Lead Quantification in Urine Samples of Athletes by Coupling DLLME with UV-Vis Spectrophotometry.

PubMed

Faraji, Hakim; Helalizadeh, Masoumeh

2017-04-01

Urine lead level is one of the most employed measures of lead exposure and risk. The urine samples used in this study were obtained from ten healthy male cyclists. Dispersive liquid-liquid microextraction combined with ultraviolet and visible spectrophotometry was utilized for preconcentration, extraction, and determination of lead in urine samples. Optimization of the independent variables was carried out based on chemometric methods in three steps. According to the screening and optimization study, 133 μL of CCl 4 (extracting solvent), 1.34 mL ethanol (dispersing solvent), pH 2.0, 0.00 % of salt, and 0.1 % O,O-diethyl dithiophosphoric (chelating agent) were used as the optimum independent variables for microextraction and determination of lead. Under the optimized conditions, R 2 was 0.9991, and linearity range was 0.01-100 μg L -1 . Precision was evaluated in terms of repeatability and intermediate precision, with relative standard deviations being <9.1 and <15.3 %, respectively. The accuracy was estimated using urine samples of cyclists as real samples and it was confirmed. The relative error of ≤5 % was considered significant in the method specificity study. The lead concentration mean for the cyclists was 3.79 μg L -1 in urine samples. As a result, the proposed method is a robust technique to quantify lead concentrations higher than 11.6 ng L -1 in urine samples.

Computational wing optimization and comparisons with experiment for a semi-span wing model

NASA Technical Reports Server (NTRS)

Waggoner, E. G.; Haney, H. P.; Ballhaus, W. F.

1978-01-01

A computational wing optimization procedure was developed and verified by an experimental investigation of a semi-span variable camber wing model in the NASA Ames Research Center 14 foot transonic wind tunnel. The Bailey-Ballhaus transonic potential flow analysis and Woodward-Carmichael linear theory codes were linked to Vanderplaats constrained minimization routine to optimize model configurations at several subsonic and transonic design points. The 35 deg swept wing is characterized by multi-segmented leading and trailing edge flaps whose hinge lines are swept relative to the leading and trailing edges of the wing. By varying deflection angles of the flap segments, camber and twist distribution can be optimized for different design conditions. Results indicate that numerical optimization can be both an effective and efficient design tool. The optimized configurations had as good or better lift to drag ratios at the design points as the best designs previously tested during an extensive parametric study.

Time domain topology optimization of 3D nanophotonic devices

NASA Astrophysics Data System (ADS)

Elesin, Y.; Lazarov, B. S.; Jensen, J. S.; Sigmund, O.

2014-02-01

We present an efficient parallel topology optimization framework for design of large scale 3D nanophotonic devices. The code shows excellent scalability and is demonstrated for optimization of broadband frequency splitter, waveguide intersection, photonic crystal-based waveguide and nanowire-based waveguide. The obtained results are compared to simplified 2D studies and we demonstrate that 3D topology optimization may lead to significant performance improvements.

Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation.

PubMed

Yuan, Haidong; Fung, Chi-Hang Fred

2015-09-11

Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.

Lead optimization of 3-carboxyl-4(1H)-quinolones to deliver orally bioavailable antimalarials.

PubMed

Zhang, Yiqun; Clark, Julie A; Connelly, Michele C; Zhu, Fangyi; Min, Jaeki; Guiguemde, W Armand; Pradhan, Anupam; Iyer, Lalitha; Furimsky, Anna; Gow, Jason; Parman, Toufan; El Mazouni, Farah; Phillips, Margaret A; Kyle, Dennis E; Mirsalis, Jon; Guy, R Kiplin

2012-05-10

Malaria is a protozoal parasitic disease that is widespread in tropical and subtropical regions of Africa, Asia, and the Americas and causes more than 800,000 deaths per year. The continuing emergence of multidrug-resistant Plasmodium falciparum drives the ongoing need for the development of new and effective antimalarial drugs. Our previous work has explored the preliminary structural optimization of 4(1H)-quinolone ester derivatives, a new series of antimalarials related to the endochins. Herein, we report the lead optimization of 4(1H)-quinolones with a focus on improving both antimalarial potency and bioavailability. These studies led to the development of orally efficacious antimalarials including quinolone analogue 20g, a promising candidate for further optimization.

Lead Optimization of 3-Carboxyl-4(1H)-Quinolones to Deliver Orally Bioavailable Antimalarials

PubMed Central

Zhang, Yiqun; Clark, Julie A; Connelly, Michele C.; Zhu, Fangyi; Min, Jaeki; Guiguemde, W. Armand; Pradhan, Anupam; Iyer, Lalitha; Furimsky, Anna; Gow, Jason; Parman, Toufan; El Mazouni, Farah; Phillips, Margaret A.; Kyle, Dennis E.; Mirsalis, Jon; Guy, R. Kiplin

2012-01-01

Malaria is a protozoal parasitic disease that is widespread in tropical and subtropical regions of Africa, Asia, and the Americas and causes more than 800,000 deaths per year. The continuing emergence of multi-drug-resistant Plasmodium falciparum drives the ongoing need for the development of new and effective antimalarial drugs. Our previous work has explored the preliminary structural optimization of 4(1H)-quinolone ester derivatives, a new series of antimalarials related to the endochins. Herein, we report the lead optimization of 4(1H)-quinolones with a focus on improving both antimalarial potency and bioavailability. These studies led to the development of orally efficacious antimalarials including quinolone analogue 20g, a promising candidate for further optimization. PMID:22435599

Minimal invasive epicardial lead implantation: optimizing cardiac resynchronization with a new mapping device for epicardial lead placement.

PubMed

Maessen, J G; Phelps, B; Dekker, A L A J; Dijkman, B

2004-05-01

To optimize resynchronization in biventricular pacing with epicardial leads, mapping to determine the best pacing site, is a prerequisite. A port access surgical mapping technique was developed that allowed multiple pace site selection and reproducible lead evaluation and implantation. Pressure-volume loops analysis was used for real time guidance in targeting epicardial lead placement. Even the smallest changes in lead position revealed significantly different functional results. Optimizing the pacing site with this technique allowed functional improvement up to 40% versus random pace site selection.

ECG-Based Detection of Early Myocardial Ischemia in a Computational Model: Impact of Additional Electrodes, Optimal Placement, and a New Feature for ST Deviation

PubMed Central

Schulze, Walther H. W.; Jiang, Yuan; Wilhelms, Mathias; Luik, Armin; Dössel, Olaf; Seemann, Gunnar

2015-01-01

In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 2–11% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold. PMID:26587538

ECG-Based Detection of Early Myocardial Ischemia in a Computational Model: Impact of Additional Electrodes, Optimal Placement, and a New Feature for ST Deviation.

PubMed

Loewe, Axel; Schulze, Walther H W; Jiang, Yuan; Wilhelms, Mathias; Luik, Armin; Dössel, Olaf; Seemann, Gunnar

2015-01-01

In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 2-11% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold.

Reducing stock-outs of essential tuberculosis medicines: a system dynamics modelling approach to supply chain management.

PubMed

Bam, L; McLaren, Z M; Coetzee, E; von Leipzig, K H

2017-10-01

The under-performance of supply chains presents a significant hindrance to disease control in developing countries. Stock-outs of essential medicines lead to treatment interruption which can force changes in patient drug regimens, drive drug resistance and increase mortality. This study is one of few to quantitatively evaluate the effectiveness of supply chain policies in reducing shortages and costs. This study develops a systems dynamics simulation model of the downstream supply chain for amikacin, a second-line tuberculosis drug using 10 years of South African data. We evaluate current supply chain performance in terms of reliability, responsiveness and agility, following the widely-used Supply Chain Operation Reference framework. We simulate 141 scenarios that represent different combinations of supplier characteristics, inventory management strategies and demand forecasting methods to identify the Pareto optimal set of management policies that jointly minimize the number of shortages and total cost. Despite long supplier lead times and unpredictable demand, the amikacin supply chain is 98% reliable and agile enough to accommodate a 20% increase in demand without a shortage. However, this is accomplished by overstocking amikacin by 167%, which incurs high holding costs. The responsiveness of suppliers is low: only 57% of orders are delivered to the central provincial drug depot within one month. We identify three Pareto optimal safety stock management policies. Short supplier lead time can produce Pareto optimal outcomes even in the absence of other optimal policies. This study produces concrete, actionable guidelines to cost-effectively reduce stock-outs by implementing optimal supply chain policies. Preferentially selecting drug suppliers with short lead times accommodates unexpected changes in demand. Optimal supply chain management should be an essential component of national policy to reduce the mortality rate. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Optimum study designs.

PubMed

Gu, C; Rao, D C

2001-01-01

Because simplistic designs will lead to prohibitively large sample sizes, the optimization of genetic study designs is critical for successfully mapping genes for complex diseases. Creative designs are necessary for detecting and amplifying the usually weak signals for complex traits. Two important outcomes of a study design--power and resolution--are implicitly tied together by the principle of uncertainty. Overemphasis on either one may lead to suboptimal designs. To achieve optimality for a particular study, therefore, practical measures such as cost-effectiveness must be used to strike a balance between power and resolution. In this light, the myriad of factors involved in study design can be checked for their effects on the ultimate outcomes, and the popular existing designs can be sorted into building blocks that may be useful for particular situations. It is hoped that imaginative construction of novel designs using such building blocks will lead to enhanced efficiency in finding genes for complex human traits.

Back to the Future: Lessons Learned in Modern Target-based and Whole-Cell Lead Optimization of Antimalarials

PubMed Central

Chatterjee, Arnab K; Yeung, Bryan KS

2012-01-01

Antimalarial drug discovery has historically benefited from the whole-cell (phenotypic) screening approach to identify lead molecules in the search for new drugs. However over the past two decades there has been a shift in the pharmaceutical industry to move away from whole-cell screening to target-based approaches. As part of a Wellcome Trust and Medicines for Malaria Venture (MMV) funded consortium to discover new blood-stage antimalarials, we used both approaches to identify new antimalarial chemotypes, two of which have progressed beyond the lead optimization phase and display excellent in vivo efficacy in mice. These two advanced series were identified through a cell-based optimization devoid of target information and in this review we summarize the advantages of this approach versus a target-based optimization. Although the each lead optimization required slightly different medicinal chemistry strategies, we observed some common issues across the different the scaffolds which could be applied to other cell based lead optimization programs. PMID:22242845

Design of experiments utilization to map the processing capabilities of a micro-spray dryer: particle design and throughput optimization in support of drug discovery.

PubMed

Ormes, James D; Zhang, Dan; Chen, Alex M; Hou, Shirley; Krueger, Davida; Nelson, Todd; Templeton, Allen

2013-02-01

There has been a growing interest in amorphous solid dispersions for bioavailability enhancement in drug discovery. Spray drying, as shown in this study, is well suited to produce prototype amorphous dispersions in the Candidate Selection stage where drug supply is limited. This investigation mapped the processing window of a micro-spray dryer to achieve desired particle characteristics and optimize throughput/yield. Effects of processing variables on the properties of hypromellose acetate succinate were evaluated by a fractional factorial design of experiments. Parameters studied include solid loading, atomization, nozzle size, and spray rate. Response variables include particle size, morphology and yield. Unlike most other commercial small-scale spray dryers, the ProCepT was capable of producing particles with a relatively wide mean particle size, ca. 2-35 µm, allowing material properties to be tailored to support various applications. In addition, an optimized throughput of 35 g/hour with a yield of 75-95% was achieved, which affords to support studies from Lead-identification/Lead-optimization to early safety studies. A regression model was constructed to quantify the relationship between processing parameters and the response variables. The response surface curves provide a useful tool to design processing conditions, leading to a reduction in development time and drug usage to support drug discovery.

Enhancing Nursing Staffing Forecasting With Safety Stock Over Lead Time Modeling.

PubMed

McNair, Douglas S

2015-01-01

In balancing competing priorities, it is essential that nursing staffing provide enough nurses to safely and effectively care for the patients. Mathematical models to predict optimal "safety stocks" have been routine in supply chain management for many years but have up to now not been applied in nursing workforce management. There are various aspects that exhibit similarities between the 2 disciplines, such as an evolving demand forecast according to acuity and the fact that provisioning "stock" to meet demand in a future period has nonzero variable lead time. Under assumptions about the forecasts (eg, the demand process is well fit as an autoregressive process) and about the labor supply process (≥1 shifts' lead time), we show that safety stock over lead time for such systems is effectively equivalent to the corresponding well-studied problem for systems with stationary demand bounds and base stock policies. Hence, we can apply existing models from supply chain analytics to find the optimal safety levels of nurse staffing. We use a case study with real data to demonstrate that there are significant benefits from the inclusion of the forecast process when determining the optimal safety stocks.

Evaluating the effects of real power losses in optimal power flow based storage integration

DOE PAGES

Castillo, Anya; Gayme, Dennice

2017-03-27

This study proposes a DC optimal power flow (DCOPF) with losses formulation (the `-DCOPF+S problem) and uses it to investigate the role of real power losses in OPF based grid-scale storage integration. We derive the `- DCOPF+S problem by augmenting a standard DCOPF with storage (DCOPF+S) problem to include quadratic real power loss approximations. This procedure leads to a multi-period nonconvex quadratically constrained quadratic program, which we prove can be solved to optimality using either a semidefinite or second order cone relaxation. Our approach has some important benefits over existing models. It is more computationally tractable than ACOPF with storagemore » (ACOPF+S) formulations and the provably exact convex relaxations guarantee that an optimal solution can be attained for a feasible problem. Adding loss approximations to a DCOPF+S model leads to a more accurate representation of locational marginal prices, which have been shown to be critical to determining optimal storage dispatch and siting in prior ACOPF+S based studies. Case studies demonstrate the improved accuracy of the `-DCOPF+S model over a DCOPF+S model and the computational advantages over an ACOPF+S formulation.« less

Safer passenger car front shapes for pedestrians: A computational approach to reduce overall pedestrian injury risk in realistic impact scenarios.

PubMed

Li, Guibing; Yang, Jikuang; Simms, Ciaran

2017-03-01

Vehicle front shape has a significant influence on pedestrian injuries and the optimal design for overall pedestrian protection remains an elusive goal, especially considering the variability of vehicle-to-pedestrian accident scenarios. Therefore this study aims to develop and evaluate an efficient framework for vehicle front shape optimization for pedestrian protection accounting for the broad range of real world impact scenarios and their distributions in recent accident data. Firstly, a framework for vehicle front shape optimization for pedestrian protection was developed based on coupling of multi-body simulations and a genetic algorithm. This framework was then applied for optimizing passenger car front shape for pedestrian protection, and its predictions were evaluated using accident data and kinematic analyses. The results indicate that the optimization shows a good convergence and predictions of the optimization framework are corroborated when compared to the available accident data, and the optimization framework can distinguish 'good' and 'poor' vehicle front shapes for pedestrian safety. Thus, it is feasible and reliable to use the optimization framework for vehicle front shape optimization for reducing overall pedestrian injury risk. The results also show the importance of considering the broad range of impact scenarios in vehicle front shape optimization. A safe passenger car for overall pedestrian protection should have a wide and flat bumper (covering pedestrians' legs from the lower leg up to the shaft of the upper leg with generally even contacts), a bonnet leading edge height around 750mm, a short bonnet (<800mm) with a shallow or steep angle (either >17° or <12°) and a shallow windscreen (≤30°). Sensitivity studies based on simulations at the population level indicate that the demands for a safe passenger car front shape for head and leg protection are generally consistent, but partially conflict with pelvis protection. In particular, both head and leg injury risk increase with increasing bumper lower height and depth, and decrease with increasing bonnet leading edge height, while pelvis injury risk increases with increasing bonnet leading edge height. However, the effects of bonnet leading edge height and windscreen design on head injury risk are complex and require further analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impact of Chaos Functions on Modern Swarm Optimizers.

PubMed

Emary, E; Zawbaa, Hossam M

2016-01-01

Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates the impact of using chaos-based control of exploration/exploitation rates against using the systematic native control. Three modern algorithms were used in the study namely grey wolf optimizer (GWO), antlion optimizer (ALO) and moth-flame optimizer (MFO) in the domain of machine learning for feature selection. Results on a set of standard machine learning data using a set of assessment indicators prove advance in optimization algorithm performance when using variational repeated periods of declined exploration rates over using systematically decreased exploration rates.

Detecting the Elusive P-Wave: A New ECG Lead to Improve the Recording of Atrial Activity.

PubMed

Kennedy, Alan; Finlay, Dewar D; Guldenring, Daniel; Bond, Raymond R; McLaughlin, James

2016-02-01

In this study, we report on a lead selection method that was developed to detect the optimal bipolar electrode placement for recording of the P-wave. The study population consisted of 117 lead body surface potential maps recorded from 229 healthy subjects. The optimal bipolar lead was developed using the training set (172 subjects) then extracted from the testing dataset (57 subjects) and compared to other lead systems previously reported for improved recording of atrial activity. All leads were assessed in terms of P-wave, QRS, and STT root mean square (RMS). The P/QRST RMS ratio was also investigated to determine the atrioventricular RMS ratio. Finally, the effect of minor electrode misplacements on the P-lead was investigated. The P-lead discovered in this study outperformed all other investigated leads in terms of P-wave RMS. The P-lead showed a significant improvement in median P-wave RMS (93 versus 72 μV, p < 0.001) over the next best lead, Lead II. An improvement in QRS and STT RMS was also observed from the P-lead in comparison to lead II (668 versus 573 μV, p < 0.001) and (327 versus 196 μV, p < 0.001). Although P-wave RMS was reduced by incorrect electrode placement, significant improvement over Lead II was still evident. The P-lead improves P-wave RMS signal strength over all other investigated leads. Also the P-lead does not reduce QRS and STT RMS making it an appropriate choice for atrial arrhythmia monitoring. Given the improvement in signal-to-noise ratio, an improvement in algorithms that rely on P-wave analysis may be achieved.

Optimal transformations leading to normal distributions of positron emission tomography standardized uptake values.

PubMed

Scarpelli, Matthew; Eickhoff, Jens; Cuna, Enrique; Perlman, Scott; Jeraj, Robert

2018-01-30

The statistical analysis of positron emission tomography (PET) standardized uptake value (SUV) measurements is challenging due to the skewed nature of SUV distributions. This limits utilization of powerful parametric statistical models for analyzing SUV measurements. An ad-hoc approach, which is frequently used in practice, is to blindly use a log transformation, which may or may not result in normal SUV distributions. This study sought to identify optimal transformations leading to normally distributed PET SUVs extracted from tumors and assess the effects of therapy on the optimal transformations. The optimal transformation for producing normal distributions of tumor SUVs was identified by iterating the Box-Cox transformation parameter (λ) and selecting the parameter that maximized the Shapiro-Wilk P-value. Optimal transformations were identified for tumor SUV max distributions at both pre and post treatment. This study included 57 patients that underwent 18 F-fluorodeoxyglucose ( 18 F-FDG) PET scans (publically available dataset). In addition, to test the generality of our transformation methodology, we included analysis of 27 patients that underwent 18 F-Fluorothymidine ( 18 F-FLT) PET scans at our institution. After applying the optimal Box-Cox transformations, neither the pre nor the post treatment 18 F-FDG SUV distributions deviated significantly from normality (P  >  0.10). Similar results were found for 18 F-FLT PET SUV distributions (P  >  0.10). For both 18 F-FDG and 18 F-FLT SUV distributions, the skewness and kurtosis increased from pre to post treatment, leading to a decrease in the optimal Box-Cox transformation parameter from pre to post treatment. There were types of distributions encountered for both 18 F-FDG and 18 F-FLT where a log transformation was not optimal for providing normal SUV distributions. Optimization of the Box-Cox transformation, offers a solution for identifying normal SUV transformations for when the log transformation is insufficient. The log transformation is not always the appropriate transformation for producing normally distributed PET SUVs.

Optimal transformations leading to normal distributions of positron emission tomography standardized uptake values

NASA Astrophysics Data System (ADS)

Scarpelli, Matthew; Eickhoff, Jens; Cuna, Enrique; Perlman, Scott; Jeraj, Robert

2018-02-01

The statistical analysis of positron emission tomography (PET) standardized uptake value (SUV) measurements is challenging due to the skewed nature of SUV distributions. This limits utilization of powerful parametric statistical models for analyzing SUV measurements. An ad-hoc approach, which is frequently used in practice, is to blindly use a log transformation, which may or may not result in normal SUV distributions. This study sought to identify optimal transformations leading to normally distributed PET SUVs extracted from tumors and assess the effects of therapy on the optimal transformations. Methods. The optimal transformation for producing normal distributions of tumor SUVs was identified by iterating the Box-Cox transformation parameter (λ) and selecting the parameter that maximized the Shapiro-Wilk P-value. Optimal transformations were identified for tumor SUVmax distributions at both pre and post treatment. This study included 57 patients that underwent 18F-fluorodeoxyglucose (18F-FDG) PET scans (publically available dataset). In addition, to test the generality of our transformation methodology, we included analysis of 27 patients that underwent 18F-Fluorothymidine (18F-FLT) PET scans at our institution. Results. After applying the optimal Box-Cox transformations, neither the pre nor the post treatment 18F-FDG SUV distributions deviated significantly from normality (P  >  0.10). Similar results were found for 18F-FLT PET SUV distributions (P  >  0.10). For both 18F-FDG and 18F-FLT SUV distributions, the skewness and kurtosis increased from pre to post treatment, leading to a decrease in the optimal Box-Cox transformation parameter from pre to post treatment. There were types of distributions encountered for both 18F-FDG and 18F-FLT where a log transformation was not optimal for providing normal SUV distributions. Conclusion. Optimization of the Box-Cox transformation, offers a solution for identifying normal SUV transformations for when the log transformation is insufficient. The log transformation is not always the appropriate transformation for producing normally distributed PET SUVs.

Lead optimization in the nondrug-like space.

PubMed

Zhao, Hongyu

2011-02-01

Drug-like space might be more densely populated with orally available compounds than the remaining chemical space, but lead optimization can still occur outside this space. Oral drug space is more dynamic than the relatively static drug-like space. As new targets emerge and optimization tools advance the oral drug space might expand. Lead optimization protocols are becoming more complex with greater optimization needs to be satisfied, which consequently could change the role of drug-likeness in the process. Whereas drug-like space should usually be explored preferentially, it can be easier to find oral drugs for certain targets in the nondrug-like space. Copyright © 2010 Elsevier Ltd. All rights reserved.

Fragment Based Optimization of Metabotropic Glutamate Receptor 2 (mGluR2) Positive Allosteric Modulators in the Absence of Structural Information.

PubMed

Szabó, György; Túrós, György I; Kolok, Sándor; Vastag, Mónika; Sánta, Zsuzsanna; Dékány, Miklós; Lévay, György I; Greiner, István; Natsumi, Minami; Tatsuya, Watanabe; Keserű, György M

2018-03-14

Metabotropic glutamate receptor 2 (mGluR2) positive allosteric modulators (PAMs) have been implicated as potential pharmacotherapy for psychiatric conditions. Screening our corporate compound deck, we identified a benzotriazole fragment (4) that was rapidly optimized to a potent and metabolically stable early lead (16). The highly lipophilic character of 16, together with its limited solubility, permeability, and high protein binding, however, did not allow reaching of the proof of concept in vivo. Since further attempts on the optimization of druglike properties were unsuccessful, the original hit 4 has been revisited and was optimized following the principles of fragment based drug discovery (FBDD). Lacking structural information on the receptor-ligand complex, we implemented a group efficiency (GE) based strategy and identified a new fragment like lead (60) with more balanced profile. Significant improvement achieved on the druglike properties nominated the compound for in vivo proof of concept studies that revealed the chemotype being a promising PAM lead targeting mGluR2 receptors.

Transesophageal Echocardiography-Guided Epicardial Left Ventricular Lead Placement by Video-Assisted Thoracoscopic Surgery in Nonresponders to Biventricular Pacing and Previous Chest Surgery.

PubMed

Schroeder, Carsten; Chung, Jane M; Mackall, Judith A; Cakulev, Ivan T; Patel, Aaron; Patel, Sunny J; Hoit, Brian D; Sahadevan, Jayakumar

2018-06-14

The aim of the study was to study the feasibility, safety, and efficacy of transesophageal echocardiography-guided intraoperative left ventricular lead placement via a video-assisted thoracoscopic surgery approach in patients with failed conventional biventricular pacing. Twelve patients who could not have the left ventricular lead placed conventionally underwent epicardial left ventricular lead placement by video-assisted thoracoscopic surgery. Eight patients had previous chest surgery (66%). Operative positioning was a modified far lateral supine exposure with 30-degree bed tilt, allowing for groin and sternal access. To determine the optimal left ventricular location for lead placement, the left ventricular surface was divided arbitrarily into nine segments. These segments were transpericardially paced using a hand-held malleable pacing probe identifying the optimal site verified by transesophageal echocardiography. The pacing leads were screwed into position via a limited pericardiotomy. The video-assisted thoracoscopic surgery approach was successful in all patients. Biventricular pacing was achieved in all patients and all reported symptomatic benefit with reduction in New York Heart Association class from III to I-II (P = 0.016). Baseline ejection fraction was 23 ± 3%; within 1-year follow-up, the ejection fraction increased to 32 ± 10% (P = 0.05). The mean follow-up was 566 days. The median length of hospital stay was 7 days with chest tube removal between postoperative days 2 and 5. In patients who are nonresponders to conventional biventricular pacing, intraoperative left ventricular lead placement using anatomical and functional characteristics via a video-assisted thoracoscopic surgery approach is effective in improving heart failure symptoms. This optimized left ventricular lead placement is feasible and safe. Previous chest surgery is no longer an exclusion criterion for a video-assisted thoracoscopic surgery approach.

Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification.

PubMed

Jekova, Irena; Krasteva, Vessela; Leber, Remo; Schmid, Ramun; Twerenbold, Raphael; Müller, Christian; Reichlin, Tobias; Abächerli, Roger

Electrocardiogram (ECG) biometrics is an advanced technology, not yet covered by guidelines on criteria, features and leads for maximal authentication accuracy. This study aims to define the minimal set of morphological metrics in 12-lead ECG by optimization towards high reliability and security, and validation in a person verification model across a large population. A standard 12-lead resting ECG database from 574 non-cardiac patients with two remote recordings (>1year apart) was used. A commercial ECG analysis module (Schiller AG) measured 202 morphological features, including lead-specific amplitudes, durations, ST-metrics, and axes. Coefficient of variation (CV, intersubject variability) and percent-mean-absolute-difference (PMAD, intrasubject reproducibility) defined the optimization (PMAD/CV→min) and restriction (CV<30%) criteria for selection of the most stable and distinctive features. Linear discriminant analysis (LDA) validated the non-redundant feature set for person verification. Maximal LDA verification sensitivity (85.3%) and specificity (86.4%) were validated for 11 optimal features: R-amplitude (I,II,V1,V2,V3,V5), S-amplitude (V1,V2), Tnegative-amplitude (aVR), and R-duration (aVF,V1). Copyright © 2016 Elsevier Inc. All rights reserved.

Computational procedure of optimal inventory model involving controllable backorder rate and variable lead time with defective units

NASA Astrophysics Data System (ADS)

Lee, Wen-Chuan; Wu, Jong-Wuu; Tsou, Hsin-Hui; Lei, Chia-Ling

2012-10-01

This article considers that the number of defective units in an arrival order is a binominal random variable. We derive a modified mixture inventory model with backorders and lost sales, in which the order quantity and lead time are decision variables. In our studies, we also assume that the backorder rate is dependent on the length of lead time through the amount of shortages and let the backorder rate be a control variable. In addition, we assume that the lead time demand follows a mixture of normal distributions, and then relax the assumption about the form of the mixture of distribution functions of the lead time demand and apply the minimax distribution free procedure to solve the problem. Furthermore, we develop an algorithm procedure to obtain the optimal ordering strategy for each case. Finally, three numerical examples are also given to illustrate the results.

Extending flood forecasting lead time in a large watershed by coupling WRF QPF with a distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, Ji; Chen, Yangbo; Wang, Huanyu; Qin, Jianming; Li, Jie; Chiao, Sen

2017-03-01

Long lead time flood forecasting is very important for large watershed flood mitigation as it provides more time for flood warning and emergency responses. The latest numerical weather forecast model could provide 1-15-day quantitative precipitation forecasting products in grid format, and by coupling this product with a distributed hydrological model could produce long lead time watershed flood forecasting products. This paper studied the feasibility of coupling the Liuxihe model with the Weather Research and Forecasting quantitative precipitation forecast (WRF QPF) for large watershed flood forecasting in southern China. The QPF of WRF products has three lead times, including 24, 48 and 72 h, with the grid resolution being 20 km  × 20 km. The Liuxihe model is set up with freely downloaded terrain property; the model parameters were previously optimized with rain gauge observed precipitation, and re-optimized with the WRF QPF. Results show that the WRF QPF has bias with the rain gauge precipitation, and a post-processing method is proposed to post-process the WRF QPF products, which improves the flood forecasting capability. With model parameter re-optimization, the model's performance improves also. This suggests that the model parameters be optimized with QPF, not the rain gauge precipitation. With the increasing of lead time, the accuracy of the WRF QPF decreases, as does the flood forecasting capability. Flood forecasting products produced by coupling the Liuxihe model with the WRF QPF provide a good reference for large watershed flood warning due to its long lead time and rational results.

Optimism and recovery after acute coronary syndrome: a clinical cohort study.

PubMed

Ronaldson, Amy; Molloy, Gerard J; Wikman, Anna; Poole, Lydia; Kaski, Juan-Carlos; Steptoe, Andrew

2015-04-01

Optimism is associated with reduced cardiovascular mortality, but its impact on recovery after acute coronary syndrome (ACS) is poorly understood. We hypothesized that greater optimism would lead to more effective physical and emotional adaptation after ACS and would buffer the impact of persistent depressive symptoms on clinical outcomes. This prospective observational clinical study took place in an urban general hospital and involved 369 patients admitted with a documented ACS. Optimism was assessed with a standardized questionnaire. The main outcomes were physical health status, depressive symptoms, smoking, physical activity, and fruit and vegetable consumption measured 12 months after ACS, and composite major adverse cardiac events (cardiovascular death, readmission with reinfarction or unstable angina, and coronary artery bypass graft surgery) assessed over an average of 45.7 months. We found that optimism predicted better physical health status 12 months after ACS independently of baseline physical health, age, sex, ethnicity, social deprivation, and clinical risk factors (B = 0.65, 95% confidence interval [CI] = 0.10-1.20). Greater optimism also predicted reduced risk of depressive symptoms (odds ratio = 0.82, 95% CI = 0.74-0.90), more smoking cessation, and more fruit and vegetable consumption at 12 months. Persistent depressive symptoms 12 months after ACS predicted major adverse cardiac events over subsequent years (odds ratio = 2.56, 95% CI = 1.16-5.67), but only among individuals low in optimism (optimism × depression interaction; p = .014). Optimism predicts better physical and emotional health after ACS. Measuring optimism may help identify individuals at risk. Pessimistic outlooks can be modified, potentially leading to improved recovery after major cardiac events.

Epicardial left ventricular lead placement for cardiac resynchronization therapy: optimal pace site selection with pressure-volume loops.

PubMed

Dekker, A L A J; Phelps, B; Dijkman, B; van der Nagel, T; van der Veen, F H; Geskes, G G; Maessen, J G

2004-06-01

Patients in heart failure with left bundle branch block benefit from cardiac resynchronization therapy. Usually the left ventricular pacing lead is placed by coronary sinus catheterization; however, this procedure is not always successful, and patients may be referred for surgical epicardial lead placement. The objective of this study was to develop a method to guide epicardial lead placement in cardiac resynchronization therapy. Eleven patients in heart failure who were eligible for cardiac resynchronization therapy were referred for surgery because of failed coronary sinus left ventricular lead implantation. Minithoracotomy or thoracoscopy was performed, and a temporary epicardial electrode was used for biventricular pacing at various sites on the left ventricle. Pressure-volume loops with the conductance catheter were used to select the best site for each individual patient. Relative to the baseline situation, biventricular pacing with an optimal left ventricular lead position significantly increased stroke volume (+39%, P =.01), maximal left ventricular pressure derivative (+20%, P =.02), ejection fraction (+30%, P =.007), and stroke work (+66%, P =.006) and reduced end-systolic volume (-6%, P =.04). In contrast, biventricular pacing at a suboptimal site did not significantly change left ventricular function and even worsened it in some cases. To optimize cardiac resynchronization therapy with epicardial leads, mapping to determine the best pace site is a prerequisite. Pressure-volume loops offer real-time guidance for targeting epicardial lead placement during minimal invasive surgery.

An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level

PubMed Central

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach. PMID:24741352

An iterative approach for the optimization of pavement maintenance management at the network level.

