization strategy. As the results, 2% maltose and 3% tryptone were determined to produce 17.93 mM GABA in modified MRS medium with 1% (w/v) MSG. In addition, the optimal MSG concentration and initial pH were determined to be 1% and 5.0, respectively, resulting in production of 18.97 mM GABA. Thereafter, response surface methodology (RSM) was applied to determine the optimal conditions of the above four factors. The results indicate that pH was the most significant factor for GABA production. The optimal culture conditions for maximum GABA production were also determined to be 2.14% (w/v) maltose, 4.01% (w/v) tryptone, 2.38% (w/v) MSG, and an initial pH of 4.74. In these conditions, GABA production by L. brevis HYE1 was predicted to be 21.44 mM using the RSM model. The experiment was performed under these optimized conditions, resulting in GABA production of 18.76 mM. These results show that the predicted and experimental values of GABA production are in good agreement.

Health versus money. Value judgments in the perspective of decision analysis.

PubMed

Thompson, M S

1983-01-01

An important, but largely uninvestigated, value trade-off balances marginal nonhealth consumption against marginal medical care. Benefit-cost analysts have traditionally, if not fully satisfactorily, dealt with this issue by valuing health gains by their effects on productivity. Cost-effectiveness analysts compare monetary and health effects and leave their relative valuations to decision makers. A decision-analytic model using the satisfaction or utility gained from nonhealth consumption and the level of health enables one to calculate willingness to pay--a theoretically superior way of assigning monetary values to effects for benefit-cost analysis-and to determine minimally acceptable cost-effectiveness ratios. Examples show how a decision-analytic model of utility can differentiate medical actions so essential that failure to take them would be considered negligent from actions so expensive as to be unjustifiable, and can help to determine optimal legal arrangements for compensation for medical malpractice.

Energy-Specific Optimization of Attenuation Thresholds for Low-Energy Virtual Monoenergetic Images in Renal Lesion Evaluation.

PubMed

Patel, Bhavik N; Farjat, Alfredo; Schabel, Christoph; Duvnjak, Petar; Mileto, Achille; Ramirez-Giraldo, Juan Carlos; Marin, Daniele

2018-05-01

The purpose of this study was to determine in vitro and in vivo the optimal threshold for renal lesion vascularity at low-energy (40-60 keV) virtual monoenergetic imaging. A rod simulating unenhanced renal parenchymal attenuation (35 HU) was fitted with a syringe containing water. Three iodinated solutions (0.38, 0.57, and 0.76 mg I/mL) were inserted into another rod that simulated enhanced renal parenchyma (180 HU). Rods were inserted into cylindric phantoms of three different body sizes and scanned with single- and dual-energy MDCT. In addition, 102 patients (32 men, 70 women; mean age, 66.8 ± 12.9 [SD] years) with 112 renal lesions (67 nonvascular, 45 vascular) measuring 1.1-8.9 cm underwent single-energy unenhanced and contrast-enhanced dual-energy CT. Optimal threshold attenuation values that differentiated vascular from nonvascular lesions at 40-60 keV were determined. Mean optimal threshold values were 30.2 ± 3.6 (standard error), 20.9 ± 1.3, and 16.1 ± 1.0 HU in the phantom, and 35.9 ± 3.6, 25.4 ± 1.8, and 17.8 ± 1.8 HU in the patients at 40, 50, and 60 keV. Sensitivity and specificity for the thresholds did not change significantly between low-energy and 70-keV virtual monoenergetic imaging (sensitivity, 87-98%; specificity, 90-91%). The AUC from 40 to 70 keV was 0.96 (95% CI, 0.93-0.99) to 0.98 (95% CI, 0.95-1.00). Low-energy virtual monoenergetic imaging at energy-specific optimized attenuation thresholds can be used for reliable characterization of renal lesions.

Properties of the optimal trajectories for coplanar, aeroassisted orbital transfer

NASA Technical Reports Server (NTRS)

Miele, A.; Wang, T.; Deaton, A. W.

1990-01-01

The optimization of trajectories for coplaner, aeroassisted orbital transfer (AOT) from a high Earth orbit (HEO) to a low Earth orbit (LEO) is examined. In particular, HEO can be a geosynchronous Earth orbit (GEO). It is assumed that the initial and final orbits are circular, that the gravitational field is central and is governed by the inverse square law, and that two impulses are employed, one at HEO exit and one at LEO entry. During the atmospheric pass, the trajectory is controlled via the lift coefficient in such a way that the total characteristic velocity is minimized. First, an ideal optimal trajectory is determined analytically for lift coefficient unbounded. This trajectory is called grazing trajectory, because the atmospheric pass is made by flying at constant altitude along the edge of the atmosphere until the excess velocity is depleted. For the grazing trajectory, the lift coefficient varies in such a way that the lift, the centrifugal force due to the Earth's curvature, the weight, and the Coriolis force due to the Earth's rotation are in static balance. Also, the grazing trajectory minimizes the total characteristic velocity and simultaneously nearly minimizes the peak values of the altitude drop, dynamic pressure, and heating rate. Next, starting from the grazing trajectory results, a real optimal trajectory is determined numerically for the lift coefficient bounded from both below and above. This trajectory is characterized by atmospheric penetration with the smallest possible entry angle, followed by flight at the lift coefficient lower bound. Consistently with the grazing trajectory behavior, the real optimal trajectory minimizes the total characteristic velocity and simultaneously nearly minimizes the peak values of the altitude drop, the dynamic pressure, and the heating rate.

Measurement of Young's modulus in the in vivo human vocal folds.

PubMed

Tran, Q T; Berke, G S; Gerratt, B R; Kreiman, J

1993-08-01

Currently, surgeons have no objective means to evaluate and optimize results of phonosurgery intraoperatively. Instead, they usually judge the vocal folds subjectively by visual inspection or by listening to the voice. This paper describes a new device that measures Young's (elastic) modulus values for the human vocal fold intraoperatively. Physiologically, the modulus of the vocal fold may be important in determining the nature of vocal fold vibration in normal and pathologic states. This study also reports the effect of recurrent laryngeal nerve stimulation on Young's modulus of the human vocal folds, measured by means of transcutaneous nerve stimulation techniques. Young's modulus increased with increases in current stimulation to the recurrent laryngeal nerve. Ultimately, Young's modulus values may assist surgeons in optimizing the results of various phonosurgeries.

Determination of the propellant combustion law under ballistic experiment conditions

NASA Astrophysics Data System (ADS)

Ishchenko, A. N.; Diachkovskii, A. S.; Zykova, A. I.; Kasimov, VZ; Samorokova, N. M.

2017-11-01

The main characteristics of ballistic experiment are the maximum pressure in the combustion chamber P max and the projectile velocity at the time of barrel leaving U M. During the work the burning law of the new high-energy fuel was determined in a ballistic experiment. This burning law was used for a parametric study of depending P max and U M from a powder charge mass and a traveling charge at initial temperature of + 20 °C was carried out. The optimal conditions for loading were obtained for improving the muzzle velocity by 14.9 %. Under optimal loading, there is defined the conditions, which is possible to get the greatest value muzzle velocity projectile at pressures up to 600 MPa.

Optimal control of the orientation and alignment of an asymmetric-top molecule with terahertz and laser pulses

NASA Astrophysics Data System (ADS)

Coudert, L. H.

2018-03-01

Quantum optimal control theory is applied to determine numerically the terahertz and nonresonant laser pulses leading, respectively, to the highest degree of orientation and alignment of the asymmetric-top H2S molecule. The optimized terahertz pulses retrieved for temperatures of zero and 50 K lead after 50 ps to an orientation with ⟨ΦZx⟩ = 0.959 73 and ⟨⟨ΦZx⟩⟩ = 0.742 30, respectively. For the zero temperature, the orientation is close to its maximum theoretical value; for the higher temperature, it is below the maximum theoretical value. The mechanism by which the terahertz pulse populates high lying rotational levels is elucidated. The 5 ps long optimized laser pulse calculated for a zero temperature leads to an alignment with ⟨ΦZy 2 ⟩ =0.944 16 and consists of several kick pulses with a duration of ≈0.1 ps. It is found that the timing of these kick pulses is such that it leads to an increase of the rotational energy of the molecule. The optimized laser pulse retrieved for a temperature of 20 K is 6 ps long and yields a lower alignment with ⟨⟨ΦZy 2 ⟩ ⟩ =0.717 20 .

A four parameter optimization and troubleshooting of a RPLC - charged aerosol detection stability indicating method for determination of S-lysophosphatidylcholines in a phospholipid formulation.

PubMed

Tam, James; Ahmad, Imad A Haidar; Blasko, Andrei

2018-06-05

A four parameter optimization of a stability indicating method for non-chromophoric degradation products of 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), 1-stearoyl-sn-glycero-3-phosphocholine and 2-stearoyl-sn-glycero-3-phosphocholine was achieved using a reverse phase liquid chromatography-charged aerosol detection (RPLC-CAD) technique. Using the hydrophobic subtraction model of selectivity, a core-shell, polar embedded RPLC column was selected followed by gradient-temperature optimization, resulting in ideal relative peak placements for a robust, stability indicating separation. The CAD instrument parameters, power function value (PFV) and evaporator temperature were optimized for lysophosphatidylcholines to give UV absorbance detector-like linearity performance within a defined concentration range. The two lysophosphatidylcholines gave the same response factor in the selected conditions. System specific power function values needed to be set for the two RPLC-CAD instruments used. A custom flow-divert profile, sending only a portion of the column effluent to the detector, was necessary to mitigate detector response drifting effects. The importance of the PFV optimization for each instrument of identical build and how to overcome recovery issues brought on by the matrix effects from the lipid-RP stationary phase interaction is reported. Copyright © 2018 Elsevier B.V. All rights reserved.

Influence of optimized leading-edge deflection and geometric anhedral on the low-speed aerodynamic characteristics of a low-aspect-ratio highly swept arrow-wing configuration. [langley 7 by 10 foot tunnel

NASA Technical Reports Server (NTRS)

Coe, P. L., Jr.; Huffman, J. K.

1979-01-01

An investigation conducted in the Langley 7 by 10 foot tunnel to determine the influence of an optimized leading-edge deflection on the low speed aerodynamic performance of a configuration with a low aspect ratio, highly swept wing. The sensitivity of the lateral stability derivative to geometric anhedral was also studied. The optimized leading edge deflection was developed by aligning the leading edge with the incoming flow along the entire span. Owing to spanwise variation of unwash, the resulting optimized leading edge was a smooth, continuously warped surface for which the deflection varied from 16 deg at the side of body to 50 deg at the wing tip. For the particular configuration studied, levels of leading-edge suction on the order of 90 percent were achieved. The results of tests conducted to determine the sensitivity of the lateral stability derivative to geometric anhedral indicate values which are in reasonable agreement with estimates provided by simple vortex-lattice theories.

Optimal waist circumference cut-off values for predicting cardiovascular risk factors in a multi-ethnic Malaysian population.

PubMed

Cheong, Kee C; Ghazali, Sumarni M; Hock, Lim K; Yusoff, Ahmad F; Selvarajah, Sharmini; Haniff, Jamaiyah; Zainuddin, Ahmad Ali; Ying, Chan Y; Lin, Khor G; Rahman, Jamalludin A; Shahar, Suzana; Mustafa, Amal N

2014-01-01

Previous studies have proposed the lower waist circumference (WC) cutoffs be used for defining abdominal obesity in Asian populations. To determine the optimal cut-offs of waist circumference (WC) in predicting cardiovascular (CV) risk factors in the multi-ethnic Malaysian population. We analysed data from 32,703 respondents (14,980 men and 17,723 women) aged 18 years and above who participated in the Third National Health and Morbidity Survey in 2006. Gender-specific logistic regression analyses were used to examine associations between WC and three CV risk factors (diabetes mellitus, hypertension, and hypercholesterolemia). The Receiver Operating Characteristic (ROC) curves were used to determine the cut-off values of WC with optimum sensitivity and specificity for detecting these CV risk factors. The odds ratio for having diabetes mellitus, hypertension, and hypercholesterolemia, or at least one of these risks, increased significantly as the WC cut-off point increased. Optimal WC cut-off values for predicting the presence of diabetes mellitus, hypertension, hypercholesterolemia and at least one of the three CV risk factors varied from 81.4 to 85.5 cm for men and 79.8 to 80.7 cm for women. Our findings indicate that WC cut-offs of 81 cm for men and 80 cm for women are appropriate for defining abdominal obesity and for recommendation to undergo cardiovascular risk screening and weight management in the Malaysian adult population. © 2014 Asian Oceanian Association for the Study of Obesity . Published by Elsevier Ltd. All rights reserved.

Optimization of Progressive Freeze Concentration on Apple Juice via Response Surface Methodology

NASA Astrophysics Data System (ADS)

Samsuri, S.; Amran, N. A.; Jusoh, M.

2018-05-01

In this work, a progressive freeze concentration (PFC) system was developed to concentrate apple juice and was optimized by response surface methodology (RSM). The effects of various operating conditions such as coolant temperature, circulation flowrate, circulation time and shaking speed to effective partition constant (K) were investigated. Five different level of central composite design (CCD) was employed to search for optimal concentration of concentrated apple juice. A full quadratic model for K was established by using method of least squares. A coefficient of determination (R2) of this model was found to be 0.7792. The optimum conditions were found to be coolant temperature = -10.59 °C, circulation flowrate = 3030.23 mL/min, circulation time = 67.35 minutes and shaking speed = 30.96 ohm. A validation experiment was performed to evaluate the accuracy of the optimization procedure and the best K value of 0.17 was achieved under the optimized conditions.

Use of principle velocity patterns in the analysis of structural acoustic optimization.

PubMed

Johnson, Wayne M; Cunefare, Kenneth A

2007-02-01

This work presents an application of principle velocity patterns in the analysis of the structural acoustic design optimization of an eight ply composite cylindrical shell. The approach consists of performing structural acoustic optimizations of a composite cylindrical shell subject to external harmonic monopole excitation. The ply angles are used as the design variables in the optimization. The results of the ply angle design variable formulation are interpreted using the singular value decomposition of the interior acoustic potential energy. The decomposition of the acoustic potential energy provides surface velocity patterns associated with lower levels of interior noise. These surface velocity patterns are shown to correspond to those from the structural acoustic optimization results. Thus, it is demonstrated that the capacity to design multi-ply composite cylinders for quiet interiors is determined by how well the cylinder be can designed to exhibit particular surface velocity patterns associated with lower noise levels.

Mechanical design optimization of bioabsorbable fixation devices for bone fractures.

PubMed

Lovald, Scott T; Khraishi, Tariq; Wagner, Jon; Baack, Bret

2009-03-01

Bioabsorbable bone plates can eliminate the necessity for a permanent implant when used to fixate fractures of the human mandible. They are currently not in widespread use because of the low strength of the materials and the requisite large volume of the resulting bone plate. The aim of the current study was to discover a minimally invasive bioabsorbable bone plate design that can provide the same mechanical stability as a standard titanium bone plate. A finite element model of a mandible with a fracture in the body region is subjected to bite loads that are common to patients postsurgery. The model is used first to determine benchmark stress and strain values for a titanium plate. These values are then set as the limits within which the bioabsorbable bone plate must comply. The model is then modified to consider a bone plate made of the polymer poly-L/DL-lactide 70/30. An optimization routine is run to determine the smallest volume of bioabsorbable bone plate that can perform and a titanium bone plate when fixating fractures of this considered type. Two design parameters are varied for the bone plate design during the optimization analysis. The analysis determined that a strut style poly-L-lactide-co-DL-lactide plate of 690 mm2 can provide as much mechanical stability as a similar titanium design structure of 172 mm2. The model has determined a bioabsorbable bone plate design that is as strong as a titanium plate when fixating fractures of the load-bearing mandible. This is an intriguing outcome, considering that the polymer material has only 6% of the stiffness of titanium.

Near-Infrared Spectroscopy Assay of Key Quality-Indicative Ingredients of Tongkang Tablets.

PubMed

Pan, Wenjie; Ma, Jinfang; Xiao, Xue; Huang, Zhengwei; Zhou, Huanbin; Ge, Fahuan; Pan, Xin

2017-04-01

The objective of this paper is to develop an easy and fast near-infrared spectroscopy (NIRS) assay for the four key quality-indicative active ingredients of Tongkang tablets by comparing the true content of the active ingredients measured by high performance liquid chromatography (HPLC) and the NIRS data. The HPLC values for the active ingredients content of Cimicifuga glycoside, calycosin glucoside, 5-O-methylvisamminol and hesperidin in Tongkang tablets were set as reference values. The NIRS raw spectra of Tongkang tablets were processed using first-order convolution method. The iterative optimization method was chosen to optimize the band for Cimicifuga glycoside and 5-O-methylvisamminol, and correlation coefficient method was used to determine the optimal band of calycosin glucoside and hesperidin. A near-infrared quantitative calibration model was established for each quality-indicative ingredient by partial least-squares method on the basis of the contents detected by HPLC and the obtained NIRS spectra. The correlation coefficient R 2 values of the four models of Cimicifuga glycoside, calycosin glucoside, 5-O-methylvisamminol and hesperidin were 0.9025, 0.8582, 0.9250, and 0.9325, respectively. It was demonstrated that the accuracy of the validation values was approximately 90% by comparison of the predicted results from NIRS models and the HPLC true values, which suggested that NIRS assay was successfully established and validated. It was expected that the quantitative analysis models of the four indicative ingredients could be used to rapidly perform quality control in industrial production of Tongkang tablets.

Methods for recalibration of mass spectrometry data

DOEpatents

Tolmachev, Aleksey V [Richland, WA; Smith, Richard D [Richland, WA

2009-03-03

Disclosed are methods for recalibrating mass spectrometry data that provide improvement in both mass accuracy and precision by adjusting for experimental variance in parameters that have a substantial impact on mass measurement accuracy. Optimal coefficients are determined using correlated pairs of mass values compiled by matching sets of measured and putative mass values that minimize overall effective mass error and mass error spread. Coefficients are subsequently used to correct mass values for peaks detected in the measured dataset, providing recalibration thereof. Sub-ppm mass measurement accuracy has been demonstrated on a complex fungal proteome after recalibration, providing improved confidence for peptide identifications.

[On the problems of the evolutionary optimization of life history. II. To justification of optimization criterion for nonlinear Leslie model].

PubMed

Pasekov, V P

2013-03-01

The paper considers the problems in the adaptive evolution of life-history traits for individuals in the nonlinear Leslie model of age-structured population. The possibility to predict adaptation results as the values of organism's traits (properties) that provide for the maximum of a certain function of traits (optimization criterion) is studied. An ideal criterion of this type is Darwinian fitness as a characteristic of success of an individual's life history. Criticism of the optimization approach is associated with the fact that it does not take into account the changes in the environmental conditions (in a broad sense) caused by evolution, thereby leading to losses in the adequacy of the criterion. In addition, the justification for this criterion under stationary conditions is not usually rigorous. It has been suggested to overcome these objections in terms of the adaptive dynamics theory using the concept of invasive fitness. The reasons are given that favor the application of the average number of offspring for an individual, R(L), as an optimization criterion in the nonlinear Leslie model. According to the theory of quantitative genetics, the selection for fertility (that is, for a set of correlated quantitative traits determined by both multiple loci and the environment) leads to an increase in R(L). In terms of adaptive dynamics, the maximum R(L) corresponds to the evolutionary stability and, in certain cases, convergent stability of the values for traits. The search for evolutionarily stable values on the background of limited resources for reproduction is a problem of linear programming.

Shelf-life prediction of canned "nasi uduk" using accelerated shelf-life test (ASLT) - Arrhenius model

NASA Astrophysics Data System (ADS)

Kurniadi, Muhamad; Salam, Nur; Kusumaningrum, Annisa; Nursiwi, Asri; Angwar, Mukhamad; Susanto, Agus; Nurhikmat, Asep; Triwiyono, Frediansyah, Andri

2017-01-01

"Nasi Uduk" is one of the Indonesian traditional food made from rice, steamed with coconut milk and seasoning. For optimizing shelf-life, canned "nasi uduk" for military and disaster-response ration, was packed using cylindrical cans of 72,63 × 53,04 mm (Ø × h) in size. One of the important aspects on quality assessment of preserved product was its rancidity. The aim of this research was to determine shelf-life of canned "nasi uduk" using ASLT method of Arrhenius model. Storage temperatures set up at 35, 45 and 55°C for 35 days. Optimization of sterilization process was conducted to achieve the optimum conditions of sterilization. Target lethality value (Fo), microorganism total plate count (TPC) and rancidity levels (TBA) were used as parameters in this research. The results showed that the optimum sterilization conditions were 121 °C for 20 minutes, TPC value of 9.5 × 101 CFU/ml and Fo value 4.14 minutes. Predicted shelf-life of canned "nasi uduk" was 9.6 months which was average TBA value still bellow of the critical point.

Balancing income and cost in red deer management.

PubMed

Skonhoft, Anders; Veiberg, Vebjørn; Gauteplass, Asle; Olaussen, Jon Olaf; Meisingset, Erling L; Mysterud, Atle

2013-01-30

This paper presents a bioeconomic analysis of a red deer population within a Norwegian institutional context. This population is managed by a well-defined manager, typically consisting of many landowners operating in a cooperative manner, with the goal of maximizing the present-value hunting related income while taking browsing and grazing damages into account. The red deer population is structured in five categories of animals (calves, female and male yearlings, adult females and adult males). It is shown that differences in the per-animal meat values and survival rates ('biological discounted' values) are instrumental in determining the optimal harvest composition. Fertility plays no direct role. It is argued that this is a general result working in stage-structured models with harvest values. In the numerical illustration it is shown that the optimal harvest pattern stays quite stable under various parameter changes. It is revealed which parameters and harvest restrictions that is most important. We also show that the current harvest pattern involves too much yearling harvest compared with the economically efficient level. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

Weighted optimization of irradiance for photodynamic therapy of port wine stains

NASA Astrophysics Data System (ADS)

He, Linhuan; Zhou, Ya; Hu, Xiaoming

2016-10-01

Planning of irradiance distribution (PID) is one of the foremost factors for on-demand treatment of port wine stains (PWS) with photodynamic therapy (PDT). A weighted optimization method for PID was proposed according to the grading of PWS with a three dimensional digital illumination instrument. Firstly, the point clouds of lesions were filtered to remove the error or redundant points, the triangulation was carried out and the lesion was divided into small triangular patches. Secondly, the parameters such as area, normal vector and orthocenter for optimization of each triangular patch were calculated, and the weighted coefficients were determined by the erythema indexes and areas of patches. Then, the optimization initial point was calculated based on the normal vectors and orthocenters to optimize the light direction. In the end, the irradiation can be optimized according to cosine values of irradiance angles and weighted coefficients. Comparing the irradiance distribution before and after optimization, the proposed weighted optimization method can make the irradiance distribution match better with the characteristics of lesions, and has the potential to improve the therapeutic efficacy.

Prognostic Value of the Amount of Bleeding After Aneurysmal Subarachnoid Hemorrhage: A Quantitative Volumetric Study.

PubMed

Lagares, Alfonso; Jiménez-Roldán, Luis; Gomez, Pedro A; Munarriz, Pablo M; Castaño-León, Ana M; Cepeda, Santiago; Alén, José F

2015-12-01

Quantitative estimation of the hemorrhage volume associated with aneurysm rupture is a new tool of assessing prognosis. To determine the prognostic value of the quantitative estimation of the amount of bleeding after aneurysmal subarachnoid hemorrhage, as well the relative importance of this factor related to other prognostic indicators, and to establish a possible cut-off value of volume of bleeding related to poor outcome. A prospective cohort of 206 patients consecutively admitted with the diagnosis of aneurysmal subarachnoid hemorrhage to Hospital 12 de Octubre were included in the study. Subarachnoid, intraventricular, intracerebral, and total bleeding volumes were calculated using analytic software. For assessing factors related to prognosis, univariate and multivariate analysis (logistic regression) were performed. The relative importance of factors in determining prognosis was established by calculating their proportion of explained variation. Maximum Youden index was calculated to determine the optimal cut point for subarachnoid and total bleeding volume. Variables independently related to prognosis were clinical grade at admission, age, and the different bleeding volumes. The proportion of variance explained is higher for subarachnoid bleeding. The optimal cut point related to poor prognosis is a volume of 20 mL both for subarachnoid and total bleeding. Volumetric measurement of subarachnoid or total bleeding volume are both independent prognostic factors in patients with aneurysmal subarachnoid hemorrhage. A volume of more than 20 mL of blood in the initial noncontrast computed tomography is related to a clear increase in poor outcome risk. : aSAH, aneurysmal subarachnoid hemorrhage.

Dimensional optimization of nanowire--complementary metal oxide--semiconductor inverter.

PubMed

Hashim, Yasir; Sidek, Othman

2013-01-01

This study is the first to demonstrate dimensional optimization of nanowire-complementary metal-oxide-semiconductor inverter. Noise margins and inflection voltage of transfer characteristics are used as limiting factors in this optimization. Results indicate that optimization depends on both dimensions ratio and digital voltage level (Vdd). Diameter optimization reveals that when Vdd increases, the optimized value of (Dp/Dn) decreases. Channel length optimization results show that when Vdd increases, the optimized value of Ln decreases and that of (Lp/Ln) increases. Dimension ratio optimization reveals that when Vdd increases, the optimized value of Kp/Kn decreases, and silicon nanowire transistor with suitable dimensions (higher Dp and Ln with lower Lp and Dn) can be fabricated.

School Cost Functions: A Meta-Regression Analysis

ERIC Educational Resources Information Center

Colegrave, Andrew D.; Giles, Margaret J.

2008-01-01

The education cost literature includes econometric studies attempting to determine economies of scale, or estimate an optimal school or district size. Not only do their results differ, but the studies use dissimilar data, techniques, and models. To derive value from these studies requires that the estimates be made comparable. One method to do…

Conversion of canola meal into a high-protein feed additive via solid-state fungal incubation process

USDA-ARS?s Scientific Manuscript database

The study goal was to determine the optimal fungal culture to reduce glucosinolates (GLS), fiber, and residual sugars while increasing the protein content and nutritional value of canola meal. Solid-state incubation conditions were used to enhance filamentous growth of the fungi. Flask trials were p...

40 CFR 91.316 - Hydrocarbon analyzer calibration.

Code of Federal Regulations, 2014 CFR

2014-07-01

... deviation from a least-squares best-fit straight line is two percent or less of the value at each data point... exceeds two percent at any point, use the best-fit non-linear equation which represents the data to within two percent of each test point to determine concentration. (d) Oxygen interference optimization...

40 CFR 90.316 - Hydrocarbon analyzer calibration.

Code of Federal Regulations, 2012 CFR

2012-07-01

... from a least-squares best-fit straight line is two percent or less of the value at each data point... exceeds two percent at any point, use the best-fit non-linear equation which represents the data to within two percent of each test point to determine concentration. (d) Oxygen interference optimization. Prior...

40 CFR 90.316 - Hydrocarbon analyzer calibration.

Code of Federal Regulations, 2013 CFR

2013-07-01

... from a least-squares best-fit straight line is two percent or less of the value at each data point... exceeds two percent at any point, use the best-fit non-linear equation which represents the data to within two percent of each test point to determine concentration. (d) Oxygen interference optimization. Prior...

40 CFR 90.316 - Hydrocarbon analyzer calibration.

Code of Federal Regulations, 2014 CFR

2014-07-01

... from a least-squares best-fit straight line is two percent or less of the value at each data point... exceeds two percent at any point, use the best-fit non-linear equation which represents the data to within two percent of each test point to determine concentration. (d) Oxygen interference optimization. Prior...

40 CFR 91.316 - Hydrocarbon analyzer calibration.

Code of Federal Regulations, 2012 CFR

2012-07-01

... deviation from a least-squares best-fit straight line is two percent or less of the value at each data point... exceeds two percent at any point, use the best-fit non-linear equation which represents the data to within two percent of each test point to determine concentration. (d) Oxygen interference optimization...

40 CFR 91.316 - Hydrocarbon analyzer calibration.

Code of Federal Regulations, 2013 CFR

2013-07-01

... deviation from a least-squares best-fit straight line is two percent or less of the value at each data point... exceeds two percent at any point, use the best-fit non-linear equation which represents the data to within two percent of each test point to determine concentration. (d) Oxygen interference optimization...

The Functional Movement Screen and Injury Risk: Association and Predictive Value in Active Men.