PubMed

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Pellicer, Eugenio; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach.

Corrections to scaling for watersheds, optimal path cracks, and bridge lines

NASA Astrophysics Data System (ADS)

Fehr, E.; Schrenk, K. J.; Araújo, N. A. M.; Kadau, D.; Grassberger, P.; Andrade, J. S., Jr.; Herrmann, H. J.

2012-07-01

We study the corrections to scaling for the mass of the watershed, the bridge line, and the optimal path crack in two and three dimensions (2D and 3D). We disclose that these models have numerically equivalent fractal dimensions and leading correction-to-scaling exponents. We conjecture all three models to possess the same fractal dimension, namely, df=1.2168±0.0005 in 2D and df=2.487±0.003 in 3D, and the same exponent of the leading correction, Ω=0.9±0.1 and Ω=1.0±0.1, respectively. The close relations between watersheds, optimal path cracks in the strong disorder limit, and bridge lines are further supported by either heuristic or exact arguments.

Resonator reset in circuit QED by optimal control for large open quantum systems

NASA Astrophysics Data System (ADS)

Boutin, Samuel; Andersen, Christian Kraglund; Venkatraman, Jayameenakshi; Ferris, Andrew J.; Blais, Alexandre

2017-10-01

We study an implementation of the open GRAPE (gradient ascent pulse engineering) algorithm well suited for large open quantum systems. While typical implementations of optimal control algorithms for open quantum systems rely on explicit matrix exponential calculations, our implementation avoids these operations, leading to a polynomial speedup of the open GRAPE algorithm in cases of interest. This speedup, as well as the reduced memory requirements of our implementation, are illustrated by comparison to a standard implementation of open GRAPE. As a practical example, we apply this open-system optimization method to active reset of a readout resonator in circuit QED. In this problem, the shape of a microwave pulse is optimized such as to empty the cavity from measurement photons as fast as possible. Using our open GRAPE implementation, we obtain pulse shapes, leading to a reset time over 4 times faster than passive reset.

Monitoring Pb in Aqueous Samples by Using Low Density Solvent on Air-Assisted Dispersive Liquid-Liquid Microextraction Coupled with UV-Vis Spectrophotometry.

PubMed

Nejad, Mina Ghasemi; Faraji, Hakim; Moghimi, Ali

2017-04-01

In this study, AA-DLLME combined with UV-Vis spectrophotometry was developed for pre-concentration, microextraction and determination of lead in aqueous samples. Optimization of the independent variables was carried out according to chemometric methods in three steps. According to the screening and optimization study, 86 μL of 1-undecanol (extracting solvent), 12 times syringe pumps, pH 2.0, 0.00% of salt and 0.1% DDTP (chelating agent) were chosen as the optimum independent variables for microextraction and determination of lead. Under the optimized conditions, R = 0.9994, and linearity range was 0.01-100 µg mL -1 . LOD and LOQ were 3.4 and 11.6 ng mL -1 , respectively. The method was applied for analysis of real water samples, such as tap, mineral, river and waste water.

76 FR 69743 - Proposed Collection; Comment Request; Application for Collaboration With the NIH Center for...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-09

... neglected disease through a variety of programs delivering assay development, screening, hit to lead chemistry, lead optimization, chemical biology studies, drug development capabilities, expertise, and clinical/regulatory resources in a collaborative environment with the goal of moving promising therapeutics...

[Hygienic assessment of a recirculatory combined air-conditioning extract-and-input system in office building].

PubMed

Malysheva, A G; Abramov, E G

2006-01-01

The high concentrations of lead were reveled in the air and dust of some premises and on the filters of a combined air-conditioning extract-and-input system in the high-rise office buildings located in the ecologically lead favorable environment. The dust content of lead in some premises on the first floors dust was as high as 200 mg/kg, which was more than 6 times higher than that in the soil at the highway near the office buildings. The use of new technologies and devices for cleaning and optimizing the air in the premises requires analytical studies to assess the quality of the environment, by taking into account the optimal conditions of their operation.

Hit-to-lead optimization of phenylsulfonyl hydrazides for a potent suppressor of PGE2 production: Synthesis, biological activity, and molecular docking study.

PubMed

Kim, Minju; Lee, Sunhoe; Park, Eun Beul; Kim, Kwang Jong; Lee, Hwi Ho; Shin, Ji-Sun; Fischer, Katrin; Koeberle, Andreas; Werz, Oliver; Lee, Kyung-Tae; Lee, Jae Yeol

2016-01-01

Preliminary hit-to-lead optimization of a novel series of phenylsulfonyl hydrazide derivatives, which were derived from the high throughput screening hit compound 1 (IC50=5700nM against PGE2 production), for a potent suppressor of PGE2 production is described. Subsequent optimization led to the identification of the potent lead compound 8n with IC50 values of 4.5 and 6.9nM, respectively, against LPS-induced PGE2 production and NO production in RAW 264.7 macrophage cells. In addition, 8n was about 30- and >150-fold more potent against mPGES-1 enzyme in a cell-free assay (IC50=70nM) than MK-886 and hit compound 1, respectively. Molecular docking suggests that compound 8n could inhibit PGE2 production by blocking the PGH2 binding site of human mPGES-1 enzyme. Copyright © 2015 Elsevier Ltd. All rights reserved.

Transient Growth Analysis of Compressible Boundary Layers with Parabolized Stability Equations

NASA Technical Reports Server (NTRS)

Paredes, Pedro; Choudhari, Meelan M.; Li, Fei; Chang, Chau-Lyan

2016-01-01

The linear form of parabolized linear stability equations (PSE) is used in a variational approach to extend the previous body of results for the optimal, non-modal disturbance growth in boundary layer flows. This methodology includes the non-parallel effects associated with the spatial development of boundary layer flows. As noted in literature, the optimal initial disturbances correspond to steady counter-rotating stream-wise vortices, which subsequently lead to the formation of stream-wise-elongated structures, i.e., streaks, via a lift-up effect. The parameter space for optimal growth is extended to the hypersonic Mach number regime without any high enthalpy effects, and the effect of wall cooling is studied with particular emphasis on the role of the initial disturbance location and the value of the span-wise wavenumber that leads to the maximum energy growth up to a specified location. Unlike previous predictions that used a basic state obtained from a self-similar solution to the boundary layer equations, mean flow solutions based on the full Navier-Stokes (NS) equations are used in select cases to help account for the viscous-inviscid interaction near the leading edge of the plate and also for the weak shock wave emanating from that region. These differences in the base flow lead to an increasing reduction with Mach number in the magnitude of optimal growth relative to the predictions based on self-similar mean-flow approximation. Finally, the maximum optimal energy gain for the favorable pressure gradient boundary layer near a planar stagnation point is found to be substantially weaker than that in a zero pressure gradient Blasius boundary layer.

77 FR 10758 - Submission for OMB Review; Comment Request; Application for Collaboration With the NIH Center for...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-23

... programs delivering assay development, screening, hit to lead chemistry, lead optimization, chemical biology studies, drug development capabilities, expertise, and clinical/regulatory resources in a collaborative environment with the goal of moving promising therapeutics into human clinical trials. NCTT uses...

Optimism and Recovery After Acute Coronary Syndrome: A Clinical Cohort Study

PubMed Central

Ronaldson, Amy; Molloy, Gerard J.; Wikman, Anna; Poole, Lydia; Kaski, Juan-Carlos; Steptoe, Andrew

2015-01-01

ABSTRACT Objective Optimism is associated with reduced cardiovascular mortality, but its impact on recovery after acute coronary syndrome (ACS) is poorly understood. We hypothesized that greater optimism would lead to more effective physical and emotional adaptation after ACS and would buffer the impact of persistent depressive symptoms on clinical outcomes. Methods This prospective observational clinical study took place in an urban general hospital and involved 369 patients admitted with a documented ACS. Optimism was assessed with a standardized questionnaire. The main outcomes were physical health status, depressive symptoms, smoking, physical activity, and fruit and vegetable consumption measured 12 months after ACS, and composite major adverse cardiac events (cardiovascular death, readmission with reinfarction or unstable angina, and coronary artery bypass graft surgery) assessed over an average of 45.7 months. Results We found that optimism predicted better physical health status 12 months after ACS independently of baseline physical health, age, sex, ethnicity, social deprivation, and clinical risk factors (B = 0.65, 95% confidence interval [CI] = 0.10–1.20). Greater optimism also predicted reduced risk of depressive symptoms (odds ratio = 0.82, 95% CI = 0.74–0.90), more smoking cessation, and more fruit and vegetable consumption at 12 months. Persistent depressive symptoms 12 months after ACS predicted major adverse cardiac events over subsequent years (odds ratio = 2.56, 95% CI = 1.16–5.67), but only among individuals low in optimism (optimism × depression interaction; p = .014). Conclusions Optimism predicts better physical and emotional health after ACS. Measuring optimism may help identify individuals at risk. Pessimistic outlooks can be modified, potentially leading to improved recovery after major cardiac events. PMID:25738438

Resource Optimization Scheme for Multimedia-Enabled Wireless Mesh Networks

PubMed Central

Ali, Amjad; Ahmed, Muhammad Ejaz; Piran, Md. Jalil; Suh, Doug Young

2014-01-01

Wireless mesh networking is a promising technology that can support numerous multimedia applications. Multimedia applications have stringent quality of service (QoS) requirements, i.e., bandwidth, delay, jitter, and packet loss ratio. Enabling such QoS-demanding applications over wireless mesh networks (WMNs) require QoS provisioning routing protocols that lead to the network resource underutilization problem. Moreover, random topology deployment leads to have some unused network resources. Therefore, resource optimization is one of the most critical design issues in multi-hop, multi-radio WMNs enabled with multimedia applications. Resource optimization has been studied extensively in the literature for wireless Ad Hoc and sensor networks, but existing studies have not considered resource underutilization issues caused by QoS provisioning routing and random topology deployment. Finding a QoS-provisioned path in wireless mesh networks is an NP complete problem. In this paper, we propose a novel Integer Linear Programming (ILP) optimization model to reconstruct the optimal connected mesh backbone topology with a minimum number of links and relay nodes which satisfies the given end-to-end QoS demands for multimedia traffic and identification of extra resources, while maintaining redundancy. We further propose a polynomial time heuristic algorithm called Link and Node Removal Considering Residual Capacity and Traffic Demands (LNR-RCTD). Simulation studies prove that our heuristic algorithm provides near-optimal results and saves about 20% of resources from being wasted by QoS provisioning routing and random topology deployment. PMID:25111241

Resource optimization scheme for multimedia-enabled wireless mesh networks.

PubMed

Ali, Amjad; Ahmed, Muhammad Ejaz; Piran, Md Jalil; Suh, Doug Young

2014-08-08

Wireless mesh networking is a promising technology that can support numerous multimedia applications. Multimedia applications have stringent quality of service (QoS) requirements, i.e., bandwidth, delay, jitter, and packet loss ratio. Enabling such QoS-demanding applications over wireless mesh networks (WMNs) require QoS provisioning routing protocols that lead to the network resource underutilization problem. Moreover, random topology deployment leads to have some unused network resources. Therefore, resource optimization is one of the most critical design issues in multi-hop, multi-radio WMNs enabled with multimedia applications. Resource optimization has been studied extensively in the literature for wireless Ad Hoc and sensor networks, but existing studies have not considered resource underutilization issues caused by QoS provisioning routing and random topology deployment. Finding a QoS-provisioned path in wireless mesh networks is an NP complete problem. In this paper, we propose a novel Integer Linear Programming (ILP) optimization model to reconstruct the optimal connected mesh backbone topology with a minimum number of links and relay nodes which satisfies the given end-to-end QoS demands for multimedia traffic and identification of extra resources, while maintaining redundancy. We further propose a polynomial time heuristic algorithm called Link and Node Removal Considering Residual Capacity and Traffic Demands (LNR-RCTD). Simulation studies prove that our heuristic algorithm provides near-optimal results and saves about 20% of resources from being wasted by QoS provisioning routing and random topology deployment.

Threshold Determination for Local Instantaneous Sea Surface Height Derivation with Icebridge Data in Beaufort Sea

NASA Astrophysics Data System (ADS)

Zhu, C.; Zhang, S.; Xiao, F.; Li, J.; Yuan, L.; Zhang, Y.; Zhu, T.

2018-05-01

The NASA Operation IceBridge (OIB) mission is the largest program in the Earth's polar remote sensing science observation project currently, initiated in 2009, which collects airborne remote sensing measurements to bridge the gap between NASA's ICESat and the upcoming ICESat-2 mission. This paper develop an improved method that optimizing the selection method of Digital Mapping System (DMS) image and using the optimal threshold obtained by experiments in Beaufort Sea to calculate the local instantaneous sea surface height in this area. The optimal threshold determined by comparing manual selection with the lowest (Airborne Topographic Mapper) ATM L1B elevation threshold of 2 %, 1 %, 0.5 %, 0.2 %, 0.1 % and 0.05 % in A, B, C sections, the mean of mean difference are 0.166 m, 0.124 m, 0.083 m, 0.018 m, 0.002 m and -0.034 m. Our study shows the lowest L1B data of 0.1 % is the optimal threshold. The optimal threshold and manual selections are also used to calculate the instantaneous sea surface height over images with leads, we find that improved methods has closer agreement with those from L1B manual selections. For these images without leads, the local instantaneous sea surface height estimated by using the linear equations between distance and sea surface height calculated over images with leads.

The Dilution Effect and Information Integration in Perceptual Decision Making

PubMed Central

Hotaling, Jared M.; Cohen, Andrew L.; Shiffrin, Richard M.; Busemeyer, Jerome R.

2015-01-01

In cognitive science there is a seeming paradox: On the one hand, studies of human judgment and decision making have repeatedly shown that people systematically violate optimal behavior when integrating information from multiple sources. On the other hand, optimal models, often Bayesian, have been successful at accounting for information integration in fields such as categorization, memory, and perception. This apparent conflict could be due, in part, to different materials and designs that lead to differences in the nature of processing. Stimuli that require controlled integration of information, such as the quantitative or linguistic information (commonly found in judgment studies), may lead to suboptimal performance. In contrast, perceptual stimuli may lend themselves to automatic processing, resulting in integration that is closer to optimal. We tested this hypothesis with an experiment in which participants categorized faces based on resemblance to a family patriarch. The amount of evidence contained in the top and bottom halves of each test face was independently manipulated. These data allow us to investigate a canonical example of sub-optimal information integration from the judgment and decision making literature, the dilution effect. Splitting the top and bottom halves of a face, a manipulation meant to encourage controlled integration of information, produced farther from optimal behavior and larger dilution effects. The Multi-component Information Accumulation model, a hybrid optimal/averaging model of information integration, successfully accounts for key accuracy, response time, and dilution effects. PMID:26406323

The Dilution Effect and Information Integration in Perceptual Decision Making.

PubMed

Hotaling, Jared M; Cohen, Andrew L; Shiffrin, Richard M; Busemeyer, Jerome R

2015-01-01

In cognitive science there is a seeming paradox: On the one hand, studies of human judgment and decision making have repeatedly shown that people systematically violate optimal behavior when integrating information from multiple sources. On the other hand, optimal models, often Bayesian, have been successful at accounting for information integration in fields such as categorization, memory, and perception. This apparent conflict could be due, in part, to different materials and designs that lead to differences in the nature of processing. Stimuli that require controlled integration of information, such as the quantitative or linguistic information (commonly found in judgment studies), may lead to suboptimal performance. In contrast, perceptual stimuli may lend themselves to automatic processing, resulting in integration that is closer to optimal. We tested this hypothesis with an experiment in which participants categorized faces based on resemblance to a family patriarch. The amount of evidence contained in the top and bottom halves of each test face was independently manipulated. These data allow us to investigate a canonical example of sub-optimal information integration from the judgment and decision making literature, the dilution effect. Splitting the top and bottom halves of a face, a manipulation meant to encourage controlled integration of information, produced farther from optimal behavior and larger dilution effects. The Multi-component Information Accumulation model, a hybrid optimal/averaging model of information integration, successfully accounts for key accuracy, response time, and dilution effects.

Volume reconstruction optimization for tomo-PIV algorithms applied to experimental data

NASA Astrophysics Data System (ADS)

Martins, Fabio J. W. A.; Foucaut, Jean-Marc; Thomas, Lionel; Azevedo, Luis F. A.; Stanislas, Michel

2015-08-01

Tomographic PIV is a three-component volumetric velocity measurement technique based on the tomographic reconstruction of a particle distribution imaged by multiple camera views. In essence, the performance and accuracy of this technique is highly dependent on the parametric adjustment and the reconstruction algorithm used. Although synthetic data have been widely employed to optimize experiments, the resulting reconstructed volumes might not have optimal quality. The purpose of the present study is to offer quality indicators that can be applied to data samples in order to improve the quality of velocity results obtained by the tomo-PIV technique. The methodology proposed can potentially lead to significantly reduction in the time required to optimize a tomo-PIV reconstruction, also leading to better quality velocity results. Tomo-PIV data provided by a six-camera turbulent boundary-layer experiment were used to optimize the reconstruction algorithms according to this methodology. Velocity statistics measurements obtained by optimized BIMART, SMART and MART algorithms were compared with hot-wire anemometer data and velocity measurement uncertainties were computed. Results indicated that BIMART and SMART algorithms produced reconstructed volumes with equivalent quality as the standard MART with the benefit of reduced computational time.

Infant Massage: A Strategy to Promote Self-Efficacy in Parents of Blind Infants

ERIC Educational Resources Information Center

Lappin, Grace

2006-01-01

For successful communication to exist between a caregiver and infant, the caregiver must feel confident about her/his ability to parent and also have specific and accurate knowledge about the behaviours required for optimal care-giving; lack of this knowledge may lead to feelings of uncertainty and less than optimal communication. Studies indicate…

The lead-lag relationship between stock index and stock index futures: A thermal optimal path method

NASA Astrophysics Data System (ADS)

Gong, Chen-Chen; Ji, Shen-Dan; Su, Li-Ling; Li, Sai-Ping; Ren, Fei

2016-02-01

The study of lead-lag relationship between stock index and stock index futures is of great importance for its wide application in hedging and portfolio investments. Previous works mainly use conventional methods like Granger causality test, GARCH model and error correction model, and focus on the causality relation between the index and futures in a certain period. By using a non-parametric approach-thermal optimal path (TOP) method, we study the lead-lag relationship between China Securities Index 300 (CSI 300), Hang Seng Index (HSI), Standard and Poor 500 (S&P 500) Index and their associated futures to reveal the variance of their relationship over time. Our finding shows evidence of pronounced futures leadership for well established index futures, namely HSI and S&P 500 index futures, while index of developing market like CSI 300 has pronounced leadership. We offer an explanation based on the measure of an indicator which quantifies the differences between spot and futures prices for the surge of lead-lag function. Our results provide new perspectives for the understanding of the dynamical evolution of lead-lag relationship between stock index and stock index futures, which is valuable for the study of market efficiency and its applications.

Study of optimal laser parameters for cutting QFN packages by Taguchi's matrix method

NASA Astrophysics Data System (ADS)

Li, Chen-Hao; Tsai, Ming-Jong; Yang, Ciann-Dong

2007-06-01

This paper reports the study of optimal laser parameters for cutting QFN (Quad Flat No-lead) packages by using a diode pumped solid-state laser system (DPSSL). The QFN cutting path includes two different materials, which are the encapsulated epoxy and a copper lead frame substrate. The Taguchi's experimental method with orthogonal array of L 9(3 4) is employed to obtain optimal combinatorial parameters. A quantified mechanism was proposed for examining the laser cutting quality of a QFN package. The influences of the various factors such as laser current, laser frequency, and cutting speed on the laser cutting quality is also examined. From the experimental results, the factors on the cutting quality in the order of decreasing significance are found to be (a) laser frequency, (b) cutting speed, and (c) laser driving current. The optimal parameters were obtained at the laser frequency of 2 kHz, the cutting speed of 2 mm/s, and the driving current of 29 A. Besides identifying this sequence of dominance, matrix experiment also determines the best level for each control factor. The verification experiment confirms that the application of laser cutting technology to QFN is very successfully by using the optimal laser parameters predicted from matrix experiments.

Removing lead from metallic mixture of waste printed circuit boards by vacuum distillation: factorial design and removal mechanism.

PubMed

Li, Xingang; Gao, Yujie; Ding, Hui

2013-10-01

The lead removal from the metallic mixture of waste printed circuit boards by vacuum distillation was optimized using experimental design, and a mathematical model was established to elucidate the removal mechanism. The variables studied in lead evaporation consisted of the chamber pressure, heating temperature, heating time, particle size and initial mass. The low-level chamber pressure was fixed at 0.1 Pa as the operation pressure. The application of two-level factorial design generated a first-order polynomial that agreed well with the data for evaporation efficiency of lead. The heating temperature and heating time exhibited significant effects on the efficiency, which was validated by means of the copper-lead mixture experiments. The optimized operating conditions within the region studied were the chamber pressure of 0.1 Pa, heating temperature of 1023 K and heating time of 120 min. After the conditions were employed to remove lead from the metallic mixture of waste printed circuit boards, the efficiency was 99.97%. The mechanism of the effects was elucidated by mathematical modeling that deals with evaporation, mass transfer and condensation, and can be applied to a wider range of metal removal by vacuum distillation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimizaton of corrosion control for lead in drinking water using computational modeling techniques

EPA Science Inventory

Computational modeling techniques have been used to very good effect in the UK in the optimization of corrosion control for lead in drinking water. A “proof-of-concept” project with three US/CA case studies sought to demonstrate that such techniques could work equally well in the...

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery.

PubMed

Heifetz, Alexander; Southey, Michelle; Morao, Inaki; Townsend-Nicholson, Andrea; Bodkin, Mike J

2018-01-01

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

An Efficient, Optimized Synthesis of Fentanyl and Related Analogs

DOE PAGES

Valdez, Carlos A.; Leif, Roald N.; Mayer, Brian P.; ...

2014-09-18

The alternate and optimized syntheses of the parent opioid fentanyl and its analogs are described. The routes presented exhibit high-yielding transformations leading to these powerful analgesics after optimization studies were carried out for each synthetic step. The general three-step strategy produced a panel of four fentanyls in excellent yields (73–78%) along with their more commonly encountered hydrochloride and citric acid salts. In conclusion, the following strategy offers the opportunity for the gram-scale, efficient production of this interesting class of opioid alkaloids.

An Efficient, Optimized Synthesis of Fentanyl and Related Analogs

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

Valdez, Carlos A.; Leif, Roald N.; Mayer, Brian P.

The alternate and optimized syntheses of the parent opioid fentanyl and its analogs are described. The routes presented exhibit high-yielding transformations leading to these powerful analgesics after optimization studies were carried out for each synthetic step. The general three-step strategy produced a panel of four fentanyls in excellent yields (73–78%) along with their more commonly encountered hydrochloride and citric acid salts. In conclusion, the following strategy offers the opportunity for the gram-scale, efficient production of this interesting class of opioid alkaloids.

Hypothesizing That Neuropharmacological and Neuroimaging Studies of Glutaminergic-Dopaminergic Optimization Complex (KB220Z) Are Associated With "Dopamine Homeostasis" in Reward Deficiency Syndrome (RDS).

PubMed

Blum, Kenneth; Febo, Marcelo; Fried, Lyle; Li, Mona; Dushaj, Kristina; Braverman, Eric R; McLaughlin, Thomas; Steinberg, Bruce; Badgaiyan, Rajendra D

2017-03-21

There is need for better treatments of addictive behaviors, both substance and non-substance related, termed Reward Deficiency Syndrome (RDS). While the FDA has approved pharmaceuticals under the umbrella term Medication Assisted Treatment (MAT), these drugs are not optimal. It is our contention that these drugs work well in the short-term by blocking dopamine function leading to psychological extinction. However, use of buprenorphine/Naloxone over a long period of time results in unwanted addiction liability, reduced emotional affect, and mood changes including suicidal ideation. We are thus proposing a paradigm shift in addiction treatment, with the long-term goal of achieving "Dopamine Homeostasis." While this may be a laudable goal, it is very difficult to achieve. Nevertheless, this commentary briefly reviews past history of developing and subsequently, utilizing a glutaminergic-dopaminergic optimization complex [Kb220Z] shown to be beneficial in at least 20 human clinical trials and in a number of published and unpublished studies. It is our opinion that, while additional required studies could confirm these findings to date, the cited studies are indicative of achieving enhanced resting state functional connectivity, connectivity volume, and possibly, neuroplasticity. Conclusions/Importance: We are proposing a Reward Deficiency Solution System (RDSS) that includes: Genetic Addiction Risk Score (GARS); Comprehensive Analysis of Reported Drugs (CARD); and a glutaminergic-dopaminergic optimization complex (Kb220Z). Continued investigation of this novel strategy may lead to a better-targeted approach in the long-term, causing dopamine regulation by balancing the glutaminergic-dopaminergic pathways. This may potentially change the landscape of treating all addictions leading us to the promised land.

Hypothesizing That Neuropharmacological and Neuroimaging Studies of Glutaminergic-Dopaminergic Optimization Complex (KB220Z) Are Associated With “Dopamine Homeostasis” in Reward Deficiency Syndrome (RDS)

PubMed Central

Blum, Kenneth; Febo, Marcelo; Fried, Lyle; Li, Mona; Dushaj, Kristina; Braverman, Eric R.; McLaughlin, Thomas; Steinberg, Bruce; Badgaiyan, Rajendra D.

2017-01-01

Background There is need for better treatments of addictive behaviors, both substance and non-substance related, termed “Reward Deficiency Syndrome” (RDS). While the FDA has approved pharmaceuticals under the umbrella term Medication Assisted Treatment (MAT), these drugs are not optimal. Objectives It is our contention that these drugs work well in the short-term by blocking dopamine function leading to psychological extinction. However, use of buprenorphine/Naloxone over a long period of time results in unwanted addiction liability, reduced emotional affect, and mood changes including suicidal ideation. Methods We are thus proposing a paradigm shift in addiction treatment, with the long-term goal of achieving “Dopamine Homeostasis.” While this may be a laudable goal, it is very difficult to achieve. Nevertheless, this commentary briefly reviews past history of developing and subsequently, utilizing a glutaminergic-dopaminergic optimization complex [Kb220Z] shown to be beneficial in at least 20 human clinical trials and in a number of published and unpublished studies. Results It is our opinion that, while additional required studies could confirm these findings to date, the cited studies are indicative of achieving enhanced resting state functional connectivity, connectivity volume, and possibly, neuroplasticity. Conclusions/Importance We are proposing a Reward Deficiency Solution System (RDSS) that includes: Genetic Addiction Risk Score (GARS); Comprehensive Analysis of Reported Drugs (CARD); and a glutaminergic-dopaminergic optimization complex (Kb220Z). Continued investigation of this novel strategy may lead to a better-targeted approach in the long-term, causing dopamine regulation by balancing the glutaminergic-dopaminergic pathways. This may potentially change the landscape of treating all addictions leading us to the promised land. PMID:28033474

Synergism of virtual screening and medicinal chemistry: identification and optimization of allosteric antagonists of metabotropic glutamate receptor 1.

PubMed

Noeske, Tobias; Trifanova, Dina; Kauss, Valerjans; Renner, Steffen; Parsons, Christopher G; Schneider, Gisbert; Weil, Tanja

2009-08-01

We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by virtual screening and subsequent hit optimization. For ligand-based virtual screening, molecules were represented by a topological pharmacophore descriptor (CATS-2D) and clustered by a self-organizing map (SOM). The most promising compounds were tested in mGluR1 functional and binding assays. We identified a potent chemotype exhibiting selective antagonistic activity at mGluR1 (functional IC(50)=0.74+/-0.29 microM). Hit optimization yielded lead structure 16 with an affinity of K(i)=0.024+/-0.001 microM and greater than 1000-fold selectivity for mGluR1 versus mGluR5. Homology-based receptor modelling suggests a binding site compatible with previously reported mutation studies. Our study demonstrates the usefulness of ligand-based virtual screening for scaffold-hopping and rapid lead structure identification in early drug discovery projects.

Separation of Lead from Crude Antimony by Pyro-Refining Process with NaPO3 Addition

NASA Astrophysics Data System (ADS)

Ye, Longgang; Hu, Yuejie; Xia, Zhimei; Chen, Yongming

2016-06-01

The main purpose of this study was to separate lead from crude antimony through an oxidation pyro-refining process and by using sodium metaphosphate as a lead elimination reagent. The process parameters that will affect the refining results were optimized experimentally under controlled conditions, such as the sodium metaphosphate charging dosage, the refining temperature and duration, and the air flow rate, to determine their effect on the lead content in refined antimony and the lead removal rate. A minimum lead content of 0.0522 wt.% and a 98.6% lead removal rate were obtained under the following optimal conditions: W_{{{NaPO}_{{3}} }} = 15% W Sb (where W represents weight), a refining temperature of 800°C, a refining time of 30 min, and an air flow rate of 3 L/min. X-ray diffractometry and scanning electron microscopy showed that high-purity antimony was obtained. The smelting operation is free from smoke or ammonia pollution when using monobasic sodium phosphate or ammonium dihydrogen phosphate as the lead elimination reagent. However, this refining process can also remove a certain amount of sulfur, cobalt, and silicon simultaneously, and smelting results also suggest that sodium metaphosphate can be used as a potential lead elimination reagent for bismuth and copper refining.

[Optimization of the parameters of microcirculatory structural adaptation model based on improved quantum-behaved particle swarm optimization algorithm].

PubMed

Pan, Qing; Yao, Jialiang; Wang, Ruofan; Cao, Ping; Ning, Gangmin; Fang, Luping

2017-08-01

The vessels in the microcirculation keep adjusting their structure to meet the functional requirements of the different tissues. A previously developed theoretical model can reproduce the process of vascular structural adaptation to help the study of the microcirculatory physiology. However, until now, such model lacks the appropriate methods for its parameter settings with subsequent limitation of further applications. This study proposed an improved quantum-behaved particle swarm optimization (QPSO) algorithm for setting the parameter values in this model. The optimization was performed on a real mesenteric microvascular network of rat. The results showed that the improved QPSO was superior to the standard particle swarm optimization, the standard QPSO and the previously reported Downhill algorithm. We conclude that the improved QPSO leads to a better agreement between mathematical simulation and animal experiment, rendering the model more reliable in future physiological studies.

Late-stage optimization of a tercyclic class of S1P3-sparing, S1P1 receptor agonists.

PubMed

Horan, Joshua C; Kuzmich, Daniel; Liu, Pingrong; DiSalvo, Darren; Lord, John; Mao, Can; Hopkins, Tamara D; Yu, Hui; Harcken, Christian; Betageri, Raj; Hill-Drzewi, Melissa; Patenaude, Lori; Patel, Monica; Fletcher, Kimberly; Terenzzio, Donna; Linehan, Brian; Xia, Heather; Patel, Mita; Studwell, Debbie; Miller, Craig; Hickey, Eugene; Levin, Jeremy I; Smith, Dustin; Kemper, Raymond A; Modis, Louise K; Bannen, Lynne C; Chan, Diva S; Mac, Morrison B; Ng, Stephanie; Wang, Yong; Xu, Wei; Lemieux, René M

2016-01-15

Poor solubility and cationic amphiphilic drug-likeness were liabilities identified for a lead series of S1P3-sparing, S1P1 agonists originally developed from a high-throughput screening campaign. This work describes the subsequent optimization of these leads by balancing potency, selectivity, solubility and overall molecular charge. Focused SAR studies revealed favorable structural modifications that, when combined, produced compounds with overall balanced profiles. The low brain exposure observed in rat suggests that these compounds would be best suited for the potential treatment of peripheral autoimmune disorders. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design, synthesis and molecular simulation studies of dihydrostilbene derivatives as potent tyrosinase inhibitors.

PubMed

Vontzalidou, Argyro; Zoidis, Grigoris; Chaita, Eliza; Makropoulou, Maria; Aligiannis, Nektarios; Lambrinidis, George; Mikros, Emmanuel; Skaltsounis, Alexios-Leandros

2012-09-01

The synthesis, molecular modeling and biological evaluation of substituted deoxybenzoins and optimized dihydrostilbenes are reported. Preliminary structure-activity relationship data were elucidated and lead compounds suitable for further optimization were discovered. Dihydrostilbene 7 is a particularly potent inhibitor (IC(50)=8.44 μM, more potent than kojic acid). Copyright © 2012 Elsevier Ltd. All rights reserved.

Free terminal time optimal control problem of an HIV model based on a conjugate gradient method.