PubMed

Bushman, Timothy T; Grier, Tyson L; Canham-Chervak, Michelle; Anderson, Morgan K; North, William J; Jones, Bruce H

2016-02-01

The Functional Movement Screen (FMS) is a series of 7 tests used to assess the injury risk in active populations. To determine the association of the FMS with the injury risk, assess predictive values, and identify optimal cut points using 3 injury types. Cohort study; Level of evidence, 2. Physically active male soldiers aged 18 to 57 years (N = 2476) completed the FMS. Demographic and fitness data were collected by survey. Medical record data for overuse injuries, traumatic injuries, and any injury 6 months after the FMS assessment were obtained. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated along with the receiver operating characteristic (ROC) to determine the area under the curve (AUC) and identify optimal cut points for the risk assessment. Risks, risk ratios (RRs), odds ratios (ORs), and 95% CIs were calculated to assess injury risks. Soldiers who scored ≤14 were at a greater risk for injuries compared with those who scored >14 using the composite score for overuse injuries (RR, 1.84; 95% CI, 1.63-2.09), traumatic injuries (RR, 1.26; 95% CI, 1.03-1.54), and any injury (RR, 1.60; 95% CI, 1.45-1.77). When controlling for other known injury risk factors, multivariate logistic regression analysis identified poor FMS performance (OR [score ≤14/19-21], 2.00; 95% CI, 1.42-2.81) as an independent risk factor for injuries. A cut point of ≤14 registered low measures of predictive value for all 3 injury types (sensitivity, 28%-37%; PPV, 19%-52%; AUC, 54%-61%). Shifting the injury risk cut point of ≤14 to the optimal cut points indicated by the ROC did not appreciably improve sensitivity or the PPV. Although poor FMS performance was associated with a higher risk of injuries, it displayed low sensitivity, PPV, and AUC. On the basis of these findings, the use of the FMS to screen for the injury risk is not recommended in this population because of the low predictive value and misclassification of the injury risk. © 2015 The Author(s).

Photometric method for determination of acidity constants through integral spectra analysis

NASA Astrophysics Data System (ADS)

Zevatskiy, Yuriy Eduardovich; Ruzanov, Daniil Olegovich; Samoylov, Denis Vladimirovich

2015-04-01

An express method for determination of acidity constants of organic acids, based on the analysis of the integral transmittance vs. pH dependence is developed. The integral value is registered as a photocurrent of photometric device simultaneously with potentiometric titration. The proposed method allows to obtain pKa using only simple and low-cost instrumentation. The optical part of the experimental setup has been optimized through the exclusion of the monochromator device. Thus it only takes 10-15 min to obtain one pKa value with the absolute error of less than 0.15 pH units. Application limitations and reliability of the method have been tested for a series of organic acids of various nature.

A decision support system for real-time hydropower scheduling in a competitive power market environment

NASA Astrophysics Data System (ADS)

Shawwash, Ziad Khaled Elias

2000-10-01

The electricity supply market is rapidly changing from a monopolistic to a competitive environment. Being able to operate their system of reservoirs and generating facilities to get maximum benefits out of existing assets and resources is important to the British Columbia Hydro Authority (B.C. Hydro). A decision support system has been developed to help B.C. Hydro operate their system in an optimal way. The system is operational and is one of the tools that are currently used by the B.C. Hydro system operations engineers to determine optimal schedules that meet the hourly domestic load and also maximize the value B.C. Hydro obtains from spot transactions in the Western U.S. and Alberta electricity markets. This dissertation describes the development and implementation of the decision support system in production mode. The decision support system consists of six components: the input data preparation routines, the graphical user interface (GUI), the communication protocols, the hydraulic simulation model, the optimization model, and the results display software. A major part of this work involved the development and implementation of a practical and detailed large-scale optimization model that determines the optimal tradeoff between the long-term value of water and the returns from spot trading transactions in real-time operations. The postmortem-testing phase showed that the gains in value from using the model accounted for 0.25% to 1.0% of the revenues obtained. The financial returns from using the decision support system greatly outweigh the costs of building it. Other benefits are the savings in the time needed to prepare the generation and trading schedules. The system operations engineers now can use the time saved to focus on other important aspects of their job. The operators are currently experimenting with the system in production mode, and are gradually gaining confidence that the advice it provides is accurate, reliable and sensible. The main lesson learned from developing and implementing the system was that there is no alternative to working very closely with the intended end-users of the system, and with the people who have deep knowledge, experience and understanding of how the system is and should be operated.

Methods of sequential estimation for determining initial data in numerical weather prediction. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Cohn, S. E.

1982-01-01

Numerical weather prediction (NWP) is an initial-value problem for a system of nonlinear differential equations, in which initial values are known incompletely and inaccurately. Observational data available at the initial time must therefore be supplemented by data available prior to the initial time, a problem known as meteorological data assimilation. A further complication in NWP is that solutions of the governing equations evolve on two different time scales, a fast one and a slow one, whereas fast scale motions in the atmosphere are not reliably observed. This leads to the so called initialization problem: initial values must be constrained to result in a slowly evolving forecast. The theory of estimation of stochastic dynamic systems provides a natural approach to such problems. For linear stochastic dynamic models, the Kalman-Bucy (KB) sequential filter is the optimal data assimilation method, for linear models, the optimal combined data assimilation-initialization method is a modified version of the KB filter.

Research on the optimization of quota design in real estate

NASA Astrophysics Data System (ADS)

Sun, Chunling; Ma, Susu; Zhong, Weichao

2017-11-01

Quota design is one of the effective methods of cost control in real estate development project and widely used in the current real estate development project to control the engineering construction cost, but quota design have many deficiencies in design process. For this purpose, this paper put forward a method to achieve investment control of real estate development project, which combine quota design and value engineering(VE) at the stage of design. Specifically, it’s an optimizing for the structure of quota design. At first, determine the design limits by investment estimate value, then using VE to carry on initial allocation of design limits and gain the functional target cost, finally, consider the whole life cycle cost (LCC) and operational problem in practical application to finish complex correction for the functional target cost. The improved process can control the project cost more effectively. It not only can control investment in a certain range, but also make the project realize maximum value within investment.

Quantifying cerebellum grey matter and white matter perfusion using pulsed arterial spin labeling.

PubMed

Li, Xiufeng; Sarkar, Subhendra N; Purdy, David E; Briggs, Richard W

2014-01-01

To facilitate quantification of cerebellum cerebral blood flow (CBF), studies were performed to systematically optimize arterial spin labeling (ASL) parameters for measuring cerebellum perfusion, segment cerebellum to obtain separate CBF values for grey matter (GM) and white matter (WM), and compare FAIR ASST to PICORE. Cerebellum GM and WM CBF were measured with optimized ASL parameters using FAIR ASST and PICORE in five subjects. Influence of volume averaging in voxels on cerebellar grey and white matter boundaries was minimized by high-probability threshold masks. Cerebellar CBF values determined by FAIR ASST were 43.8 ± 5.1 mL/100 g/min for GM and 27.6 ± 4.5 mL/100 g/min for WM. Quantitative perfusion studies indicated that CBF in cerebellum GM is 1.6 times greater than that in cerebellum WM. Compared to PICORE, FAIR ASST produced similar CBF estimations but less subtraction error and lower temporal, spatial, and intersubject variability. These are important advantages for detecting group and/or condition differences in CBF values.

Steam gasification of acid-hydrolysis biomass CAHR for clean syngas production.

PubMed

Chen, Guanyi; Yao, Jingang; Yang, Huijun; Yan, Beibei; Chen, Hong

2015-03-01

Main characteristics of gaseous product from steam gasification of acid-hydrolysis biomass CAHR have been investigated experimentally. The comparison in terms of evolution of syngas flow rate, syngas quality and apparent thermal efficiency was made between steam gasification and pyrolysis in the lab-scale apparatus. The aim of this study was to determine the effects of temperature and steam to CAHR ratio on gas quality, syngas yield and energy conversion. The results showed that syngas and energy yield were better with gasification compared to pyrolysis under identical thermal conditions. Both high gasification temperature and introduction of proper steam led to higher gas quality, higher syngas yield and higher energy conversion efficiency. However, excessive steam reduced hydrogen yield and energy conversion efficiency. The optimal value of S/B was found to be 3.3. The maximum value of energy ratio was 0.855 at 800°C with the optimal S/B value. Copyright © 2014 Elsevier Ltd. All rights reserved.

Value recovery from two mechanized bucking operations in the southeastern United States

Treesearch

Kevin Boston; Glen. Murphy

2003-01-01

The value recovered from two mechanized bucking operations in the southeastern United States was compared with the optimal value computed using an individual-stem log optimization program, AVIS. The first operation recovered 94% of the optimal value. The main cause for the value loss was a failure to capture potential sawlog volume; logs were bucked to a larger average...

Optimal design criteria - prediction vs. parameter estimation

NASA Astrophysics Data System (ADS)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

Discrete-State Simulated Annealing For Traveling-Wave Tube Slow-Wave Circuit Optimization

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.; Bulson, Brian A.; Kory, Carol L.; Williams, W. Dan (Technical Monitor)

2001-01-01

Algorithms based on the global optimization technique of simulated annealing (SA) have proven useful in designing traveling-wave tube (TWT) slow-wave circuits for high RF power efficiency. The characteristic of SA that enables it to determine a globally optimized solution is its ability to accept non-improving moves in a controlled manner. In the initial stages of the optimization, the algorithm moves freely through configuration space, accepting most of the proposed designs. This freedom of movement allows non-intuitive designs to be explored rather than restricting the optimization to local improvement upon the initial configuration. As the optimization proceeds, the rate of acceptance of non-improving moves is gradually reduced until the algorithm converges to the optimized solution. The rate at which the freedom of movement is decreased is known as the annealing or cooling schedule of the SA algorithm. The main disadvantage of SA is that there is not a rigorous theoretical foundation for determining the parameters of the cooling schedule. The choice of these parameters is highly problem dependent and the designer needs to experiment in order to determine values that will provide a good optimization in a reasonable amount of computational time. This experimentation can absorb a large amount of time especially when the algorithm is being applied to a new type of design. In order to eliminate this disadvantage, a variation of SA known as discrete-state simulated annealing (DSSA), was recently developed. DSSA provides the theoretical foundation for a generic cooling schedule which is problem independent, Results of similar quality to SA can be obtained, but without the extra computational time required to tune the cooling parameters. Two algorithm variations based on DSSA were developed and programmed into a Microsoft Excel spreadsheet graphical user interface (GUI) to the two-dimensional nonlinear multisignal helix traveling-wave amplifier analysis program TWA3. The algorithms were used to optimize the computed RF efficiency of a TWT by determining the phase velocity profile of the slow-wave circuit. The mathematical theory and computational details of the DSSA algorithms will be presented and results will be compared to those obtained with a SA algorithm.

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.

Performance optimization of the Varian aS500 EPID system.

PubMed

Berger, Lucie; François, Pascal; Gaboriaud, Geneviève; Rosenwald, Jean-Claude

2006-01-01

Today, electronic portal imaging devices (EPIDs) are widely used as a replacement to portal films for patient position verification, but the image quality is not always optimal. The general aim of this study was to optimize the acquisition parameters of an amorphous silicon EPID commercially available for clinical use in radiation therapy with the view to avoid saturation of the system. Special attention was paid to selection of the parameter corresponding to the number of rows acquired between accelerator pulses (NRP) for various beam energies and dose rates. The image acquisition system (IAS2) has been studied, and portal image acquisition was found to be strongly dependent on the accelerator pulse frequency. This frequency is set for each "energy - dose rate" combination of the linear accelerator. For all combinations, the image acquisition parameters were systematically changed to determine their influence on the performances of the Varian aS500 EPID system. New parameters such as the maximum number of rows (MNR) and the number of pulses per frame (NPF) were introduced to explain portal image acquisition theory. Theoretical and experimental values of MNR and NPF were compared, and they were in good agreement. Other results showed that NRP had a major influence on detector saturation and dose per image. A rule of thumb was established to determine the optimum NRP value to be used. This practical application was illustrated by a clinical example in which the saturation of the aSi EPID was avoided by NRP optimization. Moreover, an additional study showed that image quality was relatively insensitive to this parameter.

Automated method for determining Instron Residual Seal Force of glass vial/rubber closure systems. Part II. 13 mm vials.

PubMed

Ludwig, J D; Davis, C W

1995-01-01

Instron Residual Seal Force (IRSF) of 13 mm glass vial/rubber closure systems was determined using an Instron 4501 Materials Testing System and computerized data analysis. A series of three cap anvils varying in shape and dimensions were machined to optimize cap anvil performance. Cap anvils with spherical top surfaces and narrow internal dimensions produced uniform stress-deformation curves from which precise IRSF values were derived.

An Evaluation of Material Properties Using EMA and FEM

NASA Astrophysics Data System (ADS)

Ďuriš, Rastislav; Labašová, Eva

2016-12-01

The main goal of the paper is the determination of material properties from experimentally measured natural frequencies. A combination of two approaches to structural dynamics testing was applied: the experimental measurements of natural frequencies were performed by Experimental Modal Analysis (EMA) and the numerical simulations, were carried out by Finite Element Analysis (FEA). The optimization methods were used to determine the values of density and elasticity modulus of a specimen based on the experimental results.

[Effects of methomyl on acetylcholinesterase in erythrocyte membrane and various brain areas].

PubMed

Zhao, Fei; Li, Tao; Zhang, Changchun; Xu, Yiping; Xu, Hangong; Shi, Nian

2015-06-01

To study the toxicity of methomyl to acetylcholinesterase (AChE) in different regions. The optimal temperature and time for measurement of AChE activity were determined in vitro. The dose- and time-response relationships of methomyl with AChE activity in human erythrocyte membrane, rat erythrocyte membrane, cortical synapses, cerebellar synapses, hippocampal synapses, and striatal synapses were evaluated. The half maximal inhibitory concentration (IC50) and bimolecular rate constant (K) of methomyl for AChE activity in different regions were calculated, and the type of inhibition of AChE activity by methomyl was determined. AChE achieved the maximum activity at 370 °C, and the optimal time to determine initial reaction velocity was 0-17 min. There were dose- and time-response relationships between methomyl and AChE activity in the erythrocyte membrane and various brain areas. The IC50 value of methomyl for AChE activity in human erythrocyte membrane was higher than that in rat erythrocyte membrane, while the Ki value of methomyl for AChE activity in rat erythrocyte membrane was higher than that in human erythrocyte membrane. Among synapses in various brain areas, the striatum had the highest IC50 value, followed by the cerebellum, cerebral cortex, and hippocampus, while the cerebral cortex had the highest Ki value, followed by the hippocampus, striatum, and cerebellum. Lineweaver-Burk diagram demonstrated that with increasing concentration of methomyl, the maximum reaction velocity (Vmax) of AChE decreased, and the Michaelis constant (Km) remained the same. Methomyl is a reversible non-competitive inhibitor of AChE. AChE of rat erythrocyte membrane is more sensitive to methomyl than that of human erythrocyte membrane; the cerebral cortical synapses have the most sensitive AChE to methomyl among synapses in various brain areas.

Rapid determination of some beta-blockers in complicated matrices by tandem dispersive liquid-liquid microextraction followed by high performance liquid chromatography.

PubMed

Hemmati, Maryam; Asghari, Alireza; Bazregar, Mohammad; Rajabi, Maryam

2016-11-01

In this research work, an efficient tandem dispersive liquid-liquid microextraction (TDLLME) procedure coupled with high performance liquid chromatography-ultraviolet detection (HPLC-UV) was successfully applied for the determination of beta-blockers in human plasma and pharmaceutical wastewater samples. High clean-up and preconcentration factor are easily and rapidly feasible via this novel, cheap, and safe microextraction method, leading to high quality experimental data. It consists of two sequential dispersive liquid-liquid microextraction methods, accomplished via air/ultrasonic agitation and air agitation, respectively. In order to enrich the optimal values for the mentioned procedures, the Box-Behnken design (BBD) combined with the desirability function (DF) was used. The optimum values were found to be 11.0 % (w/v) of the salt amount, an initial pH value of 12.0, 103 μL of organic extractant phase, and 45 μL of aqueous extractant phase with pH value of 2.0, resulted in reasonable recovery percentages with a logical desirability. Under optimal experimental conditions, good linear ranges (3-2000 ng mL -1 for metoprolol and 2.5-2500 ng mL -1 for propranolol with the correlation of determinations (R 2 s) higher than 0.99) and low limits of detection (0.8 and 1.0 ng mL -1 for propranolol and metoprolol, respectively) were obtainable. Also, TDLLME-HPLC-UV provided good proper repeatabilities (relative standard deviations (RSDs) below 5.7 %, n = 3) and high enrichment factors (EFs) of 75-100. Graphical abstract TDLLME of beta-blockers from complicated matrices.

Optimization of Maillard Reaction in Model System of Glucosamine and Cysteine Using Response Surface Methodology

PubMed Central

Arachchi, Shanika Jeewantha Thewarapperuma; Kim, Ye-Joo; Kim, Dae-Wook; Oh, Sang-Chul; Lee, Yang-Bong

2017-01-01

Sulfur-containing amino acids play important roles in good flavor generation in Maillard reaction of non-enzymatic browning, so aqueous model systems of glucosamine and cysteine were studied to investigate the effects of reaction temperature, initial pH, reaction time, and concentration ratio of glucosamine and cysteine. Response surface methodology was applied to optimize the independent reaction parameters of cysteine and glucosamine in Maillard reaction. Box-Behnken factorial design was used with 30 runs of 16 factorial levels, 8 axial levels and 6 central levels. The degree of Maillard reaction was determined by reading absorption at 425 nm in a spectrophotometer and Hunter’s L, a, and b values. ΔE was consequently set as the fifth response factor. In the statistical analyses, determination coefficients (R2) for their absorbance, Hunter’s L, a, b values, and ΔE were 0.94, 0.79, 0.73, 0.96, and 0.79, respectively, showing that the absorbance and Hunter’s b value were good dependent variables for this model system. The optimum processing parameters were determined to yield glucosamine-cysteine Maillard reaction product with higher absorbance and higher colour change. The optimum estimated absorbance was achieved at the condition of initial pH 8.0, 111°C reaction temperature, 2.47 h reaction time, and 1.30 concentration ratio. The optimum condition for colour change measured by Hunter’s b value was 2.41 h reaction time, 114°C reaction temperature, initial pH 8.3, and 1.26 concentration ratio. These results can provide the basic information for Maillard reaction of aqueous model system between glucosamine and cysteine. PMID:28401086

Optimization of Maillard Reaction in Model System of Glucosamine and Cysteine Using Response Surface Methodology.

PubMed

Arachchi, Shanika Jeewantha Thewarapperuma; Kim, Ye-Joo; Kim, Dae-Wook; Oh, Sang-Chul; Lee, Yang-Bong

2017-03-01

Sulfur-containing amino acids play important roles in good flavor generation in Maillard reaction of non-enzymatic browning, so aqueous model systems of glucosamine and cysteine were studied to investigate the effects of reaction temperature, initial pH, reaction time, and concentration ratio of glucosamine and cysteine. Response surface methodology was applied to optimize the independent reaction parameters of cysteine and glucosamine in Maillard reaction. Box-Behnken factorial design was used with 30 runs of 16 factorial levels, 8 axial levels and 6 central levels. The degree of Maillard reaction was determined by reading absorption at 425 nm in a spectrophotometer and Hunter's L, a, and b values. ΔE was consequently set as the fifth response factor. In the statistical analyses, determination coefficients (R 2 ) for their absorbance, Hunter's L, a, b values, and ΔE were 0.94, 0.79, 0.73, 0.96, and 0.79, respectively, showing that the absorbance and Hunter's b value were good dependent variables for this model system. The optimum processing parameters were determined to yield glucosamine-cysteine Maillard reaction product with higher absorbance and higher colour change. The optimum estimated absorbance was achieved at the condition of initial pH 8.0, 111°C reaction temperature, 2.47 h reaction time, and 1.30 concentration ratio. The optimum condition for colour change measured by Hunter's b value was 2.41 h reaction time, 114°C reaction temperature, initial pH 8.3, and 1.26 concentration ratio. These results can provide the basic information for Maillard reaction of aqueous model system between glucosamine and cysteine.

A study of the stress wave factor technique for the characterization of composite materials

NASA Technical Reports Server (NTRS)

Henneke, E. G., II; Duke, J. C., Jr.; Stinchcomb, W. W.; Govada, A.; Lemascon, A.

1983-01-01

A testing program was undertaken to provide an independent investigation and evaluation of the stress wave factor for characterizing the mechanical behavior of composite laminates. Some of the data which was obtained after performing a very large number of tests to determine the reproducibility of the SWF measurement is presented. It was determined that, with some optimizing of experimental parameters, the SWF value can be reproduced to within + or - 10%. Results are also given which show that, after careful calibration procedures, the lowest SWF value along the length of a specimen will correlate very closely to the site of final failure when the specimen is loaded in tension. Finally, using a moire interferometry technique, it was found that local regions having the highest in plane strains under tensile loading also had the lowest SWF values.

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

Zhou, S; Fan, Q; Lei, Y

Purpose: In-Water-Output-Ratio (IWOR) plays a significant role in linac-based radiotherapy treatment planning, linking MUs to delivered radiation dose. For an open rectangular field, IWOR depends on both its width and length, and changes rapidly when one of them becomes small. In this study, a universal functional form is proposed to fit the open field IWOR tables in Varian TrueBeam representative datasets for all photon energies. Methods: A novel Generalized Mean formula is first used to estimate the Equivalent Square (ES) for a rectangular field. The formula’s weighting factor and power index are determined by collapsing all data points as muchmore » as possible onto a single curve in IWOR vs. ES plot. The result is then fitted with a novel universal function IWOR=1+b*Log(ES/10cm)/(ES/10cm)^c via a least-square procedure to determine the optimal values for parameters b and c. The maximum relative residual error in IWOR over the entire two-dimensional measurement table with field sizes between 3cm and 40cm is used to evaluate the quality of fit for the function. Results: The two-step fitting strategy works very well in determining the optimal parameter values for open field IWOR of each photon energies in the Varian data-set. Relative residual error ≤0.71% is achieved for all photon energies (including Flattening-Filter-Free modes) with field sizes between 3cm and 40cm. The optimal parameter values change smoothly with regular photon beam quality. Conclusion: The universal functional form fits the Varian TrueBeam open field IWOR measurement tables accurately with small relative residual errors for all photon energies. Therefore, it can be an excellent choice to represent IWOR in absolute dose and MU calculations. The functional form can also be used as a QA/commissioning tool to verify the measured data quality and consistency by checking the IWOR data behavior against the function for new photon energies with arbitrary beam quality.« less

A SYSTEMATIC REVIEW OF THE EXERCISES THAT PRODUCE OPTIMAL MUSCLE RATIOS OF THE SCAPULAR STABILIZERS IN NORMAL SHOULDERS

PubMed Central

Schory, Abbey; Bidinger, Erik; Wolf, Joshua

2016-01-01

ABSTRACT Purpose The purpose of this systematic review was to determine the exercises that optimize muscle ratios of the periscapular musculature for scapular stability and isolated strengthening. Methods A systematic search was performed in PubMed, CINAHL, SPORTDiscus, Scopus, and Discovery Layer. Studies were included if they examined the muscle activation of the upper trapezius compared to the middle trapezius, lower trapezius, or serratus anterior using EMG during open chain exercises. The participants were required to have healthy, nonpathological shoulders. Information obtained included maximal voluntary isometric contraction (MVIC) values, ratios, standard deviations, exercises, and exercise descriptions. The outcome of interest was determining exercises that create optimal muscle activation ratios between the scapular stabilizers. Results Fifteen observational studies met the inclusion criteria for the systematic review. Exercises with optimal ratios were eccentric exercises in the frontal and sagittal planes, especially flexion between 180 ° and 60 °. External rotation exercises with the elbow flexed to 90 ° also had optimal ratios for activating the middle trapezius in prone and side-lying positions. Exercises with optimal ratios for the lower trapezius were prone flexion, high scapular retraction, and prone external rotation with the shoulder abducted to 90 ° and elbow flexed. Exercises with optimal ratios for the serratus anterior were the diagonal exercises and scapular protraction. Conclusion This review has identified optimal positions and exercises for periscapular stability exercises. Standing exercises tend to activate the upper trapezius at a higher ratio, especially during the 60-120 ° range. The upper trapezius was the least active, while performing exercises in prone, side-lying, and supine positions. More studies need to be conducted to examine these exercises in greater detail and confirm their consistency in producing the optimal ratios determined in this review. Level of evidence 1a PMID:27274418

Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications

NASA Technical Reports Server (NTRS)

Aldrich, Jack B.; Okon, Avi B.

2012-01-01

The need to maintain optimal energy efficiency is critical during the drilling operations performed on future and current planetary rover missions (see figure). Specifically, this innovation seeks to solve the following problem. Given a spring-loaded percussive drill driven by a voice-coil motor, one needs to determine the optimal input voltage waveform (periodic function) and the optimal hammering period that minimizes the dissipated energy, while ensuring that the hammer-to-rock impacts are made with sufficient (user-defined) impact velocity (or impact energy). To solve this problem, it was first observed that when voice-coil-actuated percussive drills are driven at high power, it is of paramount importance to ensure that the electrical current of the device remains in phase with the velocity of the hammer. Otherwise, negative work is performed and the drill experiences a loss of performance (i.e., reduced impact energy) and an increase in Joule heating (i.e., reduction in energy efficiency). This observation has motivated many drilling products to incorporate the standard bang-bang control approach for driving their percussive drills. However, the bang-bang control approach is significantly less efficient than the optimal energy-efficient control approach solved herein. To obtain this solution, the standard tools of classical optimal control theory were applied. It is worth noting that these tools inherently require the solution of a two-point boundary value problem (TPBVP), i.e., a system of differential equations where half the equations have unknown boundary conditions. Typically, the TPBVP is impossible to solve analytically for high-dimensional dynamic systems. However, for the case of the spring-loaded vibro-impactor, this approach yields the exact optimal control solution as the sum of four analytic functions whose coefficients are determined using a simple, easy-to-implement algorithm. Once the optimal control waveform is determined, it can be used optimally in the context of both open-loop and closed-loop control modes (using standard realtime control hardware).

Application of Taguchi L32 orthogonal array design to optimize copper biosorption by using Spaghnum moss.

PubMed

Ozdemir, Utkan; Ozbay, Bilge; Ozbay, Ismail; Veli, Sevil

2014-09-01

In this work, Taguchi L32 experimental design was applied to optimize biosorption of Cu(2+) ions by an easily available biosorbent, Spaghnum moss. With this aim, batch biosorption tests were performed to achieve targeted experimental design with five factors (concentration, pH, biosorbent dosage, temperature and agitation time) at two different levels. Optimal experimental conditions were determined by calculated signal-to-noise ratios. "Higher is better" approach was followed to calculate signal-to-noise ratios as it was aimed to obtain high metal removal efficiencies. The impact ratios of factors were determined by the model. Within the study, Cu(2+) biosorption efficiencies were also predicted by using Taguchi method. Results of the model showed that experimental and predicted values were close to each other demonstrating the success of Taguchi approach. Furthermore, thermodynamic, isotherm and kinetic studies were performed to explain the biosorption mechanism. Calculated thermodynamic parameters were in good accordance with the results of Taguchi model. Copyright © 2014 Elsevier Inc. All rights reserved.

Hyperspectral imaging detection of decayed honey peaches based on their chlorophyll content.

PubMed

Sun, Ye; Wang, Yihang; Xiao, Hui; Gu, Xinzhe; Pan, Leiqing; Tu, Kang

2017-11-15

Honey peach is a very common but highly perishable market fruit. When pathogens infect fruit, chlorophyll as one of the important components related to fruit quality, decreased significantly. Here, the feasibility of hyperspectral imaging to determine the chlorophyll content thus distinguishing diseased peaches was investigated. Three optimal wavelengths (617nm, 675nm, and 818nm) were selected according to chlorophyll content via successive projections algorithm. Partial least square regression models were established to determine chlorophyll content. Three band ratios were obtained using these optimal wavelengths, which improved spatial details, but also integrates the information of chemical composition from spectral characteristics. The band ratio values were suitable to classify the diseased peaches with 98.75% accuracy and clearly show the spatial distribution of diseased parts. This study provides a new perspective for the selection of optimal wavelengths of hyperspectral imaging via chlorophyll content, thus enabling the detection of fungal diseases in peaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization of elutriation device for filtration of microplastic particles from sediment.

PubMed

Zhu, X

2015-03-15

The increasing presence of plastic pollution in marine ecosystems has become a major concern. In the environment, plastics break down into smaller and smaller pieces of microplastics. Methods of microplastic recovery are needed to reduce the dangers they can pose to a variety of organisms. An elutriation device was manufactured and optimized to achieve maximum microplastic recovery. The parameters flow rate and diameter of elutriation column were varied and their domain of variation was determined. A composite factorial experimental design was generated using MODDE 10.1 and was undergone. The optimal values of flow rate and column diameter were determined to be 385 L h(-1) and 5.06 cm respectively, under constraints, to achieve a maximum feasible microplastics recovery percentage of 50.2%. The elutriation process can be improved through further testing, and can be tested in the field to compare its efficiency to that of manual microplastics filtration. Copyright © 2015 Elsevier Ltd. All rights reserved.

Shape optimization of an autonomous underwater vehicle with a ducted propeller using computational fluid dynamics analysis

NASA Astrophysics Data System (ADS)

Joung, Tae-Hwan; Sammut, Karl; He, Fangpo; Lee, Seung-Keon

2012-03-01

Autonomous Underwater Vehicles (AUVs) provide a useful means of collecting detailed oceano-graphic information. The hull resistance of an AUV is an important factor in determining the power requirements and range of the vehicle. This paper describes a procedure using Computational Fluid Dynamics (CFD) for determining the hull resistance of an AUV under development, for a given propeller rotation speed and within a given range of AUV velocities. The CFD analysis results reveal the distribution of the hydrodynamic values (velocity, pressure, etc.) around the AUV hull and its ducted propeller. The paper then proceeds to present a methodology for optimizing the AUV profile in order to reduce the total resistance. This paper demonstrates that shape optimization of conceptual designs is possible using the commercial CFD package contained in Ansys™. The optimum design to minimize the drag force of the AUV was identified for a given object function and a set of constrained design parameters

User's manual for the BNW-I optimization code for dry-cooled power plants. [AMCIRC

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

Braun, D.J.; Daniel, D.J.; De Mier, W.V.

1977-01-01

This appendix provides a listing, called Program AMCIRC, of the BNW-1 optimization code for determining, for a particular size power plant, the optimum dry cooling tower design using ammonia flow in the heat exchanger tubes. The optimum design is determined by repeating the design of the cooling system over a range of design conditions in order to find the cooling system with the smallest incremental cost. This is accomplished by varying five parameters of the plant and cooling system over ranges of values. These parameters are varied systematically according to techniques that perform pattern and gradient searches. The dry coolingmore » system optimized by program AMCIRC is composed of a condenser/reboiler (condensation of steam and boiling of ammonia), piping system (transports ammonia vapor out and ammonia liquid from the dry cooling towers), and circular tower system (vertical one-pass heat exchangers situated in circular configurations with cocurrent ammonia flow in the tubes of the heat exchanger). (LCL)« less

[Diagnostic reference levels in interventional radiology].

PubMed

Vañó Carruana, E; Fernández Soto, J M; Sánchez Casanueva, R M; Ten Morón, J I

2013-12-01

This article discusses the diagnostic reference levels for radiation exposure proposed by the International Commission on Radiological Protection (ICRP) to facilitate the application of the optimization criteria in diagnostic imaging and interventional procedures. These levels are normally established as the third quartile of the dose distributions to patients in an ample sample of centers and are supposed to be representative of good practice regarding patient exposure. In determining these levels, it is important to evaluate image quality as well to ensure that it is sufficient for diagnostic purposes. When the values for the dose received by patients are systematically higher or much lower than the reference levels, an investigation should determine whether corrective measures need to be applied. The European and Spanish regulations require the use of these reference values in quality assurance programs. For interventional procedures, the dose area product (or kerma area product) values are usually used as reference values together with the time under fluoroscopy and the total number of images acquired. The most modern imaging devices allow the value of the accumulated dose at the entrance to the patient to be calculated to optimize the distribution of the dose on the skin. The ICRP recommends that the complexity of interventional procedures be taken into account when establishing reference levels. In the future, diagnostic imaging departments will have automatic systems to manage patient dosimetric data; these systems will enable continuous dosage auditing and alerts about individual procedures that might involve doses several times above the reference values. This article also discusses aspects that need to be clarified to take better advantage of the reference levels in interventional procedures. Copyright © 2013 SERAM. Published by Elsevier Espana. All rights reserved.

Diagnostic accuracy of APRI, FIB-4 and Forns for the detection of liver cirrhosis in HIV/HCV-coinfected patients.

PubMed

Merli, Marco; Galli, Laura; Castagna, Antonella; Salpietro, Stefania; Gianotti, Nicola; Messina, Emanuela; Poli, Andrea; Morsica, Giulia; Bagaglio, Sabrina; Cernuschi, Massimo; Bigoloni, Alba; Uberti-Foppa, Caterina; Lazzarin, Adriano; Hasson, Hamid

2016-04-01

We determined the diagnostic accuracy and optimal cut off of three indirect fibrosis biomarkers (APRI, FIB-4, Forns) compared with liver stiffness (LS) for the detection of liver cirrhosis in HIV/HCV-coinfected patients. An observational retrospective study on HIV/HCV-coinfected patients with concomitant LS measurement and APRI, FIB-4 and Forns was performed. The presence of liver cirrhosis was defined as a LS ≥13 KPa. The diagnostic accuracy and optimal cut-off values, compared with LS categorization (<13 vs ≥13 KPa), were determined by receiver operating characteristics (ROC) curves. The study sample included 646 patients. The area-under-the ROC curve (95% confidence interval) for the detection of liver cirrhosis were 0.84 (0.81-0.88), 0.87 (0.84-0.91) and 0.87 (0.84-0.90) for APRI, FIB-4 and Forns, respectively. According to the optimal cut off values for liver cirrhosis (≥0.97 for APRI, ≥2.02 for FIB-4 and ≥7.8 for Forns), 80%, 80% and 82% of subjects were correctly classified by the three indirect fibrosis biomarkers, respectively. Misclassifications were mostly due to false positive cases. The study suggests that indirect fibrosis biomarkers can help clinicians to exclude liver cirrhosis in the management of HIV/HCV co-infected patients, reducing the frequency of more expensive or invasive assessments.

Physicochemical properties and starch digestibility of Chinese noodles in relation to optimal cooking time.

PubMed

Ye, Xiaoting; Sui, Zhongquan

2016-03-01

Changes in the physicochemical properties and starch digestibility of white salted noodles (WSN) at different cooking stage were investigated. The noodles were dried in fresh air and then cooked for 2-12 min by boiling in distilled water to determine the properties of cooking quality, textural properties and optical characteristic. For starch digestibility, dry noodles were milled and sieved into various particle size classes ranging from 0.5 mm to 5.0 mm, and hydrolyzed by porcine pancreatic α-amylase. The optimal cooking time of WSN determined by squeezing between glasses was 6 min. The results showed that the kinetics of solvation of starch and protein molecules were responsible for changes of the physicochemical properties of WSN during cooking. The susceptibility of starch to α-amylase was influenced by the cooking time, particle size and enzyme treatment. The greater value of rapidly digestible starch (RDS) and lower value of slowly digestible starch (SDS) and resistant starch (RS) were reached at the optimal cooking stage ranging between 63.14-71.97%, 2.47-10.74% and 23.94-26.88%, respectively, indicating the susceptibility on hydrolysis by enzyme was important in defining the cooked stage. The study suggested that cooking quality and digestibility were not correlated but the texture greatly controls the digestibility of the noodles. Copyright © 2015 Elsevier B.V. All rights reserved.

Rapid and non-destructive determination of rancidity levels in butter cookies by multi-spectral imaging.

PubMed

Xia, Qing; Liu, Changhong; Liu, Jinxia; Pan, Wenjuan; Lu, Xuzhong; Yang, Jianbo; Chen, Wei; Zheng, Lei

2016-03-30

Rancidity is an important attribute for quality assessment of butter cookies, while traditional methods for rancidity measurement are usually laborious, destructive and prone to operational error. In the present paper, the potential of applying multi-spectral imaging (MSI) technology with 19 wavelengths in the range of 405-970 nm to evaluate the rancidity in butter cookies was investigated. Moisture content, acid value and peroxide value were determined by traditional methods and then related with the spectral information by partial least squares regression (PLSR) and back-propagation artificial neural network (BP-ANN). The optimal models for predicting moisture content, acid value and peroxide value were obtained by PLSR. The correlation coefficient (r) obtained by PLSR models revealed that MSI had a perfect ability to predict moisture content (r = 0.909), acid value (r = 0.944) and peroxide value (r = 0.971). The study demonstrated that the rancidity level of butter cookies can be continuously monitored and evaluated in real-time by the multi-spectral imaging, which is of great significance for developing online food safety monitoring solutions. © 2015 Society of Chemical Industry.

SU-F-T-73: Experimental Determination of the Effective Point of Measurement in Electron Beams Using a Commercial Scintillation Detector

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

Simiele, E; Smith, B; Culberson, W

2016-06-15

Purpose: The aim of this work was to determine experimentally the effective point of measurement (EPOM) in clinical electron beams for three cylindrical ionization chambers using a commercial scintillation detector as a reference detector. Methods: Percent depth dose (PDD) curves were measured using an Exradin W1 scintillation detector and were used as a representative PDD to water. Depth dose curves were measured with the Exradin A18, A1SL, and A28 ionization chambers. The raw ionization chamber curve data were corrected by the chamber fluence perturbation correction factor and restricted mass collisional stopping power ratio at each depth to obtain a percentmore » depth dose curve to the gas volume (PDDGV) of the detector. Ratios of the W1 PDD to the ion chamber PDDGV were calculated for each measurement depth. The W1 PDD curve was shifted by small depth increments, Δz, until the ratio of the W1 PDD to the ion chamber PDDGV was depth-independent (optimal Δz). A MATLAB routine was developed to determine the optimal Δz value. Results: The optimal Δz shift was used as an estimate of the EPOM for each chamber. The average calculated EPOM shifts (expressed as a fraction of the chamber cavity radius) for the A18, A1SL, and A28 ionization chambers were 0.21 ± 0.04, 0.10 ± 0.05, and 0.22 ± 0.03, respectively. Conclusion: The experimentally determined EPOM values for the A18 and A1SL in this work agreed with the simulated values of Muir and Rogers (MedPhys 2014). The results also indicate that the Exradin W1 scintillator is water equivalent for electron energies of 6 MeV, 9 MeV, 12 MeV, and 16 MeV. In addition, we confirmed that the AAPM TG51 recommended EPOM shift of 0.5 times the cavity radius is not accurate for the A18 and A1SL chambers.« less

Determination of arsenic species in rice samples using CPE and ETAAS.

PubMed

Costa, Bruno Elias Dos Santos; Coelho, Nívia Maria Melo; Coelho, Luciana Melo

2015-07-01

A highly sensitive and selective procedure for the determination of arsenate and total arsenic in food by electrothermal atomic absorption spectrometry after cloud point extraction (ETAAS/CPE) was developed. The procedure is based on the formation of a complex of As(V) ions with molybdate in the presence of 50.0 mmol L(-1) sulfuric acid. The complex was extracted into the surfactant-rich phase of 0.06% (w/v) Triton X-114. The variables affecting the complex formation, extraction and phase separation were optimized using factorial designs. Under the optimal conditions, the calibration graph was linear in the range of 0.05-10.0 μg L(-1). The detection and quantification limits were 10 and 33 ng L(-1), respectively and the corresponding value for the relative standard deviation for 10 replicates was below 5%. Recovery values of between 90.8% and 113.1% were obtained for spiked samples. The accuracy of the method was evaluated by comparison with the results obtained for the analysis of a rice flour sample (certified material IRMM-804) and no significant difference at the 95% confidence level was observed. The method was successfully applied to the determination of As(V) and total arsenic in rice samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bicarbonate Balance and Prescription in ESRD

PubMed Central

2017-01-01

The optimal approach to managing acid-base balance is less well defined for patients receiving hemodialysis than for those receiving peritoneal dialysis. Interventional studies in hemodialysis have been limited and inconsistent in their findings, whereas more compelling data are available from interventional studies in peritoneal dialysis. Both high and low serum bicarbonate levels associate with an increased risk of mortality in patients receiving hemodialysis, but high values are a marker for poor nutrition and comorbidity and are often highly variable from month to month. Measurement of pH would likely provide useful additional data. Concern has arisen regarding high-bicarbonate dialysate and dialysis-induced alkalemia, but whether these truly cause harm remains to be determined. The available evidence is insufficient for determining the optimal target for therapy at this time. PMID:27881607

Test plan for the soils facility demonstration: A petroleum contaminated soil bioremediation facility

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

Lombard, K.H.

1994-08-01

The objectives of this test plan are to show the value added by using bioremediation as an effective and environmentally sound method to remediate petroleum contaminated soils (PCS) by: demonstrating bioremediation as a permanent method for remediating soils contaminated with petroleum products; establishing the best operating conditions for maximizing bioremediation and minimizing volatilization for SRS PCS during different seasons; determining the minimum set of analyses and sampling frequency to allow efficient and cost-effective operation; determining best use of existing site equipment and personnel to optimize facility operations and conserve SRS resources; and as an ancillary objective, demonstrating and optimizing newmore » and innovative analytical techniques that will lower cost, decrease time, and decrease secondary waste streams for required PCS assays.« less

Optimizing conservation strategies for Mexican freetailed bats: a population viability and ecosystem services approach

USGS Publications Warehouse

Wiederholt, Ruscena; Lopez-Hoffman, Laura; Svancara, Colleen; McCracken, Gary; Thogmartin, Wayne E.; Diffendorfer, James E.; Mattson, Brady; Bagstad, Kenneth J.; Cryan, Paul; Russell, Amy; Semmens, Darius J.; Rodrigo A. Medellín,

2015-01-01

Conservation planning can be challenging due to the need to balance biological concerns about population viability with social concerns about the benefits biodiversity provide to society, often while operating under a limited budget. Methods and tools that help prioritize conservation actions are critical for the management of at-risk species. Here, we use a multi-attribute utility function to assess the optimal maternity roosts to conserve for maintaining the population viability and the ecosystem services of a single species, the Mexican free-tailed bat (Tadarida brasiliensis mexicana). Mexican free-tailed bats provide ecosystem services such as insect pest-suppression in agricultural areas and recreational viewing opportunities, and may be threatened by climate change and development of wind energy. We evaluated each roost based on five attributes: the maternity roost’s contribution to population viability, the pest suppression ecosystem services to the surrounding area provided by the bats residing in the roost, the ecotourism value of the roost, the risks posed to each roost structure, and the risks posed to the population of bats residing in each roost. We compared several scenarios that prioritized these attributes differently, hypothesizing that the set of roosts with the highest rankings would vary according to the conservation scenario. Our results indicate that placing higher values on different roost attributes (e.g. population importance over ecosystem service value) altered the roost rankings. We determined that the values placed on various conservation objectives are an important determinant of habitat planning.

Simulation of load traffic and steeped speed control of conveyor

NASA Astrophysics Data System (ADS)

Reutov, A. A.

2017-10-01

The article examines the possibilities of the step control simulation of conveyor speed within Mathcad, Simulink, Stateflow software. To check the efficiency of the control algorithms and to more accurately determine the characteristics of the control system, it is necessary to simulate the process of speed control with real values of traffic for a work shift or for a day. For evaluating the belt workload and absence of spillage it is necessary to use empirical values of load flow in a shorter period of time. The analytical formulas for optimal speed step values were received using empirical values of load. The simulation checks acceptability of an algorithm, determines optimal parameters of regulation corresponding to load flow characteristics. The average speed and the number of speed switching during simulation are admitted as criteria of regulation efficiency. The simulation example within Mathcad software is implemented. The average conveyor speed decreases essentially by two-step and three-step control. A further increase in the number of regulatory steps decreases average speed insignificantly but considerably increases the intensity of the speed switching. Incremental algorithm of speed regulation uses different number of stages for growing and reducing load traffic. This algorithm allows smooth control of the conveyor speed changes with monotonic variation of the load flow. The load flow oscillation leads to an unjustified increase or decrease of speed. Work results can be applied at the design of belt conveyors with adjustable drives.

A new threshold of apparent diffusion coefficient values in white matter after successful tissue plasminogen activator treatment for acute brain ischemia.

PubMed

Sato, Atsushi; Shimizu, Yusaku; Koyama, Junichi; Hongo, Kazuhiro

2017-06-01

Tissue plasminogen activator (tPA) is effective for the treatment of acute brain ischemia, but may trigger fatal brain edema or hemorrhage if the brain ischemia results in a large infarct. Herein, we attempted to predict the extent of infarcts by determining the optimal threshold of ADC values on DWI that predictively distinguishes between infarct and reversible areas, and by reconstructing color-coded images based on this threshold. The study subjects consisted of 36 patients with acute brain ischemia in whom MRA had confirmed reopening of the occluded arteries in a short time (mean: 99min) after tPA treatment. We measured the apparetnt diffusion coefficient (ADC) values in several small regions of interest over the white matter within high-intensity areas on the initial diffusion weighted image (DWI); then, by comparing the findings to the follow-up images, we obtained the optimal threshold of ADC values using receiver-operating characteristic analysis. The threshold obtained (583×10 -6 m 2 /s) was lower than those previously reported; this threshold could distinguish between infarct and reversible areas with considerable accuracy (sensitivity: 0.87, specificity: 0.94). The threshold obtained and the reconstructed images were predictive of the final radiological result of tPA treatment, and this threshold may be helpful in determining the appropriate management of patients with acute brain ischemia. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Optimization of minoxidil microemulsions using fractional factorial design approach.

PubMed

Jaipakdee, Napaphak; Limpongsa, Ekapol; Pongjanyakul, Thaned

2016-01-01

The objective of this study was to apply fractional factorial and multi-response optimization designs using desirability function approach for developing topical microemulsions. Minoxidil (MX) was used as a model drug. Limonene was used as an oil phase. Based on solubility, Tween 20 and caprylocaproyl polyoxyl-8 glycerides were selected as surfactants, propylene glycol and ethanol were selected as co-solvent in aqueous phase. Experiments were performed according to a two-level fractional factorial design to evaluate the effects of independent variables: Tween 20 concentration in surfactant system (X1), surfactant concentration (X2), ethanol concentration in co-solvent system (X3), limonene concentration (X4) on MX solubility (Y1), permeation flux (Y2), lag time (Y3), deposition (Y4) of MX microemulsions. It was found that Y1 increased with increasing X3 and decreasing X2, X4; whereas Y2 increased with decreasing X1, X2 and increasing X3. While Y3 was not affected by these variables, Y4 increased with decreasing X1, X2. Three regression equations were obtained and calculated for predicted values of responses Y1, Y2 and Y4. The predicted values matched experimental values reasonably well with high determination coefficient. By using optimal desirability function, optimized microemulsion demonstrating the highest MX solubility, permeation flux and skin deposition was confirmed as low level of X1, X2 and X4 but high level of X3.

Optimization of the canola oil based vitamin E nanoemulsions stabilized by food grade mixed surfactants using response surface methodology.

PubMed

Mehmood, Tahir

2015-09-15

The objective of the present study was to prepare canola oil based vitamin E nanoemulsions by using food grade mixed surfactants (Tween:80 and lecithin; 3:1) to replace some concentration of nonionic surfactants (Tween 80) with natural surfactant (soya lecithin) and to optimize their preparation conditions. RBD (Refined, Bleached and Deodorized) canola oil and vitamin E acetate were used in water/vitamin E/oil/surfactant system due to their nutritional benefits and oxidative stability, respectively. Response surface methodology (RSM) was used to optimize the preparation conditions. The effects of homogenization pressure (75-155MPa), oil concentrations (4-12% w/w), surfactant concentrations (3-11% w/w) and vitamin E acetate contents (0.4-1.2% w/w) on the particle size and emulsion stability were studied. RSM analysis has shown that the experimental data could be fitted well into second-order polynomial model with the coefficient of determinations of 0.9464 and 0.9278 for particle size and emulsion stability, respectively. The optimum values of independent variables were 135MPa homogenization pressure, 6.18% oil contents, 6.39% surfactant concentration and 1% vitamin E acetate concentration. The optimized response values for particle size and emulsion stability were 150.10nm and 0.338, respectively. Whereas, the experimental values for particle size and nanoemulsion stability were 156.13±2.3nm and 0.328±0.015, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

Use of microwaves to improve nutritional value of soybeans for future space inhabitants

NASA Technical Reports Server (NTRS)

Singh, G.

1983-01-01

Whole soybeans from four different varieties at different moisture contents were microwaved for varying times to determine the conditions for maximum destruction of trypsin inhibitor and lipoxygenase activities, and optimal growth of chicks. Microwaving 150 gm samples of soybeans (at 14 to 28% moisture) for 1.5 min was found optimal for reduction of trypsin inhibitor and lipoxygenase activities. Microwaving 1 kgm samples of soybeans for 9 minutes destroyed 82% of the trypsin inhibitor activity and gave optimal chick growth. It should be pointed out that the microwaving time would vary according to the weight of the sample and the power of the microwave oven. The microwave oven used in the above experiments was rated at 650 watts 2450 MHz.

Supply chain coordination with defective items and quantity discount

NASA Astrophysics Data System (ADS)

Lin, Hsien-Jen; Lin, Yu-Jen

2014-12-01

This study develops an integrated inventory system involving defective items and quantity discount for optimal pricing and ordering strategies. The model analysed in this study is one in which the buyer orders a quantity, the vendor produces more than buyer's order quantity in order to reduce set-up cost, and then he/she offers an all-units quantity discount to the buyer. Our objective is to determine the optimal order quantity, retail price, mark-up rate, and the number of shipments per production run from the vendor to the buyer, so that the entire supply chain joint total profit incurred has a maximum value. Furthermore, an algorithm of finding the optimal solution is developed. Numerical examples are provided to illustrate the theoretical results.

Optimization of chiral structures for microscale propulsion.

PubMed

Keaveny, Eric E; Walker, Shawn W; Shelley, Michael J

2013-02-13

Recent advances in micro- and nanoscale fabrication techniques allow for the construction of rigid, helically shaped microswimmers that can be actuated using applied magnetic fields. These swimmers represent the first steps toward the development of microrobots for targeted drug delivery and minimally invasive surgical procedures. To assess the performance of these devices and improve on their design, we perform shape optimization computations to determine swimmer geometries that maximize speed in the direction of a given applied magnetic torque. We directly assess aspects of swimmer shapes that have been developed in previous experimental studies, including helical propellers with elongated cross sections and attached payloads. From these optimizations, we identify key improvements to existing designs that result in swimming speeds that are 70-470% of their original values.

Harmonic Optimization in Voltage Source Inverter for PV Application using Heuristic Algorithms

NASA Astrophysics Data System (ADS)

Kandil, Shaimaa A.; Ali, A. A.; El Samahy, Adel; Wasfi, Sherif M.; Malik, O. P.

2016-12-01

Selective Harmonic Elimination (SHE) technique is the fundamental switching frequency scheme that is used to eliminate specific order harmonics. Its application to minimize low order harmonics in a three level inverter is proposed in this paper. The modulation strategy used here is SHEPWM and the nonlinear equations, that characterize the low order harmonics, are solved using Harmony Search Algorithm (HSA) to obtain the optimal switching angles that minimize the required harmonics and maintain the fundamental at the desired value. Total Harmonic Distortion (THD) of the output voltage is minimized maintaining selected harmonics within allowable limits. A comparison has been drawn between HSA, Genetic Algorithm (GA) and Newton Raphson (NR) technique using MATLAB software to determine the effectiveness of getting optimized switching angles.

Selection of optimal welding condition for GTA pulse welding in root-pass of V-groove butt joint

NASA Astrophysics Data System (ADS)

Yun, Seok-Chul; Kim, Jae-Woong

2010-12-01

In the manufacture of high-quality welds or pipeline, a full-penetration weld has to be made along the weld joint. Therefore, root-pass welding is very important, and its conditions have to be selected carefully. In this study, an experimental method for the selection of optimal welding conditions is proposed for gas tungsten arc (GTA) pulse welding in the root pass which is done along the V-grooved butt-weld joint. This method uses response surface analysis in which the width and height of back bead are chosen as quality variables of the weld. The overall desirability function, which is the combined desirability function for the two quality variables, is used as the objective function to obtain the optimal welding conditions. In our experiments, the target values of back bead width and height are 4 mm and zero, respectively, for a V-grooved butt-weld joint of a 7-mm-thick steel plate. The optimal welding conditions could determine the back bead profile (bead width and height) as 4.012 mm and 0.02 mm. From a series of welding tests, it was revealed that a uniform and full-penetration weld bead can be obtained by adopting the optimal welding conditions determined according to the proposed method.

Value centric approaches to the design, operations and maintenance of wind turbines

NASA Astrophysics Data System (ADS)

Khadabadi, Madhur Aravind

Wind turbine maintenance is emerging as an unexpectedly high component of turbine operating cost, and there is an increasing interest in managing this cost. This thesis presents an alternative view of maintenance as a value-driver, and develops an optimization algorithm to evaluate the value delivered by different maintenance techniques. I view maintenance as an operation that moves the turbine to an improved state in which it can generate more power and, thus, earn more revenue. To implement this approach, I model the stochastic deterioration of the turbine in two dimensions: the deterioration rate, and the extent of deterioration, and then use maintenance to improve the state of the turbine. The value of the turbine is the difference between the revenue from to the power generation and the costs incurred in operation and maintenance. With a focus on blade deterioration, I evaluate the value delivered by implementing two different maintenance schemes, predictive maintenance and scheduled maintenance. An example of predictive maintenance technique is the use of Condition Monitoring Systems to precisely detect deterioration. I model Condition Monitoring System (CMS) of different degrees of fidelity, where a higher fidelity CMS would allow the blade state to be determined with a higher precision. The same model is then applied for the scheduled maintenance technique. The improved state information obtained from these techniques is then used to derive an optimal maintenance strategy. The difference between the value of the turbine with and without the inspection type can be interpreted as the value of the inspection. The results indicate that a higher fidelity (and more expensive) inspection method does not necessarily yield the highest value, and, that there is an optimal level of fidelity that results in maximum value. The results also aim to inform the operator of the impact of regional parameters such as wind speed, variance and maintenance costs to the optimal maintenance strategy. The contributions of this work are twofold. First, I present a practical approach to wind turbine valuation that takes operating and market conditions into account. This work should therefore be useful to wind farm operators, investors and decision makers. Second, I show how the value of a maintenance scheme can be explicitly assessed for different conditions.

Improved Fuzzy K-Nearest Neighbor Using Modified Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Jamaluddin; Siringoringo, Rimbun

2017-12-01

Fuzzy k-Nearest Neighbor (FkNN) is one of the most powerful classification methods. The presence of fuzzy concepts in this method successfully improves its performance on almost all classification issues. The main drawbackof FKNN is that it is difficult to determine the parameters. These parameters are the number of neighbors (k) and fuzzy strength (m). Both parameters are very sensitive. This makes it difficult to determine the values of ‘m’ and ‘k’, thus making FKNN difficult to control because no theories or guides can deduce how proper ‘m’ and ‘k’ should be. This study uses Modified Particle Swarm Optimization (MPSO) to determine the best value of ‘k’ and ‘m’. MPSO is focused on the Constriction Factor Method. Constriction Factor Method is an improvement of PSO in order to avoid local circumstances optima. The model proposed in this study was tested on the German Credit Dataset. The test of the data/The data test has been standardized by UCI Machine Learning Repository which is widely applied to classification problems. The application of MPSO to the determination of FKNN parameters is expected to increase the value of classification performance. Based on the experiments that have been done indicating that the model offered in this research results in a better classification performance compared to the Fk-NN model only. The model offered in this study has an accuracy rate of 81%, while. With using Fk-NN model, it has the accuracy of 70%. At the end is done comparison of research model superiority with 2 other classification models;such as Naive Bayes and Decision Tree. This research model has a better performance level, where Naive Bayes has accuracy 75%, and the decision tree model has 70%

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models

PubMed Central

Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra. Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra. PMID:29887907

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models.

PubMed

Yu, Li; Jin, Weifeng; Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra . Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra .

Effect of high-pressure processing on quality and stability of green mango blended mayonnaise.

PubMed

Sethi, Swati; Chauhan, O P; Anurag, Rahul K

2017-07-01

The present work was aimed to study and optimize the high pressure treated green mango blended mayonnaise in terms of oxidative and emulsion stability, as a function of technical parameters; pressure intensity, dwell period and level of green mango pulp. Mayonnaise samples were treated at different combinations of pressure (400-600 MPa), holding time (5-10 min) and level of green mango pulp (10-30%) following Box-Behnken design. Mayonnaise quality was evaluated in terms of oxidative stability and emulsion stability using response surface methodology to optimize the best possible combination among all. Analysis of variance showed that the second-order polynomial model fitted well with the experimental results. Pressure and time were the most important factors determining the oxidative stability (free fatty acids, peroxide value and anisidine value) whereas; the emulsion stability (creaming and thermal creaming) was most significantly affected by the level of green mango pulp. The optimized conditions for preparing green mango blended mayonnaise with high oxidative and emulsion stability were: 435 MPa pressure, 5 min of holding time with the addition of green mango pulp at the rate of 28%. The product prepared at optimum conditions showed good correlations between predicted and actual values.

[Optimization of formulations for dietetic pastry products].

PubMed

Villarroel, M; Uquiche, E; Brito, G; Cancino, M

2000-03-01

Optimized formulations of dietetic pastry products such as cake and sponge cake premixes were formulated using the surface response methodology. % Emulsifier agent and baking time were the selected independent variables for cake, as well as % emulsifier agent % chlorinated flour the variables selected for sponge cake. Three different level of each variable summing up thirteen experimental formulae of each product were assessed to optimize the variables that could have some influence in the sensory characteristics of these dietetic products. The total sensory quality was determined for both dietetic products using the composite scoring test and a panel of 18 trained judges. Looking at the contour graphic and considering economic aspects the best combination of variables for cake formulation was 2% emulsifier agent and 48 minutes for baking time, With respect to sponge cake, the best combination was 6% emulsifier agent and 48% chlorinated flour. Shelf life studies showed that both dietetic formulations remained stable during storage conditions of 75 days at 30 degrees C. During this period, significant differences in sensory characteristics were not found (p < 0.05). Data of peroxide values were kept under the critical value reported for detection of organoleptic rancidity. Reported values of hedonic test showed that these dietetics pastry products had good acceptability, and open up marketing opportunities for new products with potential health benefits to consumers.