PubMed

Jang, Taesoo; Kwon, Hee-Dae; Lee, Jeehyun

2011-10-01

The minimum duration of treatment periods and the optimal multidrug therapy for human immunodeficiency virus (HIV) type 1 infection are considered. We formulate an optimal tracking problem, attempting to drive the states of the model to a "healthy" steady state in which the viral load is low and the immune response is strong. We study an optimal time frame as well as HIV therapeutic strategies by analyzing the free terminal time optimal tracking control problem. The minimum duration of treatment periods and the optimal multidrug therapy are found by solving the corresponding optimality systems with the additional transversality condition for the terminal time. We demonstrate by numerical simulations that the optimal dynamic multidrug therapy can lead to the long-term control of HIV by the strong immune response after discontinuation of therapy.

Genetic algorithm optimization of transcutaneous energy transmission systems for implantable ventricular assist devices.

PubMed

Byron, Kelly; Bluvshtein, Vlad; Lucke, Lori

2013-01-01

Transcutaneous energy transmission systems (TETS) wirelessly transmit power through the skin. TETS is particularly desirable for ventricular assist devices (VAD), which currently require cables through the skin to power the implanted pump. Optimizing the inductive link of the TET system is a multi-parameter problem. Most current techniques to optimize the design simplify the problem by combining parameters leading to sub-optimal solutions. In this paper we present an optimization method using a genetic algorithm to handle a larger set of parameters, which leads to a more optimal design. Using this approach, we were able to increase efficiency while also reducing power variability in a prototype, compared to a traditional manual design method.

Dynamic optimization of metabolic networks coupled with gene expression.

PubMed

Waldherr, Steffen; Oyarzún, Diego A; Bockmayr, Alexander

2015-01-21

The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problems leads to a linear program that can be efficiently solved. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle. Copyright © 2014 Elsevier Ltd. All rights reserved.

Performance assessment of deterministic and probabilistic weather predictions for the short-term optimization of a tropical hydropower reservoir

NASA Astrophysics Data System (ADS)

Mainardi Fan, Fernando; Schwanenberg, Dirk; Alvarado, Rodolfo; Assis dos Reis, Alberto; Naumann, Steffi; Collischonn, Walter

2016-04-01

Hydropower is the most important electricity source in Brazil. During recent years, it accounted for 60% to 70% of the total electric power supply. Marginal costs of hydropower are lower than for thermal power plants, therefore, there is a strong economic motivation to maximize its share. On the other hand, hydropower depends on the availability of water, which has a natural variability. Its extremes lead to the risks of power production deficits during droughts and safety issues in the reservoir and downstream river reaches during flood events. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for the short-term reservoir management, the use of probabilistic ensemble forecasts and stochastic optimization techniques receives growing attention and a number of researches have shown its benefit. The present work shows one of the first hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project (HPP) Três Marias, located in southeast Brazil. The HPP reservoir is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control at Pirapora City located 120 km downstream of the dam. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts with 50 ensemble members of the ECMWF are used as forcing of the MGB-IPH hydrological model to generate streamflow forecasts over a period of 2 years. The online optimization depends on a deterministic and multi-stage stochastic version of a model predictive control scheme. Results for the perfect forecasts show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of actual forecasts with shorter lead times of up to 15 days shows the practical benefit of actual operational data. It appears that the use of stochastic optimization combined with ensemble forecasts leads to a significant higher level of flood protection without compromising the HPP's energy production.

Optimal pitching axis location of flapping wings for efficient hovering flight.

PubMed

Wang, Q; Goosen, J F L; van Keulen, F

2017-09-01

Flapping wings can pitch passively about their pitching axes due to their flexibility, inertia, and aerodynamic loads. A shift in the pitching axis location can dynamically alter the aerodynamic loads, which in turn changes the passive pitching motion and the flight efficiency. Therefore, it is of great interest to investigate the optimal pitching axis for flapping wings to maximize the power efficiency during hovering flight. In this study, flapping wings are modeled as rigid plates with non-uniform mass distribution. The wing flexibility is represented by a linearly torsional spring at the wing root. A predictive quasi-steady aerodynamic model is used to evaluate the lift generated by such wings. Two extreme power consumption scenarios are modeled for hovering flight, i.e. the power consumed by a drive system with and without the capacity of kinetic energy recovery. For wings with different shapes, the optimal pitching axis location is found such that the cycle-averaged power consumption during hovering flight is minimized. Optimization results show that the optimal pitching axis is located between the leading edge and the mid-chord line, which shows close resemblance to insect wings. An optimal pitching axis can save up to 33% of power during hovering flight when compared to traditional wings used by most of flapping wing micro air vehicles (FWMAVs). Traditional wings typically use the straight leading edge as the pitching axis. With the optimized pitching axis, flapping wings show higher pitching amplitudes and start the pitching reversals in advance of the sweeping reversals. These phenomena lead to higher lift-to-drag ratios and, thus, explain the lower power consumption. In addition, the optimized pitching axis provides the drive system higher potential to recycle energy during the deceleration phases as compared to their counterparts. This observation underlines the particular importance of the wing pitching axis location for energy-efficient FWMAVs when using kinetic energy recovery drive systems.

Lead optimization toward proof-of-concept tools for Huntington's disease within a 4-(1H-pyrazol-4-yl)pyrimidine class of pan-JNK inhibitors.

PubMed

Wityak, John; McGee, Kevin F; Conlon, Michael P; Song, Ren Hua; Duffy, Bryan C; Clayton, Brent; Lynch, Michael; Wang, Gwen; Freeman, Emily; Haber, James; Kitchen, Douglas B; Manning, David D; Ismail, Jiffry; Khmelnitsky, Yuri; Michels, Peter; Webster, Jeff; Irigoyen, Macarena; Luche, Michele; Hultman, Monica; Bai, Mei; Kuok, IokTeng D; Newell, Ryan; Lamers, Marieke; Leonard, Philip; Yates, Dawn; Matthews, Kim; Ongeri, Lynette; Clifton, Steve; Mead, Tania; Deupree, Susan; Wheelan, Pat; Lyons, Kathy; Wilson, Claire; Kiselyov, Alex; Toledo-Sherman, Leticia; Beconi, Maria; Muñoz-Sanjuan, Ignacio; Bard, Jonathan; Dominguez, Celia

2015-04-09

Through medicinal chemistry lead optimization studies focused on calculated properties and guided by X-ray crystallography and computational modeling, potent pan-JNK inhibitors were identified that showed submicromolar activity in a cellular assay. Using in vitro ADME profiling data, 9t was identified as possessing favorable permeability and a low potential for efflux, but it was rapidly cleared in liver microsomal incubations. In a mouse pharmacokinetics study, compound 9t was brain-penetrant after oral dosing, but exposure was limited by high plasma clearance. Brain exposure at a level expected to support modulation of a pharmacodynamic marker in mouse was achieved when the compound was coadministered with the pan-cytochrome P450 inhibitor 1-aminobenzotriazole.

Topology optimization of two-dimensional elastic wave barriers

NASA Astrophysics Data System (ADS)

Van hoorickx, C.; Sigmund, O.; Schevenels, M.; Lazarov, B. S.; Lombaert, G.

2016-08-01

Topology optimization is a method that optimally distributes material in a given design domain. In this paper, topology optimization is used to design two-dimensional wave barriers embedded in an elastic halfspace. First, harmonic vibration sources are considered, and stiffened material is inserted into a design domain situated between the source and the receiver to minimize wave transmission. At low frequencies, the stiffened material reflects and guides waves away from the surface. At high frequencies, destructive interference is obtained that leads to high values of the insertion loss. To handle harmonic sources at a frequency in a given range, a uniform reduction of the response over a frequency range is pursued. The minimal insertion loss over the frequency range of interest is maximized. The resulting design contains features at depth leading to a reduction of the insertion loss at the lowest frequencies and features close to the surface leading to a reduction at the highest frequencies. For broadband sources, the average insertion loss in a frequency range is optimized. This leads to designs that especially reduce the response at high frequencies. The designs optimized for the frequency averaged insertion loss are found to be sensitive to geometric imperfections. In order to obtain a robust design, a worst case approach is followed.

Energy-saving management modelling and optimization for lead-acid battery formation process

NASA Astrophysics Data System (ADS)

Wang, T.; Chen, Z.; Xu, J. Y.; Wang, F. Y.; Liu, H. M.

2017-11-01

In this context, a typical lead-acid battery producing process is introduced. Based on the formation process, an efficiency management method is proposed. An optimization model with the objective to minimize the formation electricity cost in a single period is established. This optimization model considers several related constraints, together with two influencing factors including the transformation efficiency of IGBT charge-and-discharge machine and the time-of-use price. An example simulation is shown using PSO algorithm to solve this mathematic model, and the proposed optimization strategy is proved to be effective and learnable for energy-saving and efficiency optimization in battery producing industries.

Effect of poling process on piezoelectric properties of BCZT - 0.08 wt.% CeO{sub 2} lead-free ceramics

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

Chandrakala, E.; Praveen, J. Paul; Das, Dibakar, E-mail: ddse@uohyd.ernet.in

2016-05-06

The properties of lead free piezoelectric materials can be tuned by suitable doping in the A and B sites of the perovskite structure. In the present study, cerium has been identified as a dopant to investigate the piezoelectric properties of lead-free BCZT system. BCZT – 0.08 wt.%CeO{sub 2} lead-free ceramics have been synthesized using sol-gel technique and the effects of CeO{sub 2} dopant on their phase structure and piezoelectric properties were investigated systematically. Poling conditions, such as temperature, electric field, and poling time have been optimized to get enhanced piezoelectric response. The optimized poling conditions (50°C, 3Ec and 30min) resultedmore » in high piezoelectric charge coefficient d{sub 33} ~ 670pC/N, high electromechanical coupling coefficient k{sub p} ~ 60% and piezoelectric voltage coefficient g{sub 33} ~ 14 mV.m/N for BCZT – 0.08wt.% CeO{sub 2} ceramics.« less

Are We There Yet? Applying Thermodynamic and Kinetic Profiling on Embryonic Ectoderm Development (EED) Hit-to-Lead Program.

PubMed

Wang, Ying; Edalji, Rohinton P; Panchal, Sanjay C; Sun, Chaohong; Djuric, Stevan W; Vasudevan, Anil

2017-10-26

It is advocated that kinetic and thermodynamic profiling of bioactive compounds should be incorporated and utilized as complementary tools for hit and lead optimizations in drug discovery. To assess their applications in the EED hit-to-lead optimization process, large amount of thermodynamic and kinetic data were collected and analyzed via isothermal titration calorimetry (ITC) and surface plasmon resonance (SPR), respectively. Slower dissociation rates (k off ) of the lead compounds were observed as the program progressed. Analysis of the kinetic data indicated that compound cellular activity correlated with both K i and k off . Our analysis revealed that ITC data should be interpreted in the context of chiral purity of the compounds. The thermodynamic signatures of the EED aminopyrrolidine compounds were found to be mainly enthalpy driven with improved enthalpic contributions as the program progressed. Our study also demonstrated that significant challenges still exist in utilizing kinetic and thermodynamic parameters for hit selection.

An exercise in nostalgia: Nostalgia promotes health optimism and physical activity.

PubMed

Kersten, Mike; Cox, Cathy R; Van Enkevort, Erin A

2016-10-01

Previous research has shown that nostalgia, a sentimental longing for the past, leads to greater feelings of optimism, with other work demonstrating that optimistic thinking (general & health-orientated) is associated with better physical and psychological health. Integrating these two lines of research, the current studies examined whether nostalgia-induced health optimism promotes attitudes and behaviours associated with better physical well-being. Participants, in three experiments, were randomly assigned to write about either a nostalgic or ordinary event. Following this, everyone completed a measure of health optimism (Studies 1-3), measures of health attitudes (Study 2) and had their physical activity monitored over the course of 2 weeks (Study 3). The results revealed that, in comparison to control conditions, nostalgic reverie led to greater health optimism (Studies 1-3). Further, heightened health optimism following nostalgic reflection led to more positive health attitudes (Study 2), and increased physical activity over a two-week period (i.e. Fitbit activity trackers; Study 3). These findings highlight the importance of nostalgia on health attitudes and behaviours. Specifically, this work suggests that nostalgia can be used as a mechanism to increase the importance, perceived efficacy and behaviour associated with better physical health.

NARMAX model identification of a palm oil biodiesel engine using multi-objective optimization differential evolution

NASA Astrophysics Data System (ADS)

Mansor, Zakwan; Zakaria, Mohd Zakimi; Nor, Azuwir Mohd; Saad, Mohd Sazli; Ahmad, Robiah; Jamaluddin, Hishamuddin

2017-09-01

This paper presents the black-box modelling of palm oil biodiesel engine (POB) using multi-objective optimization differential evolution (MOODE) algorithm. Two objective functions are considered in the algorithm for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. The mathematical model used in this study to represent the POB system is nonlinear auto-regressive moving average with exogenous input (NARMAX) model. Finally, model validity tests are applied in order to validate the possible models that was obtained from MOODE algorithm and lead to select an optimal model.

Chemistry challenges in lead optimization: silicon isosteres in drug discovery.

PubMed

Showell, Graham A; Mills, John S

2003-06-15

During the lead optimization phase of drug discovery projects, the factors contributing to subsequent failure might include poor portfolio decision-making and a sub-optimal intellectual property (IP) position. The pharmaceutical industry has an ongoing need for new, safe medicines with a genuine biomedical benefit, a clean IP position and commercial viability. Inherent drug-like properties and chemical tractability are also essential for the smooth development of such agents. The introduction of bioisosteres, to improve the properties of a molecule and obtain new classes of compounds without prior art in the patent literature, is a key strategy used by medicinal chemists during the lead optimization process. Sila-substitution (C/Si exchange) of existing drugs is an approach to search for new drug-like candidates that have beneficial biological properties and a clear IP position. Some of the fundamental differences between carbon and silicon can lead to marked alterations in the physicochemical and biological properties of the silicon-containing analogues and the resulting benefits can be exploited in the drug design process.

Refined docking as a valuable tool for lead optimization: application to histamine H3 receptor antagonists.

PubMed

Levoin, Nicolas; Calmels, Thierry; Poupardin-Olivier, Olivia; Labeeuw, Olivier; Danvy, Denis; Robert, Philippe; Berrebi-Bertrand, Isabelle; Ganellin, C Robin; Schunack, Walter; Stark, Holger; Capet, Marc

2008-10-01

Drug-discovery projects frequently employ structure-based information through protein modeling and ligand docking, and there is a plethora of reports relating successful use of them in virtual screening. Hit/lead optimization, which represents the next step and the longest for the medicinal chemist, is very rarely considered. This is not surprising because lead optimization is a much more complex task. Here, a homology model of the histamine H(3) receptor was built and tested for its ability to discriminate ligands above a defined threshold of affinity. In addition, drug safety is also evaluated during lead optimization, and "antitargets" are studied. So, we have used the same benchmarking procedure with the HERG channel and CYP2D6 enzyme, for which a minimal affinity is strongly desired. For targets and antitargets, we report here an accuracy as high as at least 70%, for ligands being classified above or below the chosen threshold. Such a good result is beyond what could have been predicted, especially, since our test conditions were particularly stringent. First, we measured the accuracy by means of AUC of ROC plots, i. e. considering both false positive and false negatives. Second, we used as datasets extensive chemical libraries (nearly a thousand ligands for H(3)). All molecules considered were true H(3) receptor ligands with moderate to high affinity (from microM to nM range). Third, the database is issued from concrete SAR (Bioprojet H(3) BF2.649 library) and is not simply constituted by few active ligands buried in a chemical catalogue.

Hit-to-lead optimization of pyrrolo[1,2-a]quinoxalines as novel cannabinoid type 1 receptor antagonists.

PubMed

Szabó, György; Kiss, Róbert; Páyer-Lengyel, Dóra; Vukics, Krisztina; Szikra, Judit; Baki, Andrea; Molnár, László; Fischer, János; Keseru, György M

2009-07-01

Hit-to-lead optimization of a novel series of N-alkyl-N-[2-oxo-2-(4-aryl-4H-pyrrolo[1,2-a]quinoxaline-5-yl)-ethyl]-carboxylic acid amides, derived from a high throughput screening (HTS) hit, are described. Subsequent optimization led to identification of in vitro potent cannabinoid 1 receptor (CB1R) antagonists representing a new class of compounds in this area.

Discovery of 2-methylpyridine-based biaryl amides as γ-secretase modulators for the treatment of Alzheimer's disease.

PubMed

Chen, Jian Jeffrey; Qian, Wenyuan; Biswas, Kaustav; Yuan, Chester; Amegadzie, Albert; Liu, Qingyian; Nixey, Thomas; Zhu, Joe; Ncube, Mqhele; Rzasa, Robert M; Chavez, Frank; Chen, Ning; DeMorin, Frenel; Rumfelt, Shannon; Tegley, Christopher M; Allen, Jennifer R; Hitchcock, Stephen; Hungate, Randy; Bartberger, Michael D; Zalameda, Leeanne; Liu, Yichin; McCarter, John D; Zhang, Jianhua; Zhu, Li; Babu-Khan, Safura; Luo, Yi; Bradley, Jodi; Wen, Paul H; Reid, Darren L; Koegler, Frank; Dean, Charles; Hickman, Dean; Correll, Tiffany L; Williamson, Toni; Wood, Stephen

2013-12-01

γ-Secretase modulators (GSMs) are potentially disease-modifying treatments for Alzheimer's disease. They selectively lower pathogenic Aβ42 levels by shifting the enzyme cleavage sites without inhibiting γ-secretase activity, possibly avoiding known adverse effects observed with complete inhibition of the enzyme complex. A cell-based HTS effort identified the sulfonamide 1 as a GSM lead. Lead optimization studies identified compound 25 with improved cell potency, PKDM properties, and it lowered Aβ42 levels in the cerebrospinal fluid (CSF) of Sprague-Dawley rats following oral administration. Further optimization of 25 to improve cellular potency is described. Copyright © 2013 Elsevier Ltd. All rights reserved.

Case Example of Dose Optimization Using Data From Bortezomib Dose-Finding Clinical Trials

PubMed Central

Backenroth, Daniel; Cheung, Ying Kuen Ken; Hershman, Dawn L.; Vulih, Diana; Anderson, Barry; Ivy, Percy; Minasian, Lori

2016-01-01

Purpose The current dose-finding methodology for estimating the maximum tolerated dose of investigational anticancer agents is based on the cytotoxic chemotherapy paradigm. Molecularly targeted agents (MTAs) have different toxicity profiles, which may lead to more long-lasting mild or moderate toxicities as well as to late-onset and cumulative toxicities. Several approved MTAs have been poorly tolerated during long-term administration, leading to postmarketing dose optimization studies to re-evaluate the optimal treatment dose. Using data from completed bortezomib dose-finding trials, we explore its toxicity profile, optimize its dose, and examine the appropriateness of current designs for identifying an optimal dose. Patients and Methods We classified the toxicities captured from 481 patients in 14 bortezomib dose-finding studies conducted through the National Cancer Institute Cancer Therapy Evaluation Program, computed the incidence of late-onset toxicities, and compared the incidence of dose-limiting toxicities (DLTs) among groups of patients receiving different doses of bortezomib. Results A total of 13,008 toxicities were captured: 46% of patients’ first DLTs and 88% of dose reductions or discontinuations of treatment because of toxicity were observed after the first cycle. Moreover, for the approved dose of 1.3 mg/m2, the estimated cumulative incidence of DLT was > 50%, and the estimated cumulative incidence of dose reduction or treatment discontinuation because of toxicity was nearly 40%. Conclusions When considering the entire course of treatment, the approved bortezomib dose exceeds the conventional ceiling DLT rate of 20% to 33%. Retrospective analysis of trial data provides an opportunity for dose optimization of MTAs. Future dose-finding studies of MTAs should take into account late-onset toxicities to ensure that a tolerable dose is identified for future efficacy and comparative trials. PMID:26926682

Case Example of Dose Optimization Using Data From Bortezomib Dose-Finding Clinical Trials.

PubMed

Lee, Shing M; Backenroth, Daniel; Cheung, Ying Kuen Ken; Hershman, Dawn L; Vulih, Diana; Anderson, Barry; Ivy, Percy; Minasian, Lori

2016-04-20

The current dose-finding methodology for estimating the maximum tolerated dose of investigational anticancer agents is based on the cytotoxic chemotherapy paradigm. Molecularly targeted agents (MTAs) have different toxicity profiles, which may lead to more long-lasting mild or moderate toxicities as well as to late-onset and cumulative toxicities. Several approved MTAs have been poorly tolerated during long-term administration, leading to postmarketing dose optimization studies to re-evaluate the optimal treatment dose. Using data from completed bortezomib dose-finding trials, we explore its toxicity profile, optimize its dose, and examine the appropriateness of current designs for identifying an optimal dose. We classified the toxicities captured from 481 patients in 14 bortezomib dose-finding studies conducted through the National Cancer Institute Cancer Therapy Evaluation Program, computed the incidence of late-onset toxicities, and compared the incidence of dose-limiting toxicities (DLTs) among groups of patients receiving different doses of bortezomib. A total of 13,008 toxicities were captured: 46% of patients' first DLTs and 88% of dose reductions or discontinuations of treatment because of toxicity were observed after the first cycle. Moreover, for the approved dose of 1.3 mg/m(2), the estimated cumulative incidence of DLT was > 50%, and the estimated cumulative incidence of dose reduction or treatment discontinuation because of toxicity was nearly 40%. When considering the entire course of treatment, the approved bortezomib dose exceeds the conventional ceiling DLT rate of 20% to 33%. Retrospective analysis of trial data provides an opportunity for dose optimization of MTAs. Future dose-finding studies of MTAs should take into account late-onset toxicities to ensure that a tolerable dose is identified for future efficacy and comparative trials. © 2016 by American Society of Clinical Oncology.

Optimal design study of high efficiency indium phosphide space solar cells

NASA Technical Reports Server (NTRS)

Jain, Raj K.; Flood, Dennis J.

1990-01-01

Recently indium phosphide solar cells have achieved beginning of life AMO efficiencies in excess of 19 pct. at 25 C. The high efficiency prospects along with superb radiation tolerance make indium phosphide a leading material for space power requirements. To achieve cost effectiveness, practical cell efficiencies have to be raised to near theoretical limits and thin film indium phosphide cells need to be developed. The optimal design study is described of high efficiency indium phosphide solar cells for space power applications using the PC-1D computer program. It is shown that cells with efficiencies over 22 pct. AMO at 25 C could be fabricated by achieving proper material and process parameters. It is observed that further improvements in cell material and process parameters could lead to experimental cell efficiencies near theoretical limits. The effect of various emitter and base parameters on cell performance was studied.

Effect of aeration rate, moisture content and composting period on availability of copper and lead during pig manure composting.

PubMed

Shen, Yujun; Zhao, Lixin; Meng, Haibo; Hou, Yueqing; Zhou, Haibin; Wang, Fei; Cheng, Hongsheng; Liu, Hongbin

2016-06-01

Pollution by heavy metals, such as copper and lead, has become a limiting factor for the land application of faecal manures, such as pig manure. This study was conducted to investigate the influence of composting process parameters, including aeration rate, moisture content and composting period, on the distribution of heavy metal species during composting, and to select an optimal parameter for copper and lead inactivation. Results showed that the distribution ratios of exchangeable fractions of copper and lead had a bigger decrease under conditions of aeration rate, 0.1 m(3) min(-1) m(-3), an initial moisture content of 65% and composting period of 50 days. Suboptimal composting process conditions could lead to increased availability of heavy metals. Statistical analysis indicated that the aeration rate was the main factor affecting copper and lead inactivation, while the effects of moisture content and composting period were not significant. The rates of reduction of copper-exchangeable fractions and lead-exchangeable fractions were positively correlated with increased pH. The optimal parameters for reducing heavy metal bioavailability during pig manure composting were aeration rate, 0.1 m(3) min(-1) m(-3), initial moisture content, 65%, and composting period, 20 days. © The Author(s) 2016.

Optimal Growth in Hypersonic Boundary Layers

NASA Technical Reports Server (NTRS)

Paredes, Pedro; Choudhari, Meelan M.; Li, Fei; Chang, Chau-Lyan

2016-01-01

The linear form of the parabolized linear stability equations is used in a variational approach to extend the previous body of results for the optimal, nonmodal disturbance growth in boundary-layer flows. This paper investigates the optimal growth characteristics in the hypersonic Mach number regime without any high-enthalpy effects. The influence of wall cooling is studied, with particular emphasis on the role of the initial disturbance location and the value of the spanwise wave number that leads to the maximum energy growth up to a specified location. Unlike previous predictions that used a basic state obtained from a self-similar solution to the boundary-layer equations, mean flow solutions based on the full Navier-Stokes equations are used in select cases to help account for the viscous- inviscid interaction near the leading edge of the plate and for the weak shock wave emanating from that region. Using the full Navier-Stokes mean flow is shown to result in further reduction with Mach number in the magnitude of optimal growth relative to the predictions based on the self-similar approximation to the base flow.

Pavement maintenance optimization model using Markov Decision Processes

NASA Astrophysics Data System (ADS)

Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

2017-09-01

This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

Optimization of Bioethanol Production Using Whole Plant of Water Hyacinth as Substrate in Simultaneous Saccharification and Fermentation Process

PubMed Central

Zhang, Qiuzhuo; Weng, Chen; Huang, Huiqin; Achal, Varenyam; Wang, Duanchao

2016-01-01

Water hyacinth was used as substrate for bioethanol production in the present study. Combination of acid pretreatment and enzymatic hydrolysis was the most effective process for sugar production that resulted in the production of 402.93 mg reducing sugar at optimal condition. A regression model was built to optimize the fermentation factors according to response surface method in saccharification and fermentation (SSF) process. The optimized condition for ethanol production by SSF process was fermented at 38.87°C in 81.87 h when inoculated with 6.11 ml yeast, where 1.291 g/L bioethanol was produced. Meanwhile, 1.289 g/L ethanol was produced during experimentation, which showed reliability of presented regression model in this research. The optimization method discussed in the present study leading to relatively high bioethanol production could provide a promising way for Alien Invasive Species with high cellulose content. PMID:26779125

A single-vendor and a single-buyer integrated inventory model with ordering cost reduction dependent on lead time

NASA Astrophysics Data System (ADS)

Vijayashree, M.; Uthayakumar, R.

2017-09-01

Lead time is one of the major limits that affect planning at every stage of the supply chain system. In this paper, we study a continuous review inventory model. This paper investigates the ordering cost reductions are dependent on lead time. This study addressed two-echelon supply chain problem consisting of a single vendor and a single buyer. The main contribution of this study is that the integrated total cost of the single vendor and the single buyer integrated system is analyzed by adopting two different (linear and logarithmic) types ordering cost reductions act dependent on lead time. In both cases, we develop effective solution procedures for finding the optimal solution and then illustrative numerical examples are given to illustrate the results. The solution procedure is to determine the optimal solutions of order quantity, ordering cost, lead time and the number of deliveries from the single vendor and the single buyer in one production run, so that the integrated total cost incurred has the minimum value. Ordering cost reduction is the main aspect of the proposed model. A numerical example is given to validate the model. Numerical example solved by using Matlab software. The mathematical model is solved analytically by minimizing the integrated total cost. Furthermore, the sensitivity analysis is included and the numerical examples are given to illustrate the results. The results obtained in this paper are illustrated with the help of numerical examples. The sensitivity of the proposed model has been checked with respect to the various major parameters of the system. Results reveal that the proposed integrated inventory model is more applicable for the supply chain manufacturing system. For each case, an algorithm procedure of finding the optimal solution is developed. Finally, the graphical representation is presented to illustrate the proposed model and also include the computer flowchart in each model.

The Analytic Methods of Operations Research

DTIC Science & Technology

1977-01-01

stock market behavior (Fama, 1970), but few other applications . A 2*1 - --- 41 12. QUEUEING THEORY The study of congestion in service...Behavior," by T. von Neumann and 0. MHrgenstern, and an esoteric j - 2 paperbrtk by Charnes. Cooper, and Henderson on the optimal mixing of peanuKs and...2nd-order conditions, then i X is also globally optimal . This enables one to use local exploration to lead to the global

Multigrid solvers and multigrid preconditioners for the solution of variational data assimilation problems

NASA Astrophysics Data System (ADS)

Debreu, Laurent; Neveu, Emilie; Simon, Ehouarn; Le Dimet, Francois Xavier; Vidard, Arthur

2014-05-01

In order to lower the computational cost of the variational data assimilation process, we investigate the use of multigrid methods to solve the associated optimal control system. On a linear advection equation, we study the impact of the regularization term on the optimal control and the impact of discretization errors on the efficiency of the coarse grid correction step. We show that even if the optimal control problem leads to the solution of an elliptic system, numerical errors introduced by the discretization can alter the success of the multigrid methods. The view of the multigrid iteration as a preconditioner for a Krylov optimization method leads to a more robust algorithm. A scale dependent weighting of the multigrid preconditioner and the usual background error covariance matrix based preconditioner is proposed and brings significant improvements. [1] Laurent Debreu, Emilie Neveu, Ehouarn Simon, François-Xavier Le Dimet and Arthur Vidard, 2014: Multigrid solvers and multigrid preconditioners for the solution of variational data assimilation problems, submitted to QJRMS, http://hal.inria.fr/hal-00874643 [2] Emilie Neveu, Laurent Debreu and François-Xavier Le Dimet, 2011: Multigrid methods and data assimilation - Convergence study and first experiments on non-linear equations, ARIMA, 14, 63-80, http://intranet.inria.fr/international/arima/014/014005.html

The Role of Echocardiography in the Optimization of Cardiac Resynchronization Therapy: Current Evidence and Future Perspectives.

PubMed

Spartalis, Michael; Tzatzaki, Eleni; Spartalis, Eleftherios; Damaskos, Christos; Athanasiou, Antonios; Livanis, Efthimios; Voudris, Vassilis

2017-01-01

Cardiac resynchronization therapy (CRT) has become a mainstay in the management of heart failure. Up to one-third of patients who received resynchronization devices do not experience the full benefits of CRT. The clinical factors influencing the likelihood to respond to the therapy are wide QRS complex, left bundle branch block, female gender, non-ischaemic cardiomyopathy (highest responders), male gender, ischaemic cardiomyopathy (moderate responders) and narrow QRS complex, non-left bundle branch block (lowest, non-responders). This review provides a conceptual description of the role of echocardiography in the optimization of CRT. A literature survey was performed using PubMed database search to gather information regarding CRT and echocardiography. A total of 70 studies met selection criteria for inclusion in the review. Echocardiography helps in the initial selection of the patients with dyssynchrony, which will benefit the most from optimal biventricular pacing and provides a guide to left ventricular (LV) lead placement during implantation. Different echocardiographic parameters have shown promise and can offer the possibility of patient selection, response prediction, lead placement optimization strategies and optimization of device configurations. LV ejection fraction along with specific electrocardiographic criteria remains the cornerstone of CRT patient selection. Echocardiography is a non-invasive, cost-effective, highly reproducible method with certain limitations and accuracy that is affected by measurement errors. Echocardiography can assist with the identification of the appropriate electromechanical substrate of CRT response and LV lead placement. The targeted approach can improve the haemodynamic response, as also the patient-specific parameters estimation.

The Role of Echocardiography in the Optimization of Cardiac Resynchronization Therapy: Current Evidence and Future Perspectives

PubMed Central

Spartalis, Michael; Tzatzaki, Eleni; Spartalis, Eleftherios; Damaskos, Christos; Athanasiou, Antonios; Livanis, Efthimios; Voudris, Vassilis

2017-01-01

Background: Cardiac resynchronization therapy (CRT) has become a mainstay in the management of heart failure. Up to one-third of patients who received resynchronization devices do not experience the full benefits of CRT. The clinical factors influencing the likelihood to respond to the therapy are wide QRS complex, left bundle branch block, female gender, non-ischaemic cardiomyopathy (highest responders), male gender, ischaemic cardiomyopathy (moderate responders) and narrow QRS complex, non-left bundle branch block (lowest, non-responders). Objective: This review provides a conceptual description of the role of echocardiography in the optimization of CRT. Method: A literature survey was performed using PubMed database search to gather information regarding CRT and echocardiography. Results: A total of 70 studies met selection criteria for inclusion in the review. Echocardiography helps in the initial selection of the patients with dyssynchrony, which will benefit the most from optimal biventricular pacing and provides a guide to left ventricular (LV) lead placement during implantation. Different echocardiographic parameters have shown promise and can offer the possibility of patient selection, response prediction, lead placement optimization strategies and optimization of device configurations. Conclusion: LV ejection fraction along with specific electrocardiographic criteria remains the cornerstone of CRT patient selection. Echocardiography is a non-invasive, cost-effective, highly reproducible method with certain limitations and accuracy that is affected by measurement errors. Echocardiography can assist with the identification of the appropriate electromechanical substrate of CRT response and LV lead placement. The targeted approach can improve the haemodynamic response, as also the patient-specific parameters estimation. PMID:29387277

Comparative study about the tensile strength and yielding mechanism of pacing lead among major manufacturers.