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.

[Optimize preparation of compound licorice microemulsion with D-optimal design].

PubMed

Ma, Shu-Wei; Wang, Yong-Jie; Chen, Cheng; Qiu, Yue; Wu, Qing

2018-03-01

In order to increase the solubility of essential oil in compound licorice microemulsion and improve the efficacy of the decoction for treating chronic eczema, this experiment intends to prepare the decoction into microemulsion. The essential oil was used as the oil phase of the microemulsion and the extract was used as the water phase. Then the microemulsion area and maximum ratio of water capacity was obtained by plotting pseudo-ternary phase diagram, to determine the appropriate types of surfactant and cosurfactant, and Km value-the mass ratio between surfactant and cosurfactant. With particle size and skin retention of active ingredients as the index, microemulsion prescription was optimized by D-optimal design method, to investigate the in vitro release behavior of the optimized prescription. The results showed that the microemulsion was optimal with tween-80 as the surfactant and anhydrous ethanol as the cosurfactant. When the Km value was 1, the area of the microemulsion region was largest while when the concentration of extract was 0.5 g·mL⁻¹, it had lowest effect on the particle size distribution of microemulsion. The final optimized formulation was as follows: 9.4% tween-80, 9.4% anhydrous ethanol, 1.0% peppermint oil and 80.2% 0.5 g·mL⁻¹ extract. The microemulsion prepared under these conditions had a small viscosity, good stability and high skin retention of drug; in vitro release experiment showed that microemulsion had a sustained-release effect on glycyrrhizic acid and liquiritin, basically achieving the expected purpose of the project. Copyright© by the Chinese Pharmaceutical Association.

Optimization of GATE and PHITS Monte Carlo code parameters for uniform scanning proton beam based on simulation with FLUKA general-purpose code

NASA Astrophysics Data System (ADS)

Kurosu, Keita; Takashina, Masaaki; Koizumi, Masahiko; Das, Indra J.; Moskvin, Vadim P.

2014-10-01

Although three general-purpose Monte Carlo (MC) simulation tools: Geant4, FLUKA and PHITS have been used extensively, differences in calculation results have been reported. The major causes are the implementation of the physical model, preset value of the ionization potential or definition of the maximum step size. In order to achieve artifact free MC simulation, an optimized parameters list for each simulation system is required. Several authors have already proposed the optimized lists, but those studies were performed with a simple system such as only a water phantom. Since particle beams have a transport, interaction and electromagnetic processes during beam delivery, establishment of an optimized parameters-list for whole beam delivery system is therefore of major importance. The purpose of this study was to determine the optimized parameters list for GATE and PHITS using proton treatment nozzle computational model. The simulation was performed with the broad scanning proton beam. The influences of the customizing parameters on the percentage depth dose (PDD) profile and the proton range were investigated by comparison with the result of FLUKA, and then the optimal parameters were determined. The PDD profile and the proton range obtained from our optimized parameters list showed different characteristics from the results obtained with simple system. This led to the conclusion that the physical model, particle transport mechanics and different geometry-based descriptions need accurate customization in planning computational experiments for artifact-free MC simulation.

Anomaly detection of flight routes through optimal waypoint

NASA Astrophysics Data System (ADS)

Pusadan, M. Y.; Buliali, J. L.; Ginardi, R. V. H.

2017-01-01

Deciding factor of flight, one of them is the flight route. Flight route determined by coordinate (latitude and longitude). flight routed is determined by its coordinates (latitude and longitude) as defined is waypoint. anomaly occurs, if the aircraft is flying outside the specified waypoint area. In the case of flight data, anomalies occur by identifying problems of the flight route based on data ADS-B. This study has an aim of to determine the optimal waypoints of the flight route. The proposed methods: i) Agglomerative Hierarchical Clustering (AHC) in several segments based on range area coordinates (latitude and longitude) in every waypoint; ii) The coefficient cophenetics correlation (c) to determine the correlation between the members in each cluster; iii) cubic spline interpolation as a graphic representation of the has connected between the coordinates on every waypoint; and iv). Euclidean distance to measure distances between waypoints with 2 centroid result of clustering AHC. The experiment results are value of coefficient cophenetics correlation (c): 0,691≤ c ≤ 0974, five segments the generated of the range area waypoint coordinates, and the shortest and longest distance between the centroid with waypoint are 0.46 and 2.18. Thus, concluded that the shortest distance is used as the reference coordinates of optimal waypoint, and farthest distance can be indicated potentially detected anomaly.

Implementation of fuzzy logic to determining selling price of products in a local corporate chain store

NASA Astrophysics Data System (ADS)

Kristiana, S. P. D.

2017-12-01

Corporate chain store is one type of retail industries companies that are developing growing rapidly in Indonesia. The competition between retail companies is very tight, so retailer companies should evaluate its performance continuously in order to survive. The selling price of products is one of the essential attributes and gets attention of many consumers where it’s used to evaluate the performance of the industry. This research aimed to determine optimal selling price of product with considering cost factors, namely purchase price of the product from supplier, holding costs, and transportation costs. Fuzzy logic approach is used in data processing with MATLAB software. Fuzzy logic is selected to solve the problem because this method can consider complexities factors. The result is a model of determination of the optimal selling price by considering three cost factors as inputs in the model. Calculating MAPE and model prediction ability for some products are used as validation and verification where the average value is 0.0525 for MAPE and 94.75% for prediction ability. The conclusion is this model can predict the selling price of up to 94.75%, so it can be used as tools for the corporate chain store in particular to determine the optimal selling price for its products.

Implementation of Particle Swarm Optimization Method for Voltage Stability Analysis in 150 kV Sub System Grati – Paiton East Java

NASA Astrophysics Data System (ADS)

Kusumaningtyas, A. B.; Hidayat, M. N.; Ronilaya, F.

2018-04-01

Based on the data from State Electric Company on 15 January 2013, the undistributed power in the 150 kV sub system Grati-Paiton Region IV, that consist of 26 bus 150 kV and 2 bus generation 500 kV system, was recorded 3.286,00 MW. At the same time, the frequency of the system was down to 49 Hz. This lead to a deficit generation and unstable voltage condition in the system. Fast Voltage Stability Index (FVSI) method is used in this research to analyze the voltage stability of the buses. For buses with unstable voltage condition, reactive power will be injected through capacitor installation. The site where the capacitor will be installed is determined using the Fast Voltage Stability Index (FVSI) method while the size of the capacitor is determined using the Particle Swarm Optimization (PSO) method. The PSO method has been applied in some researches, such as to determine optimal placement and sizing in radial distribution network as well as in transmission network.. In this research, the PSO method is used to find the Qloss of an interconnection transmission system, which in turn, the value of the Qloss is used to determine the capacitance of the capacitor needed by the system.

Optimal allocation of conservation resources to species that may be extinct.

PubMed

Rout, Tracy M; Heinze, Dean; McCarthy, Michael A

2010-08-01

Statements of extinction will always be uncertain because of imperfect detection of species in the wild. Two errors can be made when declaring a species extinct. Extinction can be declared prematurely, with a resulting loss of protection and management intervention. Alternatively, limited conservation resources can be wasted attempting to protect a species that no longer exists. Rather than setting an arbitrary level of certainty at which to declare extinction, we argue that the decision must trade off the expected costs of both errors. Optimal decisions depend on the cost of continued intervention, the probability the species is extant, and the estimated value of management (the benefit of management times the value of the species). We illustrated our approach with three examples: the Dodo (Raphus cucullatus), the Ivory-billed Woodpecker (U.S. subspecies Campephilus principalis principalis), and the mountain pygmy-possum (Burramys parvus). The dodo was extremely unlikely to be extant, so managing and monitoring for it today would not be cost-effective unless the value of management was extremely high. The probability the Ivory-billed woodpecker is extant depended on whether recent controversial sightings were accepted. Without the recent controversial sightings, it was optimal to declare extinction of the species in 1965 at the latest. Accepting the recent controversial sightings, it was optimal to continue monitoring and managing until 2032 at the latest. The mountain pygmy-possum is currently extant, with a rapidly declining sighting rate. It was optimal to conduct as many as 66 surveys without sighting before declaring the species extinct. The probability of persistence remained high even after many surveys without sighting because it was difficult to determine whether the species was extinct or undetected. If the value of management is high enough, continued intervention can be cost-effective even if the species is likely to be extinct.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS.

PubMed

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-11-04

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

PubMed Central

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-01-01

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM. PMID:28774019

Battery Storage Evaluation Tool, version 1.x

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

2015-10-02

The battery storage evaluation tool developed at Pacific Northwest National Laboratory is used to run a one-year simulation to evaluate the benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a lookahead optimization is first formulated and solved to determine the battery base operating point. The minute-by-minute simulation is then performed to simulate the actual battery operation.

Analysis of an inventory model for both linearly decreasing demand and holding cost

NASA Astrophysics Data System (ADS)

Malik, A. K.; Singh, Parth Raj; Tomar, Ajay; Kumar, Satish; Yadav, S. K.

2016-03-01

This study proposes the analysis of an inventory model for linearly decreasing demand and holding cost for non-instantaneous deteriorating items. The inventory model focuses on commodities having linearly decreasing demand without shortages. The holding cost doesn't remain uniform with time due to any form of variation in the time value of money. Here we consider that the holding cost decreases with respect to time. The optimal time interval for the total profit and the optimal order quantity are determined. The developed inventory model is pointed up through a numerical example. It also includes the sensitivity analysis.

Optimizing any-aged management of mixed-species stands: II. effects of decision criteria

Treesearch

Robert G. Haight; Robert A. Monserud

1990-01-01

The effects of maximum present value and maximum volume objectives on the efficiencies of alternative silvicultural systems are determined by solving any-aged management problems for mixed-conifer stands in the Northern Rocky Mountains. Any-aged management problems are formulated with periodic planting and harvesting controls and without constraints on the stand age or...

An integer programming model to optimize resource allocation for wildfire containment.

Treesearch

Geoffrey H. Donovan; Douglas B. Rideout

2003-01-01

Determining the specific mix of fire-fighting resources for a given fire is a necessary condition for identifying the minimum of the Cost Plus Net Value Change (C+NVC) function. Current wildland fire management models may not reliably do so. The problem of identifying the most efficient wildland fire organization is characterized mathematically using integer-...

An efficient framework for optimization and parameter sensitivity analysis in arterial growth and remodeling computations

PubMed Central

Sankaran, Sethuraman; Humphrey, Jay D.; Marsden, Alison L.

2013-01-01

Computational models for vascular growth and remodeling (G&R) are used to predict the long-term response of vessels to changes in pressure, flow, and other mechanical loading conditions. Accurate predictions of these responses are essential for understanding numerous disease processes. Such models require reliable inputs of numerous parameters, including material properties and growth rates, which are often experimentally derived, and inherently uncertain. While earlier methods have used a brute force approach, systematic uncertainty quantification in G&R models promises to provide much better information. In this work, we introduce an efficient framework for uncertainty quantification and optimal parameter selection, and illustrate it via several examples. First, an adaptive sparse grid stochastic collocation scheme is implemented in an established G&R solver to quantify parameter sensitivities, and near-linear scaling with the number of parameters is demonstrated. This non-intrusive and parallelizable algorithm is compared with standard sampling algorithms such as Monte-Carlo. Second, we determine optimal arterial wall material properties by applying robust optimization. We couple the G&R simulator with an adaptive sparse grid collocation approach and a derivative-free optimization algorithm. We show that an artery can achieve optimal homeostatic conditions over a range of alterations in pressure and flow; robustness of the solution is enforced by including uncertainty in loading conditions in the objective function. We then show that homeostatic intramural and wall shear stress is maintained for a wide range of material properties, though the time it takes to achieve this state varies. We also show that the intramural stress is robust and lies within 5% of its mean value for realistic variability of the material parameters. We observe that prestretch of elastin and collagen are most critical to maintaining homeostasis, while values of the material properties are most critical in determining response time. Finally, we outline several challenges to the G&R community for future work. We suggest that these tools provide the first systematic and efficient framework to quantify uncertainties and optimally identify G&R model parameters. PMID:23626380

Optimal Sampling to Provide User-Specific Climate Information.

NASA Astrophysics Data System (ADS)

Panturat, Suwanna

The types of weather-related world problems which are of socio-economic importance selected in this study as representative of three different levels of user groups include: (i) a regional problem concerned with air pollution plumes which lead to acid rain in the north eastern United States, (ii) a state-level problem in the form of winter wheat production in Oklahoma, and (iii) an individual-level problem involving reservoir management given errors in rainfall estimation at Lake Ellsworth, upstream from Lawton, Oklahoma. The study is aimed at designing optimal sampling networks which are based on customer value systems and also abstracting from data sets that information which is most cost-effective in reducing the climate-sensitive aspects of a given user problem. Three process models being used in this study to interpret climate variability in terms of the variables of importance to the user comprise: (i) the HEFFTER-SAMSON diffusion model as the climate transfer function for acid rain, (ii) the CERES-MAIZE plant process model for winter wheat production and (iii) the AGEHYD streamflow model selected as "a black box" for reservoir management. A state-of-the-art Non Linear Program (NLP) algorithm for minimizing an objective function is employed to determine the optimal number and location of various sensors. Statistical quantities considered in determining sensor locations including Bayes Risk, the chi-squared value, the probability of the Type I error (alpha) and the probability of the Type II error (beta) and the noncentrality parameter delta^2. Moreover, the number of years required to detect a climate change resulting in a given bushel per acre change in mean wheat production is determined; the number of seasons of observations required to reduce the standard deviation of the error variance of the ambient sulfur dioxide to less than a certain percent of the mean is found; and finally the policy of maintaining pre-storm flood pools at selected levels is examined given information from the optimal sampling network as defined by the study.

Application of Differential Evolutionary Optimization Methodology for Parameter Structure Identification in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Chiu, Y.; Nishikawa, T.

2013-12-01

With the increasing complexity of parameter-structure identification (PSI) in groundwater modeling, there is a need for robust, fast, and accurate optimizers in the groundwater-hydrology field. For this work, PSI is defined as identifying parameter dimension, structure, and value. In this study, Voronoi tessellation and differential evolution (DE) are used to solve the optimal PSI problem. Voronoi tessellation is used for automatic parameterization, whereby stepwise regression and the error covariance matrix are used to determine the optimal parameter dimension. DE is a novel global optimizer that can be used to solve nonlinear, nondifferentiable, and multimodal optimization problems. It can be viewed as an improved version of genetic algorithms and employs a simple cycle of mutation, crossover, and selection operations. DE is used to estimate the optimal parameter structure and its associated values. A synthetic numerical experiment of continuous hydraulic conductivity distribution was conducted to demonstrate the proposed methodology. The results indicate that DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters (i.e., the population size, mutation scaling factor, crossover rate, and mutation schemes) was performed to examine their influence on the objective function. The proposed DE was then applied to solve a complex parameter-estimation problem for a small desert groundwater basin in Southern California. Hydraulic conductivity, specific yield, specific storage, fault conductance, and recharge components were estimated simultaneously. Comparison of DE and a traditional gradient-based approach (PEST) shows DE to be more robust and efficient. The results of this work not only provide an alternative for PSI in groundwater models, but also extend DE applications towards solving complex, regional-scale water management optimization problems.

Optimization and characterization of gelatin and chitosan extracted from fish and shrimp waste

NASA Astrophysics Data System (ADS)

Ait Boulahsen, M.; Chairi, H.; Laglaoui, A.; Arakrak, A.; Zantar, S.; Bakkali, M.; Hassani, M.

2018-05-01

Fish and seafood processing industries generate large quantities of waste which are at the origin of several environmental, economic and social problems. However fish waste could contain high value-added substances such as biopolymers. This work focuses on optimizing the gelatin and chitosan extraction from tilapia fish skins and shrimp shells respectively. The gelatin extraction process was optimized using alkali acid treatment prior to thermal hydrolysis. Three different acids were tested at different concentrations. Chitosan was obtained after acid demineralization followed by simultaneous hydrothermal deproteinization and deacetylation by an alkali treatment with different concentrations of HCl and NaOH. The extracted gelatin and chitosan with the highest yield were characterized by determining their main physicochemical properties (Degree of deacetylation, viscosity, pH, moisture and ash content). Results show a significant influence of the acid type and concentration on the extraction yield of gelatin and chitosan, with an average yield of 12.24% and 3.85% respectively. Furthermore, the obtained physicochemical properties of both extracted gelatin and chitosan were within the recommended standard values of the commercial ones used in the industry.

Application of response surface methodology (RSM) for the removal of methylene blue dye from water by nano zero-valent iron (NZVI).

PubMed

Khosravi, Morteza; Arabi, Simin

In this study, iron zero-valent nanoparticles were synthesized, characterized and studied for removal of methylene blue dye in water solution. The reactions were mathematically described as the function of parameters such as nano zero-valent iron (NZVI) dose, pH, contact time and initial dye concentration, and were modeled by the use of response surface methodology. These experiments were carried out as a central composite design consisting of 30 experiments determined by the 2(4) full factorial designs with eight axial points and six center points. The results revealed that the optimal conditions for dye removal were NZVI dose 0.1-0.9 g/L, pH 3-11, contact time 20-100 s, and initial dye concentration 10-50 mg/L, respectively. Under these optimal values of process parameters, the dye removal efficiency of 92.87% was observed, which very close to the experimental value (92.21%) in batch experiment. In the optimization, R(2) and R(2)adj correlation coefficients for the model were evaluated as 0.96 and 0.93, respectively.

Optimization of data retrieval process for spectroscopic CO2 isotopologue ratio measurements

NASA Astrophysics Data System (ADS)

Hovorka, J.; Čermák, P.; Veis, P.

2017-05-01

In this work, a numerical model was developed for critical evaluation of the 13CO2/12CO2 ratio retrievals ( Δ δ value) from laser absorption spectra. The goal of the analysis was to determine the dependency of the absolute error of δ on different experimental parameters, in order to find the optimal conditions for isotopic ratio retrievals without using calibrated reference samples. In our study, the target precision for Δ δ was set at a level of ≤slant 1 %. The analysis was performed in the spectral range of the {ν1}+{ν3} CO2 band at 1.6 μm, with the theoretical data originating from the HITRAN database. The proposed fitting algorithm allowed efficient compensation of the interference from weak transitions which are not well recognizable in a single spectrum. This effect was found to make a dominant contribution to the Δ δ value. Next, the optimal conditions for such an experiment regarding the pressure, spectral range and spectrum noise were found and discussed from the perspective of widely tunable laser applications.

Predictive value of serum β-hCG for early pregnancy outcomes among women with recurrent spontaneous abortion.

PubMed

Liu, Yinglin; Liu, Yukun; Li, Xuejiao; Jiao, Xuedan; Zhang, Rui; Zhang, Jianping

2016-10-01

To examine peak serum levels of the β-subunit of human chorionic gonadotropin (β-hCG) for prediction of early pregnancy outcomes among women with recurrent spontaneous abortion (RSA). In a retrospective study, the medical records of pregnant women with a history of RSA treated at Sun Yat-sen Memorial Hospital, China, between January 2011 and July 2013 were reviewed. Serum β-hCG had been measured twice weekly from 5 to 13weeks of pregnancy, and pregnancy was monitored by transvaginal ultrasonography to 13(+6)weeks. Optimal cutoff for peak β-hCG level was determined by receiver operator characteristic curve analysis and Youden index. Women were divided into four groups on the basis of optimal peak β-hCG cutoff and pregnancy outcome (pregnancy at 13weeks or spontaneous abortion). Peak β-hCG levels and length of pregnancy at this peak were examined. Overall, 1240 patients were included. The optimal cutoff value of peak β-hCG was 88 468IU/L, with a sensitivity, specificity, positive predictive value, and negative predictive value for successful pregnancy of 95.6%, 88.0%, 95.6%, and 89.0%, respectively. A faster rise in β-hCG, higher peak β-hCG, and longer pregnancy length at peak β-hCG were associated with successful early pregnancy. A cutoff value of serum β-hCG of 88 000IU/L could be used to predict early pregnancy outcomes for women with a history of RSA. Copyright © 2016. Published by Elsevier Ireland Ltd.

Selection, Evaluation, and Rating of Compact Heat Exchangers v. 1.006

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

Carlson, Matthew D.

2016-11-09

SEARCH determines and optimizes the design of a compact heat exchanger for specified process conditions. The user specifies process boundary conditions including the fluid state and flow rate and SEARCH will determine the optimum flow arrangement, channel geometry, and mechanical design for the unit. Fluids are modeled using NIST Refprop or tabulated values. A variety of thermal-hydraulic correlations are available including user-defined equations to accurately capture the heat transfer and pressure drop behavior of the process flows.

Cluster analysis of stress corrosion mechanisms for steel wires used in bridge cables through acoustic emission particle swarm optimization.

PubMed

Li, Dongsheng; Yang, Wei; Zhang, Wenyao

2017-05-01

Stress corrosion is the major failure type of bridge cable damage. The acoustic emission (AE) technique was applied to monitor the stress corrosion process of steel wires used in bridge cable structures. The damage evolution of stress corrosion in bridge cables was obtained according to the AE characteristic parameter figure. A particle swarm optimization cluster method was developed to determine the relationship between the AE signal and stress corrosion mechanisms. Results indicate that the main AE sources of stress corrosion in bridge cables included four types: passive film breakdown and detachment of the corrosion product, crack initiation, crack extension, and cable fracture. By analyzing different types of clustering data, the mean value of each damage pattern's AE characteristic parameters was determined. Different corrosion damage source AE waveforms and the peak frequency were extracted. AE particle swarm optimization cluster analysis based on principal component analysis was also proposed. This method can completely distinguish the four types of damage sources and simplifies the determination of the evolution process of corrosion damage and broken wire signals. Copyright © 2017. Published by Elsevier B.V.

Optimal control and optimal trajectories of regional macroeconomic dynamics based on the Pontryagin maximum principle

NASA Astrophysics Data System (ADS)

Bulgakov, V. K.; Strigunov, V. V.

2009-05-01

The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.

Constrained Optimization of Average Arrival Time via a Probabilistic Approach to Transport Reliability

PubMed Central

Namazi-Rad, Mohammad-Reza; Dunbar, Michelle; Ghaderi, Hadi; Mokhtarian, Payam

2015-01-01

To achieve greater transit-time reduction and improvement in reliability of transport services, there is an increasing need to assist transport planners in understanding the value of punctuality; i.e. the potential improvements, not only to service quality and the consumer but also to the actual profitability of the service. In order for this to be achieved, it is important to understand the network-specific aspects that affect both the ability to decrease transit-time, and the associated cost-benefit of doing so. In this paper, we outline a framework for evaluating the effectiveness of proposed changes to average transit-time, so as to determine the optimal choice of average arrival time subject to desired punctuality levels whilst simultaneously minimizing operational costs. We model the service transit-time variability using a truncated probability density function, and simultaneously compare the trade-off between potential gains and increased service costs, for several commonly employed cost-benefit functions of general form. We formulate this problem as a constrained optimization problem to determine the optimal choice of average transit time, so as to increase the level of service punctuality, whilst simultaneously ensuring a minimum level of cost-benefit to the service operator. PMID:25992902

Monte Carlo calculations of electron beam quality conversion factors for several ion chamber types.

PubMed

Muir, B R; Rogers, D W O

2014-11-01

To provide a comprehensive investigation of electron beam reference dosimetry using Monte Carlo simulations of the response of 10 plane-parallel and 18 cylindrical ion chamber types. Specific emphasis is placed on the determination of the optimal shift of the chambers' effective point of measurement (EPOM) and beam quality conversion factors. The EGSnrc system is used for calculations of the absorbed dose to gas in ion chamber models and the absorbed dose to water as a function of depth in a water phantom on which cobalt-60 and several electron beam source models are incident. The optimal EPOM shifts of the ion chambers are determined by comparing calculations of R50 converted from I50 (calculated using ion chamber simulations in phantom) to R50 calculated using simulations of the absorbed dose to water vs depth in water. Beam quality conversion factors are determined as the calculated ratio of the absorbed dose to water to the absorbed dose to air in the ion chamber at the reference depth in a cobalt-60 beam to that in electron beams. For most plane-parallel chambers, the optimal EPOM shift is inside of the active cavity but different from the shift determined with water-equivalent scaling of the front window of the chamber. These optimal shifts for plane-parallel chambers also reduce the scatter of beam quality conversion factors, kQ, as a function of R50. The optimal shift of cylindrical chambers is found to be less than the 0.5 rcav recommended by current dosimetry protocols. In most cases, the values of the optimal shift are close to 0.3 rcav. Values of kecal are calculated and compared to those from the TG-51 protocol and differences are explained using accurate individual correction factors for a subset of ion chambers investigated. High-precision fits to beam quality conversion factors normalized to unity in a beam with R50 = 7.5 cm (kQ (')) are provided. These factors avoid the use of gradient correction factors as used in the TG-51 protocol although a chamber dependent optimal shift in the EPOM is required when using plane-parallel chambers while no shift is needed with cylindrical chambers. The sensitivity of these results to parameters used to model the ion chambers is discussed and the uncertainty related to the practical use of these results is evaluated. These results will prove useful as electron beam reference dosimetry protocols are being updated. The analysis of this work indicates that cylindrical ion chambers may be appropriate for use in low-energy electron beams but measurements are required to characterize their use in these beams.

Standardization and validation of a cytometric bead assay to assess antibodies to multiple Plasmodium falciparum recombinant antigens

PubMed Central

2012-01-01

Background Multiplex cytometric bead assay (CBA) have a number of advantages over ELISA for antibody testing, but little information is available on standardization and validation of antibody CBA to multiple Plasmodium falciparum antigens. The present study was set to determine optimal parameters for multiplex testing of antibodies to P. falciparum antigens, and to compare results of multiplex CBA to ELISA. Methods Antibodies to ten recombinant P. falciparum antigens were measured by CBA and ELISA in samples from 30 individuals from a malaria endemic area of Kenya and compared to known positive and negative control plasma samples. Optimal antigen amounts, monoplex vs multiplex testing, plasma dilution, optimal buffer, number of beads required were assessed for CBA testing, and results from CBA vs. ELISA testing were compared. Results Optimal amounts for CBA antibody testing differed according to antigen. Results for monoplex CBA testing correlated strongly with multiplex testing for all antigens (r = 0.88-0.99, P values from <0.0001 - 0.004), and antibodies to variants of the same antigen were accurately distinguished within a multiplex reaction. Plasma dilutions of 1:100 or 1:200 were optimal for all antigens for CBA testing. Plasma diluted in a buffer containing 0.05% sodium azide, 0.5% polyvinylalcohol, and 0.8% polyvinylpyrrolidone had the lowest background activity. CBA median fluorescence intensity (MFI) values with 1,000 antigen-conjugated beads/well did not differ significantly from MFI with 5,000 beads/well. CBA and ELISA results correlated well for all antigens except apical membrane antigen-1 (AMA-1). CBA testing produced a greater range of values in samples from malaria endemic areas and less background reactivity for blank samples than ELISA. Conclusion With optimization, CBA may be the preferred method of testing for antibodies to P. falciparum antigens, as CBA can test for antibodies to multiple recombinant antigens from a single plasma sample and produces a greater range of values in positive samples and lower background readings for blank samples than ELISA. PMID:23259607

Optimization Research on Ampacity of Underground High Voltage Cable Based on Interior Point Method

NASA Astrophysics Data System (ADS)

Huang, Feng; Li, Jing

2017-12-01

The conservative operation method which takes unified current-carrying capacity as maximum load current can’t make full use of the overall power transmission capacity of the cable. It’s not the optimal operation state for the cable cluster. In order to improve the transmission capacity of underground cables in cluster, this paper regards the maximum overall load current as the objective function and the temperature of any cables lower than maximum permissible temperature as constraint condition. The interior point method which is very effective for nonlinear problem is put forward to solve the extreme value of the problem and determine the optimal operating current of each loop. The results show that the optimal solutions obtained with the purposed method is able to increase the total load current about 5%. It greatly improves the economic performance of the cable cluster.

g Factor of Light Ions for an Improved Determination of the Fine-Structure Constant.

PubMed

Yerokhin, V A; Berseneva, E; Harman, Z; Tupitsyn, I I; Keitel, C H

2016-03-11

A weighted difference of the g factors of the H- and Li-like ions of the same element is theoretically studied and optimized in order to maximize the cancellation of nuclear effects between the two charge states. We show that this weighted difference and its combination for two different elements can be used to extract a value for the fine-structure constant from near-future bound-electron g factor experiments with an accuracy competitive with or better than the present literature value.