PubMed

Chi-Wo, Chan; Lip-Kiong, Chan; Tongny, Lam; Kin-Keung, Tsang; Kin-Wing, Chan

2018-05-14

With extraction of cardiovascular implantable electronic devices (CIED) increasingly necessitated, various studies have contemplated to investigate clinical predictors for its success and complications. Intrinsic parameters of CIED leads have been studied less extensively and are the foci of this study. Three major pacemaker manufacturers accepted invitation. Leads then underwent tensile test in-vitro with their composite tensile strength (TS) compared. Mechanism of yielding, under tensile stress, was also observed among them. All pacing leads, participated in this study, surpassed requirement of European Standard EN 45502-2-1. Boston Scientific's FINELINE II STENOX 4456/52 cm and Medtronic's CAPSURE SENSE 4074/52 cm showed similar composite TS and both were stronger compared with St. Jude Medical's ISOFLEX OPTIM 1948/52 cm (P < 0.001). Despite a difference in the exact site, the Medtronic 4074 and St. Jude Medical 1948 yielded similarly in that their distal tip electrode remained connected with a flimsy inner coil to proximal portion of the lead after their composite TS was exceeded. Boston Scientific 4456's insulation tubing and coil wire broke almost simultaneously and separated completely from the tip electrode when it yielded. FINELINE II STENOX 4456/52 cm and CAPSURE SENSE 4074/52 cm showed stronger composite tensile strength than ISOFLEX OPTIM 1948/52 cm. FINELINE II STENOX 4456 was found more prone to complete severance. Limitations and precautions to translate these differences directly into real-life scenario are discussed. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

An NMR-Guided Screening Method for Selective Fragment Docking and Synthesis of a Warhead Inhibitor.

PubMed

Khattri, Ram B; Morris, Daniel L; Davis, Caroline M; Bilinovich, Stephanie M; Caras, Andrew J; Panzner, Matthew J; Debord, Michael A; Leeper, Thomas C

2016-07-16

Selective hits for the glutaredoxin ortholog of Brucella melitensis are determined using STD NMR and verified by trNOE and (15)N-HSQC titration. The most promising hit, RK207, was docked into the target molecule using a scoring function to compare simulated poses to experimental data. After elucidating possible poses, the hit was further optimized into the lead compound by extension with an electrophilic acrylamide warhead. We believe that focusing on selectivity in this early stage of drug discovery will limit cross-reactivity that might occur with the human ortholog as the lead compound is optimized. Kinetics studies revealed that lead compound 5 modified with an ester group results in higher reactivity than an acrylamide control; however, after modification this compound shows little selectivity for bacterial protein versus the human ortholog. In contrast, hydrolysis of compound 5 to the acid form results in a decrease in the activity of the compound. Together these results suggest that more optimization is warranted for this simple chemical scaffold, and opens the door for discovery of drugs targeted against glutaredoxin proteins-a heretofore untapped reservoir for antibiotic agents.

Performance characteristics of long-track speed skaters: a literature review.

PubMed

Konings, Marco J; Elferink-Gemser, Marije T; Stoter, Inge K; van der Meer, Dirk; Otten, Egbert; Hettinga, Florentina J

2015-04-01

Speed skating is an intriguing sport to study from different perspectives due to the peculiar way of motion and the multiple determinants for performance. This review aimed to identify what is known on (long-track) speed skating, and which individual characteristics determine speed skating performance. A total of 49 studies were included. Based on a multidimensional performance model, person-related performance characteristics were categorized in anthropometrical, technical, physiological, tactical, and psychological characteristics. Literature was found on anthropometry, technique, physiology, and tactics. However, psychological studies were clearly under-represented. In particular, the role of self-regulation might deserve more attention to further understand mechanisms relevant for optimal performance and for instance pacing. Another remarkable finding was that the technically/biomechanically favourable crouched skating technique (i.e. small knee and trunk angle) leads to a physiological disadvantage: a smaller knee angle may increase the deoxygenation of the working muscles. This is an important underlying aspect for the pacing tactics in speed skating. Elite speed skaters need to find the optimal balance between obtaining a fast start and preventing negative technical adaptations later on in the race by distributing their available energy over the race in an optimal way. More research is required to gain more insight into how this impacts on the processes of fatigue and coordination during speed skating races. This can lead to a better understanding on how elite speed skaters can maintain the optimal technical characteristics throughout the entire race, and how they can adapt their pacing to optimize all identified aspects that determine performance.

Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm.

PubMed

Pickett, Stephen D; Green, Darren V S; Hunt, David L; Pardoe, David A; Hughes, Ian

2011-01-13

Traditional lead optimization projects involve long synthesis and testing cycles, favoring extensive structure-activity relationship (SAR) analysis and molecular design steps, in an attempt to limit the number of cycles that a project must run to optimize a development candidate. Microfluidic-based chemistry and biology platforms, with cycle times of minutes rather than weeks, lend themselves to unattended autonomous operation. The bottleneck in the lead optimization process is therefore shifted from synthesis or test to SAR analysis and design. As such, the way is open to an algorithm-directed process, without the need for detailed user data analysis. Here, we present results of two synthesis and screening experiments, undertaken using traditional methodology, to validate a genetic algorithm optimization process for future application to a microfluidic system. The algorithm has several novel features that are important for the intended application. For example, it is robust to missing data and can suggest compounds for retest to ensure reliability of optimization. The algorithm is first validated on a retrospective analysis of an in-house library embedded in a larger virtual array of presumed inactive compounds. In a second, prospective experiment with MMP-12 as the target protein, 140 compounds are submitted for synthesis over 10 cycles of optimization. Comparison is made to the results from the full combinatorial library that was synthesized manually and tested independently. The results show that compounds selected by the algorithm are heavily biased toward the more active regions of the library, while the algorithm is robust to both missing data (compounds where synthesis failed) and inactive compounds. This publication places the full combinatorial library and biological data into the public domain with the intention of advancing research into algorithm-directed lead optimization methods.

Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm

PubMed Central

2010-01-01

Traditional lead optimization projects involve long synthesis and testing cycles, favoring extensive structure−activity relationship (SAR) analysis and molecular design steps, in an attempt to limit the number of cycles that a project must run to optimize a development candidate. Microfluidic-based chemistry and biology platforms, with cycle times of minutes rather than weeks, lend themselves to unattended autonomous operation. The bottleneck in the lead optimization process is therefore shifted from synthesis or test to SAR analysis and design. As such, the way is open to an algorithm-directed process, without the need for detailed user data analysis. Here, we present results of two synthesis and screening experiments, undertaken using traditional methodology, to validate a genetic algorithm optimization process for future application to a microfluidic system. The algorithm has several novel features that are important for the intended application. For example, it is robust to missing data and can suggest compounds for retest to ensure reliability of optimization. The algorithm is first validated on a retrospective analysis of an in-house library embedded in a larger virtual array of presumed inactive compounds. In a second, prospective experiment with MMP-12 as the target protein, 140 compounds are submitted for synthesis over 10 cycles of optimization. Comparison is made to the results from the full combinatorial library that was synthesized manually and tested independently. The results show that compounds selected by the algorithm are heavily biased toward the more active regions of the library, while the algorithm is robust to both missing data (compounds where synthesis failed) and inactive compounds. This publication places the full combinatorial library and biological data into the public domain with the intention of advancing research into algorithm-directed lead optimization methods. PMID:24900251

Engineering another class of anti-tubercular lead: Hit to lead optimization of an intriguing class of gyrase ATPase inhibitors.

PubMed

Jeankumar, Variam Ullas; Reshma, Rudraraju Srilakshmi; Vats, Rahul; Janupally, Renuka; Saxena, Shalini; Yogeeswari, Perumal; Sriram, Dharmarajan

2016-10-21

A structure based medium throughput virtual screening campaign of BITS-Pilani in house chemical library to identify novel binders of Mycobacterium tuberculosis gyrase ATPase domain led to the discovery of a quinoline scaffold. Further medicinal chemistry explorations on the right hand core of the early hit, engendered a potent lead demonstrating superior efficacy both in the enzyme and whole cell screening assay. The binding affinity shown at the enzyme level was further corroborated by biophysical characterization techniques. Early pharmacokinetic evaluation of the optimized analogue was encouraging and provides interesting potential for further optimization. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Outsourcing lead optimization: the eye of the storm.

PubMed

Clark, David E

2011-02-01

This article is the third in a series examining the evolution of the market for outsourced lead optimization services and covers developments from late 2006 to the present. Following an analysis of the significant events that have impacted the marketplace in recent years, a brief survey of the growing number of companies offering lead optimization services is presented. Subsequently, three notable trends that can be perceived in this highly dynamic field are discussed: the continuing rise of outsourcing companies in Asia and Eastern Europe, the increase in deals with not-for-profit organizations and, finally, the emergence of a variety of business models under which outsourced work is conducted. Copyright © 2010 Elsevier Ltd. All rights reserved.

Shape Optimization for Navier-Stokes Equations with Algebraic Turbulence Model: Existence Analysis

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

Bulicek, Miroslav; Haslinger, Jaroslav; Malek, Josef

2009-10-15

We study a shape optimization problem for the paper machine headbox which distributes a mixture of water and wood fibers in the paper making process. The aim is to find a shape which a priori ensures the given velocity profile on the outlet part. The mathematical formulation leads to an optimal control problem in which the control variable is the shape of the domain representing the header, the state problem is represented by a generalized stationary Navier-Stokes system with nontrivial mixed boundary conditions. In this paper we prove the existence of solutions both to the generalized Navier-Stokes system and tomore » the shape optimization problem.« less

Optimal Design and Operation of Permanent Irrigation Systems

NASA Astrophysics Data System (ADS)

Oron, Gideon; Walker, Wynn R.

1981-01-01

Solid-set pressurized irrigation system design and operation are studied with optimization techniques to determine the minimum cost distribution system. The principle of the analysis is to divide the irrigation system into subunits in such a manner that the trade-offs among energy, piping, and equipment costs are selected at the minimum cost point. The optimization procedure involves a nonlinear, mixed integer approach capable of achieving a variety of optimal solutions leading to significant conclusions with regard to the design and operation of the system. Factors investigated include field geometry, the effect of the pressure head, consumptive use rates, a smaller flow rate in the pipe system, and outlet (sprinkler or emitter) discharge.

Optimization of the precordial leads of the 12-lead electrocardiogram may improve detection of ST-segment elevation myocardial infarction.

PubMed

Scott, Peter J; Navarro, Cesar; Stevenson, Mike; Murphy, John C; Bennett, Johan R; Owens, Colum; Hamilton, Andrew; Manoharan, Ganesh; Adgey, A A Jennifer

2011-01-01

For the assessment of patients with chest pain, the 12-lead electrocardiogram (ECG) is the initial investigation. Major management decisions are based on the ECG findings, both for attempted coronary artery revascularization and risk stratification. The aim of this study was to determine if the current 6 precordial leads (V(1)-V(6)) are optimally located for the detection of ST-segment elevation in ST-segment elevation myocardial infarction (STEMI). We analyzed 528 (38% anterior [200], 44% inferior [233], and 18% lateral [95]) patients with STEMI with both a 12-lead ECG and an 80-lead body surface map (BSM) ECG (Prime ECG, Heartscape Technologies, Bangor, Northern Ireland). Body surface map was recorded within 15 minutes of the 12-lead ECG during the acute event and before revascularization. ST-segment elevation of each lead on the BSM was compared with the corresponding 12-lead precordial leads (V(1)-V(6)) for anterior STEMI. In addition, for lateral STEMI, leads I and aVL of the BSM were also compared; and limb leads II, III, aVF of the BSM were compared with inferior unipolar BSM leads for inferior STEMI. Leads with the greatest mean ST-segment elevation were selected, and significance was determined by analysis of variance of the mean ST segment. For anterior STEMI, leads V(1), V(2), 32, 42, 51, and 57 had the greatest mean ST elevation. These leads are located in the same horizontal plane as that of V(1) and V(2). Lead 32 had a significantly greater mean ST elevation than the corresponding precordial lead V(3) (P = .012); and leads 42, 51, and 57 were also significantly greater than corresponding leads V(4), V(5), V(6), respectively (P < .001). Similar findings were also found for lateral STEMI. For inferior STEMI, the limb leads of the BSM (II, III, and aVF) had the greatest mean ST-segment elevation; and lead III was significantly superior to the inferior unipolar leads (7, 17, 27, 37, 47, 55, and 61) of the BSM (P < .001). Leads placed on a horizontal strip, in line with leads V(1) and V(2), provided the optimal placement for the diagnosis of anterior and lateral STEMI and appear superior to leads V(3), V(4), V(5), and V(6). This is of significant clinical interest, not only for ease and replication of lead placement but also may lead to increased recruitment of patients eligible for revascularization with none or borderline ST-segment elevation on the initial 12-lead ECG. Copyright © 2011 Elsevier Inc. All rights reserved.

Optimization of 2-Anilino 4-Amino Substituted Quinazolines into Potent Antimalarial Agents with Oral in Vivo Activity.

PubMed

Gilson, Paul R; Tan, Cyrus; Jarman, Kate E; Lowes, Kym N; Curtis, Joan M; Nguyen, William; Di Rago, Adrian E; Bullen, Hayley E; Prinz, Boris; Duffy, Sandra; Baell, Jonathan B; Hutton, Craig A; Jousset Subroux, Helene; Crabb, Brendan S; Avery, Vicky M; Cowman, Alan F; Sleebs, Brad E

2017-02-09

Novel antimalarial therapeutics that target multiple stages of the parasite lifecycle are urgently required to tackle the emerging problem of resistance with current drugs. Here, we describe the optimization of the 2-anilino quinazoline class as antimalarial agents. The class, identified from publicly available antimalarial screening data, was optimized to generate lead compounds that possess potent antimalarial activity against P. falciparum parasites comparable to the known antimalarials, chloroquine and mefloquine. During the optimization process, we defined the functionality necessary for activity and improved in vitro metabolism and solubility. The resultant lead compounds possess potent activity against a multidrug resistant strain of P. falciparum and arrest parasites at the ring phase of the asexual stage and also gametocytogensis. Finally, we show that the lead compounds are orally efficacious in a 4 day murine model of malaria disease burden.

Finding the optimal shape of the leading-and-trailing car of a high-speed train using design-by-morphing

NASA Astrophysics Data System (ADS)

Oh, Sahuck; Jiang, Chung-Hsiang; Jiang, Chiyu; Marcus, Philip S.

2017-10-01

We present a new, general design method, called design-by-morphing for an object whose performance is determined by its shape due to hydrodynamic, aerodynamic, structural, or thermal requirements. To illustrate the method, we design a new leading-and-trailing car of a train by morphing existing, baseline leading-and-trailing cars to minimize the drag. In design-by-morphing, the morphing is done by representing the shapes with polygonal meshes and spectrally with a truncated series of spherical harmonics. The optimal design is found by computing the optimal weights of each of the baseline shapes so that the morphed shape has minimum drag. As a result of optimization, we found that with only two baseline trains that mimic current high-speed trains with low drag that the drag of the optimal train is reduced by 8.04% with respect to the baseline train with the smaller drag. When we repeat the optimization by adding a third baseline train that under-performs compared to the other baseline train, the drag of the new optimal train is reduced by 13.46% . This finding shows that bad examples of design are as useful as good examples in determining an optimal design. We show that design-by-morphing can be extended to many engineering problems in which the performance of an object depends on its shape.

Finding the optimal shape of the leading-and-trailing car of a high-speed train using design-by-morphing

NASA Astrophysics Data System (ADS)

Oh, Sahuck; Jiang, Chung-Hsiang; Jiang, Chiyu; Marcus, Philip S.

2018-07-01

We present a new, general design method, called design-by-morphing for an object whose performance is determined by its shape due to hydrodynamic, aerodynamic, structural, or thermal requirements. To illustrate the method, we design a new leading-and-trailing car of a train by morphing existing, baseline leading-and-trailing cars to minimize the drag. In design-by-morphing, the morphing is done by representing the shapes with polygonal meshes and spectrally with a truncated series of spherical harmonics. The optimal design is found by computing the optimal weights of each of the baseline shapes so that the morphed shape has minimum drag. As a result of optimization, we found that with only two baseline trains that mimic current high-speed trains with low drag that the drag of the optimal train is reduced by 8.04% with respect to the baseline train with the smaller drag. When we repeat the optimization by adding a third baseline train that under-performs compared to the other baseline train, the drag of the new optimal train is reduced by 13.46%. This finding shows that bad examples of design are as useful as good examples in determining an optimal design. We show that design-by-morphing can be extended to many engineering problems in which the performance of an object depends on its shape.

Lead Discovery, Chemistry Optimization, and Biological Evaluation Studies of Novel Biamide Derivatives as CB2 Receptor Inverse Agonists and Osteoclast Inhibitors

PubMed Central

Yang, Peng; Myint, Kyaw-Zeyar; Tong, Qin; Feng, Rentian; Cao, Haiping; Almehizia, Abdulrahman A.; Alqarni, Mohammed Hamed; Wang, Lirong; Bartlow, Patrick; Gao, Yingdai; Gertsch, Jürg; Teramachi, Jumpei; Kurihara, Noriyoshi; Roodman, Garson David; Cheng, Tao; Xie, Xiang-Qun

2014-01-01

N,N′-((4-(Dimethylamino)phenyl)methylene)bis(2-phenylacetamide) was discovered by using 3D pharmacophore database searches and was biologically confirmed as a new class of CB2 inverse agonists. Subsequently, 52 derivatives were designed and synthesized through lead chemistry optimization by modifying the rings A–C and the core structure in further SAR studies. Five compounds were developed and also confirmed as CB2 inverse agonists with the highest CB2 binding affinity (CB2 Ki of 22–85 nM, EC50 of 4–28 nM) and best selectivity (CB1/CB2 of 235- to 909-fold). Furthermore, osteoclastogenesis bioassay indicated that PAM compounds showed great inhibition of osteoclast formation. Especially, compound 26 showed 72% inhibition activity even at the low concentration of 0.1 µM. The cytotoxicity assay suggested that the inhibition of PAM compounds on osteoclastogenesis did not result from its cytotoxicity. Therefore, these PAM derivatives could be used as potential leads for the development of a new type of antiosteoporosis agent. PMID:23072339

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 .

Shape Optimization for Navier-Stokes Equations with Algebraic Turbulence Model: Numerical Analysis and Computation

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

Haslinger, Jaroslav, E-mail: hasling@karlin.mff.cuni.cz; Stebel, Jan, E-mail: stebel@math.cas.cz

2011-04-15

We study the shape optimization problem for the paper machine headbox which distributes a mixture of water and wood fibers in the paper making process. The aim is to find a shape which a priori ensures the given velocity profile on the outlet part. The mathematical formulation leads to the optimal control problem in which the control variable is the shape of the domain representing the header, the state problem is represented by the generalized Navier-Stokes system with nontrivial boundary conditions. This paper deals with numerical aspects of the problem.

Simultaneous optimization of the cavity heat load and trip rates in linacs using a genetic algorithm

DOE PAGES

Terzić, Balša; Hofler, Alicia S.; Reeves, Cody J.; ...

2014-10-15

In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab's Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines.

On the functional optimization of a certain class of nonstationary spatial functions

USGS Publications Warehouse

Christakos, G.; Paraskevopoulos, P.N.

1987-01-01

Procedures are developed in order to obtain optimal estimates of linear functionals for a wide class of nonstationary spatial functions. These procedures rely on well-established constrained minimum-norm criteria, and are applicable to multidimensional phenomena which are characterized by the so-called hypothesis of inherentity. The latter requires elimination of the polynomial, trend-related components of the spatial function leading to stationary quantities, and also it generates some interesting mathematics within the context of modelling and optimization in several dimensions. The arguments are illustrated using various examples, and a case study computed in detail. ?? 1987 Plenum Publishing Corporation.

A Divergent SAR Study Allows Optimization of a Potent 5-HT2c Inhibitor to a Promising Antimalarial Scaffold.

PubMed

Calderón, Félix; Vidal-Mas, Jaume; Burrows, Jeremy; de la Rosa, Juan Carlos; Jiménez-Díaz, María Belén; Mulet, Teresa; Prats, Sara; Solana, Jorge; Witty, Michael; Gamo, Francisco Javier; Fernández, Esther

2012-05-10

From the 13 533 chemical structures published by GlaxoSmithKline in 2010, we identified 47 quality starting points for lead optimization. One of the most promising hits was the TCMDC-139046, a molecule presenting an indoline core, which is well-known for its anxiolytic properties by interacting with serotonin antagonist receptors 5-HT2. The inhibition of this target will complicate the clinical development of these compounds as antimalarials. Herein, we present the antimalarial profile of this series and our efforts to avoid interaction with this receptor, while maintaining a good antiparasitic potency. By using a double-divergent structure-activity relationship analysis, we have obtained a novel lead compound harboring an indoline core.

Early Probe and Drug Discovery in Academia: A Minireview.

PubMed

Roy, Anuradha

2018-02-09

Drug discovery encompasses processes ranging from target selection and validation to the selection of a development candidate. While comprehensive drug discovery work flows are implemented predominantly in the big pharma domain, early discovery focus in academia serves to identify probe molecules that can serve as tools to study targets or pathways. Despite differences in the ultimate goals of the private and academic sectors, the same basic principles define the best practices in early discovery research. A successful early discovery program is built on strong target definition and validation using a diverse set of biochemical and cell-based assays with functional relevance to the biological system being studied. The chemicals identified as hits undergo extensive scaffold optimization and are characterized for their target specificity and off-target effects in in vitro and in animal models. While the active compounds from screening campaigns pass through highly stringent chemical and Absorption, Distribution, Metabolism, and Excretion (ADME) filters for lead identification, the probe discovery involves limited medicinal chemistry optimization. The goal of probe discovery is identification of a compound with sub-µM activity and reasonable selectivity in the context of the target being studied. The compounds identified from probe discovery can also serve as starting scaffolds for lead optimization studies.

Application of Box-Behnken design for modeling of lead adsorption onto unmodified and NaCl-modified zeolite NaA obtained from biosilica.

PubMed

Terzioğlu, Pinar; Yücel, Sevil; Öztürk, Mehmet

2017-01-01

The main objective of the present study was to optimize lead adsorption onto zeolite NaA. For this purpose, to synthesize zeolite NaA under hydrothermal conditions, local wheat husk was precleaned with chemical treatment using hydrochloric acid solution. The unmodified (ZU) and NaCl-modified (ZN) zeolites were characterized by Brunauer-Emmett-Teller, scanning electron microscopy coupled with energy dispersive spectroscopy and X-ray diffraction. The optimization of adsorption process was examined using Box-Behnken Experimental Design in response surface methodology by Design Expert Version 7.0.0 (Stat-Ease, USA). The effects of initial lead (II) concentration, temperature, and time were selected as independent variables. Lack of fit test indicates that the quadratic regression model was significant with the high coefficients of determination values for both adsorbents. Optimum process conditions for lead (II) adsorption onto ZU and ZN were found to be 64.40°C and 64.80°C, respectively, and 90.80 min, and 350 mg L -1 initial lead(II) concentration for both adsorbents. Under these conditions, maximum adsorption capacities of ZU and ZN for lead (II) were 293.38 mg g -1 and 321.85 mg g -1 , respectively.

A Pilot Study Assessing ECG versus ECHO Ventriculoventricular Optimization in Pediatric Resynchronization Patients.

PubMed

Punn, Rajesh; Hanisch, Debra; Motonaga, Kara S; Rosenthal, David N; Ceresnak, Scott R; Dubin, Anne M

2016-02-01

Cardiac resynchronization therapy indications and management are well described in adults. Echocardiography (ECHO) has been used to optimize mechanical synchrony in these patients; however, there are issues with reproducibility and time intensity. Pediatric patients add challenges, with diverse substrates and limited capacity for cooperation. Electrocardiographic (ECG) methods to assess electrical synchrony are expeditious but have not been extensively studied in children. We sought to compare ECHO and ECG CRT optimization in children. Prospective, pediatric, single-center cross-over trial comparing ECHO and ECG optimization with CRT. Patients were assigned to undergo either ECHO or ECG optimization, followed for 6 months, and crossed-over to the other assignment for another 6 months. ECHO pulsed-wave tissue Doppler and 12-lead ECG were obtained for 5 VV delays. ECG optimization was defined as the shortest QRSD and ECHO optimization as the lowest dyssynchrony index. ECHOs/ECGs were interpreted by readers blinded to optimization technique. After each 6 month period, these data were collected: ejection fraction, velocimetry-derived cardiac index, quality of life, ECHO-derived stroke distance, M-mode dyssynchrony, study cost, and time. Outcomes for each optimization method were compared. From June 2012 to December 2013, 19 patients enrolled. Mean age was 9.1 ± 4.3 years; 14 (74%) had structural heart disease. The mean time for optimization was shorter using ECG than ECHO (9 ± 1 min vs. 68 ± 13 min, P < 0.01). Mean cost for charges was $4,400 ± 700 less for ECG. No other outcome differed between groups. ECHO optimization of synchrony was not superior to ECG optimization in this pilot study. ECG optimization required less time and cost than ECHO optimization. © 2015 Wiley Periodicals, Inc.

Evaluating Thermodynamic Integration Performance of the New Amber Molecular Dynamics Package and Assess Potential Halogen Bonds of Enoyl-ACP Reductase (FabI) Benzimidazole Inhibitors

PubMed Central

Su, Pin-Chih; Johnson, Michael E.

2015-01-01

Thermodynamic integration (TI) can provide accurate binding free energy insights in a lead optimization program, but its high computational expense has limited its usage. In the effort of developing an efficient and accurate TI protocol for FabI inhibitors lead optimization program, we carefully compared TI with different Amber molecular dynamics (MD) engines (sander and pmemd), MD simulation lengths, the number of intermediate states and transformation steps, and the Lennard-Jones and Coulomb Softcore potentials parameters in the one-step TI, using eleven benzimidazole inhibitors in complex with Francisella tularensis enoyl acyl reductase (FtFabI). To our knowledge, this is the first study to extensively test the new AMBER MD engine, pmemd, on TI and compare the parameters of the Softcore potentials in the one-step TI in a protein-ligand binding system. The best performing model, the one-step pmemd TI, using 6 intermediate states and 1 ns MD simulations, provides better agreement with experimental results (RMSD = 0.52 kcal/mol) than the best performing implicit solvent method, QM/MM-GBSA from our previous study (RMSD = 3.00 kcal/mol), while maintaining similar efficiency. Briefly, we show the optimized TI protocol to be highly accurate and affordable for the FtFabI system. This approach can be implemented in a larger scale benzimidazole scaffold lead optimization against FtFabI. Lastly, the TI results here also provide structure-activity relationship insights, and suggest the para-halogen in benzimidazole compounds might form a weak halogen bond with FabI, which is a well-known halogen bond favoring enzyme. PMID:26666582

Evaluating thermodynamic integration performance of the new amber molecular dynamics package and assess potential halogen bonds of enoyl-ACP reductase (FabI) benzimidazole inhibitors.

PubMed

Su, Pin-Chih; Johnson, Michael E

2016-04-05

Thermodynamic integration (TI) can provide accurate binding free energy insights in a lead optimization program, but its high computational expense has limited its usage. In the effort of developing an efficient and accurate TI protocol for FabI inhibitors lead optimization program, we carefully compared TI with different Amber molecular dynamics (MD) engines (sander and pmemd), MD simulation lengths, the number of intermediate states and transformation steps, and the Lennard-Jones and Coulomb Softcore potentials parameters in the one-step TI, using eleven benzimidazole inhibitors in complex with Francisella tularensis enoyl acyl reductase (FtFabI). To our knowledge, this is the first study to extensively test the new AMBER MD engine, pmemd, on TI and compare the parameters of the Softcore potentials in the one-step TI in a protein-ligand binding system. The best performing model, the one-step pmemd TI, using 6 intermediate states and 1 ns MD simulations, provides better agreement with experimental results (RMSD = 0.52 kcal/mol) than the best performing implicit solvent method, QM/MM-GBSA from our previous study (RMSD = 3.00 kcal/mol), while maintaining similar efficiency. Briefly, we show the optimized TI protocol to be highly accurate and affordable for the FtFabI system. This approach can be implemented in a larger scale benzimidazole scaffold lead optimization against FtFabI. Lastly, the TI results here also provide structure-activity relationship insights, and suggest the parahalogen in benzimidazole compounds might form a weak halogen bond with FabI, which is a well-known halogen bond favoring enzyme. © 2015 Wiley Periodicals, Inc.

First-Principles Investigations of Lead-Free Formamidinium Based Hybrid Perovskites

NASA Astrophysics Data System (ADS)

Murat, Altynbek; Schwingenschlögl, Udo

2015-03-01

Hybrid organic-inorganic perovskite solar cells have recently emerged as the next-generation photovoltaic technology. Most of the research work has been focused on the prototype MAPbI3 perovskite (MA = Methylammonium = CH3NH3+) and its analogues that have lead to power conversion efficiencies in excess of 15%. Despite the huge success, these materials are still non-optimal in terms of optical absorption where the bandgaps are greater than 1.6 eV as well as the toxicology issue of lead. Thus, investigation and development of lead-free perovskites with bandgaps closer to optimal, allowing greater spectral absorption, is of great interest. In this work, we perform first principles calculations to study the structural, optical, and electronic properties of new derivatives of MAPbI3 in which the organic MA cation is replaced by other organic amines of similar size such as Formamidinium (FA) and/or the Pb cation replaced by similar elements such as Sn. In particular, we investigate the role and effect of FA and Pb cations on the electronic and optical properties and analyze to which extend the bandgaps can be tuned.

[Parameters optimization and cleaning efficiency evaluation of attrition scrubbing remediation of Pb-contaminated soil].

PubMed

Yang, Wen; Huang, Jin-lou; Peng, Hui-qing; Li, Si-tuo

2013-09-01

Attrition scrubbing was used to remediate lead contaminated-site soil, and the main purpose was to remove fine particles and lead contaminants from the surface of sand. The optimal parameters of attrition scrubbing were determined by orthogonal experiment, and three soil samples with different lead concentration were subjected to attrition scrubbing experiments. The results showed that the optimal scrubbing parameters were: a solid ratio of 70% dry matter, a temperature of 25 degrees C, an attrition time of 30 min, and an attrition speed of 1200 r x min(-1). Before attrition scrubbing, the screening and analysis of soil showed that in all three soil samples, lead was mainly enriched on sand and fine particles, and the distribution of lead was highly correlated to the organic matter. After attrition scrubbing, the washing efficiency of the original state lead contaminated sand soil in triplicates was 67.61%, 31.71% and 41.01%, respectively, which indicates that attrition scrubbing can remove part of the fine soil and lead contaminants from the surface of sand, to accomplish the purpose of pollutants enrichment. Scanning electron microscopy (SEM) analysis showed that the sand surface became smooth after attrition scrubbing. The results above show that attrition scrubbing has a good washing effect for the remediation of lead contaminated sand soil.

Tracing binding modes in hit-to-lead optimization: chameleon-like poses of aspartic protease inhibitors.

PubMed

Kuhnert, Maren; Köster, Helene; Bartholomäus, Ruben; Park, Ah Young; Shahim, Amir; Heine, Andreas; Steuber, Holger; Klebe, Gerhard; Diederich, Wibke E

2015-02-23

Successful lead optimization in structure-based drug discovery depends on the correct deduction and interpretation of the underlying structure-activity relationships (SAR) to facilitate efficient decision-making on the next candidates to be synthesized. Consequently, the question arises, how frequently a binding mode (re)-validation is required, to ensure not to be misled by invalid assumptions on the binding geometry. We present an example in which minor chemical modifications within one inhibitor series lead to surprisingly different binding modes. X-ray structure determination of eight inhibitors derived from one core scaffold resulted in four different binding modes in the aspartic protease endothiapepsin, a well-established surrogate for e.g. renin and β-secretase. In addition, we suggest an empirical metrics that might serve as an indicator during lead optimization to qualify compounds as candidates for structural revalidation. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Site Optimization Tracker: Crossley Farm Superfund Site, Hereford and Washington Townships, Berks County, Pennsylvania

EPA Pesticide Factsheets

Pilot Region-Based Optimization Program for Fund-Lead Sites in EPA Region 3. Site Optimization Tracking information for Crossley Farm Superfund Site, Hereford and Washington Townships, Berks County, Pennsylvania.

Joint global optimization of tomographic data based on particle swarm optimization and decision theory

NASA Astrophysics Data System (ADS)

Paasche, H.; Tronicke, J.

2012-04-01

In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto optimality of the found solutions can be made. Identification of the leading particle traditionally requires a costly combination of ranking and niching techniques. In our approach, we use a decision rule under uncertainty to identify the currently leading particle of the swarm. In doing so, we consider the different objectives of our optimization problem as competing agents with partially conflicting interests. Analysis of the maximin fitness function allows for robust and cheap identification of the currently leading particle. The final optimization result comprises a set of possible models spread along the Pareto front. For convex Pareto fronts, solution density is expected to be maximal in the region ideally compromising all objectives, i.e. the region of highest curvature.

Discovery and hit-to-lead optimization of 2,6-diaminopyrimidine inhibitors of interleukin-1 receptor-associated kinase 4

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

McElroy, William T.; Michael Seganish, W.; Jason Herr, R.

2015-05-01

Interleukin receptor-associated kinase 4 (IRAK4) is a critical element of the Toll-like/interleukin-1 receptor inflammation signaling pathway. A screening campaign identified a novel diaminopyrimidine hit that exhibits weak IRAK4 inhibitory activity and a ligand efficiency of 0.25. Hit-to-lead activities were conducted through independent SAR studies of each of the four pyrimidine substituents. Optimal activity was observed upon removal of the pyrimidine C-4 chloro substituent. The intact C-6 carboribose is required for IRAK4 inhibition. Numerous heteroaryls were tolerated at the C-5 position, with azabenzothiazoles conferring the best activities. Aminoheteroaryls were preferred at the C-2 position. These studies led to the discovery ofmore » inhibitors 35, 36, and 38 that exhibit nanomolar inhibition of IRAK4, improved ligand efficiencies, and modest kinase selectivities.« less

Discovery and hit-to-lead optimization of 2,6-diaminopyrimidine inhibitors of interleukin-1 receptor-associated kinase 4.

PubMed

McElroy, William T; Michael Seganish, W; Jason Herr, R; Harding, James; Yang, Jinhai; Yet, Larry; Komanduri, Venukrishnan; Prakash, Koraboina Chandra; Lavey, Brian; Tulshian, Deen; Greenlee, William J; Sondey, Christopher; Fischmann, Thierry O; Niu, Xiaoda

2015-05-01

Interleukin receptor-associated kinase 4 (IRAK4) is a critical element of the Toll-like/interleukin-1 receptor inflammation signaling pathway. A screening campaign identified a novel diaminopyrimidine hit that exhibits weak IRAK4 inhibitory activity and a ligand efficiency of 0.25. Hit-to-lead activities were conducted through independent SAR studies of each of the four pyrimidine substituents. Optimal activity was observed upon removal of the pyrimidine C-4 chloro substituent. The intact C-6 carboribose is required for IRAK4 inhibition. Numerous heteroaryls were tolerated at the C-5 position, with azabenzothiazoles conferring the best activities. Aminoheteroaryls were preferred at the C-2 position. These studies led to the discovery of inhibitors 35, 36, and 38 that exhibit nanomolar inhibition of IRAK4, improved ligand efficiencies, and modest kinase selectivities. Copyright © 2015 Elsevier Ltd. All rights reserved.

Drug efficiency: a new concept to guide lead optimization programs towards the selection of better clinical candidates.

PubMed

Braggio, Simone; Montanari, Dino; Rossi, Tino; Ratti, Emiliangelo

2010-07-01

As a result of their wide acceptance and conceptual simplicity, drug-like concepts are having a major influence on the drug discovery process, particularly in the selection of the 'optimal' absorption, distribution, metabolism, excretion and toxicity and physicochemical parameters space. While they have an undisputable value when assessing the potential of lead series or in evaluating inherent risk of a portfolio of drug candidates, they result much less useful in weighing up compounds for the selection of the best potential clinical candidate. We introduce the concept of drug efficiency as a new tool both to guide the drug discovery program teams during the lead optimization phase and to better assess the developability potential of a drug candidate.

Placement of implantable cardioverter-defibrillators in paediatric and congenital heart defect patients: a pipeline for model generation and simulation prediction of optimal configurations

PubMed Central

Rantner, Lukas J; Vadakkumpadan, Fijoy; Spevak, Philip J; Crosson, Jane E; Trayanova, Natalia A

2013-01-01

There is currently no reliable way of predicting the optimal implantable cardioverter-defibrillator (ICD) placement in paediatric and congenital heart defect (CHD) patients. This study aimed to: (1) develop a new image processing pipeline for constructing patient-specific heart–torso models from clinical magnetic resonance images (MRIs); (2) use the pipeline to determine the optimal ICD configuration in a paediatric tricuspid valve atresia patient; (3) establish whether the widely used criterion of shock-induced extracellular potential (Φe) gradients ≥5 V cm−1 in ≥95% of ventricular volume predicts defibrillation success. A biophysically detailed heart–torso model was generated from patient MRIs. Because transvenous access was impossible, three subcutaneous and three epicardial lead placement sites were identified along with five ICD scan locations. Ventricular fibrillation was induced, and defibrillation shocks were applied from 11 ICD configurations to determine defibrillation thresholds (DFTs). Two configurations with epicardial leads resulted in the lowest DFTs overall and were thus considered optimal. Three configurations shared the lowest DFT among subcutaneous lead ICDs. The Φe gradient criterion was an inadequate predictor of defibrillation success, as defibrillation failed in numerous instances even when 100% of the myocardium experienced such gradients. In conclusion, we have developed a new image processing pipeline and applied it to a CHD patient to construct the first active heart–torso model from clinical MRIs. PMID:23798492

Optimality of affine control system of several species in competition on a sequential batch reactor

NASA Astrophysics Data System (ADS)

Rodríguez, J. C.; Ramírez, H.; Gajardo, P.; Rapaport, A.

2014-09-01

In this paper, we analyse the optimality of affine control system of several species in competition for a single substrate on a sequential batch reactor, with the objective being to reach a given (low) level of the substrate. We allow controls to be bounded measurable functions of time plus possible impulses. A suitable modification of the dynamics leads to a slightly different optimal control problem, without impulsive controls, for which we apply different optimality conditions derived from Pontryagin principle and the Hamilton-Jacobi-Bellman equation. We thus characterise the singular trajectories of our problem as the extremal trajectories keeping the substrate at a constant level. We also establish conditions for which an immediate one impulse (IOI) strategy is optimal. Some numerical experiences are then included in order to illustrate our study and show that those conditions are also necessary to ensure the optimality of the IOI strategy.

Optimal back-to-front airplane boarding.

PubMed

Bachmat, Eitan; Khachaturov, Vassilii; Kuperman, Ran

2013-06-01

The problem of finding an optimal back-to-front airplane boarding policy is explored, using a mathematical model that is related to the 1+1 polynuclear growth model with concave boundary conditions and to causal sets in gravity. We study all airplane configurations and boarding group sizes. Optimal boarding policies for various airplane configurations are presented. Detailed calculations are provided along with simulations that support the main conclusions of the theory. We show that the effectiveness of back-to-front policies undergoes a phase transition when passing from lightly congested airplanes to heavily congested airplanes. The phase transition also affects the nature of the optimal or near-optimal policies. Under what we consider to be realistic conditions, optimal back-to-front policies lead to a modest 8-12% improvement in boarding time over random (no policy) boarding, using two boarding groups. Having more than two groups is not effective.

Beitrag zum mechanismus der oxydation von freiblei in bleiakkumulatorpaste bei der reifung

NASA Astrophysics Data System (ADS)

Duc Hung, Nguyen; Garche, J.; Wiesener, K.

The kinetics of lead oxidation during curing was studied by chemical analysis of the free lead content as well as by the gas volumetry of oxygen. The difference in the results in this research lies in the evolution of hydrogen as a curing reaction. This agrees with the results of curing the paste The optimal water content of the paste for lead oxidation was determined. A model for the electrolyte film during curing has been developed, which allows the results to be interpreted satisfactorily.

Library design practices for success in lead generation with small molecule libraries.

PubMed

Goodnow, R A; Guba, W; Haap, W

2003-11-01

The generation of novel structures amenable to rapid and efficient lead optimization comprises an emerging strategy for success in modern drug discovery. Small molecule libraries of sufficient size and diversity to increase the chances of discovery of novel structures make the high throughput synthesis approach the method of choice for lead generation. Despite an industry trend for smaller, more focused libraries, the need to generate novel lead structures makes larger libraries a necessary strategy. For libraries of a several thousand or more members, solid phase synthesis approaches are the most suitable. While the technology and chemistry necessary for small molecule library synthesis continue to advance, success in lead generation requires rigorous consideration in the library design process to ensure the synthesis of molecules possessing the proper characteristics for subsequent lead optimization. Without proper selection of library templates and building blocks, solid phase synthesis methods often generate molecules which are too heavy, too lipophilic and too complex to be useful for lead optimization. The appropriate filtering of virtual library designs with multiple computational tools allows the generation of information-rich libraries within a drug-like molecular property space. An understanding of the hit-to-lead process provides a practical guide to molecular design characteristics. Examples of leads generated from library approaches also provide a benchmarking of successes as well as aspects for continued development of library design practices.

Effects of lead time of verbal collision warning messages on driving behavior in connected vehicle settings.

PubMed

Wan, Jingyan; Wu, Changxu; Zhang, Yiqi

2016-09-01

Under the connected vehicle environment, vehicles will be able to exchange traffic information with roadway infrastructure and other vehicles. With such information, collision warning systems (CWSs) will be able to warn drivers with potentially hazardous situations within or out of sight and reduce collision accidents. The lead time of warning messages is a crucial factor in determining the effectiveness of CWSs in the prevention of traffic accidents. Accordingly, it is necessary to understand the effects of lead time on driving behaviors and explore the optimal lead time in various collision scenarios. The present driving simulator experiment studied the effects of controlled lead time at 16 levels (predetermined time headway from the subject vehicle to the collision location when the warning message broadcasted to a driver) on driving behaviors in various collision scenarios. Maximum effectiveness of warning messages was achieved when the controlled lead time was within the range of 5s to 8s. Specifically, the controlled lead time ranging from 4s to 8s led to the optimal safety benefit; and the controlled lead time ranging from 5s to 8s led to more gradual braking and shorter reaction time. Furthermore, a trapezoidal distribution of warning effectiveness was found by building a statistic model using curve estimation considering lead time, lifetime driving experience, and driving speed. The results indicated that the controlled lead time significantly affected driver performance. The findings have implications for the design of collision warning systems. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Optimal cost-effective designs of Phase II proof of concept trials and associated go-no go decisions.

PubMed

Chen, Cong; Beckman, Robert A

2009-01-01

This manuscript discusses optimal cost-effective designs for Phase II proof of concept (PoC) trials. Unlike a confirmatory registration trial, a PoC trial is exploratory in nature, and sponsors of such trials have the liberty to choose the type I error rate and the power. The decision is largely driven by the perceived probability of having a truly active treatment per patient exposure (a surrogate measure to development cost), which is naturally captured in an efficiency score to be defined in this manuscript. Optimization of the score function leads to type I error rate and power (and therefore sample size) for the trial that is most cost-effective. This in turn leads to cost-effective go-no go criteria for development decisions. The idea is applied to derive optimal trial-level, program-level, and franchise-level design strategies. The study is not meant to provide any general conclusion because the settings used are largely simplified for illustrative purposes. However, through the examples provided herein, a reader should be able to gain useful insight into these design problems and apply them to the design of their own PoC trials.

Concern for Others Leads to Vicarious Optimism

PubMed Central

Kappes, Andreas; Faber, Nadira S.; Kahane, Guy; Savulescu, Julian; Crockett, Molly J.

2018-01-01

An optimistic learning bias leads people to update their beliefs in response to better-than-expected good news but neglect worse-than-expected bad news. Because evidence suggests that this bias arises from self-concern, we hypothesized that a similar bias may affect beliefs about other people’s futures, to the extent that people care about others. Here, we demonstrated the phenomenon of vicarious optimism and showed that it arises from concern for others. Participants predicted the likelihood of unpleasant future events that could happen to either themselves or others. In addition to showing an optimistic learning bias for events affecting themselves, people showed vicarious optimism when learning about events affecting friends and strangers. Vicarious optimism for strangers correlated with generosity toward strangers, and experimentally increasing concern for strangers amplified vicarious optimism for them. These findings suggest that concern for others can bias beliefs about their future welfare and that optimism in learning is not restricted to oneself. PMID:29381448

Concern for Others Leads to Vicarious Optimism.

PubMed

Kappes, Andreas; Faber, Nadira S; Kahane, Guy; Savulescu, Julian; Crockett, Molly J

2018-03-01

An optimistic learning bias leads people to update their beliefs in response to better-than-expected good news but neglect worse-than-expected bad news. Because evidence suggests that this bias arises from self-concern, we hypothesized that a similar bias may affect beliefs about other people's futures, to the extent that people care about others. Here, we demonstrated the phenomenon of vicarious optimism and showed that it arises from concern for others. Participants predicted the likelihood of unpleasant future events that could happen to either themselves or others. In addition to showing an optimistic learning bias for events affecting themselves, people showed vicarious optimism when learning about events affecting friends and strangers. Vicarious optimism for strangers correlated with generosity toward strangers, and experimentally increasing concern for strangers amplified vicarious optimism for them. These findings suggest that concern for others can bias beliefs about their future welfare and that optimism in learning is not restricted to oneself.

Optimization principles and the figure of merit for triboelectric generators.

PubMed

Peng, Jun; Kang, Stephen Dongmin; Snyder, G Jeffrey

2017-12-01

Energy harvesting with triboelectric nanogenerators is a burgeoning field, with a growing portfolio of creative application schemes attracting much interest. Although power generation capabilities and its optimization are one of the most important subjects, a satisfactory elemental model that illustrates the basic principles and sets the optimization guideline remains elusive. We use a simple model to clarify how the energy generation mechanism is electrostatic induction but with a time-varying character that makes the optimal matching for power generation more restrictive. By combining multiple parameters into dimensionless variables, we pinpoint the optimum condition with only two independent parameters, leading to predictions of the maximum limit of power density, which allows us to derive the triboelectric material and device figure of merit. We reveal the importance of optimizing device capacitance, not only load resistance, and minimizing the impact of parasitic capacitance. Optimized capacitances can lead to an overall increase in power density of more than 10 times.

Optimizing chirped laser pulse parameters for electron acceleration in vacuum

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

Akhyani, Mina; Jahangiri, Fazel; Niknam, Ali Reza

2015-11-14

Electron dynamics in the field of a chirped linearly polarized laser pulse is investigated. Variations of electron energy gain versus chirp parameter, time duration, and initial phase of laser pulse are studied. Based on maximizing laser pulse asymmetry, a numerical optimization procedure is presented, which leads to the elimination of rapid fluctuations of gain versus the chirp parameter. Instead, a smooth variation is observed that considerably reduces the accuracy required for experimentally adjusting the chirp parameter.

Optimization of imprintable nanostructured a-Si solar cells: FDTD study.

PubMed

Fisker, Christian; Pedersen, Thomas Garm

2013-03-11

We present a finite-difference time-domain (FDTD) study of an amorphous silicon (a-Si) thin film solar cell, with nano scale patterns on the substrate surface. The patterns, based on the geometry of anisotropically etched silicon gratings, are optimized with respect to the period and anti-reflection (AR) coating thickness for maximal absorption in the range of the solar spectrum. The structure is shown to increase the cell efficiency by 10.2% compared to a similar flat solar cell with an optimized AR coating thickness. An increased back reflection can be obtained with a 50 nm zinc oxide layer on the back reflector, which gives an additional efficiency increase, leading to a total of 14.9%. In addition, the patterned cells are shown to be up to 3.8% more efficient than an optimized textured reference cell based on the Asahi U-type glass surface. The effects of variations of the optimized solar cell structure due to the manufacturing process are investigated, and shown to be negligible for variations below ±10%.

Optimization and characterization of stable lipid-based, oxygen-filled microbubbles by mixture design.

PubMed

Polizzotti, Brian D; Thomson, Lindsay M; O'Connell, Daniel W; McGowan, Francis X; Kheir, John N

2014-08-01

Tissue hypoxia is a final common pathway that leads to cellular injury and death in a number of critical illnesses. Intravenous injections of self-assembling, lipid-based oxygen microbubbles (LOMs) can be used to deliver oxygen gas, preventing organ injury and death from systemic hypoxemia. However, current formulations exhibit high polydispersity indices (which may lead to microvascular obstruction) and poor shelf-lives, limiting the translational capacity of LOMs. In this study, we report our efforts to optimize LOM formulations using a mixture response surface methodology (mRSM). We study the effect of changing excipient proportions (the independent variables) on microbubble diameter and product loss (the dependent variables). By using mRSM analysis, the experimental data were fit using a reduced Scheffé linear mixture model. We demonstrate that formulations manufactured from 1,2-distearoyl-sn-glycero-3-phosphocholine, corn syrup, and water produce micron-sized microbubbles with low polydispersity indices, and decreased product loss (relative to previously described formulations) when stored at room temperature over a 30-day period. Optimized LOMs were subsequently tested for their oxygen-releasing ability and found to have similar release kinetics as prior formulations. © 2014 Wiley Periodicals, Inc.

Optimization of integrated impeller mixer via radiotracer experiments.

PubMed

Othman, N; Kamarudin, S K; Takriff, M S; Rosli, M I; Engku Chik, E M F; Adnan, M A K

2014-01-01

Radiotracer experiments are carried out in order to determine the mean residence time (MRT) as well as percentage of dead zone, V dead (%), in an integrated mixer consisting of Rushton and pitched blade turbine (PBT). Conventionally, optimization was performed by varying one parameter and others were held constant (OFAT) which lead to enormous number of experiments. Thus, in this study, a 4-factor 3-level Taguchi L9 orthogonal array was introduced to obtain an accurate optimization of mixing efficiency with minimal number of experiments. This paper describes the optimal conditions of four process parameters, namely, impeller speed, impeller clearance, type of impeller, and sampling time, in obtaining MRT and V dead (%) using radiotracer experiments. The optimum conditions for the experiments were 100 rpm impeller speed, 50 mm impeller clearance, Type A mixer, and 900 s sampling time to reach optimization.

Optimal Design for Regression Discontinuity Studies with Clustering

ERIC Educational Resources Information Center

Rhoads, Christopher; Dye, Charles

2014-01-01

Recent years have seen an increased interest in quantitative educational research studies that use random assignment (RA) to evaluate the causal impacts of educational interventions (Angrist, 2004). The multi-level structure of the public education system in the United States often leads to experimental designs where naturally occurring clusters…

Robust Portfolio Optimization Using Pseudodistances.

PubMed

Toma, Aida; Leoni-Aubin, Samuela

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.

Robust Portfolio Optimization Using Pseudodistances

PubMed Central

2015-01-01

The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948

Optimization of cathodic arc deposition and pulsed plasma melting techniques for growing smooth superconducting Pb photoemissive films for SRF injectors

NASA Astrophysics Data System (ADS)

Nietubyć, Robert; Lorkiewicz, Jerzy; Sekutowicz, Jacek; Smedley, John; Kosińska, Anna

2018-05-01

Superconducting photoinjectors have a potential to be the optimal solution for moderate and high current cw operating free electron lasers. For this application, a superconducting lead (Pb) cathode has been proposed to simplify the cathode integration into a 1.3 GHz, TESLA-type, 1.6-cell long purely superconducting gun cavity. In the proposed design, a lead film several micrometres thick is deposited onto a niobium plug attached to the cavity back wall. Traditional lead deposition techniques usually produce very non-uniform emission surfaces and often result in a poor adhesion of the layer. A pulsed plasma melting procedure reducing the non-uniformity of the lead photocathodes is presented. In order to determine the parameters optimal for this procedure, heat transfer from plasma to the film was first modelled to evaluate melting front penetration range and liquid state duration. The obtained results were verified by surface inspection of witness samples. The optimal procedure was used to prepare a photocathode plug, which was then tested in an electron gun. The quantum efficiency and the value of cavity quality factor have been found to satisfy the requirements for an injector of the European-XFEL facility.

Lead optimization of N-3-substituted 7-morpholinotriazolopyrimidines as dual phosphoinositide 3-kinase/mammalian target of rapamycin inhibitors: discovery of PKI-402.

PubMed

Dehnhardt, Christoph M; Venkatesan, Aranapakam M; Delos Santos, Efren; Chen, Zecheng; Santos, Osvaldo; Ayral-Kaloustian, Semiramis; Brooijmans, Natasja; Mallon, Robert; Hollander, Irwin; Feldberg, Larry; Lucas, Judy; Chaudhary, Inder; Yu, Ker; Gibbons, Jay; Abraham, Robert; Mansour, Tarek S

2010-01-28

Herein we describe the identification and lead optimization of triazolopyrimidines as a novel class of potent dual PI3K/mTOR inhibitors, resulting in the discovery of 3 (PKI-402). Compound 3 exhibits good physical properties and PK parameters, low nanomolar potency against PI3Kalpha and mTOR, and excellent inhibition of cell proliferation in several human cancer cell lines. Furthermore, in vitro and in vivo biomarker studies demonstrated the ability of 3 to shut down the PI3K/Akt pathway and induce apoptosis in cancer cells. In addition, 3 showed excellent in vivo efficacy in various human cancer xenografts, validating suppression of PI3K/mTOR signaling as a potential anticancer therapy.

Simulation and Optimization of an Airfoil with Leading Edge Slat

NASA Astrophysics Data System (ADS)

Schramm, Matthias; Stoevesandt, Bernhard; Peinke, Joachim

2016-09-01

A gradient-based optimization is used in order to improve the shape of a leading edge slat upstream of a DU 91-W2-250 airfoil. The simulations are performed by solving the Reynolds-Averaged Navier-Stokes equations (RANS) using the open source CFD code OpenFOAM. Gradients are computed via the adjoint approach, which is suitable to deal with many design parameters, but keeping the computational costs low. The implementation is verified by comparing the gradients from the adjoint method with gradients obtained by finite differences for a NACA 0012 airfoil. The simulations of the leading edge slat are validated against measurements from the acoustic wind tunnel of Oldenburg University at a Reynolds number of Re = 6 • 105. The shape of the slat is optimized using the adjoint approach resulting in a drag reduction of 2%. Although the optimization is done for Re = 6 • 105, the improvements also hold for a higher Reynolds number of Re = 7.9 • 106, which is more realistic at modern wind turbines.

Non-optimal microbial response to antibiotics underlies suppressive drug interactions

PubMed Central

Bollenbach, Tobias; Quan, Selwyn; Chait, Remy; Kishony, Roy

2010-01-01

SUMMARY Antibiotics inhibiting translation can increase bacterial growth rate in the presence of DNA synthesis inhibitors. Here, we show that this extreme type of drug antagonism, termed suppression, results from non-optimal regulation of ribosomal genes, leading to sub-maximal growth in the presence of DNA stress. Using GFP-tagged transcription reporters in Escherichia coli, we find that ribosomal genes are not directly regulated by DNA stress, leading to an imbalance between cellular DNA and protein content. Sequential deletion of up to 6 of the 7 ribosomal RNA operons corrects this imbalance and leads to improved survival and growth under DNA synthesis inhibition. Further, this genetic manipulation completely removes the suppressive drug interaction. Mathematical modeling shows that non-optimal regulation of ribosome synthesis under DNA stress can be explained as a side-effect of optimal growth-rate-dependent regulation in different nutrient environments. Together, these results reveal the genetic mechanism underlying an important class of suppressive drug interactions. PMID:19914165

5-HT7 Receptor Antagonists with an Unprecedented Selectivity Profile.

PubMed

Ates, Ali; Burssens, Pierre; Lorthioir, Olivier; Lo Brutto, Patrick; Dehon, Gwenael; Keyaerts, Jean; Coloretti, Francis; Lallemand, Bénédicte; Verbois, Valérie; Gillard, Michel; Vermeiren, Céline

2018-04-23

Selective leads: In this study, we generated a new series of serotonin 5-HT 7 receptor antagonists. Their synthesis, structure-activity relationships, and selectivity profiles are reported. This series includes 5-HT 7 antagonists with unprecedented high selectivity for the 5-HT 7 receptor, setting the stage for lead optimization of drugs acting on a range of neurological targets. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design of optimal groundwater remediation systems under flexible environmental-standard constraints.

PubMed

Fan, Xing; He, Li; Lu, Hong-Wei; Li, Jing

2015-01-01

In developing optimal groundwater remediation strategies, limited effort has been exerted to solve the uncertainty in environmental quality standards. When such uncertainty is not considered, either over optimistic or over pessimistic optimization strategies may be developed, probably leading to the formulation of rigid remediation strategies. This study advances a mathematical programming modeling approach for optimizing groundwater remediation design. This approach not only prevents the formulation of over optimistic and over pessimistic optimization strategies but also provides a satisfaction level that indicates the degree to which the environmental quality standard is satisfied. Therefore the approach may be expected to be significantly more acknowledged by the decision maker than those who do not consider standard uncertainty. The proposed approach is applied to a petroleum-contaminated site in western Canada. Results from the case study show that (1) the peak benzene concentrations can always satisfy the environmental standard under the optimal strategy, (2) the pumping rates of all wells decrease under a relaxed standard or long-term remediation approach, (3) the pumping rates are less affected by environmental quality constraints under short-term remediation, and (4) increased flexible environmental standards have a reduced effect on the optimal remediation strategy.

Binding Free Energy Calculations for Lead Optimization: Assessment of Their Accuracy in an Industrial Drug Design Context.

PubMed

Homeyer, Nadine; Stoll, Friederike; Hillisch, Alexander; Gohlke, Holger

2014-08-12

Correctly ranking compounds according to their computed relative binding affinities will be of great value for decision making in the lead optimization phase of industrial drug discovery. However, the performance of existing computationally demanding binding free energy calculation methods in this context is largely unknown. We analyzed the performance of the molecular mechanics continuum solvent, the linear interaction energy (LIE), and the thermodynamic integration (TI) approach for three sets of compounds from industrial lead optimization projects. The data sets pose challenges typical for this early stage of drug discovery. None of the methods was sufficiently predictive when applied out of the box without considering these challenges. Detailed investigations of failures revealed critical points that are essential for good binding free energy predictions. When data set-specific features were considered accordingly, predictions valuable for lead optimization could be obtained for all approaches but LIE. Our findings lead to clear recommendations for when to use which of the above approaches. Our findings also stress the important role of expert knowledge in this process, not least for estimating the accuracy of prediction results by TI, using indicators such as the size and chemical structure of exchanged groups and the statistical error in the predictions. Such knowledge will be invaluable when it comes to the question which of the TI results can be trusted for decision making.

Nozzle design study for a quasi-axisymmetric scramjet-powered vehicle at Mach 7.9 flight conditions

NASA Astrophysics Data System (ADS)

Tanimizu, Katsuyoshi; Mee, David J.; Stalker, Raymond J.; Jacobs, Peter A.

2013-09-01

A nozzle shape optimization study for a quasi-axisymmetric scramjet has been performed for a Mach 7.9 operating condition with hydrogen fuel, aiming at the application of a hypersonic airbreathing vehicle. In this study, the nozzle geometry which is parameterized by a set of design variables, is optimized for the single objective of maximum net thrust using an in-house CFD solver for inviscid flowfields with a simple force prediction methodology. The combustion is modelled using a simple chemical reaction code. The effects of the nozzle design on the overall vehicle performance are discussed. For the present geometry, net thrust is achieved for the optimized vehicle design. The results of the nozzle-optimization study show that performance is limited by the nozzle area ratio that can be incorporated into the vehicle without leading to too large a base diameter of the vehicle and increasing the external drag of the vehicle. This study indicates that it is very difficult to achieve positive thrust at Mach 7.9 using the basic geometry investigated.

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.

Self-transcending meditation is good for mental health: why this should be the case.

PubMed

Hankey, Alex; Shetkar, Rashmi

2016-06-01

A simple theory of health has recently been proposed: while poor quality regulation corresponds to poor quality health so that improving regulation should improve health, optimal regulation optimizes function and optimizes health. Examining the term 'optimal regulation' in biological systems leads to a straightforward definition in terms of 'criticality' in complexity biology, a concept that seems to apply universally throughout biology. Criticality maximizes information processing and sensitivity of response to external stimuli, and for these reasons may be held to optimize regulation. In this way a definition of health has been given in terms of regulation, a scientific concept, which ties into detailed properties of complex systems, including brain cortices, and mental health. Models of experience and meditation built on complexity also point to criticality: it represents the condition making self-awareness possible, and is strengthened by meditation practices leading to the state of pure consciousness-the content-free state of mind in deep meditation. From this it follows that healthy function of the brain cortex, its sensitivity,y and consistency of response to external challenges should improve by practicing techniques leading to content-free awareness-transcending the original focus introduced during practice. Evidence for this is reviewed.

Some Results of Weak Anticipative Concept Applied in Simulation Based Decision Support in Enterprise

NASA Astrophysics Data System (ADS)

Kljajić, Miroljub; Kofjač, Davorin; Kljajić Borštnar, Mirjana; Škraba, Andrej

2010-11-01

The simulation models are used as for decision support and learning in enterprises and in schools. Tree cases of successful applications demonstrate usefulness of weak anticipative information. Job shop scheduling production with makespan criterion presents a real case customized flexible furniture production optimization. The genetic algorithm for job shop scheduling optimization is presented. Simulation based inventory control for products with stochastic lead time and demand describes inventory optimization for products with stochastic lead time and demand. Dynamic programming and fuzzy control algorithms reduce the total cost without producing stock-outs in most cases. Values of decision making information based on simulation were discussed too. All two cases will be discussed from optimization, modeling and learning point of view.

Pilot Project to Optimize Superfund-financed Pump and Treat Systems: Summary Report and Lessons Learned

EPA Pesticide Factsheets

This report summarizes Phase II (site optimization) of the Nationwide Fund-lead Pump and Treat Optimization Project. This phase included conducting Remediation System Evaluations (RSEs) at each of the 20 sites selected in Phase I.

Optimism and Cause-Specific Mortality: A Prospective Cohort Study

PubMed Central

Kim, Eric S.; Hagan, Kaitlin A.; Grodstein, Francine; DeMeo, Dawn L.; De Vivo, Immaculata; Kubzansky, Laura D.

2017-01-01

Growing evidence has linked positive psychological attributes like optimism to a lower risk of poor health outcomes, especially cardiovascular disease. It has been demonstrated in randomized trials that optimism can be learned. If associations between optimism and broader health outcomes are established, it may lead to novel interventions that improve public health and longevity. In the present study, we evaluated the association between optimism and cause-specific mortality in women after considering the role of potential confounding (sociodemographic characteristics, depression) and intermediary (health behaviors, health conditions) variables. We used prospective data from the Nurses’ Health Study (n = 70,021). Dispositional optimism was measured in 2004; all-cause and cause-specific mortality rates were assessed from 2006 to 2012. Using Cox proportional hazard models, we found that a higher degree of optimism was associated with a lower mortality risk. After adjustment for sociodemographic confounders, compared with women in the lowest quartile of optimism, women in the highest quartile had a hazard ratio of 0.71 (95% confidence interval: 0.66, 0.76) for all-cause mortality. Adding health behaviors, health conditions, and depression attenuated but did not eliminate the associations (hazard ratio = 0.91, 95% confidence interval: 0.85, 0.97). Associations were maintained for various causes of death, including cancer, heart disease, stroke, respiratory disease, and infection. Given that optimism was associated with numerous causes of mortality, it may provide a valuable target for new research on strategies to improve health. PMID:27927621

An assessment of separable fluid connector system parameters to perform a connector system design optimization study

NASA Technical Reports Server (NTRS)

Prasthofer, W. P.

1974-01-01

The key to optimization of design where there are a large number of variables, all of which may not be known precisely, lies in the mathematical tool of dynamic programming developed by Bellman. This methodology can lead to optimized solutions to the design of critical systems in a minimum amount of time, even when there are a great number of acceptable configurations to be considered. To demonstrate the usefulness of dynamic programming, an analytical method is developed for evaluating the relationship among existing numerous connector designs to find the optimum configuration. The data utilized in the study were generated from 900 flanges designed for six subsystems of the S-1B stage of the Saturn 1B space carrier vehicle.

Strategies for the generation, validation and application of in silico ADMET models in lead generation and optimization.

PubMed

Gleeson, Matthew Paul; Montanari, Dino

2012-11-01

The most desirable chemical starting point in drug discovery is a hit or lead with a good overall profile, and where there may be issues; a clear SAR strategy should be identifiable to minimize the issue. Filtering based on drug-likeness concepts are a first step, but more accurate theoretical methods are needed to i) estimate the biological profile of molecule in question and ii) based on the underlying structure-activity relationships used by the model, estimate whether it is likely that the molecule in question can be altered to remove these liabilities. In this paper, the authors discuss the generation of ADMET models and their practical use in decision making. They discuss the issues surrounding data collation, experimental errors, the model assessment and validation steps, as well as the different types of descriptors and statistical models that can be used. This is followed by a discussion on how the model accuracy will dictate when and where it can be used in the drug discovery process. The authors also discuss how models can be developed to more effectively enable multiple parameter optimization. Models can be applied in lead generation and lead optimization steps to i) rank order a collection of hits, ii) prioritize the experimental assays needed for different hit series, iii) assess the likelihood of resolving a problem that might be present in a particular series in lead optimization and iv) screen a virtual library based on a hit or lead series to assess the impact of diverse structural changes on the predicted properties.