Wireless Sensor Network Quality of Service Improvement on Flooding Attack Condition

NASA Astrophysics Data System (ADS)

Hartono, R.; Widyawan; Wibowo, S. B.; Purnomo, A.; Hartatik

2018-03-01

There are two methods of building communication using wireless media. The first method is building a base infrastructure as an intermediary between users. Problems that arise on this type of network infrastructure is limited space to build any network physical infrastructure and also the cost factor. The second method is to build an ad hoc network between users who will communicate. On ad hoc network, each user must be willing to send data from source to destination for the occurrence of a communication. One of network protocol in Ad Hoc, Ad hoc on demand Distance Vector (AODV), has the smallest overhead value, easier to adapt to dynamic network and has small control message. One AODV protocol’s drawback is route finding process’ security for sending the data. In this research, AODV protocol is optimized by determining Expanding Ring Search (ERS) best value. Random topology is used with variation in the number of nodes: 25, 50, 75, 100, 125 and 150 with node’s speed of 10m/s in the area of 1000m x 1000m on flooding network condition. Parameters measured are Throughput, Packet Delivery Ratio, Average Delay and Normalized Routing Load. From the test results of AODV protocol optimization with best value of Expanding Ring Search (ERS), throughput increased by 5.67%, packet delivery ratio increased by 5.73%, and as for Normalized Routing Load decreased by 4.66%. ERS optimal value for each node’s condition depending on the number of nodes on the network.

System level analysis and control of manufacturing process variation

DOEpatents

Hamada, Michael S.; Martz, Harry F.; Eleswarpu, Jay K.; Preissler, Michael J.

2005-05-31

A computer-implemented method is implemented for determining the variability of a manufacturing system having a plurality of subsystems. Each subsystem of the plurality of subsystems is characterized by signal factors, noise factors, control factors, and an output response, all having mean and variance values. Response models are then fitted to each subsystem to determine unknown coefficients for use in the response models that characterize the relationship between the signal factors, noise factors, control factors, and the corresponding output response having mean and variance values that are related to the signal factors, noise factors, and control factors. The response models for each subsystem are coupled to model the output of the manufacturing system as a whole. The coefficients of the fitted response models are randomly varied to propagate variances through the plurality of subsystems and values of signal factors and control factors are found to optimize the output of the manufacturing system to meet a specified criterion.

An Efficient Method Coupling Kernel Principal Component Analysis with Adjoint-Based Optimal Control and Its Goal-Oriented Extensions

NASA Astrophysics Data System (ADS)

Thimmisetty, C.; Talbot, C.; Tong, C. H.; Chen, X.

2016-12-01

The representativeness of available data poses a significant fundamental challenge to the quantification of uncertainty in geophysical systems. Furthermore, the successful application of machine learning methods to geophysical problems involving data assimilation is inherently constrained by the extent to which obtainable data represent the problem considered. We show how the adjoint method, coupled with optimization based on methods of machine learning, can facilitate the minimization of an objective function defined on a space of significantly reduced dimension. By considering uncertain parameters as constituting a stochastic process, the Karhunen-Loeve expansion and its nonlinear extensions furnish an optimal basis with respect to which optimization using L-BFGS can be carried out. In particular, we demonstrate that kernel PCA can be coupled with adjoint-based optimal control methods to successfully determine the distribution of material parameter values for problems in the context of channelized deformable media governed by the equations of linear elasticity. Since certain subsets of the original data are characterized by different features, the convergence rate of the method in part depends on, and may be limited by, the observations used to furnish the kernel principal component basis. By determining appropriate weights for realizations of the stochastic random field, then, one may accelerate the convergence of the method. To this end, we present a formulation of Weighted PCA combined with a gradient-based means using automatic differentiation to iteratively re-weight observations concurrent with the determination of an optimal reduced set control variables in the feature space. We demonstrate how improvements in the accuracy and computational efficiency of the weighted linear method can be achieved over existing unweighted kernel methods, and discuss nonlinear extensions of the algorithm.

Determining optimal gestational weight gain in the Korean population: a retrospective cohort study.

PubMed

Choi, Sae Kyung; Lee, Guisera; Kim, Yeon Hee; Park, In Yang; Ko, Hyun Sun; Shin, Jong Chul

2017-08-22

The World Health Organization (WHO) international body mass index (BMI) cut-off points defining pre-pregnancy BMI categories in the Institute of Medicine (IOM) guidelines are not directly applicable to Asians. We aimed to define the optimal gestational weight gain (GWG) for the Korean population based on Asia-specific BMI categories. Data from 2702 live singleton deliveries in three tertiary centers between 2010 and 2011 were analyzed retrospectively. A multivariable logistic regression analysis was conducted to determine the lowest aggregated risk of composite perinatal outcomes based on Asia-specific BMI categories. The perinatal outcomes included gestational hypertensive disorder, emergency cesarean section, and fetal size for gestational age. In each BMI category, the GWG value corresponding to the lowest aggregated risk was defined as the optimal GWG. Among the study population, 440 (16.3%) were underweight (BMI < 18.5), 1459 (54.0%) were normal weight (18.5 ≤ BMI < 23), 392 (14.5%) were overweight (23 ≤ BMI < 25) and 411 (15.2%) were obese (BMI ≥ 25). The optimal GWG by Asia-specific BMI category was 20.8 kg (range, 16.7 to 24.7) for underweight, 16.6 kg (11.5 to 21.5) for normal weight, 13.1 kg (8.0 to 17.7) for overweight, and 14.4 kg (7.5 to 21.9) for obese. Considerably higher and wider optimal GWG ranges than recommended by IOM are found in our study in order to avoid adverse perinatal outcomes. Revised IOM recommendations for GWG could be considered for Korean women according to Asian BMI categories. Further prospective studies are needed in order to determine the optimal GWG for the Korean population.

Quantitative colorimetry of atherosclerotic plaque using the L*a*b* color space during angioscopy for the detection of lipid cores underneath thin fibrous caps.

PubMed

Ishibashi, Fumiyuki; Yokoyama, Shinya; Miyahara, Kengo; Dabreo, Alexandra; Weiss, Eric R; Iafrati, Mark; Takano, Masamichi; Okamatsu, Kentaro; Mizuno, Kyoichi; Waxman, Sergio

2007-12-01

Yellow plaques seen during angioscopy are thought to represent lipid cores underneath thin fibrous caps (LCTCs) and may be indicative of vulnerable sites. However, plaque color assessment during angioscopy has been criticized because of its qualitative nature. The purpose of the present study was to test the ability of a quantitative colorimetric system to measure yellow color intensity of atherosclerotic plaques during angioscopy and to characterize the color of LCTCs. Using angioscopy and a quantitative colorimetry system based on the L*a*b* color space [L* describes brightness (-100 to +100), b* describes blue to yellow (-100 to +100)], the optimal conditions for measuring plaque color were determined in three flat standard color samples and five artificial plaque models in cylinder porcine carotid arteries. In 88 human tissue samples, the colorimetric characteristics of LCTCs were then evaluated. In in-vitro samples and ex-vivo plaque models, brightness L* between 40 and 80 was determined to be optimal for acquiring b* values, and the variables unique to angioscopy in color perception did not impact b* values after adjusting for brightness L* by manipulating light or distance. In ex-vivo human tissue samples, b* value >/=23 (35.91 +/- 8.13) with L* between 40 and 80 was associated with LCTCs (fibrous caps <100 mum). Atherosclerotic plaque color can be consistently measured during angioscopy with quantitative colorimetry. High yellow color intensity, determined by this system, was associated with LCTCs. Quantitative colorimetry during angioscopy may be used for detection of LCTCs, which may be markers of vulnerability.

Modal Damping Ratio and Optimal Elastic Moduli of Human Body Segments for Anthropometric Vibratory Model of Standing Subjects.

PubMed

Gupta, Manoj; Gupta, T C

2017-10-01

The present study aims to accurately estimate inertial, physical, and dynamic parameters of human body vibratory model consistent with physical structure of the human body that also replicates its dynamic response. A 13 degree-of-freedom (DOF) lumped parameter model for standing person subjected to support excitation is established. Model parameters are determined from anthropometric measurements, uniform mass density, elastic modulus of individual body segments, and modal damping ratios. Elastic moduli of ellipsoidal body segments are initially estimated by comparing stiffness of spring elements, calculated from a detailed scheme, and values available in literature for same. These values are further optimized by minimizing difference between theoretically calculated platform-to-head transmissibility ratio (TR) and experimental measurements. Modal damping ratios are estimated from experimental transmissibility response using two dominant peaks in the frequency range of 0-25 Hz. From comparison between dynamic response determined form modal analysis and experimental results, a set of elastic moduli for different segments of human body and a novel scheme to determine modal damping ratios from TR plots, are established. Acceptable match between transmissibility values calculated from the vibratory model and experimental measurements for 50th percentile U.S. male, except at very low frequencies, establishes the human body model developed. Also, reasonable agreement obtained between theoretical response curve and experimental response envelop for average Indian male, affirms the technique used for constructing vibratory model of a standing person. Present work attempts to develop effective technique for constructing subject specific damped vibratory model based on its physical measurements.

Performance evaluation of laser induced breakdown spectroscopy in the measurement of liquid and solid samples

NASA Astrophysics Data System (ADS)

Bilge, Gonca; Sezer, Banu; Boyaci, Ismail Hakki; Eseller, Kemal Efe; Berberoglu, Halil

2018-07-01

Liquid analysis by using LIBS is a complicated process due to difficulties encountered during the collection of light and formation of plasma in liquid. To avoid these, some applications are performed such as aerosol formation and transforming liquid into solid state. However, performance of LIBS in liquid samples still remains a challenging issue. In this study, performance evaluation of LIBS and parameter optimizations in liquid and solid phase samples were performed. For this purpose, milk was chosen as model sample; milk powder was used as solid sample, and milk was used as liquid sample in the experiments. Different experimental setups have been constructed for each sampling technique, and optimizations were performed to determine suitable parameters such as delay time, laser energy, repetition rate and speed of rotary table for solid sampling technique, and flow rate of carrier gas for liquid sampling technique. Target element was determined as Ca, which is a critically important element in milk for determining its nutritional value and Ca addition. In optimum parameters, limit of detection (LOD), limit of quantification (LOQ) and relative standard deviation (RSD) values were calculated as 0.11%, 0.36% and 8.29% respectively for milk powders samples; while LOD, LOQ and RSD values were calculated as 0.24%, 0.81%, and 10.93% respectively for milk samples. It can be said that LIBS is an applicable method in both liquid and solid samples with suitable systems and parameters. However, liquid analysis requires much more developed systems for more accurate results.

Optimal control of vaccination rate in an epidemiological model of Clostridium difficile transmission.

PubMed

Stephenson, Brittany; Lanzas, Cristina; Lenhart, Suzanne; Day, Judy

2017-12-01

The spore-forming, gram-negative bacteria Clostridium difficile can cause severe intestinal illness. A striking increase in the number of cases of C. difficile infection (CDI) among hospitals has highlighted the need to better understand how to prevent the spread of CDI. In our paper, we modify and update a compartmental model of nosocomial C. difficile transmission to include vaccination. We then apply optimal control theory to determine the time-varying optimal vaccination rate that minimizes a combination of disease prevalence and spread in the hospital population as well as cost, in terms of time and money, associated with vaccination. Various hospital scenarios are considered, such as times of increased antibiotic prescription rate and times of outbreak, to see how such scenarios modify the optimal vaccination rate. By comparing the values of the objective functional with constant vaccination rates to those with time-varying optimal vaccination rates, we illustrate the benefits of time-varying controls.

An artificial system for selecting the optimal surgical team.

PubMed

Saberi, Nahid; Mahvash, Mohsen; Zenati, Marco

2015-01-01

We introduce an intelligent system to optimize a team composition based on the team's historical outcomes and apply this system to compose a surgical team. The system relies on a record of the procedures performed in the past. The optimal team composition is the one with the lowest probability of unfavorable outcome. We use the theory of probability and the inclusion exclusion principle to model the probability of team outcome for a given composition. A probability value is assigned to each person of database and the probability of a team composition is calculated from them. The model allows to determine the probability of all possible team compositions even if there is no recoded procedure for some team compositions. From an analytical perspective, assembling an optimal team is equivalent to minimizing the overlap of team members who have a recurring tendency to be involved with procedures of unfavorable results. A conceptual example shows the accuracy of the proposed system on obtaining the optimal team.

Valence electronic structure of cobalt phthalocyanine from an optimally tuned range-separated hybrid functional.

PubMed

Brumboiu, Iulia Emilia; Prokopiou, Georgia; Kronik, Leeor; Brena, Barbara

2017-07-28

We analyse the valence electronic structure of cobalt phthalocyanine (CoPc) by means of optimally tuning a range-separated hybrid functional. The tuning is performed by modifying both the amount of short-range exact exchange (α) included in the hybrid functional and the range-separation parameter (γ), with two strategies employed for finding the optimal γ for each α. The influence of these two parameters on the structural, electronic, and magnetic properties of CoPc is thoroughly investigated. The electronic structure is found to be very sensitive to the amount and range in which the exact exchange is included. The electronic structure obtained using the optimal parameters is compared to gas-phase photo-electron data and GW calculations, with the unoccupied states additionally compared with inverse photo-electron spectroscopy measurements. The calculated spectrum with tuned γ, determined for the optimal value of α = 0.1, yields a very good agreement with both experimental results and with GW calculations that well-reproduce the experimental data.

Physical characterization and optimal magnification of a portal imaging system

NASA Astrophysics Data System (ADS)

Bissonnette, Jean-Pierre; Jaffray, David A.; Fenster, Aaron; Munro, Peter

1992-06-01

One problem in radiation therapy is ensuring accurate positioning of the patient so that the prescribed dose is delivered to the diseased regions while healthy tissues are spared. Positioning is usually assessed by exposing film to the high-energy treatment beam. Unfortunately, these films exhibit poor image quality (primarily due to low subject contrast) and the development delays make film impractical to check patient positioning routinely. Therefore, we have been developing a digital video-based imaging system to replace film. The system consists of a copper plate/fluorescent screen detector, a 45 degree(s) mirror, and a TV camera equipped with a large aperture lens. We have determined the signal and noise transfer properties of the imaging system by measuring its MTF(f) and NPS(f) and used these valued to estimate the optimal magnification for the imaging system. We have found that the optimal magnification is 2.3 - 2.5 when optimizing signal transfer (spatial resolution) alone; however, the optimal magnification is only 1.5 - 2.0 if SNR transfer is considered.

Overtaking method based on sand-sifter mechanism: Why do optimistic value functions find optimal solutions in multi-armed bandit problems?

PubMed

Ochi, Kento; Kamiura, Moto

2015-09-01

A multi-armed bandit problem is a search problem on which a learning agent must select the optimal arm among multiple slot machines generating random rewards. UCB algorithm is one of the most popular methods to solve multi-armed bandit problems. It achieves logarithmic regret performance by coordinating balance between exploration and exploitation. Since UCB algorithms, researchers have empirically known that optimistic value functions exhibit good performance in multi-armed bandit problems. The terms optimistic or optimism might suggest that the value function is sufficiently larger than the sample mean of rewards. The first definition of UCB algorithm is focused on the optimization of regret, and it is not directly based on the optimism of a value function. We need to think the reason why the optimism derives good performance in multi-armed bandit problems. In the present article, we propose a new method, which is called Overtaking method, to solve multi-armed bandit problems. The value function of the proposed method is defined as an upper bound of a confidence interval with respect to an estimator of expected value of reward: the value function asymptotically approaches to the expected value of reward from the upper bound. If the value function is larger than the expected value under the asymptote, then the learning agent is almost sure to be able to obtain the optimal arm. This structure is called sand-sifter mechanism, which has no regrowth of value function of suboptimal arms. It means that the learning agent can play only the current best arm in each time step. Consequently the proposed method achieves high accuracy rate and low regret and some value functions of it can outperform UCB algorithms. This study suggests the advantage of optimism of agents in uncertain environment by one of the simplest frameworks. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Determination of the chemical composition of human renal stones with MDCT: influence of the surrounding media

NASA Astrophysics Data System (ADS)

Grosjean, Romain; Sauer, Benoît; Guerra, Rui; Kermarrec, Isabelle; Ponvianne, Yannick; Winninger, Daniel; Daudon, Michel; Blum, Alain; Felblinger, Jacques; Hubert, Jacques

2007-03-01

The selection of the optimal treatment method for urinary stones diseases depends on the chemical composition of the stone and its corresponding fragility. MDCT has become the most used modality to determine rapidly and accurately the presence of stones when evaluating urinary lithiasis treatment. That is why several studies have tempted to determine the chemical composition of the stones based on the stone X-ray attenuation in-vitro and invivo. However, in-vitro studies did not reproduce the normal abdominal wall and fat, making uncertain the standardization of the obtained values. The aim of this study is to obtain X-ray attenuation values (in Hounsfield Units) of the six more frequent types of human renal stones (n=217) and to analyze the influence of the surrounding media on these values. The stones were first placed in a jelly, which X-ray attenuation is similar to that of the human kidney (30 HU at 120 kV). They were then stuck on a grid, scanned in a water tank and finally scanned in the air. Significant differences in CT-attenuation values were obtained with the three different surrounding media (jelly, water, air). Furthermore there was an influence of the surrounding media and consequently discrepancies in determination of the chemical composition of the renal stones. Consequently, CT-attenuation values found in in-vitro studies cannot really be considered as a reference for the determination of the chemical composition except if the used phantom is an anthropomorphic one.

Flexible operation strategy for environment control system in abnormal supply power condition

NASA Astrophysics Data System (ADS)

Liping, Pang; Guoxiang, Li; Hongquan, Qu; Yufeng, Fang

2017-04-01

This paper establishes an optimization method that can be applied to the flexible operation of the environment control system in an abnormal supply power condition. A proposed conception of lifespan is used to evaluate the depletion time of the non-regenerative substance. The optimization objective function is to maximize the lifespans. The optimization variables are the allocated powers of subsystems. The improved Non-dominated Sorting Genetic Algorithm is adopted to obtain the pareto optimization frontier with the constraints of the cabin environmental parameters and the adjustable operating parameters of the subsystems. Based on the same importance of objective functions, the preferred power allocation of subsystems can be optimized. Then the corresponding running parameters of subsystems can be determined to ensure the maximum lifespans. A long-duration space station with three astronauts is used to show the implementation of the proposed optimization method. Three different CO2 partial pressure levels are taken into consideration in this study. The optimization results show that the proposed optimization method can obtain the preferred power allocation for the subsystems when the supply power is at a less-than-nominal value. The method can be applied to the autonomous control for the emergency response of the environment control system.

Preparation method and quality control of multigamma volume sources with different matrices.

PubMed

Listkowska, A; Lech, E; Saganowski, P; Tymiński, Z; Dziel, T; Cacko, D; Ziemek, T; Kołakowska, E; Broda, R

2018-04-01

The aim of the work was to develop new radioactive standard sources based on epoxy resins. The optimal proportions of the components and the homogeneity of the matrices were determined. The activity of multigamma sources prepared in Marinelli beakers was determined with reference to the National Standard of Radionuclides Activity in Poland. The difference of radionuclides activity values determined using calibrated gamma spectrometer and the activity of standard solutions used are in most cases significantly lower than measurement uncertainty limits. Sources production method and quality control procedure have been developed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk assessment of drug-drug interactions using hepatocytes suspended in serum during the drug discovery process.

PubMed

Kosugi, Yohei; Hirabayashi, Hideki; Igari, Tomoko; Fujioka, Yasushi; Okuda, Teruaki; Moriwaki, Toshiya

2014-04-01

1. This study optimized the reported approach for the prediction of drug-drug interactions (DDIs) using hepatocytes suspended in serum (HHSS) and provided a practical usage of HHSS in the early and late phases of drug discovery. 2. First, the IC50 was determined using HHSS and evaluated as a qualitative index for DDI risks in the early phase. A retrospective study on clinical DDI cases revealed that inhibitors with IC50 < 100 μmol/L caused clinical DDIs while those with IC50 > 100 μmol/L showed weak or no potential for DDIs. Meanwhile, a pragmatic cutoff value could not be determined using previously reported Ki values of recombinant human cytochrome P450s. 3. Second, for a more substantial DDI risk assessment in the later phase, quantitative predictions of clinical DDI based on a static model were attempted by optimizing the most appropriate inhibitor concentration ([I]). The use of hepatic input plasma concentrations as a surrogate for [I] achieved the most successful predictions of the magnitude of increase in the AUC (within a 2-fold range of the observed values for 93.8% of inhibitors). 4. Through this study, we proposed the practical application of HHSS for an effective workflow to explore and profile candidates with less DDI liability.

Use of urea and creatinine levels in vaginal fluid for the diagnosis of preterm premature rupture of membranes and delivery interval after membrane rupture.

PubMed

Gezer, Cenk; Ekin, Atalay; Golbasi, Ceren; Kocahakimoglu, Ceysu; Bozkurt, Umit; Dogan, Askin; Solmaz, Ulaş; Golbasi, Hakan; Taner, Cuneyt Eftal

2017-04-01

To determine whether urea and creatinine measurements in vaginal fluid could be used to diagnose preterm premature rupture of membranes (PPROM) and predict delivery interval after PPROM. A prospective study conducted with 100 pregnant women with PPROM and 100 healthy pregnant women between 24 + 0 and 36 + 6 gestational weeks. All patients underwent sampling for urea and creatinine concentrations in vaginal fluid at the time of admission. Receiver operator curve analysis was used to determine the cutoff values for the presence of PPROM and delivery within 48 h after PPROM. In multivariate logistic regression analysis, vaginal fluid urea and creatinine levels were found to be significant predictors of PPROM (p < 0.001 and p < 0.001, respectively) and delivery within 48 h after PPROM (p = 0.012 and p = 0.017, respectively). The optimal cutoff values for the diagnosis of PPROM were >6.7 mg/dl for urea and >0.12 mg/dl for creatinine. The optimal cutoff values for the detection of delivery within 48 h were >19.4 mg/dl for urea and >0.23 mg/dl for creatinine. Measurement of urea and creatinine levels in vaginal fluid is a rapid and reliable test for diagnosing and also for predicting delivery interval after PPROM.

QSAR models for thiophene and imidazopyridine derivatives inhibitors of the Polo-Like Kinase 1.

PubMed

Comelli, Nieves C; Duchowicz, Pablo R; Castro, Eduardo A

2014-10-01

The inhibitory activity of 103 thiophene and 33 imidazopyridine derivatives against Polo-Like Kinase 1 (PLK1) expressed as pIC50 (-logIC50) was predicted by QSAR modeling. Multivariate linear regression (MLR) was employed to model the relationship between 0D and 3D molecular descriptors and biological activities of molecules using the replacement method (MR) as variable selection tool. The 136 compounds were separated into several training and test sets. Two splitting approaches, distribution of biological data and structural diversity, and the statistical experimental design procedure D-optimal distance were applied to the dataset. The significance of the training set models was confirmed by statistically higher values of the internal leave one out cross-validated coefficient of determination (Q2) and external predictive coefficient of determination for the test set (Rtest2). The model developed from a training set, obtained with the D-optimal distance protocol and using 3D descriptor space along with activity values, separated chemical features that allowed to distinguish high and low pIC50 values reasonably well. Then, we verified that such model was sufficient to reliably and accurately predict the activity of external diverse structures. The model robustness was properly characterized by means of standard procedures and their applicability domain (AD) was analyzed by leverage method. Copyright © 2014 Elsevier B.V. All rights reserved.

Geodesic regression on orientation distribution functions with its application to an aging study.

PubMed

Du, Jia; Goh, Alvina; Kushnarev, Sergey; Qiu, Anqi

2014-02-15

In this paper, we treat orientation distribution functions (ODFs) derived from high angular resolution diffusion imaging (HARDI) as elements of a Riemannian manifold and present a method for geodesic regression on this manifold. In order to find the optimal regression model, we pose this as a least-squares problem involving the sum-of-squared geodesic distances between observed ODFs and their model fitted data. We derive the appropriate gradient terms and employ gradient descent to find the minimizer of this least-squares optimization problem. In addition, we show how to perform statistical testing for determining the significance of the relationship between the manifold-valued regressors and the real-valued regressands. Experiments on both synthetic and real human data are presented. In particular, we examine aging effects on HARDI via geodesic regression of ODFs in normal adults aged 22 years old and above. © 2013 Elsevier Inc. All rights reserved.

Progress in multirate digital control system design

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.

1991-01-01

A new methodology for multirate sampled-data control design based on a new generalized control law structure, two new parameter-optimization-based control law synthesis methods, and a new singular-value-based robustness analysis method are described. The control law structure can represent multirate sampled-data control laws of arbitrary structure and dynamic order, with arbitrarily prescribed sampling rates for all sensors and update rates for all processor states and actuators. The two control law synthesis methods employ numerical optimization to determine values for the control law parameters. The robustness analysis method is based on the multivariable Nyquist criterion applied to the loop transfer function for the sampling period equal to the period of repetition of the system's complete sampling/update schedule. The complete methodology is demonstrated by application to the design of a combination yaw damper and modal suppression system for a commercial aircraft.

GW quasiparticle bandgaps of anatase TiO2 starting from DFT + U.

PubMed

Patrick, Christopher E; Giustino, Feliciano

2012-05-23

We investigate the quasiparticle band structure of anatase TiO(2), a wide gap semiconductor widely employed in photovoltaics and photocatalysis. We obtain GW quasiparticle energies starting from density-functional theory (DFT) calculations including Hubbard U corrections. Using a simple iterative procedure we determine the value of the Hubbard parameter yielding a vanishing quasiparticle correction to the fundamental bandgap of anatase TiO(2). The bandgap (3.3 eV) calculated using this optimal Hubbard parameter is smaller than the value obtained by applying many-body perturbation theory to standard DFT eigenstates and eigenvalues (3.7 eV). We extend our analysis to the rutile polymorph of TiO(2) and reach similar conclusions. Our work highlights the role of the starting non-interacting Hamiltonian in the calculation of GW quasiparticle energies in TiO(2) and suggests an optimal Hubbard parameter for future calculations.

Sizes of particles formed during municipal wastewater treatment.

PubMed

Lech, Smoczynski; Marta, Kosobucka; Michal, Smoczynski; Harsha, Ratnaweera; Krystyna, Pieczulis-Smoczynska

2017-02-01

Volumetric diameters Dv and specific surface area SpS of sludge particles formed during chemical coagulation and electrocoagulation of sewage were determined. The obtained aggregate-flocs differed substantially in both Dv and SpS values. The differences in Dv and SpS values of the analyzed particles were interpreted based on theoretical models for expanding aggregates. The most uniform particles were formed under exposure to: (a) optimal and maximal doses of PIX, (b) optimal doses of PAX, (c) maximal doses of the Al electro-coagulant. The lowest PIX dose produced the least uniform particles. Sludge aggregates-particles produced under exposure to minimal doses of PIX and the Al electro-coagulant were characterized by the lowest SpS values. Sludge particles coagulated by PAX and the particles formed at higher doses of PIX and the Al electro-coagulant had higher SpS values. The particles formed at all doses of the applied coagulants and electro-coagulants were generally classified into two size ranges: the main range and the secondary range. Most particles belonged to the main size range. An increase in the percentage of colloidal hydroxide particles in sewage sludge increased SpS.

Optimize Short Term load Forcasting Anomalous Based Feed Forward Backpropagation

NASA Astrophysics Data System (ADS)

Mulyadi, Y.; Abdullah, A. G.; Rohmah, K. A.

2017-03-01

This paper contains the Short-Term Load Forecasting (STLF) using artificial neural network especially feed forward back propagation algorithm which is particularly optimized in order to getting a reduced error value result. Electrical load forecasting target is a holiday that hasn’t identical pattern and different from weekday’s pattern, in other words the pattern of holiday load is an anomalous. Under these conditions, the level of forecasting accuracy will be decrease. Hence we need a method that capable to reducing error value in anomalous load forecasting. Learning process of algorithm is supervised or controlled, then some parameters are arranged before performing computation process. Momentum constant a value is set at 0.8 which serve as a reference because it has the greatest converge tendency. Learning rate selection is made up to 2 decimal digits. In addition, hidden layer and input component are tested in several variation of number also. The test result leads to the conclusion that the number of hidden layer impact on the forecasting accuracy and test duration determined by the number of iterations when performing input data until it reaches the maximum of a parameter value.

Tolerance of brightness and contrast adjustments on chronic apical abscess and apical granuloma interpretation

NASA Astrophysics Data System (ADS)

Purnamasari, L.; Iskandar, H. H. B.; Makes, B. N.

2017-08-01

In digitized radiography techniques, adjusting the image enhancement can improve the subjective image quality by optimizing the brightness and contrast for diagnostic needs. To determine the value range of image enhancement (brightness and contrast) on chronic apical abscess and apical granuloma interpretation. 30 periapical radiographs that diagnosed chronic apical abscess and 30 that diagnosed apical granuloma were adjusted by changing brightness and contrast values. The value range of brightness and contrast adjustment that can be tolerated in radiographic interpretations of chronic apical abscess and apical granuloma spans from -10 to +10. Brightness and contrast adjustments on digital radiographs do not affect the radiographic interpretation of chronic apical abscess and apical granuloma if conducted within the value range.