Engagement and Arousal: Optimism’s Effects During a Brief Stressor

PubMed Central

Nes, Lise Solberg; Segerstrom, Suzanne C.; Sephton, Sandra E.

2005-01-01

Optimism is usually associated with better psychological and physiological adjustment to stressors, but some contradictory findings exist. The purpose of this study was to investigate how optimism could result in negative immunological changes following difficult stressors. Because optimists are likely to see positive outcomes as attainable, they may invest greater effort to achieve their goals. It is proposed that such engagement would be more physiologically demanding when pursuing difficult goals. Participants (N = 54) worked on 11 difficult or insoluble anagrams. Optimism when combined with high self-awareness increased time spent working on the anagrams and skin conductance and salivary cortisol during the recovery period. The results support the notion that the increased engagement that arises from optimism may lead to short-term physiological costs. PMID:15574666

[Study on the optimization of monitoring indicators of drinking water quality during health supervision].

PubMed

Ye, Bixiong; E, Xueli; Zhang, Lan

2015-01-01

To optimize non-regular drinking water quality indices (except Giardia and Cryptosporidium) of urban drinking water. Several methods including drinking water quality exceed the standard, the risk of exceeding standard, the frequency of detecting concentrations below the detection limit, water quality comprehensive index evaluation method, and attribute reduction algorithm of rough set theory were applied, redundancy factor of water quality indicators were eliminated, control factors that play a leading role in drinking water safety were found. Optimization results showed in 62 unconventional water quality monitoring indicators of urban drinking water, 42 water quality indicators could be optimized reduction by comprehensively evaluation combined with attribute reduction of rough set. Optimization of the water quality monitoring indicators and reduction of monitoring indicators and monitoring frequency could ensure the safety of drinking water quality while lowering monitoring costs and reducing monitoring pressure of the sanitation supervision departments.

Fast globally optimal segmentation of 3D prostate MRI with axial symmetry prior.

PubMed

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

We propose a novel global optimization approach to segmenting a given 3D prostate T2w magnetic resonance (MR) image, which enforces the inherent axial symmetry of the prostate shape and simultaneously performs a sequence of 2D axial slice-wise segmentations with a global 3D coherence prior. We show that the proposed challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. With this regard, we introduce a novel coupled continuous max-flow model, which is dual to the studied convex relaxed optimization formulation and leads to an efficient multiplier augmented algorithm based on the modern convex optimization theory. Moreover, the new continuous max-flow based algorithm was implemented on GPUs to achieve a substantial improvement in computation. Experimental results using public and in-house datasets demonstrate great advantages of the proposed method in terms of both accuracy and efficiency.

Optimal False Discovery Rate Control for Dependent Data

PubMed Central

Xie, Jichun; Cai, T. Tony; Maris, John; Li, Hongzhe

2013-01-01

This paper considers the problem of optimal false discovery rate control when the test statistics are dependent. An optimal joint oracle procedure, which minimizes the false non-discovery rate subject to a constraint on the false discovery rate is developed. A data-driven marginal plug-in procedure is then proposed to approximate the optimal joint procedure for multivariate normal data. It is shown that the marginal procedure is asymptotically optimal for multivariate normal data with a short-range dependent covariance structure. Numerical results show that the marginal procedure controls false discovery rate and leads to a smaller false non-discovery rate than several commonly used p-value based false discovery rate controlling methods. The procedure is illustrated by an application to a genome-wide association study of neuroblastoma and it identifies a few more genetic variants that are potentially associated with neuroblastoma than several p-value-based false discovery rate controlling procedures. PMID:23378870

On the optimal use of a slow server in two-stage queueing systems

NASA Astrophysics Data System (ADS)

Papachristos, Ioannis; Pandelis, Dimitrios G.

2017-07-01

We consider two-stage tandem queueing systems with a dedicated server in each queue and a slower flexible server that can attend both queues. We assume Poisson arrivals and exponential service times, and linear holding costs for jobs present in the system. We study the optimal dynamic assignment of servers to jobs assuming that two servers cannot collaborate to work on the same job and preemptions are not allowed. We formulate the problem as a Markov decision process and derive properties of the optimal allocation for the dedicated (fast) servers. Specifically, we show that the one downstream should not idle, and the same is true for the one upstream when holding costs are larger there. The optimal allocation of the slow server is investigated through extensive numerical experiments that lead to conjectures on the structure of the optimal policy.

Nonparametric variational optimization of reaction coordinates

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

Banushkina, Polina V.; Krivov, Sergei V., E-mail: s.krivov@leeds.ac.uk

State of the art realistic simulations of complex atomic processes commonly produce trajectories of large size, making the development of automated analysis tools very important. A popular approach aimed at extracting dynamical information consists of projecting these trajectories into optimally selected reaction coordinates or collective variables. For equilibrium dynamics between any two boundary states, the committor function also known as the folding probability in protein folding studies is often considered as the optimal coordinate. To determine it, one selects a functional form with many parameters and trains it on the trajectories using various criteria. A major problem with such anmore » approach is that a poor initial choice of the functional form may lead to sub-optimal results. Here, we describe an approach which allows one to optimize the reaction coordinate without selecting its functional form and thus avoiding this source of error.« less

Optimization-based additive decomposition of weakly coercive problems with applications

DOE PAGES

Bochev, Pavel B.; Ridzal, Denis

2016-01-27

In this study, we present an abstract mathematical framework for an optimization-based additive decomposition of a large class of variational problems into a collection of concurrent subproblems. The framework replaces a given monolithic problem by an equivalent constrained optimization formulation in which the subproblems define the optimization constraints and the objective is to minimize the mismatch between their solutions. The significance of this reformulation stems from the fact that one can solve the resulting optimality system by an iterative process involving only solutions of the subproblems. Consequently, assuming that stable numerical methods and efficient solvers are available for every subproblem,more » our reformulation leads to robust and efficient numerical algorithms for a given monolithic problem by breaking it into subproblems that can be handled more easily. An application of the framework to the Oseen equations illustrates its potential.« less

Shape Optimization and Modular Discretization for the Development of a Morphing Wingtip

NASA Astrophysics Data System (ADS)

Morley, Joshua

Better knowledge in the areas of aerodynamics and optimization has allowed designers to develop efficient wingtip structures in recent years. However, the requirements faced by wingtip devices can be considerably different amongst an aircraft's flight regimes. Traditional static wingtip devices are then a compromise between conflicting requirements, resulting in less than optimal performance within each regime. Alternatively, a morphing wingtip can reconfigure leading to improved performance over a range of dissimilar flight conditions. Developed within this thesis, is a modular morphing wingtip concept that centers on the use of variable geometry truss mechanisms to permit morphing. A conceptual design framework is established to aid in the development of the concept. The framework uses a metaheuristic optimization procedure to determine optimal continuous wingtip configurations. The configurations are then discretized for the modular concept. The functionality of the framework is demonstrated through a design study on a hypothetical wing/winglet within the thesis.

Optimization of PbTiO3 Seed Layers for PZT MEMS Actuators

DTIC Science & Technology

2008-12-01

14. ABSTRACT The material properties of sol-gel lead zirconate titanate ( PZT ) are inherently linked with its crystallinity and texture . The use...will lead to a greater degree of texturing within the PZT thin film. Figure 6. X-ray diffraction data for PT seed solution. (001) oriented...previous studies PZT 45/55 has shown a higher piezoelectric coefficient compared to PZT 52/48 due to the random crystalline texture of the existing

Nonlinear optimal control for the synchronization of chaotic and hyperchaotic finance systems

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Loia, V.; Ademi, S.; Ghosh, T.

2017-11-01

It is possible to make specific finance systems get synchronized to other finance systems exhibiting chaotic and hyperchaotic dynamics, by applying nonlinear optimal (H-infinity) control. This signifies that chaotic behavior can be generated in finance systems by exerting a suitable control input. Actually, a lead financial system is considered which exhibits inherently chaotic dynamics. Moreover, a follower finance system is introduced having parameters in its model that inherently prohibit the appearance of chaotic dynamics. Through the application of a suitable nonlinear optimal (H-infinity) control input it is proven that the follower finance system can replicate the chaotic dynamics of the lead finance system. By applying Lyapunov analysis it is proven that asymptotically the follower finance system gets synchronized with the lead system and that the tracking error between the state variables of the two systems vanishes.

Optimization of the magnetic dynamo.

PubMed

Willis, Ashley P

2012-12-21

In stars and planets, magnetic fields are believed to originate from the motion of electrically conducting fluids in their interior, through a process known as the dynamo mechanism. In this Letter, an optimization procedure is used to simultaneously address two fundamental questions of dynamo theory: "Which velocity field leads to the most magnetic energy growth?" and "How large does the velocity need to be relative to magnetic diffusion?" In general, this requires optimization over the full space of continuous solenoidal velocity fields possible within the geometry. Here the case of a periodic box is considered. Measuring the strength of the flow with the root-mean-square amplitude, an optimal velocity field is shown to exist, but without limitation on the strain rate, optimization is prone to divergence. Measuring the flow in terms of its associated dissipation leads to the identification of a single optimal at the critical magnetic Reynolds number necessary for a dynamo. This magnetic Reynolds number is found to be only 15% higher than that necessary for transient growth of the magnetic field.

Targeted left ventricular lead placement to guide cardiac resynchronization therapy: the TARGET study: a randomized, controlled trial.

PubMed

Khan, Fakhar Z; Virdee, Mumohan S; Palmer, Christopher R; Pugh, Peter J; O'Halloran, Denis; Elsik, Maros; Read, Philip A; Begley, David; Fynn, Simon P; Dutka, David P

2012-04-24

This study sought to assess the impact of targeted left ventricular (LV) lead placement on outcomes of cardiac resynchronization therapy (CRT). Placement of the LV lead to the latest sites of contraction and away from the scar confers the best response to CRT. We conducted a randomized, controlled trial to compare a targeted approach to LV lead placement with usual care. A total of 220 patients scheduled for CRT underwent baseline echocardiographic speckle-tracking 2-dimensional radial strain imaging and were then randomized 1:1 into 2 groups. In group 1 (TARGET [Targeted Left Ventricular Lead Placement to Guide Cardiac Resynchronization Therapy]), the LV lead was positioned at the latest site of peak contraction with an amplitude of >10% to signify freedom from scar. In group 2 (control) patients underwent standard unguided CRT. Patients were classified by the relationship of the LV lead to the optimal site as concordant (at optimal site), adjacent (within 1 segment), or remote (≥2 segments away). The primary endpoint was a ≥15% reduction in LV end-systolic volume at 6 months. Secondary endpoints were clinical response (≥1 improvement in New York Heart Association functional class), all-cause mortality, and combined all-cause mortality and heart failure-related hospitalization. The groups were balanced at randomization. In the TARGET group, there was a greater proportion of responders at 6 months (70% vs. 55%, p = 0.031), giving an absolute difference in the primary endpoint of 15% (95% confidence interval: 2% to 28%). Compared with controls, TARGET patients had a higher clinical response (83% vs. 65%, p = 0.003) and lower rates of the combined endpoint (log-rank test, p = 0.031). Compared with standard CRT treatment, the use of speckle-tracking echocardiography to the target LV lead placement yields significantly improved response and clinical status and lower rates of combined death and heart failure-related hospitalization. (Targeted Left Ventricular Lead Placement to Guide Cardiac Resynchronization Therapy [TARGET] study); ISRCTN19717943). Copyright © 2012 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Finding the Right Candidate for the Right Position: A Fast NMR-Assisted Combinatorial Method for Optimizing Nucleic Acids Binders.

PubMed

Jiménez-Moreno, Ester; Montalvillo-Jiménez, Laura; Santana, Andrés G; Gómez, Ana M; Jiménez-Osés, Gonzalo; Corzana, Francisco; Bastida, Agatha; Jiménez-Barbero, Jesús; Cañada, Francisco Javier; Gómez-Pinto, Irene; González, Carlos; Asensio, Juan Luis

2016-05-25

Development of strong and selective binders from promiscuous lead compounds represents one of the most expensive and time-consuming tasks in drug discovery. We herein present a novel fragment-based combinatorial strategy for the optimization of multivalent polyamine scaffolds as DNA/RNA ligands. Our protocol provides a quick access to a large variety of regioisomer libraries that can be tested for selective recognition by combining microdialysis assays with simple isotope labeling and NMR experiments. To illustrate our approach, 20 small libraries comprising 100 novel kanamycin-B derivatives have been prepared and evaluated for selective binding to the ribosomal decoding A-Site sequence. Contrary to the common view of NMR as a low-throughput technique, we demonstrate that our NMR methodology represents a valuable alternative for the detection and quantification of complex mixtures, even integrated by highly similar or structurally related derivatives, a common situation in the context of a lead optimization process. Furthermore, this study provides valuable clues about the structural requirements for selective A-site recognition.

An Optimal Image-Based Method for Identification of Acoustic Emission (AE) Sources in Plate-Like Structures Using a Lead Zirconium Titanate (PZT) Sensor Array.

PubMed

Yan, Gang; Zhou, Li

2018-02-21

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method.

Nonlinear Transient Growth and Boundary Layer Transition

NASA Technical Reports Server (NTRS)

Paredes, Pedro; Choudhari, Meelan M.; Li, Fei

2016-01-01

Parabolized stability equations (PSE) are used in a variational approach to study the optimal, non-modal disturbance growth in a Mach 3 at plate boundary layer and a Mach 6 circular cone boundary layer. As noted in previous works, the optimal initial disturbances correspond to steady counter-rotating streamwise vortices, which subsequently lead to the formation of streamwise-elongated structures, i.e., streaks, via a lift-up effect. The nonlinear evolution of the linearly optimal stationary perturbations is computed using the nonlinear plane-marching PSE for stationary perturbations. A fully implicit marching technique is used to facilitate the computation of nonlinear streaks with large amplitudes. To assess the effect of the finite-amplitude streaks on transition, the linear form of plane- marching PSE is used to investigate the instability of the boundary layer flow modified by spanwise periodic streaks. The onset of bypass transition is estimated by using an N- factor criterion based on the amplification of the streak instabilities. Results show that, for both flow configurations of interest, streaks of sufficiently large amplitude can lead to significantly earlier onset of transition than that in an unperturbed boundary layer without any streaks.

An Optimal Image-Based Method for Identification of Acoustic Emission (AE) Sources in Plate-Like Structures Using a Lead Zirconium Titanate (PZT) Sensor Array

PubMed Central

Zhou, Li

2018-01-01

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method. PMID:29466310

Dependency of Optimal Parameters of the IRIS Template on Image Quality and Border Detection Error

NASA Astrophysics Data System (ADS)

Matveev, I. A.; Novik, V. P.

2017-05-01

Generation of a template containing spatial-frequency features of iris is an important stage of identification. The template is obtained by a wavelet transform in an image region specified by iris borders. One of the main characteristics of the identification system is the value of recognition error, equal error rate (EER) is used as criterion here. The optimal values (in sense of minimizing the EER) of wavelet transform parameters depend on many factors: image quality, sharpness, size of characteristic objects, etc. It is hard to isolate these factors and their influences. The work presents an attempt to study an influence of following factors to EER: iris segmentation precision, defocus level, noise level. Several public domain iris image databases were involved in experiments. The images were subjected to modelled distortions of said types. The dependencies of wavelet parameter and EER values from the distortion levels were build. It is observed that the increase of the segmentation error and image noise leads to the increase of the optimal wavelength of the wavelets, whereas the increase of defocus level leads to decreasing of this value.

Trajectory Optimization Using Adjoint Method and Chebyshev Polynomial Approximation for Minimizing Fuel Consumption During Climb

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Hornby, Gregory; Ishihara, Abe

2013-01-01

This paper describes two methods of trajectory optimization to obtain an optimal trajectory of minimum-fuel- to-climb for an aircraft. The first method is based on the adjoint method, and the second method is based on a direct trajectory optimization method using a Chebyshev polynomial approximation and cubic spine approximation. The approximate optimal trajectory will be compared with the adjoint-based optimal trajectory which is considered as the true optimal solution of the trajectory optimization problem. The adjoint-based optimization problem leads to a singular optimal control solution which results in a bang-singular-bang optimal control.

Hit to lead optimization of pyrazolo[1,5-a]pyrimidines as B-Raf kinase inhibitors.

PubMed

Gopalsamy, Ariamala; Ciszewski, Greg; Shi, Mengxiao; Berger, Dan; Hu, Yongbo; Lee, Frederick; Feldberg, Larry; Frommer, Eileen; Kim, Steven; Collins, Karen; Wojciechowicz, Donald; Mallon, Robert

2009-12-15

Our continued effort towards optimization of the pyrazolo[1,5-a]pyrimidine scaffold as B-Raf kinase inhibitors is described. Structure guided design was utilized to introduce kinase hinge region interacting groups in the 2-position of the scaffold. This strategy led to the identification of lead compound 9 with enhanced enzyme and cellular potency, while maintaining good selectivity over a number of kinases.

The Weighted-Average Lagged Ensemble.

PubMed

DelSole, T; Trenary, L; Tippett, M K

2017-11-01

A lagged ensemble is an ensemble of forecasts from the same model initialized at different times but verifying at the same time. The skill of a lagged ensemble mean can be improved by assigning weights to different forecasts in such a way as to maximize skill. If the forecasts are bias corrected, then an unbiased weighted lagged ensemble requires the weights to sum to one. Such a scheme is called a weighted-average lagged ensemble. In the limit of uncorrelated errors, the optimal weights are positive and decay monotonically with lead time, so that the least skillful forecasts have the least weight. In more realistic applications, the optimal weights do not always behave this way. This paper presents a series of analytic examples designed to illuminate conditions under which the weights of an optimal weighted-average lagged ensemble become negative or depend nonmonotonically on lead time. It is shown that negative weights are most likely to occur when the errors grow rapidly and are highly correlated across lead time. The weights are most likely to behave nonmonotonically when the mean square error is approximately constant over the range forecasts included in the lagged ensemble. An extreme example of the latter behavior is presented in which the optimal weights vanish everywhere except at the shortest and longest lead times.

Streamlined approach to high-quality purification and identification of compound series using high-resolution MS and NMR.

PubMed

Mühlebach, Anneke; Adam, Joachim; Schön, Uwe

2011-11-01

Automated medicinal chemistry (parallel chemistry) has become an integral part of the drug-discovery process in almost every large pharmaceutical company. Parallel array synthesis of individual organic compounds has been used extensively to generate diverse structural libraries to support different phases of the drug-discovery process, such as hit-to-lead, lead finding, or lead optimization. In order to guarantee effective project support, efficiency in the production of compound libraries has been maximized. As a consequence, also throughput in chromatographic purification and analysis has been adapted. As a recent trend, more laboratories are preparing smaller, yet more focused libraries with even increasing demands towards quality, i.e. optimal purity and unambiguous confirmation of identity. This paper presents an automated approach how to combine effective purification and structural conformation of a lead optimization library created by microwave-assisted organic synthesis. The results of complementary analytical techniques such as UHPLC-HRMS and NMR are not only regarded but even merged for fast and easy decision making, providing optimal quality of compound stock. In comparison with the previous procedures, throughput times are at least four times faster, while compound consumption could be decreased more than threefold. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal perturbations of a finite-width mixing layer near the trailing edge

NASA Astrophysics Data System (ADS)

Gumbart, James C.; Rabchuk, James

2002-03-01

The trailing edge of a surface separating two fluid flows can act as an efficient receptor for acoustic or other disturbances. The incident wave energy is converted by a linear mechanism into incipient flow instabilities which lead further downstream to the transition to turbulence. Understanding this process is essential for analyzing feedback loops and other resonances which can cause unwanted structural vibrations in the surface material or directed acoustic emissions from the mixing region. Previously, the modes of instability in a finite-width mixing layer near the trailing edge were studied as a function of frequency by assuming that vorticity was continually being introduced into the flow at the trailing edge by the forcing field. It was found that the initial amplitude of the growing instability mode was a sharply decreasing function of forcing frequency, and that the initial amplitude was a minimum for the frequency at which the rate of instability growth was a maximum^1. This result has led to a study of the adjoint equation for the perturbation stream function, whose eigensolutions are known to be associated with the optimal perturbation field for the frequency of forcing leading to the greatest instability growth downstream. We have obtained these solutions for a piecewise linear velocity profile near the trailing edge using group-theoretic techniques and have shown that they are indeed optimal. We have also analyzed the nature of the physical forcing field that might produce these optimal perturbations. ^1 Rabchuk, J.A., July 2000, Physics of Fluids.

DEMONSTRATION BULLETIN: COGNIS TERRAMET LEAD EXTRACTION PROCESS - TWIN CITIES ARMY AMMUNITION PLANT - COGNIS, INC.

EPA Science Inventory

The TERRAMET® soil remediation system leaches and recovers lead (including metallic lead, and lead salts and oxides), and other metals from contaminated soil, sludge, or sediment. The system uses a proprietary aqueous leachant that is optimized through treatability tests for the ...

Biosorption of Pb(II) Ions by Klebsiella sp. 3S1 Isolated from a Wastewater Treatment Plant: Kinetics and Mechanisms Studies

PubMed Central

Muñoz, Antonio Jesús; Espínola, Francisco; Moya, Manuel; Ruiz, Encarnación

2015-01-01

Lead biosorption by Klebsiella sp. 3S1 isolated from a wastewater treatment plant was investigated through a Rotatable Central Composite Experimental Design. The optimisation study indicated the following optimal values of operating variables: 0.4 g/L of biosorbent dosage, pH 5, and 34°C. According to the results of the kinetic studies, the biosorption process can be described by a two-step process, one rapid, almost instantaneous, and one slower, both contributing significantly to the overall biosorption; the model that best fits the experimental results was pseudo-second order. The equilibrium studies showed a maximum lead uptake value of 140.19 mg/g according to the Langmuir model. The mechanism study revealed that lead ions were bioaccumulated into the cytoplasm and adsorbed on the cell surface. The bacterium  Klebsiella sp. 3S1 has a good potential in the bioremoval of lead in an inexpensive and effective process. PMID:26504824

Optimization of forest wildlife objectives

Treesearch

John Hof; Robert Haight

2007-01-01

This chapter presents an overview of methods for optimizing wildlife-related objectives. These objectives hinge on landscape pattern, so we refer to these methods as "spatial optimization." It is currently possible to directly capture deterministic characterizations of the most basic spatial relationships: proximity relationships (including those that lead to...

Reliability and paste process optimization of eutectic and lead-free for mixed packaging

NASA Technical Reports Server (NTRS)

Ramkumar, S. M.; Ganeshan, V.; Thenalur, K.; Ghaffarian, R.

2002-01-01

This paper reports the results of an experiment that utilized the JPL's area array consortium test vehicle design, containing a myriad of mixed technology components with an OSP finish. The details of the reliability study are presented in this paper.

An algorithmic programming approach for back pain symptoms in failed back surgery syndrome using spinal cord stimulation with a multicolumn surgically implanted epidural lead: a multicenter international prospective study.

PubMed

Rigoard, Philippe; Jacques, Line; Delmotte, Alexandre; Poon, Katherine; Munson, Russell; Monlezun, Olivier; Roulaud, Manuel; Prevost, Audrey; Guetarni, Farid; Bataille, Benoit; Kumar, Krishna

2015-03-01

Many studies have demonstrated the efficacy and the medical/economic value of epidural spinal cord stimulation for the treatment of "failed back surgery syndrome" (FBSS). However, the back pain component of FBSS has been recalcitrant. Recent clinical trials have suggested that multicolumn surgically implanted leads combined with enhanced programming capabilities in the newer implantable pulse generators demonstrate the ability to treat the back pain component of FBSS. The objective of our present international multicentre study is to prospectively evaluate these findings in a larger population. We conducted a prospective, nonrandomized, observational study on 76 patients with refractory FBSS, consecutively implanted with multicolumn spinal cord stimulation (SCS) between 2008 and 2011 in three neurosurgical pain management centers (Poitiers, France; Montréal, Canada; and Regina, Canada). The primary objective of this study was to prospectively analyze the effect of multicolumn lead programming on paresthesia coverage for the back pain region in these patients. The secondary objective was to assess the analgesic efficacy of this technique on the global and back pain components. Paresthesia could be induced in the lower extremities in the majority of patients with at least one of the configurations tested. Bilateral low back paresthesia was induced in 53.5% of patients, while unilateral low back paresthesia was induced in 78.9% of patients. Multicolumn configurations were statistically more effective than monocolumn configurations for all anatomic regions studied. At 6 months, 75.4% of patients receiving multicolumn stimulation (n = 57) obtained at least a 30% improvement of the back pain VAS score, while 42.1% of patients obtained at least a 50% improvement of the back pain VAS score. This study confirms the hypothesis that multicolumn SCS should be considered as an important tool in the treatment of radicular and axial pain in FBSS patients. The efficacy of this modality is based on a rigorous patient selection process, access to new generation lead technologies, but most importantly an algorithmic programming approach for optimal stimulation and electrical field shaping. With over 40 million potential programming combinations associated with 16 contact leads to achieve paresthesia coverage, optimal stimulation is often missed as either the patient or the clinician become exhausted or overwhelmed during the course of therapy programming and optimization session. © 2014 World Institute of Pain.

Lead Optimization Studies on FimH Antagonists: Discovery of Potent and Orally Bioavailable Ortho-substituted Biphenyl Mannosides

PubMed Central

Han, Zhenfu; Pinkner, Jerome S.; Ford, Bradley; Chorell, Erik; Crowley, Jan M.; Cusumano, Corinne K.; Campbell, Scott; Henderson, Jeffrey P.; Hultgren, Scott J.; Janetka, James W.

2012-01-01

Herein, we describe the X-ray structure-based design and optimization of biaryl mannoside FimH inhibitors. Diverse modifications to the biaryl ring to improve drug-like physical and pharmacokinetic properties of mannosides were assessed for FimH binding affinity based on their effects on hemagglutination and biofilm formation along with direct FimH binding assays. Substitution on the mannoside phenyl ring ortho to the glycosidic bond results in large potency enhancements of several-fold higher than corresponding unsubstituted matched pairs and can be rationalized from increased hydrophobic interactions with the FimH hydrophobic ridge (Ile13) or “tyrosine gate” (Tyr137 and Tyr48) also lined by Ile52. The lead mannosides have increased metabolic stability and oral bioavailability as determined from in vitro PAMPA predictive model of cellular permeability and in vivo pharmacokinetic studies in mice, thereby representing advanced preclinical candidates with promising potential as novel therapeutics for the clinical treatment and prevention of recurring urinary tract infections. PMID:22449031

Increasing Optimism Protects Against Pain-Induced Impairment in Task-Shifting Performance.

PubMed

Boselie, Jantine J L M; Vancleef, Linda M G; Peters, Madelon L

2017-04-01

Persistent pain can lead to difficulties in executive task performance. Three core executive functions that are often postulated are inhibition, updating, and shifting. Optimism, the tendency to expect that good things happen in the future, has been shown to protect against pain-induced performance deterioration in executive function updating. This study tested whether this protective effect of a temporary optimistic state by means of a writing and visualization exercise extended to executive function shifting. A 2 (optimism: optimism vs no optimism) × 2 (pain: pain vs no pain) mixed factorial design was conducted. Participants (N = 61) completed a shifting task once with and once without concurrent painful heat stimulation after an optimism or neutral manipulation. Results showed that shifting performance was impaired when experimental heat pain was applied during task execution, and that optimism counteracted pain-induced deterioration in task-shifting performance. Experimentally-induced heat pain impairs shifting task performance and manipulated optimism or induced optimism counteracted this pain-induced performance deterioration. Identifying psychological factors that may diminish the negative effect of persistent pain on the ability to function in daily life is imperative. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Optimism and proactive coping in relation to burnout among nurses.

PubMed

Chang, Yuhsuan; Chan, Hsin-Ju

2015-04-01

The study investigated the three symptoms of burnout among hospital nurses and examined the buffering effects of optimism and proactive coping in relation to burnout. Nursing is a profession that can easily lead to burnout. Burnout has been one of the most investigated work outcomes in current research. Previous research has largely ignored the positive influence of individuals on job outcomes and has not tested a constructive framework that might facilitate interventions to prevent burnout. A cross-sectional survey of 314 staff nurses in general hospitals in Taiwan. Participants completed a set of questionnaires with demographic information. The findings suggested that higher levels of proactive coping behaviours and optimism were associated with lower levels of burnout. Optimism was found to have the strongest relationship with the decreased personal accomplishment of burnout. The findings of this study confirmed the importance of optimism and proactive coping in prevention of symptoms of burnout. The results of this study provided important recommendations regarding stress management interventions for health-care managers, nurses, psychologists and human resource staff in the reduction of burnout to promote mental health in an organisation. © 2013 John Wiley & Sons Ltd.

Development of a Standardized Cranial Phantom for Training and Optimization of Functional Stereotactic Operations.

PubMed

Krüger, Marie T; Coenen, Volker A; Egger, Karl; Shah, Mukesch; Reinacher, Peter C

2018-06-13

In recent years, simulations based on phantom models have become increasingly popular in the medical field. In the field of functional and stereotactic neurosurgery, a cranial phantom would be useful to train operative techniques, such as stereo-electroencephalography (SEEG), to establish new methods as well as to develop and modify radiological techniques. In this study, we describe the construction of a cranial phantom and show examples for it in stereotactic and functional neurosurgery and its applicability with different radiological modalities. We prepared a plaster skull filled with agar. A complete operation for deep brain stimulation (DBS) was simulated using directional leads. Moreover, a complete SEEG operation including planning, implantation of the electrodes, and intraoperative and postoperative imaging was simulated. An optimally customized cranial phantom is filled with 10% agar. At 7°C, it can be stored for approximately 4 months. A DBS and an SEEG procedure could be realistically simulated. Lead artifacts can be studied in CT, X-ray, rotational fluoroscopy, and MRI. This cranial phantom is a simple and effective model to simulate functional and stereotactic neurosurgical operations. This might be useful for teaching and training of neurosurgeons, establishing operations in a new center and for optimization of radiological examinations. © 2018 S. Karger AG, Basel.

A Hybrid Interval-Robust Optimization Model for Water Quality Management.

PubMed

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-05-01

In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

Optimization of microphysics in the Unified Model, using the Micro-genetic algorithm.

NASA Astrophysics Data System (ADS)

Jang, J.; Lee, Y.; Lee, H.; Lee, J.; Joo, S.

2016-12-01

This study focuses on parameter optimization of microphysics in the Unified Model (UM) using the Micro-genetic algorithm (Micro-GA). We need the optimization of microphysics in UM. Because, Microphysics in the Numerical Weather Prediction (NWP) model is important to Quantitative Precipitation Forecasting (QPF). The Micro-GA searches for optimal parameters on the basis of fitness function. The five parameters are chosen. The target parameters include x1, x2 related to raindrop size distribution, Cloud-rain correlation coefficient, Surface droplet number and Droplet taper height. The fitness function is based on the skill score that is BIAS and Critical Successive Index (CSI). An interface between UM and Micro-GA is developed and applied to three precipitation cases in Korea. The cases are (ⅰ) heavy rainfall in the Southern area because of typhoon NAKRI, (ⅱ) heavy rainfall in the Youngdong area, and (ⅲ) heavy rainfall in the Seoul metropolitan area. When the optimized result is compared to the control result (using the UM default value, CNTL), the optimized result leads to improvements in precipitation forecast, especially for heavy rainfall of the late forecast time. Also, we analyze the skill score of precipitation forecasts in terms of various thresholds of CNTL, Optimized result, and experiments on each optimized parameter for five parameters. Generally, the improvement is maximized when the five optimized parameters are used simultaneously. Therefore, this study demonstrates the ability to improve Korean precipitation forecasts by optimizing microphysics in UM.

Finding Optimal Gains In Linear-Quadratic Control Problems

NASA Technical Reports Server (NTRS)

Milman, Mark H.; Scheid, Robert E., Jr.

1990-01-01

Analytical method based on Volterra factorization leads to new approximations for optimal control gains in finite-time linear-quadratic control problem of system having infinite number of dimensions. Circumvents need to analyze and solve Riccati equations and provides more transparent connection between dynamics of system and optimal gain.

Fiber ring resonator based opto-electronic oscillator: phase noise optimisation and thermal stability study

NASA Astrophysics Data System (ADS)

Saleh, K.; Bouchier, A.; Merrer, P. H.; Llopis, O.; Cibiel, G.