[Simultaneous determination of delta13C values of glycerol and ethanol in wine by liquid chromatography coupled with isotope ratio mass spectrometry].

PubMed

Li, Xuemin; Jia, Guangqun; Cao, Yanzhong; Zhang, Jinjie; Wang, Lei; Sun, Huiyuan

2013-12-01

A novel procedure was established for the characterization of delta13C values of glycerol and ethanol in wine by liquid chromatography-isotope ratio mass spectrometry (LC-IRMS). Several parameters influencing the separation of glycerol and ethanol from wine matrix were optimized. The precision and accuracy of the proposed method were 0.15 per thousand to 0.26 per thousand and 0.11 per thousand to 0.28 per thousand, respectively. The results obtained for 40 wine samples displayed that the delta13C value of glycerol ranged from--26.87 per thousand to--32.96 per thousand and that of ethanol ranged from--24.06 per thousand to--28.29 per thousand. Close correlations (R = 0.82) were obtained between the delta13C values of glycerol and ethanol. The proposed method didn't need complex sample treatment, and the delta13C values of glycerol and ethanol in wine can be simultaneously determined, thus improving the method in terms of simplicity and speed compared with traditional methods.

Simultaneous spectrophotometric determination of synthetic dyes in food samples after cloud point extraction using multiple response optimizations.

PubMed

Heidarizadi, Elham; Tabaraki, Reza

2016-01-01

A sensitive cloud point extraction method for simultaneous determination of trace amounts of sunset yellow (SY), allura red (AR) and brilliant blue (BB) by spectrophotometry was developed. Experimental parameters such as Triton X-100 concentration, KCl concentration and initial pH on extraction efficiency of dyes were optimized using response surface methodology (RSM) with a Doehlert design. Experimental data were evaluated by applying RSM integrating a desirability function approach. The optimum condition for extraction efficiency of SY, AR and BB simultaneously were: Triton X-100 concentration 0.0635 mol L(-1), KCl concentration 0.11 mol L(-1) and pH 4 with maximum overall desirability D of 0.95. Correspondingly, the maximum extraction efficiency of SY, AR and BB were 100%, 92.23% and 95.69%, respectively. At optimal conditions, extraction efficiencies were 99.8%, 92.48% and 95.96% for SY, AR and BB, respectively. These values were only 0.2%, 0.25% and 0.27% different from the predicted values, suggesting that the desirability function approach with RSM was a useful technique for simultaneously dye extraction. Linear calibration curves were obtained in the range of 0.02-4 for SY, 0.025-2.5 for AR and 0.02-4 μg mL(-1) for BB under optimum condition. Detection limit based on three times the standard deviation of the blank (3Sb) was 0.009, 0.01 and 0.007 μg mL(-1) (n=10) for SY, AR and BB, respectively. The method was successfully used for the simultaneous determination of the dyes in different food samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Bicarbonate Balance and Prescription in ESRD.

PubMed

Abramowitz, Matthew K

2017-03-01

The optimal approach to managing acid-base balance is less well defined for patients receiving hemodialysis than for those receiving peritoneal dialysis. Interventional studies in hemodialysis have been limited and inconsistent in their findings, whereas more compelling data are available from interventional studies in peritoneal dialysis. Both high and low serum bicarbonate levels associate with an increased risk of mortality in patients receiving hemodialysis, but high values are a marker for poor nutrition and comorbidity and are often highly variable from month to month. Measurement of pH would likely provide useful additional data. Concern has arisen regarding high-bicarbonate dialysate and dialysis-induced alkalemia, but whether these truly cause harm remains to be determined. The available evidence is insufficient for determining the optimal target for therapy at this time. Copyright © 2017 by the American Society of Nephrology.

Experimental parameters optimization of instrumental neutron activation analysis in order to determine selected elements in some industrial soils in Turkey

NASA Astrophysics Data System (ADS)

Haciyakupoglu, Sevilay; Nur Esen, Ayse; Erenturk, Sema

2014-08-01

The purpose of this study is optimization of the experimental parameters for analysis of soil matrix by instrumental neutron activation analysis and quantitative determination of barium, cerium, lanthanum, rubidium, scandium and thorium in soil samples collected from industrialized urban areas near Istanbul. Samples were irradiated in TRIGA MARK II Research Reactor of Istanbul Technical University. Two types of reference materials were used to check the accuracy of the applied method. The achieved results were found to be in compliance with certified values of the reference materials. The calculated En numbers for mentioned elements were found to be less than 1. The presented data of element concentrations in soil samples will help to trace the pollution as an impact of urbanization and industrialization, as well as providing database for future studies.

Enhancement of 2,3-Butanediol Production by Klebsiella oxytoca PTCC 1402

PubMed Central

Anvari, Maesomeh; Safari Motlagh, Mohammad Reza

2011-01-01

Optimal operating parameters of 2,3-Butanediol production using Klebsiella oxytoca under submerged culture conditions are determined by using Taguchi method. The effect of different factors including medium composition, pH, temperature, mixing intensity, and inoculum size on 2,3-butanediol production was analyzed using the Taguchi method in three levels. Based on these analyses the optimum concentrations of glucose, acetic acid, and succinic acid were found to be 6, 0.5, and 1.0 (% w/v), respectively. Furthermore, optimum values for temperature, inoculum size, pH, and the shaking speed were determined as 37°C, 8 (g/L), 6.1, and 150 rpm, respectively. The optimal combinations of factors obtained from the proposed DOE methodology was further validated by conducting fermentation experiments and the obtained results revealed an enhanced 2,3-Butanediol yield of 44%. PMID:21318172

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.

Systematic wavelength selection for improved multivariate spectral analysis

DOEpatents

Thomas, Edward V.; Robinson, Mark R.; Haaland, David M.

1995-01-01

Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=.function.(cost, performance). The method includes the steps of: (1) using one or more applications of a genetic algorithm to produce one or more count spectra, with multiple count spectra then combined to produce a combined count spectrum; (2) smoothing the count spectrum; (3) selecting a threshold count from a count spectrum to select these wavelength subsets which optimize the fitness function; and (4) eliminating a portion of the selected wavelength subsets. The determination of the unknown values can be made: (1) noninvasively and in vivo; (2) invasively and in vivo; or (3) in vitro.

Screening Natural Content of Water-Soluble B Vitamins in Fish: Enzymatic Extraction, HILIC Separation, and Tandem Mass Spectrometric Determination.

PubMed

Chatterjee, Niladri Sekhar; Kumar, K Ashok; Ajeeshkumar, K K; Kumari, K R Remya; Vishnu, K V; Anandan, Rangasamy; Mathew, Suseela; Ravishankar, C N

2017-05-01

Despite the potential of LC with tandem MS (MS/MS) in improving sensitivity and selectivity, analytical methods are scarce for the determination of protein-bound and phosphorylated forms of B vitamins in food. This prompted us to develop a method for LC-MS/MS determination of naturally occurring nicotinamide, nicotinic acid, thiamine, pyridoxine, riboflavin, pantothenic acid, biotin, folic acid, and cyanocobalamin in fish. Baseline separation of the vitamins was achieved in a hydrophilic interaction LC condition. An ultrasonication-assisted enzymatic extraction protocol for sample preparation was optimized and validated. The time required for extraction was significantly reduced (to 4 h), while maintaining good extraction efficiency. Acetonitrile content (80%, v/v) in the prepared sample was found to be optimum for excellent peak shape and sensitivity. The dynamic linear range of the vitamins ranged from 2.5 to 500 ng/g, and the regression coefficient values were greater than 0.99. LOQ values ranged from 0.4 to 50 ng/g for the different vitamins. The spike recovery values at 50 and 100 ng/g ranged from 87.5 to 97.5%. The intra- and interday precision values were satisfactory. Accuracy of the developed method was determined by analysis of a Certified Reference Material. The method could also be used for unambiguous determination of the natural content of the target vitamins in fish.

Parameter Optimization for Turbulent Reacting Flows Using Adjoints

NASA Astrophysics Data System (ADS)

Lapointe, Caelan; Hamlington, Peter E.

2017-11-01

The formulation of a new adjoint solver for topology optimization of turbulent reacting flows is presented. This solver provides novel configurations (e.g., geometries and operating conditions) based on desired system outcomes (i.e., objective functions) for complex reacting flow problems of practical interest. For many such problems, it would be desirable to know optimal values of design parameters (e.g., physical dimensions, fuel-oxidizer ratios, and inflow-outflow conditions) prior to real-world manufacture and testing, which can be expensive, time-consuming, and dangerous. However, computational optimization of these problems is made difficult by the complexity of most reacting flows, necessitating the use of gradient-based optimization techniques in order to explore a wide design space at manageable computational cost. The adjoint method is an attractive way to obtain the required gradients, because the cost of the method is determined by the dimension of the objective function rather than the size of the design space. Here, the formulation of a novel solver is outlined that enables gradient-based parameter optimization of turbulent reacting flows using the discrete adjoint method. Initial results and an outlook for future research directions are provided.

Results of an integrated structure/control law design sensitivity analysis

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.

1989-01-01

A design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations is discussed. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changes in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient than finite difference methods for the computation of the equivalent sensitivity information.

Optimal Trajectories for the Helicopter in One-Engine-Inoperative Terminal-Area Operations

NASA Technical Reports Server (NTRS)

Zhao, Yiyuan; Chen, Robert T. N.

1996-01-01

This paper presents a summary of a series of recent analytical studies conducted to investigate One-Engine-Inoperative (OEI) optimal control strategies and the associated optimal trajectories for a twin engine helicopter in Category-A terminal-area operations. These studies also examine the associated heliport size requirements and the maximum gross weight capability of the helicopter. Using an eight states, two controls, augmented point-mass model representative of the study helicopter, Continued TakeOff (CTO), Rejected TakeOff (RTO), Balked Landing (BL), and Continued Landing (CL) are investigated for both Vertical-TakeOff-and-Landing (VTOL) and Short-TakeOff-and-Landing (STOL) terminal-area operations. The formulation of the nonlinear optimal control problems with considerations for realistic constraints, solution methods for the two-point boundary-value problem, a new real-time generation method for the optimal OEI trajectories, and the main results of this series of trajectory optimization studies are presented. In particular, a new balanced- weight concept for determining the takeoff decision point for VTOL Category-A operations is proposed, extending the balanced-field length concept used for STOL operations.

Optimization of fuels from waste composition with application of genetic algorithm.

PubMed

Małgorzata, Wzorek

2014-05-01

The objective of this article is to elaborate a method to optimize the composition of the fuels from sewage sludge (PBS fuel - fuel based on sewage sludge and coal slime, PBM fuel - fuel based on sewage sludge and meat and bone meal, PBT fuel - fuel based on sewage sludge and sawdust). As a tool for an optimization procedure, the use of a genetic algorithm is proposed. The optimization task involves the maximization of mass fraction of sewage sludge in a fuel developed on the basis of quality-based criteria for the use as an alternative fuel used by the cement industry. The selection criteria of fuels composition concerned such parameters as: calorific value, content of chlorine, sulphur and heavy metals. Mathematical descriptions of fuel compositions and general forms of the genetic algorithm, as well as the obtained optimization results are presented. The results of this study indicate that the proposed genetic algorithm offers an optimization tool, which could be useful in the determination of the composition of fuels that are produced from waste.

Optimization methodology for the global 10 Hz orbit feedback in RHIC

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

Liu, Chuyu; Hulsart, R.; Mernick, K.

To combat beam oscillations induced by triplet vibrations at the Relativistic Heavy Ion Collider (RHIC), a global orbit feedback system was developed and applied at injection and top energy in 2011, and during beam acceleration in 2012. Singular Value Decomposition (SVD) was employed to determine the strengths and currents of the applied corrections. The feedback algorithm was optimized for different magnetic configurations (lattices) at fixed beam energies and during beam acceleration. While the orbit feedback performed well since its inception, corrector current transients and feedback-induced beam oscillations were observed during the polarized proton program in 2015. In this paper, wemore » present the feedback algorithm, the optimization of the algorithm for various lattices and the solution adopted to mitigate the observed current transients during beam acceleration.« less

FPGA Implementation of Optimal 3D-Integer DCT Structure for Video Compression

PubMed Central

2015-01-01

A novel optimal structure for implementing 3D-integer discrete cosine transform (DCT) is presented by analyzing various integer approximation methods. The integer set with reduced mean squared error (MSE) and high coding efficiency are considered for implementation in FPGA. The proposed method proves that the least resources are utilized for the integer set that has shorter bit values. Optimal 3D-integer DCT structure is determined by analyzing the MSE, power dissipation, coding efficiency, and hardware complexity of different integer sets. The experimental results reveal that direct method of computing the 3D-integer DCT using the integer set [10, 9, 6, 2, 3, 1, 1] performs better when compared to other integer sets in terms of resource utilization and power dissipation. PMID:26601120

Optimization methodology for the global 10 Hz orbit feedback in RHIC

DOE PAGES

Liu, Chuyu; Hulsart, R.; Mernick, K.; ...

2018-05-08

To combat beam oscillations induced by triplet vibrations at the Relativistic Heavy Ion Collider (RHIC), a global orbit feedback system was developed and applied at injection and top energy in 2011, and during beam acceleration in 2012. Singular Value Decomposition (SVD) was employed to determine the strengths and currents of the applied corrections. The feedback algorithm was optimized for different magnetic configurations (lattices) at fixed beam energies and during beam acceleration. While the orbit feedback performed well since its inception, corrector current transients and feedback-induced beam oscillations were observed during the polarized proton program in 2015. In this paper, wemore » present the feedback algorithm, the optimization of the algorithm for various lattices and the solution adopted to mitigate the observed current transients during beam acceleration.« less

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

NASA Technical Reports Server (NTRS)

Patrick, Nicholas J. M.; Sheridan, Thomas B.

1996-01-01

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance vary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are: (1) determining what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major u.s. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort-topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimality with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider unmodelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

How to Assess the Value of Medicines?

PubMed Central

Simoens, Steven

2010-01-01

This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value. PMID:21607066

How to assess the value of medicines?

PubMed

Simoens, Steven

2010-01-01

This study aims to discuss approaches to assessing the value of medicines. Economic evaluation assesses value by means of the incremental cost-effectiveness ratio (ICER). Health is maximized by selecting medicines with increasing ICERs until the budget is exhausted. The budget size determines the value of the threshold ICER and vice versa. Alternatively, the threshold value can be inferred from pricing/reimbursement decisions, although such values vary between countries. Threshold values derived from the value-of-life literature depend on the technique used. The World Health Organization has proposed a threshold value tied to the national GDP. As decision makers may wish to consider multiple criteria, variable threshold values and weighted ICERs have been suggested. Other approaches (i.e., replacement approach, program budgeting and marginal analysis) have focused on improving resource allocation, rather than maximizing health subject to a budget constraint. Alternatively, the generalized optimization framework and multi-criteria decision analysis make it possible to consider other criteria in addition to value.

Maximizing carbon storage in the Appalachians: A method for considering the risk of disturbance events

Treesearch

Michael R. Vanderberg; Kevin Boston; John Bailey

2011-01-01

Accounting for the probability of loss due to disturbance events can influence the prediction of carbon flux over a planning horizon, and can affect the determination of optimal silvicultural regimes to maximize terrestrial carbon storage. A preliminary model that includes forest disturbance-related carbon loss was developed to maximize expected values of carbon stocks...

Multivariate optimization of a procedure employing microwave-assisted digestion for the determination of nickel and vanadium in crude oil by ICP OES.

PubMed

Dos Anjos, Shirlei L; Alves, Jeferson C; Rocha Soares, Sarah A; Araujo, Rennan G O; de Oliveira, Olivia M C; Queiroz, Antonio F S; Ferreira, Sergio L C

2018-02-01

This work presents the optimization of a sample preparation procedure using microwave-assisted digestion for the determination of nickel and vanadium in crude oil employing inductively coupled plasma optical emission spectrometry (ICP OES). The optimization step was performed utilizing a two-level full factorial design involving the following factors: concentrated nitric acid and hydrogen peroxide volumes, and microwave-assisted digestion temperature. Nickel and vanadium concentrations were used as responses. Additionally, a multiple response based on the normalization of the concentrations by the highest values was built to establish a compromise condition between the two analytes. A Doehlert matrix optimized the instrumental conditions of the ICP OE spectrometer. In this design, the plasma robustness was used as chemometric response. The experiments were performed using a digested oil sample solution doped with magnesium(II) ions, as well as a standard magnesium solution. The optimized method allows for the determination of nickel and vanadium with quantification limits of 0.79 and 0.20μgg -1 , respectively, for a digested sample mass of 0.1g. The precision (expressed as relative standard deviations) was determined using five replicates of two oil samples and the results obtained were 1.63% and 3.67% for nickel and 0.42% and 4.64% for vanadium. Bismuth and yttrium were also tested as internal standards, and the results demonstrate that yttrium allows for a better precision for the method. The accuracy was confirmed by the analysis of the certified reference material trace element in fuel oil (CRM NIST 1634c). The proposed method was applied for the determination of nickel and vanadium in five crude oil samples from Brazilian Basins. The metal concentrations found varied from 7.30 to 33.21μgg -1 for nickel and from 0.63 to 19.42μgg -1 for vanadium. Copyright © 2017. Published by Elsevier B.V.

Calculation of the Target Lumbar Lordosis Angle for Restoring an Optimal Pelvic Tilt in Elderly Patients With Adult Spinal Deformity.

PubMed

Yamato, Yu; Hasegawa, Tomohiko; Kobayashi, Sho; Yasuda, Tatsuya; Togawa, Daisuke; Arima, Hideyuki; Oe, Shin; Iida, Takahiro; Matsumura, Akira; Hosogane, Naobumi; Matsumoto, Morio; Matsuyama, Yukihiro

2016-02-01

This investigation consisted of a cross-sectional study and a retrospective multicenter case series. This investigation sought to identify the ideal lumbar lordosis (LL) angle for restoring an optimal pelvic tilt (PT) in patients with adult spinal deformity (ASD). To achieve successful corrective fusion in ASD patients with sagittal imbalance, it is essential to correct the sagittal spinal alignment and obtain a suitable pelvic inclination. We determined the LL angle that would restore the optimal PT following ASD surgery. The cross-sectional study included 184 elderly volunteers (mean age 64 years) with an Oswestry Disability Index score less than 20%. The relationship between PT or LL and the pelvic incidence (PI) in normal individuals was investigated. The second study included 116 ASD patients (mean age 66 years) who underwent thoracolumbar corrective fusion at 1 of 4 spine centers. The postoperative PT values were calculated using the parameters measured. On the basis of these studies, an ideal LL angle was determined. In the cross-sectional study, the linear regression equation for the optimal PT as a function of PI was "optimal PT = 0.47 × PI - 7.5." In the second study, the postoperative PT was determined as a function of PI and corrected LL, using the equation "postoperative PT = 0.7 × PI - 0.5 × corrected LL + 8.1." The target LL angle was determined by mathematically equalizing the PTs of these 2 equations: "target LL = 0.45 × PI + 31.8." The ideal LL angle can be determined using the equation "LL = 0.45 × PI + 31.8," which can be used as a reference during surgical planning in ASD cases. 4.

Exploration of Objective Functions for Optimal Placement of Weather Stations

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2016-12-01

Many regions of Earth lack ground-based sensing of weather variables. For example, most countries in Sub-Saharan Africa do not have reliable weather station networks. This absence of sensor data has many consequences ranging from public safety (poor prediction and detection of severe weather events), to agriculture (lack of crop insurance), to science (reduced quality of world-wide weather forecasts, climate change measurement, etc.). The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to locate each weather station. We can formulate this as the following optimization problem: Determine a set of N sites that jointly optimize the value of an objective function. The purpose of this poster is to propose and assess several objective functions. In addition to standard objectives (e.g., minimizing the summed squared error of interpolated values over the entire region), we consider objectives that minimize the maximum error over the region and objectives that optimize the detection of extreme events. An additional issue is that each station measures more than 10 variables—how should we balance the accuracy of our interpolated maps for each variable? Weather sensors inevitably drift out of calibration or fail altogether. How can we incorporate robustness to failed sensors into our network design? Another important requirement is that the network should make it possible to detect failed sensors by comparing their readings with those of other stations. How can this requirement be met? Finally, we provide an initial assessment of the computational cost of optimizing these various objective functions. We invite everyone to join the discussion at our poster by proposing additional objectives, identifying additional issues to consider, and expanding our bibliography of relevant papers. A prize (derived from grapes grown in Oregon) will be awarded for the most insightful contribution to the discussion!

Determination of heat transfer coefficients in plastic French straws plunged in liquid nitrogen.

PubMed

Santos, M Victoria; Sansinena, M; Chirife, J; Zaritzky, N

2014-12-01

The knowledge of the thermodynamic process during the cooling of reproductive biological systems is important to assess and optimize the cryopreservation procedures. The time-temperature curve of a sample immersed in liquid nitrogen enables the calculation of cooling rates and helps to determine whether it is vitrified or undergoes phase change transition. When dealing with cryogenic liquids, the temperature difference between the solid and the sample is high enough to cause boiling of the liquid, and the sample can undergo different regimes such as film and/or nucleate pool boiling. In the present work, the surface heat transfer coefficients (h) for plastic French straws plunged in liquid nitrogen were determined using the measurement of time-temperature curves. When straws filled with ice were used the cooling curve showed an abrupt slope change which was attributed to the transition of film into nucleate pool boiling regime. The h value that fitted each stage of the cooling process was calculated using a numerical finite element program that solves the heat transfer partial differential equation under transient conditions. In the cooling process corresponding to film boiling regime, the h that best fitted experimental results was h=148.12±5.4 W/m(2) K and for nucleate-boiling h=1355±51 W/m(2) K. These values were further validated by predicting the time-temperature curve for French straws filled with a biological fluid system (bovine semen-extender) which undergoes freezing. Good agreement was obtained between the experimental and predicted temperature profiles, further confirming the accuracy of the h values previously determined for the ice-filled straw. These coefficients were corroborated using literature correlations. The determination of the boiling regimes that govern the cooling process when plunging straws in liquid nitrogen constitutes an important issue when trying to optimize cryopreservation procedures. Furthermore, this information can lead to improvements in the design of cooling devices in the cryobiology field. Copyright © 2014 Elsevier Inc. All rights reserved.

Determination of thermodynamic values of acidic dissociation constants and complexation constants of profens and their utilization for optimization of separation conditions by Simul 5 Complex.

PubMed

Riesová, Martina; Svobodová, Jana; Ušelová, Kateřina; Tošner, Zdeněk; Zusková, Iva; Gaš, Bohuslav

2014-10-17

In this paper we determine acid dissociation constants, limiting ionic mobilities, complexation constants with β-cyclodextrin or heptakis(2,3,6-tri-O-methyl)-β-cyclodextrin, and mobilities of resulting complexes of profens, using capillary zone electrophoresis and affinity capillary electrophoresis. Complexation parameters are determined for both neutral and fully charged forms of profens and further corrected for actual ionic strength and variable viscosity in order to obtain thermodynamic values of complexation constants. The accuracy of obtained complexation parameters is verified by multidimensional nonlinear regression of affinity capillary electrophoretic data, which provides the acid dissociation and complexation parameters within one set of measurements, and by NMR technique. A good agreement among all discussed methods was obtained. Determined complexation parameters were used as input parameters for simulations of electrophoretic separation of profens by Simul 5 Complex. An excellent agreement of experimental and simulated results was achieved in terms of positions, shapes, and amplitudes of analyte peaks, confirming the applicability of Simul 5 Complex to complex systems, and accuracy of obtained physical-chemical constants. Simultaneously, we were able to demonstrate the influence of electromigration dispersion on the separation efficiency, which is not possible using the common theoretical approaches, and predict the electromigration order reversals of profen peaks. We have shown that determined acid dissociation and complexation parameters in combination with tool Simul 5 Complex software can be used for optimization of separation conditions in capillary electrophoresis. Copyright © 2014 Elsevier B.V. All rights reserved.

Study on the synergic effect of natural compounds on the microbial quality decay of packed fish hamburger.

PubMed

Corbo, M R; Speranza, B; Filippone, A; Granatiero, S; Conte, A; Sinigaglia, M; Del Nobile, M A

2008-10-31

The effectiveness of natural compounds in slowing down the microbial quality decay of refrigerated fish hamburger is addressed in this study. In particular, the control of the microbiological spoilage by combined use of three antimicrobials, and the determination of their optimal composition to extend the fish hamburger Microbiological Stability Limit (MAL) are the main objectives of this work. Thymol, grapefruit seed extract (GFSE) and lemon extract were tested for monitoring the cell growth of the main fish spoilage microorganisms (Pseudomonas fluorescens, Photobacterium phosphoreum and Shewanella putrefaciens), inoculated in fish hamburgers, and the growth of mesophilic and psychrotrophic bacteria. A Central Composite Design (CCD) was developed to highlight a possible synergic effect of the above natural compounds. Results showed an increase in the MAL value for hamburgers mixed with the antimicrobial compounds, compared to the control sample. The optimal antimicrobial compound composition, which corresponds to the maximal MAL value determined in this study, is: 110 mgL(-1) of thymol, 100 mgL(-1) of GFSE and 120 mgL(-1) of lemon extract. The presence of the natural compounds delay the sensorial quality decay without compromising the flavor of the fish hamburgers.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2007-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine's performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2007-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least-squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2005-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs such as thrust. The engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends upon knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined which accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

Optimized determination method for trans-10-hydroxy-2-decenoic acid content in royal jelly by high-performance liquid chromatography with an internal standard.

PubMed

Zhou, Jinhui; Xue, Xiaofeng; Li, Yi; Zhang, Jinzhen; Zhao, Jing

2007-01-01

An optimized reversed-phase high-performance liquid chromatography method was developed to detect the trans-10-hydroxy-2-decenoic acid (10-HDA) content in royal jelly cream and lyophilized powder. The sample was extracted using absolute ethanol. Chromatographic separation of 10-HDA and methyl 4-hydroxybenzoate as the internal standard was performed on a Nova-pak C18 column. The average recoveries were 95.0-99.2% (n = 5) with relative standard deviation (RSD) values of 1.3-2.1% for royal jelly cream and 98.0-100.0% (n = 5) with RSD values of 1.6-3.0% for lyophilized powder, respectively. The limits of detection and quantitation were 0.5 and 1.5 mg/kg, respectively, for both royal jelly cream and lyophilized powder. The method was validated for the determination of practical royal jelly products. The concentration of 10-HDA ranged from 1.26 to 2.21% for pure royal jelly cream samples and 3.01 to 6.19% for royal jelly lyophilized powder samples. For 30 royal jelly products, the 10-HDA content varied from not detectable to 0.98%.

High-Resolution Free-Energy Landscape Analysis of α-Helical Protein Folding: HP35 and Its Double Mutant

PubMed Central

2013-01-01

The free-energy landscape can provide a quantitative description of folding dynamics, if determined as a function of an optimally chosen reaction coordinate. Here, we construct the optimal coordinate and the associated free-energy profile for all-helical proteins HP35 and its norleucine (Nle/Nle) double mutant, based on realistic equilibrium folding simulations [Piana et al. Proc. Natl. Acad. Sci. U.S.A.2012, 109, 17845]. From the obtained profiles, we directly determine such basic properties of folding dynamics as the configurations of the minima and transition states (TS), the formation of secondary structure and hydrophobic core during the folding process, the value of the pre-exponential factor and its relation to the transition path times, the relation between the autocorrelation times in TS and minima. We also present an investigation of the accuracy of the pre-exponential factor estimation based on the transition-path times. Four different estimations of the pre-exponential factor for both proteins give k0–1 values of approximately a few tens of nanoseconds. Our analysis gives detailed information about folding of the proteins and can serve as a rigorous common language for extensive comparison between experiment and simulation. PMID:24348206

Approach toward enhancement of halophilic protease production by Halobacterium sp. strain LBU50301 using statistical design response surface methodology.

PubMed

Chuprom, Julalak; Bovornreungroj, Preeyanuch; Ahmad, Mehraj; Kantachote, Duangporn; Dueramae, Sawitree

2016-06-01

A new potent halophilic protease producer, Halobacterium sp. strain LBU50301 was isolated from salt-fermented fish samples ( budu ) and identified by phenotypic analysis, and 16S rDNA gene sequencing. Thereafter, sequential statistical strategy was used to optimize halophilic protease production from Halobacterium sp. strain LBU50301 by shake-flask fermentation. The classical one-factor-at-a-time (OFAT) approach determined gelatin was the best nitrogen source. Based on Plackett - Burman (PB) experimental design; gelatin, MgSO 4 ·7H 2 O, NaCl and pH significantly influenced the halophilic protease production. Central composite design (CCD) determined the optimum level of medium components. Subsequently, an 8.78-fold increase in corresponding halophilic protease yield (156.22 U/mL) was obtained, compared with that produced in the original medium (17.80 U/mL). Validation experiments proved the adequacy and accuracy of model, and the results showed the predicted value agreed well with the experimental values. An overall 13-fold increase in halophilic protease yield was achieved using a 3 L laboratory fermenter and optimized medium (231.33 U/mL).

Removal of iron ore slimes from a highly turbid water by DAF.

PubMed

Faustino, L M; Braga, A S; Sacchi, G D; Whitaker, W; Reali, M A P; Leal Filho, L S; Daniel, L A

2018-05-30

This paper addresses Dissolved Air Flotation (DAF) process variables, such as the flocculation parameters and the recycle water addition, as well as the pretreatment chemical variables (coagulation conditions), to determine the optimal values for the flotation of iron ore slimes found in a highly turbid water sample from the Gualaxo do Norte River, a tributary of the Doce River Basin in Minas Gerais, Brazil. This work was conducted using a flotatest batch laboratory-scale device to evaluate the effectiveness of DAF for cleaning the water polluted by the Samarco tailings dam leakage and determine the ability of DAF to reduce the water turbidity from 358 NTU to values below 100 NTU, aiming to comply with current legislation. The results showed that the four types of tested coagulants (PAC, ferric chloride, Tanfloc SG and Tanfloc SL) provided adequate conditions for coagulation, flocculation and flotation (in the range of 90-99.6% turbidity reduction). Although the process variables were optimized and low residual turbidity vales were achieved, results revealed that a portion of the flocs settled at the bottom of the flotatest columns, which indicated that the turbidity results represented removal caused by a combination of flotation and sedimentation processes simultaneously.

High-Resolution Free-Energy Landscape Analysis of α-Helical Protein Folding: HP35 and Its Double Mutant.

PubMed

Banushkina, Polina V; Krivov, Sergei V

2013-12-10

The free-energy landscape can provide a quantitative description of folding dynamics, if determined as a function of an optimally chosen reaction coordinate. Here, we construct the optimal coordinate and the associated free-energy profile for all-helical proteins HP35 and its norleucine (Nle/Nle) double mutant, based on realistic equilibrium folding simulations [Piana et al. Proc. Natl. Acad. Sci. U.S.A. 2012 , 109 , 17845]. From the obtained profiles, we directly determine such basic properties of folding dynamics as the configurations of the minima and transition states (TS), the formation of secondary structure and hydrophobic core during the folding process, the value of the pre-exponential factor and its relation to the transition path times, the relation between the autocorrelation times in TS and minima. We also present an investigation of the accuracy of the pre-exponential factor estimation based on the transition-path times. Four different estimations of the pre-exponential factor for both proteins give k 0 -1 values of approximately a few tens of nanoseconds. Our analysis gives detailed information about folding of the proteins and can serve as a rigorous common language for extensive comparison between experiment and simulation.

Value of long-term streamflow forecast to reservoir operations for water supply in snow-dominated catchments

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

Anghileri, Daniela; Voisin, Nathalie; Castelletti, Andrea F.

In this study, we develop a forecast-based adaptive control framework for Oroville reservoir, California, to assess the value of seasonal and inter-annual forecasts for reservoir operation.We use an Ensemble Streamflow Prediction (ESP) approach to generate retrospective, one-year-long streamflow forecasts based on the Variable Infiltration Capacity hydrology model. The optimal sequence of daily release decisions from the reservoir is then determined by Model Predictive Control, a flexible and adaptive optimization scheme.We assess the forecast value by comparing system performance based on the ESP forecasts with that based on climatology and a perfect forecast. In addition, we evaluate system performance based onmore » a synthetic forecast, which is designed to isolate the contribution of seasonal and inter-annual forecast skill to the overall value of the ESP forecasts.Using the same ESP forecasts, we generalize our results by evaluating forecast value as a function of forecast skill, reservoir features, and demand. Our results show that perfect forecasts are valuable when the water demand is high and the reservoir is sufficiently large to allow for annual carry-over. Conversely, ESP forecast value is highest when the reservoir can shift water on a seasonal basis.On average, for the system evaluated here, the overall ESP value is 35% less than the perfect forecast value. The inter-annual component of the ESP forecast contributes 20-60% of the total forecast value. Improvements in the seasonal component of the ESP forecast would increase the overall ESP forecast value between 15 and 20%.« less

Quality by design case study 1: Design of 5-fluorouracil loaded lipid nanoparticles by the W/O/W double emulsion - Solvent evaporation method.

PubMed

Amasya, Gulin; Badilli, Ulya; Aksu, Buket; Tarimci, Nilufer

2016-03-10

With Quality by Design (QbD), a systematic approach involving design and development of all production processes to achieve the final product with a predetermined quality, you work within a design space that determines the critical formulation and process parameters. Verification of the quality of the final product is no longer necessary. In the current study, the QbD approach was used in the preparation of lipid nanoparticle formulations to improve skin penetration of 5-Fluorouracil, a widely-used compound for treating non-melanoma skin cancer. 5-Fluorouracil-loaded lipid nanoparticles were prepared by the W/O/W double emulsion - solvent evaporation method. Artificial neural network software was used to evaluate the data obtained from the lipid nanoparticle formulations, to establish the design space, and to optimize the formulations. Two different artificial neural network models were developed. The limit values of the design space of the inputs and outputs obtained by both models were found to be within the knowledge space. The optimal formulations recommended by the models were prepared and the critical quality attributes belonging to those formulations were assigned. The experimental results remained within the design space limit values. Consequently, optimal formulations with the critical quality attributes determined to achieve the Quality Target Product Profile were successfully obtained within the design space by following the QbD steps. Copyright © 2016 Elsevier B.V. All rights reserved.

Method of multi-mode vibration control for the carbody of high-speed electric multiple unit trains

NASA Astrophysics Data System (ADS)

Gong, Dao; Zhou, Jinsong; Sun, Wenjing; Sun, Yu; Xia, Zhanghui

2017-11-01

A method of multi-mode vibration control for the carbody of high-speed electric multiple unit (EMU) trains by using the onboard and suspended equipments as dynamic vibration absorbers (DVAs) is proposed. The effect of the multi-mode vibration on the ride quality of a high-speed EMU train was studied, and the target modes of vibration control were determined. An equivalent mass identification method was used to determine the equivalent mass for the target modes at the device installation positions. To optimize the vibration acceleration response of the carbody, the natural frequencies and damping ratios of the lateral and vertical vibration were designed based on the theory of dynamic vibration absorption. In order to realize the optimized design values of the natural frequencies for the lateral and vertical vibrations simultaneously, a new type of vibration absorber was designed in which a belleville spring and conventional rubber parts are connected in parallel. This design utilizes the negative stiffness of the belleville spring. Results show that, as compared to rigid equipment connections, the proposed method effectively reduces the multi-mode vibration of a carbody in a high-speed EMU train, thereby achieving the control objectives. The ride quality in terms of the lateral and vertical vibration of the carbody is considerably improved. Moreover, the optimal value of the damping ratio is effective in dissipating the vibration energy, which reduces the vibration of both the carbody and the equipment.

Dipstick measurements of urine specific gravity are unreliable.

PubMed

de Buys Roessingh, A S; Drukker, A; Guignard, J P

2001-08-01

To evaluate the reliability of dipstick measurements of urine specific gravity (U-SG). Fresh urine specimens were tested for urine pH and osmolality (U-pH, U-Osm) by a pH meter and an osmometer, and for U-SG by three different methods (refractometry, automatic readout of a dipstick (Clinitek-50), and (visual) change of colour of the dipstick). The correlations between the visual U-SG dipstick measurements and U-SG determined by a refractometer and the comparison of Clinitek((R))-50 dipstick U-SG measurements with U-Osm were less than optimal, showing very wide scatter of values. Only the U-SG refractometer values and U-Osm had a good linear correlation. The tested dipstick was unreliable for the bedside determination of U-SG, even after correction for U-pH, as recommended by the manufacturer. Among the bedside determinations, only refractometry gives reliable U-SG results. Dipstick U-SG measurements should be abandoned.

Determination of full piezoelectric complex parameters using gradient-based optimization algorithm

NASA Astrophysics Data System (ADS)

Kiyono, C. Y.; Pérez, N.; Silva, E. C. N.

2016-02-01

At present, numerical techniques allow the precise simulation of mechanical structures, but the results are limited by the knowledge of the material properties. In the case of piezoelectric ceramics, the full model determination in the linear range involves five elastic, three piezoelectric, and two dielectric complex parameters. A successful solution to obtaining piezoceramic properties consists of comparing the experimental measurement of the impedance curve and the results of a numerical model by using the finite element method (FEM). In the present work, a new systematic optimization method is proposed to adjust the full piezoelectric complex parameters in the FEM model. Once implemented, the method only requires the experimental data (impedance modulus and phase data acquired by an impedometer), material density, geometry, and initial values for the properties. This method combines a FEM routine implemented using an 8-noded axisymmetric element with a gradient-based optimization routine based on the method of moving asymptotes (MMA). The main objective of the optimization procedure is minimizing the quadratic difference between the experimental and numerical electrical conductance and resistance curves (to consider resonance and antiresonance frequencies). To assure the convergence of the optimization procedure, this work proposes restarting the optimization loop whenever the procedure ends in an undesired or an unfeasible solution. Two experimental examples using PZ27 and APC850 samples are presented to test the precision of the method and to check the dependency of the frequency range used, respectively.

Optimization of dose and image quality in adult and pediatric computed tomography scans

NASA Astrophysics Data System (ADS)

Chang, Kwo-Ping; Hsu, Tzu-Kun; Lin, Wei-Ting; Hsu, Wen-Lin

2017-11-01

Exploration to maximize CT image and reduce radiation dose was conducted while controlling for multiple factors. The kVp, mAs, and iteration reconstruction (IR), affect the CT image quality and radiation dose absorbed. The optimal protocols (kVp, mAs, IR) are derived by figure of merit (FOM) based on CT image quality (CNR) and CT dose index (CTDIvol). CT image quality metrics such as CT number accuracy, SNR, low contrast materials' CNR and line pair resolution were also analyzed as auxiliary assessments. CT protocols were carried out with an ACR accreditation phantom and a five-year-old pediatric head phantom. The threshold values of the adult CT scan parameters, 100 kVp and 150 mAs, were determined from the CT number test and line pairs in ACR phantom module 1and module 4 respectively. The findings of this study suggest that the optimal scanning parameters for adults be set at 100 kVp and 150-250 mAs. However, for improved low- contrast resolution, 120 kVp and 150-250 mAs are optimal. Optimal settings for pediatric head CT scan were 80 kVp/50 mAs, for maxillary sinus and brain stem, while 80 kVp /300 mAs for temporal bone. SNR is not reliable as the independent image parameter nor the metric for determining optimal CT scan parameters. The iteration reconstruction (IR) approach is strongly recommended for both adult and pediatric CT scanning as it markedly improves image quality without affecting radiation dose.

Experimental design and response surface modelling for optimization of vat dye from water by nano zero valent iron (NZVI).

PubMed

Arabi, Simin; Sohrabi, Mahmoud Reza

2013-01-01

In this study, NZVI particles was prepared and studied for the removal of vat green 1 dye from aqueous solution. A four-factor central composite design (CCD) combined with response surface modeling (RSM) to evaluate the combined effects of variables as well as optimization was employed for maximizing the dye removal by prepared NZVI based on 30 different experimental data obtained in a batch study. Four independent variables, viz. NZVI dose (0.1-0.9 g/L), pH (1.5-9.5), contact time (20-100 s), and initial dye concentration (10-50 mg/L) were transform to coded values and quadratic model was built to predict the responses. The significant of independent variables and their interactions were tested by the analysis of variance (ANOVA). Adequacy of the model was tested by the correlation between experimental and predicted values of the response and enumeration of prediction errors. The ANOVA results indicated that the proposed model can be used to navigate the design space. Optimization of the variables for maximum adsorption of dye by NZVI particles was performed using quadratic model. The predicted maximum adsorption efficiency (96.97%) under the optimum conditions of the process variables (NZVI dose 0.5 g/L, pH 4, contact time 60 s, and initial dye concentration 30 mg/L) was very close to the experimental value (96.16%) determined in batch experiment. In the optimization, R2 and R2adj correlation coefficients for the model were evaluated as 0.95 and 0.90, respectively.

Development of an hp-version finite element method for computational optimal control

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Warner, Michael S.

1993-01-01

The purpose of this research effort was to begin the study of the application of hp-version finite elements to the numerical solution of optimal control problems. Under NAG-939, the hybrid MACSYMA/FORTRAN code GENCODE was developed which utilized h-version finite elements to successfully approximate solutions to a wide class of optimal control problems. In that code the means for improvement of the solution was the refinement of the time-discretization mesh. With the extension to hp-version finite elements, the degrees of freedom include both nodal values and extra interior values associated with the unknown states, co-states, and controls, the number of which depends on the order of the shape functions in each element. One possible drawback is the increased computational effort within each element required in implementing hp-version finite elements. We are trying to determine whether this computational effort is sufficiently offset by the reduction in the number of time elements used and improved Newton-Raphson convergence so as to be useful in solving optimal control problems in real time. Because certain of the element interior unknowns can be eliminated at the element level by solving a small set of nonlinear algebraic equations in which the nodal values are taken as given, the scheme may turn out to be especially powerful in a parallel computing environment. A different processor could be assigned to each element. The number of processors, strictly speaking, is not required to be any larger than the number of sub-regions which are free of discontinuities of any kind.

Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements

PubMed Central

Whitaker, May

2016-01-01

Purpose Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. Material and methods This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. Results The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. Conclusions The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected. PMID:27504129

Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements.

PubMed

Poder, Joel; Whitaker, May

2016-06-01

Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected.

Optimization and Calibration of Slat Position for a SPECT With Slit-Slat Collimator and Pixelated Detector Crystals

NASA Astrophysics Data System (ADS)

Deng, Xiao; Ma, Tianyu; Lecomte, Roger; Yao, Rutao

2011-10-01

To expand the availability of SPECT for biomedical research, we developed a SPECT imaging system on an existing animal PET detector by adding a slit-slat collimator. As the detector crystals are pixelated, the relative slat-to-crystal position (SCP) in the axial direction affects the photon flux distribution onto the crystals. The accurate knowledge of SCP is important to the axial resolution and sensitivity of the system. This work presents a method for optimizing SCP in system design and for determining SCP in system geometrical calibration. The optimization was achieved by finding the SCP that provides higher spatial resolution in terms of average-root-mean-square (R̅M̅S̅) width of the axial point spread function (PSF) without loss of sensitivity. The calibration was based on the least-square-error method that minimizes the difference between the measured and modeled axial point spread projections. The uniqueness and accuracy of the calibration results were validated through a singular value decomposition (SVD) based approach. Both the optimization and calibration techniques were evaluated with Monte Carlo (MC) simulated data. We showed that the [R̅M̅S̅] was improved about 15% with the optimal SCP as compared to the least-optimal SCP, and system sensitivity was not affected by SCP. The SCP error achieved by the proposed calibration method was less than 0.04 mm. The calibrated SCP value was used in MC simulation to generate the system matrix which was used for image reconstruction. The images of simulated phantoms showed the expected resolution performance and were artifact free. We conclude that the proposed optimization and calibration method is effective for the slit-slat collimator based SPECT systems.

Quantifying Cerebellum Grey Matter and White Matter Perfusion Using Pulsed Arterial Spin Labeling

PubMed Central

Li, Xiufeng; Sarkar, Subhendra N.; Purdy, David E.; Briggs, Richard W.

2014-01-01

To facilitate quantification of cerebellum cerebral blood flow (CBF), studies were performed to systematically optimize arterial spin labeling (ASL) parameters for measuring cerebellum perfusion, segment cerebellum to obtain separate CBF values for grey matter (GM) and white matter (WM), and compare FAIR ASST to PICORE. Cerebellum GM and WM CBF were measured with optimized ASL parameters using FAIR ASST and PICORE in five subjects. Influence of volume averaging in voxels on cerebellar grey and white matter boundaries was minimized by high-probability threshold masks. Cerebellar CBF values determined by FAIR ASST were 43.8 ± 5.1 mL/100 g/min for GM and 27.6 ± 4.5 mL/100 g/min for WM. Quantitative perfusion studies indicated that CBF in cerebellum GM is 1.6 times greater than that in cerebellum WM. Compared to PICORE, FAIR ASST produced similar CBF estimations but less subtraction error and lower temporal, spatial, and intersubject variability. These are important advantages for detecting group and/or condition differences in CBF values. PMID:24949416

A generic hydrological model for a green roof drainage layer.

PubMed

Vesuviano, Gianni; Stovin, Virginia

2013-01-01

A rainfall simulator of length 5 m and width 1 m was used to supply constant intensity and largely spatially uniform water inflow events to 100 different configurations of commercially available green roof drainage layer and protection mat. The runoff from each inflow event was collected and sampled at one-second intervals. Time-series runoff responses were subsequently produced for each of the tested configurations, using the average response of three repeat tests. Runoff models, based on storage routing (dS/dt = I-Q) and a power-law relationship between storage and runoff (Q = kS(n)), and incorporating a delay parameter, were created. The parameters k, n and delay were optimized to best fit each of the runoff responses individually. The range and pattern of optimized parameter values was analysed with respect to roof and event configuration. An analysis was performed to determine the sensitivity of the shape of the runoff profile to changes in parameter values. There appears to be potential to consolidate values of n by roof slope and drainage component material.

Reliability models: the influence of model specification in generation expansion planning

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

Stremel, J.P.

1982-10-01

This paper is a critical evaluation of reliability methods used for generation expansion planning. It is shown that the methods for treating uncertainty are critical for determining the relative reliability value of expansion alternatives. It is also shown that the specification of the reliability model will not favor all expansion options equally. Consequently, the model is biased. In addition, reliability models should be augmented with an economic value of reliability (such as the cost of emergency procedures or energy not served). Generation expansion evaluations which ignore the economic value of excess reliability can be shown to be inconsistent. The conclusionsmore » are that, in general, a reliability model simplifies generation expansion planning evaluations. However, for a thorough analysis, the expansion options should be reviewed for candidates which may be unduly rejected because of the bias of the reliability model. And this implies that for a consistent formulation in an optimization framework, the reliability model should be replaced with a full economic optimization which includes the costs of emergency procedures and interruptions in the objective function.« less

Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

NASA Astrophysics Data System (ADS)

Song, Chen; Zhong-Cheng, Wu; Hong, Lv

2018-03-01

Building Energy forecasting plays an important role in energy management and plan. Using mind evolutionary algorithm to find the optimal network weights and threshold, to optimize the BP neural network, can overcome the problem of the BP neural network into a local minimum point. The optimized network is used for time series prediction, and the same month forecast, to get two predictive values. Then two kinds of predictive values are put into neural network, to get the final forecast value. The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

An intelligent emissions controller for fuel lean gas reburn in coal-fired power plants.

PubMed

Reifman, J; Feldman, E E; Wei, T Y; Glickert, R W

2000-02-01

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NOx) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NOx reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach. Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NOx emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.

Antifungal Susceptibility Testing of Malassezia spp. with an Optimized Colorimetric Broth Microdilution Method.

PubMed

Leong, Cheryl; Buttafuoco, Antonino; Glatz, Martin; Bosshard, Philipp P

2017-06-01

Malassezia is a genus of lipid-dependent yeasts. It is associated with common skin diseases such as pityriasis versicolor and atopic dermatitis and can cause systemic infections in immunocompromised individuals. Owing to the slow growth and lipid requirements of these fastidious yeasts, convenient and reliable antifungal drug susceptibility testing assays for Malassezia spp. are not widely available. Therefore, we optimized a broth microdilution assay for the testing of Malassezia that is based on the CLSI and EUCAST assays for Candida and other yeasts. The addition of ingredients such as lipids and esculin provided a broth medium formulation that enabled the growth of all Malassezia spp. and could be read, with the colorimetric indicator resazurin, by visual and fluorescence readings. We tested the susceptibility of 52 strains of 13 Malassezia species to 11 commonly used antifungals. MIC values determined by visual readings were in good agreement with MIC values determined by fluorescence readings. The lowest MICs were found for the azoles itraconazole, posaconazole, and voriconazole, with MIC 90 values of 0.03 to 1.0 μg/ml, 0.06 to 0.5 μg/ml, and 0.03 to 2.0 μg/ml, respectively. All Malassezia spp. were resistant to echinocandins and griseofulvin. Some Malassezia spp. also showed high MIC values for ketoconazole, which is the most widely recommended topical antifungal to treat Malassezia skin infections. In summary, our assay enables the fast and reliable susceptibility testing of Malassezia spp. with a large panel of different antifungals. Copyright © 2017 American Society for Microbiology.

Antifungal Susceptibility Testing of Malassezia spp. with an Optimized Colorimetric Broth Microdilution Method

PubMed Central

Leong, Cheryl; Buttafuoco, Antonino

2017-01-01

ABSTRACT Malassezia is a genus of lipid-dependent yeasts. It is associated with common skin diseases such as pityriasis versicolor and atopic dermatitis and can cause systemic infections in immunocompromised individuals. Owing to the slow growth and lipid requirements of these fastidious yeasts, convenient and reliable antifungal drug susceptibility testing assays for Malassezia spp. are not widely available. Therefore, we optimized a broth microdilution assay for the testing of Malassezia that is based on the CLSI and EUCAST assays for Candida and other yeasts. The addition of ingredients such as lipids and esculin provided a broth medium formulation that enabled the growth of all Malassezia spp. and could be read, with the colorimetric indicator resazurin, by visual and fluorescence readings. We tested the susceptibility of 52 strains of 13 Malassezia species to 11 commonly used antifungals. MIC values determined by visual readings were in good agreement with MIC values determined by fluorescence readings. The lowest MICs were found for the azoles itraconazole, posaconazole, and voriconazole, with MIC90 values of 0.03 to 1.0 μg/ml, 0.06 to 0.5 μg/ml, and 0.03 to 2.0 μg/ml, respectively. All Malassezia spp. were resistant to echinocandins and griseofulvin. Some Malassezia spp. also showed high MIC values for ketoconazole, which is the most widely recommended topical antifungal to treat Malassezia skin infections. In summary, our assay enables the fast and reliable susceptibility testing of Malassezia spp. with a large panel of different antifungals. PMID:28381607

Preliminary study on the diagnostic value of single-source dual-energy CT in diagnosing cervical lymph node metastasis of thyroid carcinoma

PubMed Central

Zhao, Yanfeng; Li, Xiaolu; Wang, Xiaoyi; Lin, Meng; Zhao, Xinming; Luo, Dehong; Li, Jianying

2017-01-01

Background To investigate the value of single-source dual-energy spectral CT imaging in improving the accuracy of preoperative diagnosis of lymph node metastasis of thyroid carcinoma. Methods Thirty-four thyroid carcinoma patients were enrolled and received spectral CT scanning before thyroidectomy and cervical lymph node dissection surgery. Iodine-based material decomposition (MD) images and 101 sets of monochromatic images from 40 to 140 keV were reconstructed after CT scans. The iodine concentrations (IC) of lymph nodes were measured on the MD images and was normalized to that of common carotid artery to obtain the normalized iodine concentration (NIC). The CT number of lymph nodes as function of photon energy was measured on the 101 sets of images to generate a spectral HU curve and to calculate its slope λHU. The measurements between the metastatic and non-metastatic lymph nodes were statistically compared and receiver operating characteristic (ROC) curves were used to determine the optimal thresholds of these measurements for diagnosing lymph nodes metastasis. Results There were 136 lymph nodes that were pathologically confirmed. Among them, 102 (75%) were metastatic and 34 (25%) were non-metastatic. The IC, NIC and the slope λHU of the metastatic lymph nodes were 3.93±1.58 mg/mL, 0.70±0.55 and 4.63±1.91, respectively. These values were statistically higher than the respective values of 1.77±0.71 mg/mL, 0.29±0.16 and 2.19±0.91 for the non-metastatic lymph nodes (all P<0.001). ROC analysis determined the optimal diagnostic threshold for IC as 2.56 mg/mL, with the sensitivity, specificity and accuracy of 83.3%, 91.2% and 85.3%, respectively. The optimal threshold for NIC was 0.289, with the sensitivity, specificity and accuracy of 96.1%, 76.5% and 91.2%, respectively. The optimal threshold for the spectral curve slope λHU was 2.692, with the sensitivity, specificity and accuracy of 88.2%, 82.4% and 86.8%, respectively. Conclusions The measurements obtained in dual-energy spectral CT improve the sensitivity and accuracy for preoperatively diagnosing lymph node metastasis in thyroid carcinoma. PMID:29268547

Near-infrared reflectance spectroscopy (NIRS) for rapid determination of ginsenoside Rg1 and Re in Chinese patent medicine Naosaitong pill

NASA Astrophysics Data System (ADS)

Zhang, Wei; Qu, Zhengyi; Wang, Yingping; Yao, Chunlin; Bai, Xueyuan; Bian, Shuai; Zhao, Bing

2015-03-01

Ginsenosides in plant samples have been extensively studied because protopanaxadiol saponins are ubiquitous in Chinese patent medicines, in which they can be used in promoting human health as the main active ingredients. A method for rapid determination of two ginsenosides (Rg1 and Re) in Naosaitong (NST) samples using near-infrared reflectance spectroscopy (NIRS) is studied to determine the contents of ginsenoside Rg1 and Re in this work. Partial least square (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. A total of 93 samples were scanned by NIRS, and also by high performance liquid chromatography coupled to a diode array detector to determine the contents of ginsenoside Rg1 and Re. The calibration models for Rg1 and Re had high values of the coefficient of determination (R2) (0.9766 and 0.9764) and low root mean square error of cross validation (RMSECV) (0.0136 and 0.0104), and the values of the standard error of prediction set (SEP) are 0.00764 and 0.0103, which indicate a good correlation between reference values and NIRS predicted values. The overall results show that NIRS could be applied for the rapid determination of the contents of ginsenosides in Ginseng byproducts for pharmaceuticals that develop high-quality Chinese patent medicines.

Automated respiratory cycles selection is highly specific and improves respiratory mechanics analysis.

PubMed

Rigo, Vincent; Graas, Estelle; Rigo, Jacques

2012-07-01

Selected optimal respiratory cycles should allow calculation of respiratory mechanic parameters focusing on patient-ventilator interaction. New computer software automatically selecting optimal breaths and respiratory mechanics derived from those cycles are evaluated. Retrospective study. University level III neonatal intensive care unit. Ten mins synchronized intermittent mandatory ventilation and assist/control ventilation recordings from ten newborns. The ventilator provided respiratory mechanic data (ventilator respiratory cycles) every 10 secs. Pressure, flow, and volume waves and pressure-volume, pressure-flow, and volume-flow loops were reconstructed from continuous pressure-volume recordings. Visual assessment determined assisted leak-free optimal respiratory cycles (selected respiratory cycles). New software graded the quality of cycles (automated respiratory cycles). Respiratory mechanic values were derived from both sets of optimal cycles. We evaluated quality selection and compared mean values and their variability according to ventilatory mode and respiratory mechanic provenance. To assess discriminating power, all 45 "t" values obtained from interpatient comparisons were compared for each respiratory mechanic parameter. A total of 11,724 breaths are evaluated. Automated respiratory cycle/selected respiratory cycle selections agreement is high: 88% of maximal κ with linear weighting. Specificity and positive predictive values are 0.98 and 0.96, respectively. Averaged values are similar between automated respiratory cycle and ventilator respiratory cycle. C20/C alone is markedly decreased in automated respiratory cycle (1.27 ± 0.37 vs. 1.81 ± 0.67). Tidal volume apparent similarity disappears in assist/control: automated respiratory cycle tidal volume (4.8 ± 1.0 mL/kg) is significantly lower than for ventilator respiratory cycle (5.6 ± 1.8 mL/kg). Coefficients of variation decrease for all automated respiratory cycle parameters in all infants. "t" values from ventilator respiratory cycle data are two to three times higher than ventilator respiratory cycles. Automated selection is highly specific. Automated respiratory cycle reflects most the interaction of both ventilator and patient. Improving discriminating power of ventilator monitoring will likely help in assessing disease status and following trends. Averaged parameters derived from automated respiratory cycles are more precise and could be displayed by ventilators to improve real-time fine tuning of ventilator settings.

CFD modelling of sampling locations for early detection of spontaneous combustion in long-wall gob areas.

PubMed

Yuan, Liming; Smith, Alex C

In this study, computational fluid dynamics (CFD) modeling was conducted to optimize gas sampling locations for the early detection of spontaneous heating in longwall gob areas. Initial simulations were carried out to predict carbon monoxide (CO) concentrations at various regulators in the gob using a bleeder ventilation system. Measured CO concentration values at these regulators were then used to calibrate the CFD model. The calibrated CFD model was used to simulate CO concentrations at eight sampling locations in the gob using a bleederless ventilation system to determine the optimal sampling locations for early detection of spontaneous combustion.

Application of the GA-BP Neural Network in Earthwork Calculation

NASA Astrophysics Data System (ADS)

Fang, Peng; Cai, Zhixiong; Zhang, Ping

2018-01-01

The calculation of earthwork quantity is the key factor to determine the project cost estimate and the optimization of the scheme. It is of great significance and function in the excavation of earth and rock works. We use optimization principle of GA-BP intelligent algorithm running process, and on the basis of earthwork quantity and cost information database, the design of the GA-BP neural network intelligent computing model, through the network training and learning, the accuracy of the results meet the actual engineering construction of gauge fan requirements, it provides a new approach for other projects the calculation, and has good popularization value.