2011-03-01

In the microwave domain and among many other advantages, optics represents an elegant solution to increase the quality Q factor in a system. Different types of optical resonators lead to Q factors above 109, and these resonators can be used as an alternative to optical delay lines to set up the frequency in optoelectronic oscillators (OEO). However, microwave-optics is also a complex field, and if the use of optical resonators in high spectral purity frequency generation systems like OEO has been already demonstrated, many aspects of these OEOs are still incompletely understood, especially the contribution to the oscillator phase noise of the different optical and microwave elements used in the oscillator system. In order to improve the phase noise of a fiber ring resonator based OEO, this oscillator has been theoretically studied in term of white frequency noise. In this paper, we present a theoretical study that has lead us to optimize a fiber ring resonator and the experimental phase noise results obtained for an OEO based on an optimized optical resonator. The OEO thermal stability is also investigated in this paper.

A study of some economic factors relating to the development and implementation of a satellite power system

NASA Technical Reports Server (NTRS)

1978-01-01

Areas are examined relating to the design, development and implementation of a satellite power system (SPS): an analysis of the effect of energy R&D programs in general and SPS in particular on optimal fossil fuel consumption patterns, a study of alternative uses of SPS technologies, and a study of the electric power market penetration potential for SPS. It is shown that a credible program of R&D on long-range energy alternatives leads to lower optimal prices for fossil fuels, resulting in large short-term benefits accruing to the specific program elements. Several alternative uses of SPS technologies were identified; however the markets for these technologies are generally quite diffuse and difficult to assess. The notable exception is solar array technology which has, potentially, a very large non-SPS market. It is shown that the market for SPS units derives from two components of demand: the demand created by growth in the electrical energy demand which leads to an increased demand for baseload generating capacity, and a demand created by the need to replace retiring capacity.

Study on the effect of the runner design parameters on 50 MW Francis hydro turbine model performance

NASA Astrophysics Data System (ADS)

Shrestha, Ujjwal; Chen, Zhenmu; Choi, Young-Do

2018-06-01

Francis hydro turbine is the dominant turbine in the hydropower generation. Francis turbine has been installed at most 60% of the hydropower in the world at present. Although the basic design for the Francis turbine has various method regarding the specific speed. The runner meridional shape varies with different specific speed. Despite having, the basic design but there is still some room for the optimization. In this study 50 MW, Francis hydro turbine with specific speed 323 m-kW was designed and considered for the optimization. The various parameter as runner meridional shape (curve profile of hub, shroud, leading edge and trailing edge), blade angle and its distribution, blade thickness, runner inlet width that has been considered for the optimization of the runner for enhancement of the performance.

Architectured Materials to Improve the Reliability of Power Electronics Modules: Substrate and Lead-Free Solder

NASA Astrophysics Data System (ADS)

Kaabi, Abderrahmen; Bienvenu, Yves; Ryckelynck, David; Pierre, Bertrand

2014-03-01

Power electronics modules (>100 A, >500 V) are essential components for the development of electrical and hybrid vehicles. These modules are formed from silicon chips (transistors and diodes) assembled on copper substrates by soldering. Owing to the fact that the assembly is heterogeneous, and because of thermal gradients, shear stresses are generated in the solders and cause premature damage to such electronics modules. This work focuses on architectured materials for the substrate and on lead-free solders to reduce the mechanical effects of differential expansion, improve the reliability of the assembly, and achieve a suitable operating temperature (<175°C). These materials are composites whose thermomechanical properties have been optimized by numerical simulation and validated experimentally. The substrates have good thermal conductivity (>280 W m-1 K-1) and a macroscopic coefficient of thermal expansion intermediate between those of Cu and Si, as well as limited structural evolution in service conditions. An approach combining design, optimization, and manufacturing of new materials has been followed in this study, leading to improved thermal cycling behavior of the component.

A novel 3,4-dihydropyrimidin-2(1H)-one: HIV-1 replication inhibitors with improved metabolic stability.

PubMed

Kim, Junwon; Ok, Taedong; Park, Changmin; So, Wonyoung; Jo, Mina; Kim, Youngmi; Seo, Minjung; Lee, Doohyun; Jo, Suyeon; Ko, Yoonae; Choi, Inhee; Park, Youngsam; Yoon, Jaewan; Ju, Moon Kyeong; Ahn, JiYe; Kim, Junghwan; Han, Sung-Jun; Kim, Tae-Hee; Cechetto, Jonathan; Nam, Jiyoun; Liuzzi, Michel; Sommer, Peter; No, Zaesung

2012-04-01

Following the previous SAR of a novel dihydropyrimidinone scaffold as HIV-1 replication inhibitors a detailed study directed towards optimizing the metabolic stability of the ester functional group in the dihydropyrimidinone (DHPM) scaffold is described. Replacement of the ester moiety by thiazole ring significantly improved the metabolic stability while retaining antiviral activity against HIV-1 replication. These novel and potent DHPMs with bioisosteres could serve as advanced leads for further optimization. Copyright © 2012 Elsevier Ltd. All rights reserved.

Digital adaptive flight controller development

NASA Technical Reports Server (NTRS)

Kaufman, H.; Alag, G.; Berry, P.; Kotob, S.

1974-01-01

A design study of adaptive control logic suitable for implementation in modern airborne digital flight computers was conducted. Two designs are described for an example aircraft. Each of these designs uses a weighted least squares procedure to identify parameters defining the dynamics of the aircraft. The two designs differ in the way in which control law parameters are determined. One uses the solution of an optimal linear regulator problem to determine these parameters while the other uses a procedure called single stage optimization. Extensive simulation results and analysis leading to the designs are presented.

Optimization of Water Management of Cranberry Fields under Current and Future Climate Conditions

NASA Astrophysics Data System (ADS)

Létourneau, G.; Gumiere, S.; Mailhot, E.; Rousseau, A. N.

2016-12-01

In North America, cranberry production is on the rise. Since 2005, land area dedicated to cranberry doubled, principally in Canada. Recent studies have shown that sub-irrigation could lead to improvements in yield, water use efficiency and pumping energy requirements compared to conventional sprinkler irrigation. However, the experimental determination of the optimal water table level of each production site may be expensiveand time-consuming. The primary objective of this study is to optimize the water table level as a function of typical soil properties, and climatic conditions observed in major production areas using a numerical modeling approach. The second objective is to evaluate the impacts of projected climatic conditions on water management of cranberry fields. To that end, cranberry-specific management operations such as harvest flooding, rapid drainage following heavy rainfall, or hydric stress management during dry weather conditions were simulated with the HYDRUS 2D software. Results have shown that maintaining the water table approximately at 60 cm provides optimal results for most of the studied soils. However, under certain extreme climatic conditions, the drainage system design may not allow maintaining optimal hydric conditions for cranberry growth. The long-term benefit of this study has potential to advance the design of drainage/sub-irrigation systems.

Comparison of linear and nonlinear programming approaches for "worst case dose" and "minmax" robust optimization of intensity-modulated proton therapy dose distributions.

PubMed

Zaghian, Maryam; Cao, Wenhua; Liu, Wei; Kardar, Laleh; Randeniya, Sharmalee; Mohan, Radhe; Lim, Gino

2017-03-01

Robust optimization of intensity-modulated proton therapy (IMPT) takes uncertainties into account during spot weight optimization and leads to dose distributions that are resilient to uncertainties. Previous studies demonstrated benefits of linear programming (LP) for IMPT in terms of delivery efficiency by considerably reducing the number of spots required for the same quality of plans. However, a reduction in the number of spots may lead to loss of robustness. The purpose of this study was to evaluate and compare the performance in terms of plan quality and robustness of two robust optimization approaches using LP and nonlinear programming (NLP) models. The so-called "worst case dose" and "minmax" robust optimization approaches and conventional planning target volume (PTV)-based optimization approach were applied to designing IMPT plans for five patients: two with prostate cancer, one with skull-based cancer, and two with head and neck cancer. For each approach, both LP and NLP models were used. Thus, for each case, six sets of IMPT plans were generated and assessed: LP-PTV-based, NLP-PTV-based, LP-worst case dose, NLP-worst case dose, LP-minmax, and NLP-minmax. The four robust optimization methods behaved differently from patient to patient, and no method emerged as superior to the others in terms of nominal plan quality and robustness against uncertainties. The plans generated using LP-based robust optimization were more robust regarding patient setup and range uncertainties than were those generated using NLP-based robust optimization for the prostate cancer patients. However, the robustness of plans generated using NLP-based methods was superior for the skull-based and head and neck cancer patients. Overall, LP-based methods were suitable for the less challenging cancer cases in which all uncertainty scenarios were able to satisfy tight dose constraints, while NLP performed better in more difficult cases in which most uncertainty scenarios were hard to meet tight dose limits. For robust optimization, the worst case dose approach was less sensitive to uncertainties than was the minmax approach for the prostate and skull-based cancer patients, whereas the minmax approach was superior for the head and neck cancer patients. The robustness of the IMPT plans was remarkably better after robust optimization than after PTV-based optimization, and the NLP-PTV-based optimization outperformed the LP-PTV-based optimization regarding robustness of clinical target volume coverage. In addition, plans generated using LP-based methods had notably fewer scanning spots than did those generated using NLP-based methods. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Elevated depressive symptoms enhance reflexive but not reflective auditory category learning.

PubMed

Maddox, W Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G

2014-09-01

In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Elevated Depressive Symptoms Enhance Reflexive but not Reflective Auditory Category Learning

PubMed Central

Maddox, W. Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G.

2014-01-01

In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. PMID:25041936

Aircraft Trajectory Optimization and Contrails Avoidance in the Presence of Winds

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Chen, Neil Y.

2010-01-01

There are indications that persistent contrails can lead to adverse climate change, although the complete effect on climate forcing is still uncertain. A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the regions of airspace prone to persistent contrails formation. The optimal trajectories are developed by solving a non-linear optimal control problem with path constraints. The regions of airspace favorable to persistent contrails formation are modeled as penalty areas that aircraft should avoid and are adjustable. The tradeoff between persistent contrails formation and additional fuel consumption is investigated, with and without altitude optimization, for 12 city-pairs in the continental United States. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a two percent increase in total fuel consumption can reduce the total travel times through contrail regions by more than six times. Allowing further increase in fuel consumption does not seem to result in proportionate decrease in contrail travel times.

Efficient and lightweight current leads

NASA Astrophysics Data System (ADS)

Bromberg, L.; Dietz, A. J.; Michael, P. C.; Gold, C.; Cheadle, M.

2014-01-01

Current leads generate substantial cryogenic heat loads in short length High Temperature Superconductor (HTS) distribution systems. Thermal conduction, as well as Joule losses (I2R) along the current leads, comprises the largest cryogenic loads for short distribution systems. Current leads with two temperature stages have been designed, constructed and tested, with the goal of minimizing the electrical power consumption, and to provide thermal margin for the cable. We present the design of a two-stage current lead system, operating at 140 K and 55 K. This design is very attractive when implemented with a turbo-Brayton cycle refrigerator (two-stage), with substantial power and weight reduction. A heat exchanger is used at each temperature station, with conduction-cooled stages in-between. Compact, efficient heat exchangers are challenging, because of the gaseous coolant. Design, optimization and performance of the heat exchangers used for the current leads will be presented. We have made extensive use of CFD models for optimizing hydraulic and thermal performance of the heat exchangers. The methodology and the results of the optimization process will be discussed. The use of demountable connections between the cable and the terminations allows for ease of assembly, but require means of aggressively cooling the region of the joint. We will also discuss the cooling of the joint. We have fabricated a 7 m, 5 kA cable with second generation HTS tapes. The performance of the system will be described.

Encoded library technology as a source of hits for the discovery and lead optimization of a potent and selective class of bactericidal direct inhibitors of Mycobacterium tuberculosis InhA.

PubMed

Encinas, Lourdes; O'Keefe, Heather; Neu, Margarete; Remuiñán, Modesto J; Patel, Amish M; Guardia, Ana; Davie, Christopher P; Pérez-Macías, Natalia; Yang, Hongfang; Convery, Maire A; Messer, Jeff A; Pérez-Herrán, Esther; Centrella, Paolo A; Alvarez-Gómez, Daniel; Clark, Matthew A; Huss, Sophie; O'Donovan, Gary K; Ortega-Muro, Fátima; McDowell, William; Castañeda, Pablo; Arico-Muendel, Christopher C; Pajk, Stane; Rullás, Joaquín; Angulo-Barturen, Iñigo; Alvarez-Ruíz, Emilio; Mendoza-Losana, Alfonso; Ballell Pages, Lluís; Castro-Pichel, Julia; Evindar, Ghotas

2014-02-27

Tuberculosis (TB) is one of the world's oldest and deadliest diseases, killing a person every 20 s. InhA, the enoyl-ACP reductase from Mycobacterium tuberculosis, is the target of the frontline antitubercular drug isoniazid (INH). Compounds that directly target InhA and do not require activation by mycobacterial catalase peroxidase KatG are promising candidates for treating infections caused by INH resistant strains. The application of the encoded library technology (ELT) to the discovery of direct InhA inhibitors yielded compound 7 endowed with good enzymatic potency but with low antitubercular potency. This work reports the hit identification, the selected strategy for potency optimization, the structure-activity relationships of a hundred analogues synthesized, and the results of the in vivo efficacy studies performed with the lead compound 65.

Selection and optimization of hits from a high-throughput phenotypic screen against Trypanosoma cruzi.

PubMed

Keenan, Martine; Alexander, Paul W; Chaplin, Jason H; Abbott, Michael J; Diao, Hugo; Wang, Zhisen; Best, Wayne M; Perez, Catherine J; Cornwall, Scott M J; Keatley, Sarah K; Thompson, R C Andrew; Charman, Susan A; White, Karen L; Ryan, Eileen; Chen, Gong; Ioset, Jean-Robert; von Geldern, Thomas W; Chatelain, Eric

2013-10-01

Inhibitors of Trypanosoma cruzi with novel mechanisms of action are urgently required to diversify the current clinical and preclinical pipelines. Increasing the number and diversity of hits available for assessment at the beginning of the discovery process will help to achieve this aim. We report the evaluation of multiple hits generated from a high-throughput screen to identify inhibitors of T. cruzi and from these studies the discovery of two novel series currently in lead optimization. Lead compounds from these series potently and selectively inhibit growth of T. cruzi in vitro and the most advanced compound is orally active in a subchronic mouse model of T. cruzi infection. High-throughput screening of novel compound collections has an important role to play in diversifying the trypanosomatid drug discovery portfolio. A new T. cruzi inhibitor series with good drug-like properties and promising in vivo efficacy has been identified through this process.

Optimal Demand Execution Strategy for the Defense Logistics Agency

DTIC Science & Technology

2014-12-01

PLT Production Lead-Time PTO Paid Time Off FSC Federal Stock /Supply Class NIIN National Item Identification Number S&OP Sales and Operations...new software sets a recommended inventory level that balances the risk of stock out with holding cost expenses and buys to the optimal level instead...when a PR should be generated. A Time Phased Inventory Plan (TPIP) is computed daily that accounts for the lead-time and current stock on the shelf

Aspirational characteristics for effective leadership of improvement teams.

PubMed

Donnelly, Lane F

2017-01-01

Working on quality improvement has become an innate part of managing a pediatric radiology service. To help radiologists effectively lead improvement teams, eight aspirational characteristics are discussed. These are: 1) Be a good listener, 2) Effectively communicate around an accountability cycle, 3) Stress simplicity: Prioritization and pace, 4) Expend energy to optimize people development, 5) Lead with optimism, 6) Create a culture of wellness and sustainability, 7) Have a progressive attitude toward failure and 8) Project humility over arrogance.

Laser-induced fluorescence detection of lead atoms in a laser-induced plasma: An experimental analytical optimization study

NASA Astrophysics Data System (ADS)

Laville, Stéphane; Goueguel, Christian; Loudyi, Hakim; Vidal, François; Chaker, Mohamed; Sabsabi, Mohamad

2009-04-01

The combination of the laser-induced breakdown spectroscopy (LIBS) and laser-induced fluorescence (LIF) techniques was investigated to improve the limit of detection (LoD) of trace elements in solid matrices. The influence of the main experimental parameters on the LIF signal, namely the ablation fluence, the excitation energy, and the inter-pulse delay, was studied experimentally and a discussion of the results was presented. For illustrative purpose we considered detection of lead in brass samples. The plasma was produced by a Q-switched Nd:YAG laser and then re-excited by a nanosecond Optical Parametric Oscillator (OPO) laser. The experiments were performed in air at atmospheric pressure. We found out that the optimal conditions were obtained for our experimental set-up using relatively weak ablation fluence of 2-3 J/cm 2 and an inter-pulse delay of about 5-10 μs. Also, a few tens of microjoules was typically required to maximize the LIF signal. Using the LIBS-LIFS technique, a single-shot LoD for lead of about 1.5 part per million (ppm) was obtained while a value of 0.2 ppm was obtained after accumulating over 100 shots. These values represent an improvement of about two orders of magnitude with respect to LIBS.

Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.

PubMed

Therrien, Eric; Weill, Nathanael; Tomberg, Anna; Corbeil, Christopher R; Lee, Devin; Moitessier, Nicolas

2014-11-24

The use of predictive computational methods in the drug discovery process is in a state of continual growth. Over the last two decades, an increasingly large number of docking tools have been developed to identify hits or optimize lead molecules through in-silico screening of chemical libraries to proteins. In recent years, the focus has been on implementing protein flexibility and water molecules. Our efforts led to the development of Fitted first reported in 2007 and further developed since then. In this study, we wished to evaluate the impact of protein flexibility and occurrence of water molecules on the accuracy of the Fitted docking program to discriminate active compounds from inactive compounds in virtual screening (VS) campaigns. For this purpose, a total of 171 proteins cocrystallized with small molecules representing 40 unique enzymes and receptors as well as sets of known ligands and decoys were selected from the Protein Data Bank (PDB) and the Directory of Useful Decoys (DUD), respectively. This study revealed that implementing displaceable crystallographic or computationally placed particle water molecules and protein flexibility can improve the enrichment in active compounds. In addition, an informed decision based on library diversity or research objectives (hit discovery vs lead optimization) on which implementation to use may lead to significant improvements.

Model-based optimization of near-field binary-pixelated beam shapers

DOE PAGES

Dorrer, C.; Hassett, J.

2017-01-23

The optimization of components that rely on spatially dithered distributions of transparent or opaque pixels and an imaging system with far-field filtering for transmission control is demonstrated. The binary-pixel distribution can be iteratively optimized to lower an error function that takes into account the design transmission and the characteristics of the required far-field filter. Simulations using a design transmission chosen in the context of high-energy lasers show that the beam-fluence modulation at an image plane can be reduced by a factor of 2, leading to performance similar to using a non-optimized spatial-dithering algorithm with pixels of size reduced by amore » factor of 2 without the additional fabrication complexity or cost. The optimization process preserves the pixel distribution statistical properties. Analysis shows that the optimized pixel distribution starting from a high-noise distribution defined by a random-draw algorithm should be more resilient to fabrication errors than the optimized pixel distributions starting from a low-noise, error-diffusion algorithm, while leading to similar beamshaping performance. Furthermore, this is confirmed by experimental results obtained with various pixel distributions and induced fabrication errors.« less

Computational modeling in the optimization of corrosion control to reduce lead in drinking water

EPA Science Inventory

An international “proof-of-concept” research project (UK, US, CA) will present its findings during this presentation. An established computational modeling system developed in the UK is being calibrated and validated in U.S. and Canadian case studies. It predicts LCR survey resul...

Optimizing Visually-Assisted Listening Comprehension

ERIC Educational Resources Information Center

Kashani, Ahmad Sabouri; Sajjadi, Samad; Sohrabi, Mohammad Reza; Younespour, Shima

2011-01-01

The fact that visual aids such as pictures or graphs can lead to greater comprehension by language learners has been well established. Nonetheless, the order of presenting visuals to listeners is left unattended. This study examined listening comprehension from a strategy of introducing visual information, either prior to or during an audio…

Developing hazelnut tissue culture medium free of ion confounding

USDA-ARS?s Scientific Manuscript database

The general approach for tissue culture medium optimization is to use salts as factors in experimental design and analysis. However, using salts as factors leads to ion confounding, making it difficult to detect the effects of individual ions on particular growth responses. This study focused on tes...

A Study of Flow Theory in the Foreign Language Classroom.

ERIC Educational Resources Information Center

Egbert, Joy

2003-01-01

Focuses on the relationship between flow experiences and language learning. Flow theory suggests that flow experiences can lead to optimal learning. Findings suggest flow does exist in the foreign language classroom and that flow theory offers an interesting and useful framework for conceptualizing and evaluating language learning activities.…

Stabilize lead and cadmium in contaminated soils using hydroxyapatite and potassium chloride.

PubMed

Wang, Li; Li, Yonghua; Li, Hairong; Liao, Xiaoyong; Wei, Binggan; Ye, Bixiong; Zhang, Fengying; Yang, Linsheng; Wang, Wuyi; Krafft, Thomas

2014-12-01

Combination of hydroxyapatite (HAP) and potassium chloride (KCl) was used to stabilize lead and cadmium in contaminated mining soils. Pot experiments of chilli (Capsicum annuum) and rape (Brassica rapachinensis) were used to evaluate the stabilization efficiency. The results were the following: (1) the optimal combination decreased the leachable lead by 83.3 and 97.27 %, and decreased leachable cadmium by 57.82 and 35.96% for soil HF1 and soil HF2, respectively; (2) the total lead and cadmium concentrations in both plants decreased 69 and 44 %, respectively; (3) The total lead and cadmium concentrations in the edible parts of both vegetables also decreased significantly. This study reflected that potassium chloride can improve the stabilization efficiency of hydroxyapatite, and the combination of hydroxyapatite and potassium chloride can be effectively used to remediate lead and cadmium contaminated mining soil.

Understanding charge transport in lead iodide perovskite thin-film field-effect transistors

PubMed Central

Senanayak, Satyaprasad P.; Yang, Bingyan; Thomas, Tudor H.; Giesbrecht, Nadja; Huang, Wenchao; Gann, Eliot; Nair, Bhaskaran; Goedel, Karl; Guha, Suchi; Moya, Xavier; McNeill, Christopher R.; Docampo, Pablo; Sadhanala, Aditya; Friend, Richard H.; Sirringhaus, Henning

2017-01-01

Fundamental understanding of the charge transport physics of hybrid lead halide perovskite semiconductors is important for advancing their use in high-performance optoelectronics. We use field-effect transistors (FETs) to probe the charge transport mechanism in thin films of methylammonium lead iodide (MAPbI3). We show that through optimization of thin-film microstructure and source-drain contact modifications, it is possible to significantly minimize instability and hysteresis in FET characteristics and demonstrate an electron field-effect mobility (μFET) of 0.5 cm2/Vs at room temperature. Temperature-dependent transport studies revealed a negative coefficient of mobility with three different temperature regimes. On the basis of electrical and spectroscopic studies, we attribute the three different regimes to transport limited by ion migration due to point defects associated with grain boundaries, polarization disorder of the MA+ cations, and thermal vibrations of the lead halide inorganic cages. PMID:28138550

Crash pulse optimization for occupant protection at various impact velocities.

PubMed

Ito, Daisuke; Yokoi, Yusuke; Mizuno, Koji

2015-01-01

Vehicle deceleration has a large influence on occupant kinematic behavior and injury risks in crashes, and the optimization of the vehicle crash pulse that mitigates occupant loadings has been the subject of substantial research. These optimization research efforts focused on only high-velocity impact in regulatory or new car assessment programs though vehicle collisions occur over a wide range of velocities. In this study, the vehicle crash pulse was optimized for various velocities with a genetic algorithm. Vehicle deceleration was optimized in a full-frontal rigid barrier crash with a simple spring-mass model that represents the vehicle-occupant interaction and a Hybrid III 50th percentile male multibody model. To examine whether the vehicle crash pulse optimized at the high impact velocity is useful for reducing occupant loading at all impact velocities less than the optimized velocity, the occupant deceleration was calculated at various velocities for the optimized crash pulse determined at a high speed. The optimized vehicle deceleration-deformation characteristics that are effective for various velocities were investigated with 2 approaches. The optimized vehicle crash pulse at a single impact velocity consists of a high initial impulse followed by zero deceleration and then constant deceleration in the final stage. The vehicle deceleration optimized with the Hybrid III model was comparable to that determined from the spring-mass model. The optimized vehicle deceleration-deformation characteristics determined at a high speed did not necessarily lead to an occupant deceleration reduction at a lower velocity. The maximum occupant deceleration at each velocity was normalized by the maximum deceleration determined in the single impact velocity optimization. The resulting vehicle deceleration-deformation characteristic was a square crash pulse. The objective function was defined as the number of injuries, which was the product of the number of collisions at the velocity and the probability of occupant injury. The optimized vehicle deceleration consisted of a high deceleration in the initial phase, a small deceleration in the middle phase, and then a high deceleration in the final phase. The optimized vehicle crash pulse at a single impact velocity is effective for reducing occupant deceleration in a crash at the specific impact velocity. However, the crash pulse does not necessarily lead to occupant deceleration reduction at a lower velocity. The optimized vehicle deceleration-deformation characteristics, which are effective for all impact velocities, depend on the weighting of the occupant injury measures at each impact velocity.

Investigating absence of optimal photovoltaics response in CZTS solar cell

NASA Astrophysics Data System (ADS)

Kumar, Atul; Thakur, Ajay D.

2018-05-01

Cu2ZnSnS4 (CZTS) has an optimal bandgap of 1.5eV. However contrary to expecting an optimal photovoltaic (PV) behavior is usually not seen from using solution processed approach. Here we try to understand the possible key reasons behind this based on the material attributes. The CZTS film is synthesized using two different solvents of Methoxy-ethanol and DMSO. The effect of air annealing and sulphurisation is studied on these two samples for their phase formation mechanism. XRD, TGA, Raman, UV-Vis, AFM and electrical characterization of the films are performed. A diode behavior is obtained in heterojunction of the CZTS/ZnO. Presence of secondary phases and interfacial recombination leads to poor PV behavior without any PV response.

Remediation of lead from lead electroplating industrial effluent using sago waste.

PubMed

Jeyanthi, G P; Shanthi, G

2007-01-01

Heavy metals are known toxicants, which inflict acute disorders to the living beings. Electroplating industries pose great threat to the environment through heavy load of metals in the wastewater discharged on land and water sources. In the present study, sago processing waste, which is both a waste and a pollutant, was used to adsorb lead ions from lead electroplating industrial effluent. Two types of sago wastes, namely, coarse sago waste and fine sago waste were used to study their adsorption capacity with the batch adsorption and Freundlich adsorption isotherm. The parameters that were considered for batch adsorption were pH (4, 5 and 6), time of contact (1, 2 and 3 hrs), temperature (30, 37 and 45 degrees C) and dosage of the adsorbent (2,4 and 6 g/L). The optimal condition for the effective removal of lead was found to be pH 5, time of contact 3 hrs, temperature 30 degrees C and dosage 4 g/L with coarse sago waste than fine sago waste.

Compound scale-up at the discovery-development interface.

PubMed

Nikitenko, Antonia A

2006-11-01

As a result of an economically challenging environment within the pharmaceutical industry, pharmaceutical companies and their departments must increase productivity and cut costs to stay in line with the market. Discovery-led departments such as the medicinal chemistry and lead optimization groups focus on synthesizing large varieties of compounds in minimal amounts, while the chemical development groups must then deliver a few chosen leads employing an optimized synthesis method and using multi-kilogram quantities of material. A research group at the discovery-development interface has the task of medium-scale synthesis which is important in the lead selection stage. The primary objective of this group is the initial scale-up of promising leads for extensive physicochemical and biological testing. The challenge of the interface group involves overcoming synthetic issues within the rigid, accelerated timelines.

[How I treat: from specialized pharmacology to drug therapy: a plea for an optimal educational program for rational therapeutics, from decision making to drug prescription].

PubMed

Scheen, A J

2000-09-01

Clinical pharmacology and therapeutics are two complementary disciplines which should lead the medical student, through an optimized training, to a rational prescription of drugs, ultimate and important step of the medical approach. Such a learning should occur progressively throughout the medical education, focusing, first, on the therapeutic reasoning ("why?") and, second, on the practical application leading to the prescription ("how?"). The medical student should learn the difficult task of integrating disease, drug and patient, in order to optimize the benefit/risk ratio, while being informed about new concepts such as "Evidence-Based Medicine" and pharmacoeconomics.

Morphing Wings: A Study Using High-Fidelity Aerodynamic Shape Optimization

NASA Astrophysics Data System (ADS)

Curiale, Nathanael J.

With the aviation industry under pressure to reduce fuel consumption, morphing wings have the capacity to improve aircraft performance, thereby making a significant contribution to reversing climate change. Through high-fidelity aerodynamic shape optimization, various forms of morphing wings are assessed for a hypothetical regional-class aircraft. The framework used solves the Reynolds-averaged Navier-Stokes equations and utilizes a gradient-based optimization algorithm. Baseline geometries are developed through multipoint optimization, where the average drag coefficient is minimized over a range of flight conditions with additional dive constraints. Morphing optimizations are then performed, beginning with these baseline shapes. Five distinct types of morphing are investigated and compared. Overall, a theoretical fully adaptable wing produces roughly a 2% improvement in average performance, whereas trailing-edge morphing with a 27-point multipoint baseline results in just over a 1% improvement in average performance. Trailing-edge morphing proves to be more beneficial than leading-edge morphing, upper-surface morphing, and a conventional flap.

A Fuzzy Approach of the Competition on the Air Transport Market

NASA Technical Reports Server (NTRS)

Charfeddine, Souhir; DeColigny, Marc; Camino, Felix Mora; Cosenza, Carlos Alberto Nunes

2003-01-01

The aim of this communication is to study with a new scope the conditions of the equilibrium in an air transport market where two competitive airlines are operating. Each airline is supposed to adopt a strategy maximizing its profit while its estimation of the demand has a fuzzy nature. This leads each company to optimize a program of its proposed services (frequency of the flights and ticket prices) characterized by some fuzzy parameters. The case of monopoly is being taken as a benchmark. Classical convex optimization can be used to solve this decision problem. This approach provides the airline with a new decision tool where uncertainty can be taken into account explicitly. The confrontation of the strategies of the companies, in the ease of duopoly, leads to the definition of a fuzzy equilibrium. This concept of fuzzy equilibrium is more general and can be applied to several other domains. The formulation of the optimization problem and the methodological consideration adopted for its resolution are presented in their general theoretical aspect. In the case of air transportation, where the conditions of management of operations are critical, this approach should offer to the manager elements needed to the consolidation of its decisions depending on the circumstances (ordinary, exceptional events,..) and to be prepared to face all possibilities. Keywords: air transportation, competition equilibrium, convex optimization , fuzzy modeling,

Smartphone ECG for evaluation of ST-segment elevation myocardial infarction (STEMI): Design of the ST LEUIS International Multicenter Study.

PubMed

Barbagelata, Alejandro; Bethea, Charles F; Severance, Harry W; Mentz, Robert J; Albert, David; Barsness, Gregory W; Le, Viet T; Anderson, Jeffrey L; Bunch, T Jared; Yanowitz, Frank; Chisum, Benjamin; Ronnow, Brianna S; Muhlestein, Joseph B

In patients experiencing an ST-elevation myocardial infarction (STEMI), rapid diagnosis and immediate access to reperfusion therapy leads to optimal clinical outcomes. The rate-limiting step in STEMI diagnosis is the availability and performance of a 12-lead ECG. Recent technology has provided access to a reliable means of obtaining an ECG reading through a smartphone application (app) that works with an attachment providing all 12-leads of a standard ECG system. The ST LEUIS study was designed to validate the smartphone ECG app and its ability to accurately assess the presence or absence of STEMI in patients presenting with chest pain compared with the gold standard 12-lead ECG. We aimed to support the diagnostic utility of smartphone technology to provide a timely diagnosis and treatment of STEMI. The study will take place over 12months at five institutions. Approximately 60 patients will be enrolled per institution, for a total recruitment of 300 patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimization of the Caco-2 permeability assay to screen drug compounds for intestinal absorption and efflux.

PubMed

Press, Barry

2011-01-01

In vitro permeability assays are a valuable tool for scientists during lead compound optimization. As a majority of discovery projects are focused on the development of orally bioavailable drugs, correlation of in vitro permeability data to in vivo absorption results is critical for understanding the structural-physicochemical relationship (SPR) of drugs exhibiting low levels of absorption. For more than a decade, the Caco-2 screening assay has remained a popular, in vitro system to test compounds for both intestinal permeability and efflux liability. Despite advances in artificial membrane technology and in silico modeling systems, drug compounds still benefit from testing in cell-based epithelial monolayer assays for lead optimization. This chapter provides technical information for performing and optimizing the Caco-2 assay. In addition, techniques are discussed for dealing with some of the most pressing issues surrounding in vitro permeability assays (i.e., low aqueous solubility of test compounds and low postassay recovery). Insights are offered to help researchers avoid common pitfalls in the interpretation of in vitro permeability data, which can often lead to the perception of misleading results for correlation to in vivo data.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

Library-based illumination synthesis for critical CMOS patterning.