Hybrid near-optimal aeroassisted orbit transfer plane change trajectories

NASA Technical Reports Server (NTRS)

Calise, Anthony J.; Duckeman, Gregory A.

1994-01-01

In this paper, a hybrid methodology is used to determine optimal open loop controls for the atmospheric portion of the aeroassisted plane change problem. The method is hybrid in the sense that it combines the features of numerical collocation with the analytically tractable portions of the problem which result when the two-point boundary value problem is cast in the form of a regular perturbation problem. Various levels of approximation are introduced by eliminating particular collocation parameters and their effect upon problem complexity and required number of nodes is discussed. The results include plane changes of 10, 20, and 30 degrees for a given vehicle.

Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm

PubMed Central

Tamjidy, Mehran; Baharudin, B. T. Hang Tuah; Paslar, Shahla; Matori, Khamirul Amin; Sulaiman, Shamsuddin; Fadaeifard, Firouz

2017-01-01

The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon’s entropy. PMID:28772893

Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm.

PubMed

Tamjidy, Mehran; Baharudin, B T Hang Tuah; Paslar, Shahla; Matori, Khamirul Amin; Sulaiman, Shamsuddin; Fadaeifard, Firouz

2017-05-15

The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon's entropy.

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations.

PubMed

León Blanco, José M; González-R, Pedro L; Arroyo García, Carmen Martina; Cózar-Bernal, María José; Calle Suárez, Marcos; Canca Ortiz, David; Rabasco Álvarez, Antonio María; González Rodríguez, María Luisa

2018-01-01

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was hypothesized on timolol-loaded liposomes. As tutorial data for ANN, causal factors were used, which were fed into the computer program. The number of training cycles has been identified in order to optimize the performance of the ANN. The optimization was performed by minimizing the error between the predicted and real response values in the training step. The results showed that training was stopped at 10 000 training cycles with 80% of the pattern values, because at this point the ANN generalizes better. Minimum validation error was achieved at 12 hidden neurons in a single layer. MLR has great prediction ability, with errors between predicted and real values lower than 1% in some of the parameters evaluated. Thus, the performance of this model was compared to that of the MLR using a factorial design. Optimal formulations were identified by minimizing the distance among measured and theoretical parameters, by estimating the prediction errors. Results indicate that the ANN shows much better predictive ability than the MLR model. These findings demonstrate the increased efficiency of the combination of ANN and design of experiments, compared to the conventional MLR modeling techniques.

[Particle size determination by radioisotope x-ray absorptiometry with sedimentation method].

PubMed

Matsui, Y; Furuta, T; Miyagawa, S

1976-09-01

The possibility of radioisotope X-ray absorptiometry to determine the particle size of powder in conjunction with sedimentation was investigated. The experimental accuracy was primarily determined by Cow and X-ray intensity. where Co'=weight concentration of the particle in the suspension w'=(micron/rho)l/(mu/rho)s-rhol/rhos rho; density micron/rho; mass absorption coefficient, suffix l and s indicate dispersion and particle, respectively. The radiosiotopes, Fe-55, Pu-238 and Cd-109 have high w-values over the wide range of the atomic number. However, a source of high micron value such as Fe-55 is not suitable because the optimal X-ray transmission length, Lopt is decided by the expression, micronlLopt approximately 2/(1+C'ow') by using Cd-109 AgKX-ray source, the weight size distribution of particles from the heavy elements such as PbO2 to light elements such as Al2O3 or flyash was determined.

Optimization of diesel oil biodegradation in seawater using statistical experimental methodology.

PubMed

Xia, Wenxiang; Li, Jincheng; Xia, Yan; Song, Zhiwen; Zhou, Jihong

2012-01-01

Petroleum hydrocarbons released into the environment can be harmful to higher organisms, but they can be utilized by microorganisms as the sole source of energy for metabolism. To investigate the optimal conditions of diesel oil biodegradation, the Plackett-Burman (PB) design was used for the optimization in the first step, and N source (NaNO₃), P source (KH₂PO₄) and pH were found to be significant factors affecting oil degradation. Then the response surface methodology (RSM) using a central composite design (CCD) was adopted for the augmentation of diesel oil biodegradation and a fitted quadratic model was obtained. The model F-value of 27.25 and the low probability value (<0.0001) indicate that the model is significant and that the concentration of NaNO₃N, KH₂PO₄ and pH had significant effects on oil removal during the study. Three-dimensional response surface plots were constructed by plotting the response (oil degradation efficiency) on the z-axis against any two independent variables, and the optimal biodegradation conditions of diesel oil (original total petroleum hydrocarbons 125 mg/L) were determined as follows: NaNO₃ 0.143 g, KH₂PO₄ 0.022 g and pH 7.4. These results fit quite well with the C, N and P ratio in biological cells. Results from the present study might provide a new method to estimate the optimal nitrogen and phosphorus concentration in advance for oil biodegradation according to the composition of petroleum.

Time-oriented experimental design method to optimize hydrophilic matrix formulations with gelation kinetics and drug release profiles.

PubMed

Shin, Sangmun; Choi, Du Hyung; Truong, Nguyen Khoa Viet; Kim, Nam Ah; Chu, Kyung Rok; Jeong, Seong Hoon

2011-04-04

A new experimental design methodology was developed by integrating the response surface methodology and the time series modeling. The major purposes were to identify significant factors in determining swelling and release rate from matrix tablets and their relative factor levels for optimizing the experimental responses. Properties of tablet swelling and drug release were assessed with ten factors and two default factors, a hydrophilic model drug (terazosin) and magnesium stearate, and compared with target values. The selected input control factors were arranged in a mixture simplex lattice design with 21 experimental runs. The obtained optimal settings for gelation were PEO, LH-11, Syloid, and Pharmacoat with weight ratios of 215.33 (88.50%), 5.68 (2.33%), 19.27 (7.92%), and 3.04 (1.25%), respectively. The optimal settings for drug release were PEO and citric acid with weight ratios of 191.99 (78.91%) and 51.32 (21.09%), respectively. Based on the results of matrix swelling and drug release, the optimal solutions, target values, and validation experiment results over time were similar and showed consistent patterns with very small biases. The experimental design methodology could be a very promising experimental design method to obtain maximum information with limited time and resources. It could also be very useful in formulation studies by providing a systematic and reliable screening method to characterize significant factors in the sustained release matrix tablet. Copyright © 2011 Elsevier B.V. All rights reserved.

Applying genetic algorithms to set the optimal combination of forest fire related variables and model forest fire susceptibility based on data mining models. The case of Dayu County, China.

PubMed

Hong, Haoyuan; Tsangaratos, Paraskevas; Ilia, Ioanna; Liu, Junzhi; Zhu, A-Xing; Xu, Chong

2018-07-15

The main objective of the present study was to utilize Genetic Algorithms (GA) in order to obtain the optimal combination of forest fire related variables and apply data mining methods for constructing a forest fire susceptibility map. In the proposed approach, a Random Forest (RF) and a Support Vector Machine (SVM) was used to produce a forest fire susceptibility map for the Dayu County which is located in southwest of Jiangxi Province, China. For this purpose, historic forest fires and thirteen forest fire related variables were analyzed, namely: elevation, slope angle, aspect, curvature, land use, soil cover, heat load index, normalized difference vegetation index, mean annual temperature, mean annual wind speed, mean annual rainfall, distance to river network and distance to road network. The Natural Break and the Certainty Factor method were used to classify and weight the thirteen variables, while a multicollinearity analysis was performed to determine the correlation among the variables and decide about their usability. The optimal set of variables, determined by the GA limited the number of variables into eight excluding from the analysis, aspect, land use, heat load index, distance to river network and mean annual rainfall. The performance of the forest fire models was evaluated by using the area under the Receiver Operating Characteristic curve (ROC-AUC) based on the validation dataset. Overall, the RF models gave higher AUC values. Also the results showed that the proposed optimized models outperform the original models. Specifically, the optimized RF model gave the best results (0.8495), followed by the original RF (0.8169), while the optimized SVM gave lower values (0.7456) than the RF, however higher than the original SVM (0.7148) model. The study highlights the significance of feature selection techniques in forest fire susceptibility, whereas data mining methods could be considered as a valid approach for forest fire susceptibility modeling. Copyright © 2018 Elsevier B.V. All rights reserved.

Recursive Branching Simulated Annealing Algorithm

NASA Technical Reports Server (NTRS)

Bolcar, Matthew; Smith, J. Scott; Aronstein, David

2012-01-01

This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal solution, and the region from which new configurations can be selected shrinks as the search continues. The key difference between these algorithms is that in the SA algorithm, a single path, or trajectory, is taken in parameter space, from the starting point to the globally optimal solution, while in the RBSA algorithm, many trajectories are taken; by exploring multiple regions of the parameter space simultaneously, the algorithm has been shown to converge on the globally optimal solution about an order of magnitude faster than when using conventional algorithms. Novel features of the RBSA algorithm include: 1. More efficient searching of the parameter space due to the branching structure, in which multiple random configurations are generated and multiple promising regions of the parameter space are explored; 2. The implementation of a trust region for each parameter in the parameter space, which provides a natural way of enforcing upper- and lower-bound constraints on the parameters; and 3. The optional use of a constrained gradient- search optimization, performed on the continuous variables around each branch s configuration in parameter space to improve search efficiency by allowing for fast fine-tuning of the continuous variables within the trust region at that configuration point.

Optimization of brain PET imaging for a multicentre trial: the French CATI experience.

PubMed

Habert, Marie-Odile; Marie, Sullivan; Bertin, Hugo; Reynal, Moana; Martini, Jean-Baptiste; Diallo, Mamadou; Kas, Aurélie; Trébossen, Régine

2016-12-01

CATI is a French initiative launched in 2010 to handle the neuroimaging of a large cohort of subjects recruited for an Alzheimer's research program called MEMENTO. This paper presents our test protocol and results obtained for the 22 PET centres (overall 13 different scanners) involved in the MEMENTO cohort. We determined acquisition parameters using phantom experiments prior to patient studies, with the aim of optimizing PET quantitative values to the highest possible per site, while reducing, if possible, variability across centres. Jaszczak's and 3D-Hoffman's phantom measurements were used to assess image spatial resolution (ISR), recovery coefficients (RC) in hot and cold spheres, and signal-to-noise ratio (SNR). For each centre, the optimal reconstruction parameters were chosen as those maximizing ISR and RC without a noticeable decrease in SNR. Point-spread-function (PSF) modelling reconstructions were discarded. The three figures of merit extracted from the images reconstructed with optimized parameters and routine schemes were compared, as were volumes of interest ratios extracted from Hoffman acquisitions. The net effect of the 3D-OSEM reconstruction parameter optimization was investigated on a subset of 18 scanners without PSF modelling reconstruction. Compared to the routine parameters of the 22 PET centres, average RC in the two smallest hot and cold spheres and average ISR remained stable or were improved with the optimized reconstruction, at the expense of slight SNR degradation, while the dispersion of values was reduced. For the subset of scanners without PSF modelling, the mean RC of the smallest hot sphere obtained with the optimized reconstruction was significantly higher than with routine reconstruction. The putamen and caudate-to-white matter ratios measured on 3D-Hoffman acquisitions of all centres were also significantly improved by the optimization, while the variance was reduced. This study provides guidelines for optimizing quantitative results for multicentric PET neuroimaging trials.

SU-F-T-187: Quantifying Normal Tissue Sparing with 4D Robust Optimization of Intensity Modulated Proton Therapy

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

Newpower, M; Ge, S; Mohan, R

Purpose: To report an approach to quantify the normal tissue sparing for 4D robustly-optimized versus PTV-optimized IMPT plans. Methods: We generated two sets of 90 DVHs from a patient’s 10-phase 4D CT set; one by conventional PTV-based optimization done in the Eclipse treatment planning system, and the other by an in-house robust optimization algorithm. The 90 DVHs were created for the following scenarios in each of the ten phases of the 4DCT: ± 5mm shift along x, y, z; ± 3.5% range uncertainty and a nominal scenario. A Matlab function written by Gay and Niemierko was modified to calculate EUDmore » for each DVH for the following structures: esophagus, heart, ipsilateral lung and spinal cord. An F-test determined whether or not the variances of each structure’s DVHs were statistically different. Then a t-test determined if the average EUDs for each optimization algorithm were statistically significantly different. Results: T-test results showed each structure had a statistically significant difference in average EUD when comparing robust optimization versus PTV-based optimization. Under robust optimization all structures except the spinal cord received lower EUDs than PTV-based optimization. Using robust optimization the average EUDs decreased 1.45% for the esophagus, 1.54% for the heart and 5.45% for the ipsilateral lung. The average EUD to the spinal cord increased 24.86% but was still well below tolerance. Conclusion: This work has helped quantify a qualitative relationship noted earlier in our work: that robust optimization leads to plans with greater normal tissue sparing compared to PTV-based optimization. Except in the case of the spinal cord all structures received a lower EUD under robust optimization and these results are statistically significant. While the average EUD to the spinal cord increased to 25.06 Gy under robust optimization it is still well under the TD50 value of 66.5 Gy from Emami et al. Supported in part by the NCI U19 CA021239.« less

Determination of COD based on Photoelectrocatalysis of FeTiO3.TiO2/Ti Electrode

NASA Astrophysics Data System (ADS)

Wibowo, D.; Ruslan; Maulidiyah; Nurdin, M.

2017-11-01

Iron infrastructure technology of (Fe)-doped TiO2 nanotubes arrays (NTAs) was prepared for COD photoelectrocatalysis sensor. Fe-TiO2 NTAs was prepared using sol-gel method and coated with TiO2/Ti electrode by immersion technique. The optimization of COD photoelectrocatalytic sensor against Rhodamine B, Methyl Orange, and Methylene Blue organic dyes using photoelectrochemical system in a batch reactor. The high ordered FeTiO3.TiO2/Ti NTAs to determine COD value showed the high photocurrent response linearity and sensitivity to MO organic dye from the concentration of 5 ppm to 75 ppm with an average RSD value of 3.35. The development in this research is to utilize ilmenite mineral as model applied to COD sensor.

Photometric method for determination of acidity constants through integral spectra analysis.

PubMed

Zevatskiy, Yuriy Eduardovich; Ruzanov, Daniil Olegovich; Samoylov, Denis Vladimirovich

2015-04-15

An express method for determination of acidity constants of organic acids, based on the analysis of the integral transmittance vs. pH dependence is developed. The integral value is registered as a photocurrent of photometric device simultaneously with potentiometric titration. The proposed method allows to obtain pKa using only simple and low-cost instrumentation. The optical part of the experimental setup has been optimized through the exclusion of the monochromator device. Thus it only takes 10-15 min to obtain one pKa value with the absolute error of less than 0.15 pH units. Application limitations and reliability of the method have been tested for a series of organic acids of various nature. Copyright © 2015 Elsevier B.V. All rights reserved.

Classification of wetlands vegetation using small scale color infrared imagery

NASA Technical Reports Server (NTRS)

Williamson, F. S. L.

1975-01-01

A classification system for Chesapeake Bay wetlands was derived from the correlation of film density classes and actual vegetation classes. The data processing programs used were developed by the Laboratory for the Applications of Remote Sensing. These programs were tested for their value in classifying natural vegetation, using digitized data from small scale aerial photography. Existing imagery and the vegetation map of Farm Creek Marsh were used to determine the optimal number of classes, and to aid in determining if the computer maps were a believable product.

Method for Household Refrigerators Efficiency Increasing

NASA Astrophysics Data System (ADS)

Lebedev, V. V.; Sumzina, L. V.; Maksimov, A. V.

2017-11-01

The relevance of working processes parameters optimization in air conditioning systems is proved in the work. The research is performed with the use of the simulation modeling method. The parameters optimization criteria are considered, the analysis of target functions is given while the key factors of technical and economic optimization are considered in the article. The search for the optimal solution at multi-purpose optimization of the system is made by finding out the minimum of the dual-target vector created by the Pareto method of linear and weight compromises from target functions of the total capital costs and total operating costs. The tasks are solved in the MathCAD environment. The research results show that the values of technical and economic parameters of air conditioning systems in the areas relating to the optimum solutions’ areas manifest considerable deviations from the minimum values. At the same time, the tendencies for significant growth in deviations take place at removal of technical parameters from the optimal values of both the capital investments and operating costs. The production and operation of conditioners with the parameters which are considerably deviating from the optimal values will lead to the increase of material and power costs. The research allows one to establish the borders of the area of the optimal values for technical and economic parameters at air conditioning systems’ design.

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 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.

Optimal control theory for non-scalar-valued performance criteria. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gerring, H. P.

1971-01-01

The theory of optimal control for nonscalar-valued performance criteria is discussed. In the space, where the performance criterion attains its value, the relations better than, worse than, not better than, and not worse than are defined by a partial order relation. The notion of optimality splits up into superiority and non-inferiority, because worse than is not the complement of better than, in general. A superior solution is better than every other solution. A noninferior solution is not worse than any other solution. Noninferior solutions have been investigated particularly for vector-valued performance criteria. Superior solutions for non-scalar-valued performance criteria attaining their values in abstract partially ordered spaces are emphasized. The main result is the infimum principle which constitutes necessary conditions for a control to be a superior solution to an optimal control problem.

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.

Pharmacist-driven antimicrobial optimization in the emergency department.

PubMed

Davis, Lucretia C; Covey, Robin B; Weston, Jaye S; Hu, Bee Bee Y; Laine, Gregory A

2016-03-01

A pharmacist-driven antimicrobial optimization service in the non-trauma emergency department (ED) of an 864-bed non-profit tertiary care teaching hospital was reviewed to assess its value. Local antimicrobial resistance patterns of urine, wound, stool, and blood cultures were also studied to determine whether or not empiric prescribing practices should be modified. A retrospective electronic chart review was performed for ED patients with positive cultures during two different three-month periods. During Period 1, ED nursing management performed positive culture follow-up. During Period 2, ED clinical pharmacists performed this role. The primary objective was to determine the value of the pharmacist-driven antimicrobial optimization service as measured by the number of clinical interventions made when indicated. The secondary objective was to examine resistance patterns of urine and wound isolates in order to determine if empiric prescribing patterns in the ED should be modified. During Period 1, there were 499 patient visits with subsequent positive cultures. Of those, 76 patients (15%) were discharged home. Nursing management intervened on 21 of 42 (50%) positive cultures that required an intervention; in Period 2, there were 473 patient visits with subsequent positive cultures, and 64 (14%) were discharged home. Pharmacists intervened on 24 of 30 (80%) cultures where an intervention was indicated resulting in a 30% increase in interventions for inappropriate therapy (p = 0.01). A review of the secondary objective revealed a 38% fluoroquinolone resistance rate of E. coli, the most frequently isolated urinary organism. Pharmacist-driven antimicrobial stewardship program resulted in a 30% absolute increase in interventions for inappropriate therapy as compared to the nursing-driven model. This stewardship program has further demonstrated the value of ED pharmacists. Pharmacist interventions should help to ensure that infections are resolved through modification of antimicrobial therapies for patients with bug-drug mismatches. The fluoroquinolone resistance rate indicates a need to consider alternative therapies for uncomplicated urinary tract infections. Nitrofurantoin remains with good coverage against E. coli and Enterococcus species but should be used in uncomplicated patients with normal renal function. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Preparation and Optimization of Immediate Release/Sustained Release Bilayered Tablets of Loxoprofen Using Box-Behnken Design.

PubMed

Tak, Jin Wook; Gupta, Biki; Thapa, Raj Kumar; Woo, Kyu Bong; Kim, Sung Yub; Go, Toe Gyeong; Choi, Yongjoo; Choi, Ju Yeon; Jeong, Jee-Heon; Choi, Han-Gon; Yong, Chul Soon; Kim, Jong Oh

2017-05-01

The aim of our current study was to characterize and optimize loxoprofen immediate release (IR)/sustained release (SR) tablet utilizing a three-factor, three-level Box-Behnken design (BBD) combined with a desirability function. The independent factors included ratio of drug in the IR layer to total drug (X 1 ), ratio of HPMC to drug in the SR layer (X 2 ), and ratio of Eudragit RL PO to drug in the SR layer (X 3 ). The dependent variables assessed were % drug released in distilled water at 30 min (Y 1 ), % drug released in pH 1.2 at 2 h (Y 2 ), and % drug released in pH 6.8 at 12 h (Y 3 ). The responses were fitted to suitable models and statistical validation was performed using analysis of variance. In addition, response surface graphs and contour plots were constructed to determine the effects of different factor level combinations on the responses. The optimized loxoprofen IR/SR tablets were successfully prepared with the determined amounts of ingredients that showed close agreement in the predicted and experimental values of tablet characterization and drug dissolution profile. Therefore, BBD can be utilized for successful optimization of loxoprofen IR/SR tablet, which can be regarded as a suitable substitute for the current marketed formulations.

Optimization of a hardware implementation for pulse coupled neural networks for image applications

NASA Astrophysics Data System (ADS)

Gimeno Sarciada, Jesús; Lamela Rivera, Horacio; Warde, Cardinal

2010-04-01

Pulse Coupled Neural Networks are a very useful tool for image processing and visual applications, since it has the advantages of being invariant to image changes as rotation, scale, or certain distortion. Among other characteristics, the PCNN changes a given image input into a temporal representation which can be easily later analyzed for pattern recognition. The structure of a PCNN though, makes it necessary to determine all of its parameters very carefully in order to function optimally, so that the responses to the kind of inputs it will be subjected are clearly discriminated allowing for an easy and fast post-processing yielding useful results. This tweaking of the system is a taxing process. In this paper we analyze and compare two methods for modeling PCNNs. A purely mathematical model is programmed and a similar circuital model is also designed. Both are then used to determine the optimal values of the several parameters of a PCNN: gain, threshold, time constants for feed-in and threshold and linking leading to an optimal design for image recognition. The results are compared for usefulness, accuracy and speed, as well as the performance and time requirements for fast and easy design, thus providing a tool for future ease of management of a PCNN for different tasks.

Optimal control of hybrid qubits: Implementing the quantum permutation algorithm

NASA Astrophysics Data System (ADS)

Rivera-Ruiz, C. M.; de Lima, E. F.; Fanchini, F. F.; Lopez-Richard, V.; Castelano, L. K.

2018-03-01

The optimal quantum control theory is employed to determine electric pulses capable of producing quantum gates with a fidelity higher than 0.9997, when noise is not taken into account. Particularly, these quantum gates were chosen to perform the permutation algorithm in hybrid qubits in double quantum dots (DQDs). The permutation algorithm is an oracle based quantum algorithm that solves the problem of the permutation parity faster than a classical algorithm without the necessity of entanglement between particles. The only requirement for achieving the speedup is the use of a one-particle quantum system with at least three levels. The high fidelity found in our results is closely related to the quantum speed limit, which is a measure of how fast a quantum state can be manipulated. Furthermore, we model charge noise by considering an average over the optimal field centered at different values of the reference detuning, which follows a Gaussian distribution. When the Gaussian spread is of the order of 5 μ eV (10% of the correct value), the fidelity is still higher than 0.95. Our scheme also can be used for the practical realization of different quantum algorithms in DQDs.

Optimization of critical medium components using response surface methodology for biomass and extracellular polysaccharide production by Agaricus blazei.

PubMed

Liu, Gao-Qiang; Wang, Xiao-Ling

2007-02-01

Response surface methodology (RSM) was applied to optimize the critical medium ingredients of Agaricus blazei. A three-level Box-Behnken factorial design was employed to determine the maximum biomass and extracellular polysaccharide (EPS) yields at optimum levels for glucose, yeast extract (YE), and peptone. A mathematical model was then developed to show the effect of each medium composition and its interactions on the production of mycelial biomass and EPS. The model predicted the maximum biomass yield of 10.86 g/l that appeared at glucose, YE, peptone of 26.3, 6.84, and 6.62 g/l, respectively, while a maximum EPS yield of 348.4 mg/l appeared at glucose, YE, peptone of 28.4, 4.96, 5.60 g/l, respectively. These predicted values were also verified by validation experiments. The excellent correlation between predicted and measured values of each model justifies the validity of both the response models. The results of bioreactor fermentation also show that the optimized culture medium enhanced both biomass (13.91 +/- 0.71 g/l) and EPS (363 +/- 4.1 mg/l) production by Agaricus blazei in a large-scale fermentation process.

A suggestion for computing objective function in model calibration

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang

2014-01-01

A parameter-optimization process (model calibration) is usually required for numerical model applications, which involves the use of an objective function to determine the model cost (model-data errors). The sum of square errors (SSR) has been widely adopted as the objective function in various optimization procedures. However, ‘square error’ calculation was found to be more sensitive to extreme or high values. Thus, we proposed that the sum of absolute errors (SAR) may be a better option than SSR for model calibration. To test this hypothesis, we used two case studies—a hydrological model calibration and a biogeochemical model calibration—to investigate the behavior of a group of potential objective functions: SSR, SAR, sum of squared relative deviation (SSRD), and sum of absolute relative deviation (SARD). Mathematical evaluation of model performance demonstrates that ‘absolute error’ (SAR and SARD) are superior to ‘square error’ (SSR and SSRD) in calculating objective function for model calibration, and SAR behaved the best (with the least error and highest efficiency). This study suggests that SSR might be overly used in real applications, and SAR may be a reasonable choice in common optimization implementations without emphasizing either high or low values (e.g., modeling for supporting resources management).

Kalai-Smorodinsky bargaining solution for optimal resource allocation over wireless DS-CDMA visual sensor networks

NASA Astrophysics Data System (ADS)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2012-01-01

Surveillance applications usually require high levels of video quality, resulting in high power consumption. The existence of a well-behaved scheme to balance video quality and power consumption is crucial for the system's performance. In the present work, we adopt the game-theoretic approach of Kalai-Smorodinsky Bargaining Solution (KSBS) to deal with the problem of optimal resource allocation in a multi-node wireless visual sensor network (VSN). In our setting, the Direct Sequence Code Division Multiple Access (DS-CDMA) method is used for channel access, while a cross-layer optimization design, which employs a central processing server, accounts for the overall system efficacy through all network layers. The task assigned to the central server is the communication with the nodes and the joint determination of their transmission parameters. The KSBS is applied to non-convex utility spaces, efficiently distributing the source coding rate, channel coding rate and transmission powers among the nodes. In the underlying model, the transmission powers assume continuous values, whereas the source and channel coding rates can take only discrete values. Experimental results are reported and discussed to demonstrate the merits of KSBS over competing policies.

BBD Optimization of K-ZnO Catalyst Modification Process for Heterogeneous Transesterification of Rice Bran Oil to Biodiesel

NASA Astrophysics Data System (ADS)

Kabo, K. S.; Yacob, A. R.; Bakar, W. A. W. A.; Buang, N. A.; Bello, A. M.; Ruskam, A.

2016-07-01

Environmentally benign zinc oxide (ZnO) was modified with 0-15% (wt.) potassium through wet impregnation and used in transesterification of rice bran oil (RBO) to form biodiesel. The catalyst was characterized by X-Ray powder Diffraction (XRD), its basic sites determined by back titration and Response Surface Methodology (RSM) Box-Behnken Design (BBD) was used to optimize the modification process variables on the basic sites of the catalyst. The transesterification product, biodiesel was analyzed by Nuclear Magnetic Resonance (NMR) spectroscopy. The result reveals K-modified ZnO with highly increased basic sites. Quadratic model with high regression R2 = 0.9995 was obtained from the ANOVA of modification process, optimization at maximum basic sites criterion gave optimum modification conditions of K-loading = 8.5% (wt.), calcination temperature = 480 oC and time = 4 hours with response and basic sites = 8.14 mmol/g which is in close agreement with the experimental value of 7.64 mmol/g. The catalyst was used and a value of 95.53% biodiesel conversion was obtained and effect of potassium leaching was not significant in the process

Reconstruction of the temperature field for inverse ultrasound hyperthermia calculations at a muscle/bone interface.

PubMed

Liauh, Chihng-Tsung; Shih, Tzu-Ching; Huang, Huang-Wen; Lin, Win-Li

2004-02-01

An inverse algorithm with Tikhonov regularization of order zero has been used to estimate the intensity ratios of the reflected longitudinal wave to the incident longitudinal wave and that of the refracted shear wave to the total transmitted wave into bone in calculating the absorbed power field and then to reconstruct the temperature distribution in muscle and bone regions based on a limited number of temperature measurements during simulated ultrasound hyperthermia. The effects of the number of temperature sensors are investigated, as is the amount of noise superimposed on the temperature measurements, and the effects of the optimal sensor location on the performance of the inverse algorithm. Results show that noisy input data degrades the performance of this inverse algorithm, especially when the number of temperature sensors is small. Results are also presented demonstrating an improvement in the accuracy of the temperature estimates by employing an optimal value of the regularization parameter. Based on the analysis of singular-value decomposition, the optimal sensor position in a case utilizing only one temperature sensor can be determined to make the inverse algorithm converge to the true solution.