PubMed

Yu, Jue-Chin; Yu, Peichen; Chao, Hsueh-Yung

2013-07-01

In optical microlithography, the illumination source for critical complementary metal-oxide-semiconductor layers needs to be determined in the early stage of a technology node with very limited design information, leading to simple binary shapes. Recently, the availability of freeform sources permits us to increase pattern fidelity and relax mask complexities with minimal insertion risks to the current manufacturing flow. However, source optimization across many patterns is often treated as a design-of-experiments problem, which may not fully exploit the benefits of a freeform source. In this paper, a rigorous source-optimization algorithm is presented via linear superposition of optimal sources for pre-selected patterns. We show that analytical solutions are made possible by using Hopkins formulation and quadratic programming. The algorithm allows synthesized illumination to be linked with assorted pattern libraries, which has a direct impact on design rule studies for early planning and design automation for full wafer optimization.

Transformational leadership in the local police in Spain: a leader-follower distance approach.

PubMed

Álvarez, Octavio; Lila, Marisol; Tomás, Inés; Castillo, Isabel

2014-01-01

Based on the transformational leadership theory (Bass, 1985), the aim of the present study was to analyze the differences in leadership styles according to the various leading ranks and the organizational follower-leader distance reported by a representative sample of 975 local police members (828 male and 147 female) from Valencian Community (Spain). Results showed differences by rank (p < .01), and by rank distance (p < .05). The general intendents showed the most optimal profile of leadership in all the variables examined (transformational-leadership behaviors, transactional-leadership behaviors, laissez-faire behaviors, satisfaction with the leader, extra effort by follower, and perceived leadership effectiveness). By contrast, the least optimal profiles were presented by intendents. Finally, the maximum distance (five ranks) generally yielded the most optimal profiles, whereas the 3-rank distance generally produced the least optimal profiles for all variables examined. Outcomes and practical implications for the workforce dimensioning are also discussed.

The optimization of total laboratory automation by simulation of a pull-strategy.

PubMed

Yang, Taho; Wang, Teng-Kuan; Li, Vincent C; Su, Chia-Lo

2015-01-01

Laboratory results are essential for physicians to diagnose medical conditions. Because of the critical role of medical laboratories, an increasing number of hospitals use total laboratory automation (TLA) to improve laboratory performance. Although the benefits of TLA are well documented, systems occasionally become congested, particularly when hospitals face peak demand. This study optimizes TLA operations. Firstly, value stream mapping (VSM) is used to identify the non-value-added time. Subsequently, batch processing control and parallel scheduling rules are devised and a pull mechanism that comprises a constant work-in-process (CONWIP) is proposed. Simulation optimization is then used to optimize the design parameters and to ensure a small inventory and a shorter average cycle time (CT). For empirical illustration, this approach is applied to a real case. The proposed methodology significantly improves the efficiency of laboratory work and leads to a reduction in patient waiting times and increased service level.

Analysis of the faster-than-Nyquist optimal linear multicarrier system

NASA Astrophysics Data System (ADS)

Marquet, Alexandre; Siclet, Cyrille; Roque, Damien

2017-02-01

Faster-than-Nyquist signalization enables a better spectral efficiency at the expense of an increased computational complexity. Regarding multicarrier communications, previous work mainly relied on the study of non-linear systems exploiting coding and/or equalization techniques, with no particular optimization of the linear part of the system. In this article, we analyze the performance of the optimal linear multicarrier system when used together with non-linear receiving structures (iterative decoding and direct feedback equalization), or in a standalone fashion. We also investigate the limits of the normality assumption of the interference, used for implementing such non-linear systems. The use of this optimal linear system leads to a closed-form expression of the bit-error probability that can be used to predict the performance and help the design of coded systems. Our work also highlights the great performance/complexity trade-off offered by decision feedback equalization in a faster-than-Nyquist context. xml:lang="fr"

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability. PMID:26880881

Trajectory optimization for the National Aerospace Plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1993-01-01

The objective of this second phase research is to investigate the optimal ascent trajectory for the National Aerospace Plane (NASP) from runway take-off to orbital insertion and address the unique problems associated with the hypersonic flight trajectory optimization. The trajectory optimization problem for an aerospace plane is a highly challenging problem because of the complexity involved. Previous work has been successful in obtaining sub-optimal trajectories by using energy-state approximation and time-scale decomposition techniques. But it is known that the energy-state approximation is not valid in certain portions of the trajectory. This research aims at employing full dynamics of the aerospace plane and emphasizing direct trajectory optimization methods. The major accomplishments of this research include the first-time development of an inverse dynamics approach in trajectory optimization which enables us to generate optimal trajectories for the aerospace plane efficiently and reliably, and general analytical solutions to constrained hypersonic trajectories that has wide application in trajectory optimization as well as in guidance and flight dynamics. Optimal trajectories in abort landing and ascent augmented with rocket propulsion and thrust vectoring control were also investigated. Motivated by this study, a new global trajectory optimization tool using continuous simulated annealing and a nonlinear predictive feedback guidance law have been under investigation and some promising results have been obtained, which may well lead to more significant development and application in the near future.

Taxation of United States general aviation

NASA Astrophysics Data System (ADS)

Sobieralski, Joseph Bernard

General aviation in the United States has been an important part of the economy and American life. General aviation is defined as all flying excluding military and scheduled airline operations, and is utilized in many areas of our society. The majority of aircraft operations and airports in the United States are categorized as general aviation, and general aviation contributes more than one percent to the United States gross domestic product each year. Despite the many benefits of general aviation, the lead emissions from aviation gasoline consumption are of great concern. General aviation emits over half the lead emissions in the United States or over 630 tons in 2005. The other significant negative externality attributed to general aviation usage is aircraft accidents. General aviation accidents have caused over 8000 fatalities over the period 1994-2006. A recent Federal Aviation Administration proposed increase in the aviation gasoline tax from 19.4 to 70.1 cents per gallon has renewed interest in better understanding the implications of such a tax increase as well as the possible optimal rate of taxation. Few studies have examined aviation fuel elasticities and all have failed to study general aviation fuel elasticities. Chapter one fills that gap and examines the elasticity of aviation gasoline consumption in United States general aviation. Utilizing aggregate time series and dynamic panel data, the price and income elasticities of demand are estimated. The price elasticity of demand for aviation gasoline is estimated to range from -0.093 to -0.185 in the short-run and from -0.132 to -0.303 in the long-run. These results prove to be similar in magnitude to automobile gasoline elasticities and therefore tax policies could more closely mirror those of automobile tax policies. The second chapter examines the costs associated with general aviation accidents. Given the large number of general aviation operations as well as the large number of fatalities and injuries attributed to general aviation accidents in the United States, understanding the costs to society is of great importance. This chapter estimates the direct and indirect costs associated with general aviation accidents in the United States. The indirect costs are estimated via the human capital approach in addition to the willingness-to-pay approach. The average annual accident costs attributed to general aviation are found to be 2.32 billion and 3.81 billion (2006 US) utilizing the human capital approach and willingness-to-pay approach, respectively. These values appear to be fairly robust when subjected to a sensitivity analysis. These costs highlight the large societal benefits from accident and fatality reduction. The final chapter derives a second-best optimal aviation gasoline tax developed from previous general equilibrium frameworks. This optimal tax reflects both the lead pollution and accident externalities, as well as the balance between excise taxes and labor taxes to finance government spending. The calculated optimal tax rate is 4.07 per gallon, which is over 20 times greater than the current tax rate and 5 times greater than the Federal Aviation Administration proposed tax rate. The calculated optimal tax rate is also over 3 times greater than automobile gasoline optimal tax rates calculated by previous studies. The Pigovian component is 1.36, and we observe that the accident externality is taxed more severely than the pollution externality. The largest component of the optimal tax rate is the Ramsey component. At 2.70, the Ramsey component reflects the ability of the government to raise revenue aviation gasoline which is price inelastic. The calculated optimal tax is estimated to reduce lead emissions by over 10 percent and reduce accidents by 20 percent. Although unlikely to be adopted by policy makers, the optimal tax benefits are apparent and it sheds light on the need to reduce these negative externalities via policy changes.

[Optimization of radiological scoliosis assessment].

PubMed

Enríquez, Goya; Piqueras, Joaquim; Catalá, Ana; Oliva, Glòria; Ruiz, Agustí; Ribas, Montserrat; Duran, Carmina; Rodrigo, Carlos; Rodríguez, Eugenia; Garriga, Victoria; Maristany, Teresa; García-Fontecha, César; Baños, Joan; Muchart, Jordi; Alava, Fernando

2014-07-01

Most scoliosis are idiopathic (80%) and occur more frequently in adolescent girls. Plain radiography is the imaging method of choice, both for the initial study and follow-up studies but has the disadvantage of using ionizing radiation. The breasts are exposed to x-ray along these repeated examinations. The authors present a range of recommendations in order to optimize radiographic exam technique for both conventional and digital x-ray settings to prevent unnecessary patients' radiation exposure and to reduce the risk of breast cancer in patients with scoliosis. With analogue systems, leaded breast protectors should always be used, and with any radiographic equipment, analog or digital radiography, the examination should be performed in postero-anterior projection and optimized low-dose techniques. The ALARA (as low as reasonable achievable) rule should always be followed to achieve diagnostic quality images with the lowest feasible dose. Copyright © 2014. Published by Elsevier Espana.

Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification

PubMed Central

Desroches, Joannie; Jermyn, Michael; Mok, Kelvin; Lemieux-Leduc, Cédric; Mercier, Jeanne; St-Arnaud, Karl; Urmey, Kirk; Guiot, Marie-Christine; Marple, Eric; Petrecca, Kevin; Leblond, Frédéric

2015-01-01

A detailed characterization study is presented of a Raman spectroscopy system designed to maximize the volume of resected cancer tissue in glioma surgery based on in vivo molecular tissue characterization. It consists of a hand-held probe system measuring spectrally resolved inelastically scattered light interacting with tissue, designed and optimized for in vivo measurements. Factors such as linearity of the signal with integration time and laser power, and their impact on signal to noise ratio, are studied leading to optimal data acquisition parameters. The impact of ambient light sources in the operating room is assessed and recommendations made for optimal operating conditions. In vivo Raman spectra of normal brain, cancer and necrotic tissue were measured in 10 patients, demonstrating that real-time inelastic scattering measurements can distinguish necrosis from vital tissue (including tumor and normal brain tissue) with an accuracy of 87%, a sensitivity of 84% and a specificity of 89%. PMID:26203368

Structural synthesis: Precursor and catalyst

NASA Technical Reports Server (NTRS)

Schmit, L. A.

1984-01-01

More than twenty five years have elapsed since it was recognized that a rather general class of structural design optimization tasks could be properly posed as an inequality constrained minimization problem. It is suggested that, independent of primary discipline area, it will be useful to think about: (1) posing design problems in terms of an objective function and inequality constraints; (2) generating design oriented approximate analysis methods (giving special attention to behavior sensitivity analysis); (3) distinguishing between decisions that lead to an analysis model and those that lead to a design model; (4) finding ways to generate a sequence of approximate design optimization problems that capture the essential characteristics of the primary problem, while still having an explicit algebraic form that is matched to one or more of the established optimization algorithms; (5) examining the potential of optimum design sensitivity analysis to facilitate quantitative trade-off studies as well as participation in multilevel design activities. It should be kept in mind that multilevel methods are inherently well suited to a parallel mode of operation in computer terms or to a division of labor between task groups in organizational terms. Based on structural experience with multilevel methods general guidelines are suggested.

Improved helicopter aeromechanical stability analysis using segmented constrained layer damping and hybrid optimization

NASA Astrophysics Data System (ADS)

Liu, Qiang; Chattopadhyay, Aditi

2000-06-01

Aeromechanical stability plays a critical role in helicopter design and lead-lag damping is crucial to this design. In this paper, the use of segmented constrained damping layer (SCL) treatment and composite tailoring is investigated for improved rotor aeromechanical stability using formal optimization technique. The principal load-carrying member in the rotor blade is represented by a composite box beam, of arbitrary thickness, with surface bonded SCLs. A comprehensive theory is used to model the smart box beam. A ground resonance analysis model and an air resonance analysis model are implemented in the rotor blade built around the composite box beam with SCLs. The Pitt-Peters dynamic inflow model is used in air resonance analysis under hover condition. A hybrid optimization technique is used to investigate the optimum design of the composite box beam with surface bonded SCLs for improved damping characteristics. Parameters such as stacking sequence of the composite laminates and placement of SCLs are used as design variables. Detailed numerical studies are presented for aeromechanical stability analysis. It is shown that optimum blade design yields significant increase in rotor lead-lag regressive modal damping compared to the initial system.

Do Dogs Know Related Rates Rather than Optimization?

ERIC Educational Resources Information Center

Perruchet, Pierre; Gallego, Jorge

2006-01-01

Although dogs seemingly follow the optimal path where they get to a ball thrown into the water, they certainly do not know the minimization function proposed in the calculus books. Trading the optimization problem for a related rates problem leads to a mathematically identical solution, which, it is argued here, is a more plausible model for the…

Optimizing Requirements Decisions with KEYS

NASA Technical Reports Server (NTRS)

Jalali, Omid; Menzies, Tim; Feather, Martin

2008-01-01

Recent work with NASA's Jet Propulsion Laboratory has allowed for external access to five of JPL's real-world requirements models, anonymized to conceal proprietary information, but retaining their computational nature. Experimentation with these models, reported herein, demonstrates a dramatic speedup in the computations performed on them. These models have a well defined goal: select mitigations that retire risks which, in turn, increases the number of attainable requirements. Such a non-linear optimization is a well-studied problem. However identification of not only (a) the optimal solution(s) but also (b) the key factors leading to them is less well studied. Our technique, called KEYS, shows a rapid way of simultaneously identifying the solutions and their key factors. KEYS improves on prior work by several orders of magnitude. Prior experiments with simulated annealing or treatment learning took tens of minutes to hours to terminate. KEYS runs much faster than that; e.g for one model, KEYS ran 13,000 times faster than treatment learning (40 minutes versus 0.18 seconds). Processing these JPL models is a non-linear optimization problem: the fewest mitigations must be selected while achieving the most requirements. Non-linear optimization is a well studied problem. With this paper, we challenge other members of the PROMISE community to improve on our results with other techniques.

Optimism and Cause-Specific Mortality: A Prospective Cohort Study.

PubMed

Kim, Eric S; Hagan, Kaitlin A; Grodstein, Francine; DeMeo, Dawn L; De Vivo, Immaculata; Kubzansky, Laura D

2017-01-01

Growing evidence has linked positive psychological attributes like optimism to a lower risk of poor health outcomes, especially cardiovascular disease. It has been demonstrated in randomized trials that optimism can be learned. If associations between optimism and broader health outcomes are established, it may lead to novel interventions that improve public health and longevity. In the present study, we evaluated the association between optimism and cause-specific mortality in women after considering the role of potential confounding (sociodemographic characteristics, depression) and intermediary (health behaviors, health conditions) variables. We used prospective data from the Nurses' Health Study (n = 70,021). Dispositional optimism was measured in 2004; all-cause and cause-specific mortality rates were assessed from 2006 to 2012. Using Cox proportional hazard models, we found that a higher degree of optimism was associated with a lower mortality risk. After adjustment for sociodemographic confounders, compared with women in the lowest quartile of optimism, women in the highest quartile had a hazard ratio of 0.71 (95% confidence interval: 0.66, 0.76) for all-cause mortality. Adding health behaviors, health conditions, and depression attenuated but did not eliminate the associations (hazard ratio = 0.91, 95% confidence interval: 0.85, 0.97). Associations were maintained for various causes of death, including cancer, heart disease, stroke, respiratory disease, and infection. Given that optimism was associated with numerous causes of mortality, it may provide a valuable target for new research on strategies to improve health. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Hybrid Interval–Robust Optimization Model for Water Quality Management

PubMed Central

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-01-01

Abstract In water quality management problems, uncertainties may exist in many system components and pollution-related processes (i.e., random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval–robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements. PMID:23922495

Large-scale optimal control of interconnected natural gas and electrical transmission systems

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

Chiang, Nai-Yuan; Zavala, Victor M.

2016-04-01

We present a detailed optimal control model that captures spatiotemporal interactions between gas and electric transmission networks. We use the model to study flexibility and economic opportunities provided by coordination. A large-scale case study in the Illinois system reveals that coordination can enable the delivery of significantly larger amounts of natural gas to the power grid. In particular, under a coordinated setting, gas-fired generators act as distributed demand response resources that can be controlled by the gas pipeline operator. This enables more efficient control of pressures and flows in space and time and overcomes delivery bottlenecks. We demonstrate that themore » additional flexibility not only can benefit the gas operator but can also lead to more efficient power grid operations and results in increased revenue for gas-fired power plants. We also use the optimal control model to analyze computational issues arising in these complex models. We demonstrate that the interconnected Illinois system with full physical resolution gives rise to a highly nonlinear optimal control problem with 4400 differential and algebraic equations and 1040 controls that can be solved with a state-of-the-art sparse optimization solver. (C) 2016 Elsevier Ltd. All rights reserved.« less

Joint Optimization of Distribution Network Design and Two-Echelon Inventory Control with Stochastic Demand and CO2 Emission Tax Charges.

PubMed

Li, Shuangyan; Li, Xialian; Zhang, Dezhi; Zhou, Lingyun

2017-01-01

This study develops an optimization model to integrate facility location and inventory control for a three-level distribution network consisting of a supplier, multiple distribution centers (DCs), and multiple retailers. The integrated model addressed in this study simultaneously determines three types of decisions: (1) facility location (optimal number, location, and size of DCs); (2) allocation (assignment of suppliers to located DCs and retailers to located DCs, and corresponding optimal transport mode choices); and (3) inventory control decisions on order quantities, reorder points, and amount of safety stock at each retailer and opened DC. A mixed-integer programming model is presented, which considers the carbon emission taxes, multiple transport modes, stochastic demand, and replenishment lead time. The goal is to minimize the total cost, which covers the fixed costs of logistics facilities, inventory, transportation, and CO2 emission tax charges. The aforementioned optimal model was solved using commercial software LINGO 11. A numerical example is provided to illustrate the applications of the proposed model. The findings show that carbon emission taxes can significantly affect the supply chain structure, inventory level, and carbon emission reduction levels. The delay rate directly affects the replenishment decision of a retailer.

Optimization of the ANFIS using a genetic algorithm for physical work rate classification.

PubMed

Habibi, Ehsanollah; Salehi, Mina; Yadegarfar, Ghasem; Taheri, Ali

2018-03-13

Recently, a new method was proposed for physical work rate classification based on an adaptive neuro-fuzzy inference system (ANFIS). This study aims to present a genetic algorithm (GA)-optimized ANFIS model for a highly accurate classification of physical work rate. Thirty healthy men participated in this study. Directly measured heart rate and oxygen consumption of the participants in the laboratory were used for training the ANFIS classifier model in MATLAB version 8.0.0 using a hybrid algorithm. A similar process was done using the GA as an optimization technique. The accuracy, sensitivity and specificity of the ANFIS classifier model were increased successfully. The mean accuracy of the model was increased from 92.95 to 97.92%. Also, the calculated root mean square error of the model was reduced from 5.4186 to 3.1882. The maximum estimation error of the optimized ANFIS during the network testing process was ± 5%. The GA can be effectively used for ANFIS optimization and leads to an accurate classification of physical work rate. In addition to high accuracy, simple implementation and inter-individual variability consideration are two other advantages of the presented model.

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

NASA Technical Reports Server (NTRS)

Davis, W. H., Jr.

1985-01-01

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

Assessment of precursory information in seismo-electromagnetic phenomena

NASA Astrophysics Data System (ADS)

Han, P.; Hattori, K.; Zhuang, J.

2017-12-01

Previous statistical studies showed that there were correlations between seismo-electromagnetic phenomena and sizeable earthquakes in Japan. In this study, utilizing Molchan's error diagram, we evaluate whether these phenomena contain precursory information and discuss how they can be used in short-term forecasting of large earthquake events. In practice, for given series of precursory signals and related earthquake events, each prediction strategy is characterized by the leading time of alarms, the length of alarm window, the alarm radius (area) and magnitude. The leading time is the time length between a detected anomaly and its following alarm, and the alarm window is the duration that an alarm lasts. The alarm radius and magnitude are maximum predictable distance and minimum predictable magnitude of earthquake events, respectively. We introduce the modified probability gain (PG') and the probability difference (D') to quantify the forecasting performance and to explore the optimal prediction parameters for a given electromagnetic observation. The above methodology is firstly applied to ULF magnetic data and GPS-TEC data. The results show that the earthquake predictions based on electromagnetic anomalies are significantly better than random guesses, indicating the data contain potential useful precursory information. Meanwhile, we reveal the optimal prediction parameters for both observations. The methodology proposed in this study could be also applied to other pre-earthquake phenomena to find out whether there is precursory information, and then on this base explore the optimal alarm parameters in practical short-term forecast.

[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.

Structure-Guided Design and Optimization of Dipeptidyl Inhibitors of Norovirus 3CL Protease. Structure–Activity Relationships and Biochemical, X-ray Crystallographic, Cell-Based, and In Vivo Studies

DOE PAGES

Galasiti Kankanamalage, Anushka C.; Kim, Yunjeong; Weerawarna, Pathum M.; ...

2015-04-09

Norovirus infection constitutes the primary cause of acute viral gastroenteritis. There are currently no vaccines or norovirus-specific antiviral therapeutics available for the management of norovirus infection. Norovirus 3C-like protease is essential for viral replication, consequently, inhibition of this enzyme is a fruitful avenue of investigation that may lead to the emergence of antinorovirus therapeutics. We describe herein the optimization of dipeptidyl inhibitors of norovirus 3C-like protease using iterative SAR, X-ray crystallographic, and enzyme and cell-based studies. We also demonstrate herein in vivo efficacy of an inhibitor using the murine model of norovirus infection.

Left Ventricular Lead Placement Targeted at the Latest Activated Site Guided by Electrophysiological Mapping in Coronary Sinus Branches Improves Response to Cardiac Resynchronization Therapy.

PubMed

Liang, Yanchun; Yu, Haibo; Zhou, Weiwei; Xu, Guoqing; Sun, Y I; Liu, Rong; Wang, Zulu; Han, Yaling

2015-12-01

Electrophysiological mapping (EPM) in coronary sinus (CS) branches is feasible for guiding LV lead placement to the optimal, latest activated site at cardiac resynchronization therapy (CRT) procedures. However, whether this procedure optimizes the response to CRT has not been demonstrated. This study was to evaluate effects of targeting LV lead at the latest activated site guided by EPM during CRT. Seventy-six consecutive patients with advanced heart failure who were referred for CRT were divided into mapping (MG) and control groups (CG). In MG, the LV lead, also used as a mapping bipolar electrode, was placed at the latest activated site determined by EPM in CS branches. In CG, conventional CRT procedure was performed. Patients were followed for 6 months after CRT. Baseline characteristics were comparable between the 2 groups. In MG (n = 29), EPM was successfully performed in 85 of 91 CS branches during CRT. A LV lead was successfully placed at the latest activated site guided by EPM in 27 (93.1%) patients. Compared with CG (n = 47), MG had a significantly higher rate (86.2% vs. 63.8%, P = 0.039) of response (>15% reduction in LV end-systolic volume) to CRT, a higher percentage of patients with clinical improvement of ≥2 NYHA functional classes (72.4% vs. 44.7%, P = 0.032), and a shorter QRS duration (P = 0.004). LV lead placed at the latest activated site guided by EPM resulted in a significantly greater CRT response, and a shorter QRS duration. © 2015 Wiley Periodicals, Inc.

1,4-Oxazine β-Secretase 1 (BACE1) Inhibitors: From Hit Generation to Orally Bioavailable Brain Penetrant Leads.

PubMed

Rombouts, Frederik J R; Tresadern, Gary; Delgado, Oscar; Martínez-Lamenca, Carolina; Van Gool, Michiel; García-Molina, Aránzazu; Alonso de Diego, Sergio A; Oehlrich, Daniel; Prokopcova, Hana; Alonso, José Manuel; Austin, Nigel; Borghys, Herman; Van Brandt, Sven; Surkyn, Michel; De Cleyn, Michel; Vos, Ann; Alexander, Richard; Macdonald, Gregor; Moechars, Dieder; Gijsen, Harrie; Trabanco, Andrés A

2015-10-22

1,4-Oxazines are presented, which show good in vitro inhibition in enzymatic and cellular BACE1 assays. We describe lead optimization focused on reducing the amidine pKa while optimizing interactions in the BACE1 active site. Our strategy permitted modulation of properties such as permeation and especially P-glycoprotein efflux. This led to compounds which were orally bioavailable, centrally active, and which demonstrated robust lowering of brain and CSF Aβ levels, respectively, in mouse and dog models. The amyloid lowering potential of these molecules makes them valuable leads in the search for new BACE1 inhibitors for the treatment of Alzheimer's disease.

Synthesis and structure-activity relationship of piperidine-derived non-urea soluble epoxide hydrolase inhibitors

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

Pecic, Stevan; Pakhomova, Svetlana; Newcomer, Marcia E.

2013-09-27

A series of potent amide non-urea inhibitors of soluble epoxide hydrolase (sEH) is disclosed. The inhibition of soluble epoxide hydrolase leads to elevated levels of epoxyeicosatrienoic acids (EETs), and thus inhibitors of sEH represent one of a novel approach to the development of vasodilatory and anti-inflammatory drugs. Structure–activities studies guided optimization of a lead compound, identified through high-throughput screening, gave rise to sub-nanomolar inhibitors of human sEH with stability in human liver microsomal assay suitable for preclinical development.

Rethinking FCV/BEV Vehicle Range: A Consumer Value Trade-off Perspective

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

Lin, Zhenhong; Greene, David L

2010-01-01

The driving range of FCV and BEV is often analyzed by simple analogy to conventional vehicles without proper consideration of differences in energy storage technology, infrastructure, and market context. This study proposes a coherent framework to optimize the driving range by minimizing costs associated with range, including upfront storage cost, fuel availability cost for FCV and range anxiety cost for BEV. It is shown that the conventional assumption of FCV range can lead to overestimation of FCV market barrier by over $8000 per vehicle in the near-term market. Such exaggeration of FCV market barrier can be avoided with range optimization.more » Compared to the optimal BEV range, the 100-mile range chosen by automakers appears to be near optimal for modest drivers, but far less than optimal for frequent drivers. With range optimization, the probability that the BEV is unable to serve a long-trip day is generally less than 5%, depending on driving intensity. Range optimization can help diversify BEV products for different consumers. It is also demonstrated and argued that the FCV/BEV range should adapt to the technology and infrastructure developments.« less

A time-domain decomposition iterative method for the solution of distributed linear quadratic optimal control problems

NASA Astrophysics Data System (ADS)

Heinkenschloss, Matthias

2005-01-01

We study a class of time-domain decomposition-based methods for the numerical solution of large-scale linear quadratic optimal control problems. Our methods are based on a multiple shooting reformulation of the linear quadratic optimal control problem as a discrete-time optimal control (DTOC) problem. The optimality conditions for this DTOC problem lead to a linear block tridiagonal system. The diagonal blocks are invertible and are related to the original linear quadratic optimal control problem restricted to smaller time-subintervals. This motivates the application of block Gauss-Seidel (GS)-type methods for the solution of the block tridiagonal systems. Numerical experiments show that the spectral radii of the block GS iteration matrices are larger than one for typical applications, but that the eigenvalues of the iteration matrices decay to zero fast. Hence, while the GS method is not expected to convergence for typical applications, it can be effective as a preconditioner for Krylov-subspace methods. This is confirmed by our numerical tests.A byproduct of this research is the insight that certain instantaneous control techniques can be viewed as the application of one step of the forward block GS method applied to the DTOC optimality system.

Optimism and its impact on mental and physical well-being.

PubMed

Conversano, Ciro; Rotondo, Alessandro; Lensi, Elena; Della Vista, Olivia; Arpone, Francesca; Reda, Mario Antonio

2010-05-14

Many studies have been carried out about the effectiveness of optimism as a psychological phenomenon, leading to various theoretical formulations of the same concept, conceptualized as "disposition", "attributional style", "cognitive bias", or "shared illusion". This overview is an attempt to explore the "optimism" concept and its relations with mental health, physical health, coping, quality of life and adaptation of purpose, health lifestyle and risk perception. Positive and negative expectations regarding the future are important for understanding the vulnerability to mental disorders, in particular mood and anxiety disorders, as well as to physical illness. A significant positive relation emerges between optimism and coping strategies focused on social support and emphasis on positive aspects of stressful situations. Through employment of specific coping strategies, optimism exerts an indirect influence also on the quality of life. There is evidence that optimistic people present a higher quality of life compared to those with low levels of optimism or even pessimists. Optimism may significantly influence mental and physical well-being by the promotion of a healthy lifestyle as well as by adaptive behaviours and cognitive responses, associated with greater flexibility, problem-solving capacity and a more efficient elaboration of negative information.

Image reconstruction and scan configurations enabled by optimization-based algorithms in multispectral CT

NASA Astrophysics Data System (ADS)

Chen, Buxin; Zhang, Zheng; Sidky, Emil Y.; Xia, Dan; Pan, Xiaochuan

2017-11-01

Optimization-based algorithms for image reconstruction in multispectral (or photon-counting) computed tomography (MCT) remains a topic of active research. The challenge of optimization-based image reconstruction in MCT stems from the inherently non-linear data model that can lead to a non-convex optimization program for which no mathematically exact solver seems to exist for achieving globally optimal solutions. In this work, based upon a non-linear data model, we design a non-convex optimization program, derive its first-order-optimality conditions, and propose an algorithm to solve the program for image reconstruction in MCT. In addition to consideration of image reconstruction for the standard scan configuration, the emphasis is on investigating the algorithm’s potential for enabling non-standard scan configurations with no or minimum hardware modification to existing CT systems, which has potential practical implications for lowered hardware cost, enhanced scanning flexibility, and reduced imaging dose/time in MCT. Numerical studies are carried out for verification of the algorithm and its implementation, and for a preliminary demonstration and characterization of the algorithm in reconstructing images and in enabling non-standard configurations with varying scanning angular range and/or x-ray illumination coverage in MCT.

Accurate Binding Free Energy Predictions in Fragment Optimization.

PubMed

Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody

2015-11-23

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

Speed and convergence properties of gradient algorithms for optimization of IMRT.

PubMed

Zhang, Xiaodong; Liu, Helen; Wang, Xiaochun; Dong, Lei; Wu, Qiuwen; Mohan, Radhe

2004-05-01

Gradient algorithms are the most commonly employed search methods in the routine optimization of IMRT plans. It is well known that local minima can exist for dose-volume-based and biology-based objective functions. The purpose of this paper is to compare the relative speed of different gradient algorithms, to investigate the strategies for accelerating the optimization process, to assess the validity of these strategies, and to study the convergence properties of these algorithms for dose-volume and biological objective functions. With these aims in mind, we implemented Newton's, conjugate gradient (CG), and the steepest decent (SD) algorithms for dose-volume- and EUD-based objective functions. Our implementation of Newton's algorithm approximates the second derivative matrix (Hessian) by its diagonal. The standard SD algorithm and the CG algorithm with "line minimization" were also implemented. In addition, we investigated the use of a variation of the CG algorithm, called the "scaled conjugate gradient" (SCG) algorithm. To accelerate the optimization process, we investigated the validity of the use of a "hybrid optimization" strategy, in which approximations to calculated dose distributions are used during most of the iterations. Published studies have indicated that getting trapped in local minima is not a significant problem. To investigate this issue further, we first obtained, by trial and error, and starting with uniform intensity distributions, the parameters of the dose-volume- or EUD-based objective functions which produced IMRT plans that satisfied the clinical requirements. Using the resulting optimized intensity distributions as the initial guess, we investigated the possibility of getting trapped in a local minimum. For most of the results presented, we used a lung cancer case. To illustrate the generality of our methods, the results for a prostate case are also presented. For both dose-volume and EUD based objective functions, Newton's method far outperforms other algorithms in terms of speed. The SCG algorithm, which avoids expensive "line minimization," can speed up the standard CG algorithm by at least a factor of 2. For the same initial conditions, all algorithms converge essentially to the same plan. However, we demonstrate that for any of the algorithms studied, starting with previously optimized intensity distributions as the initial guess but for different objective function parameters, the solution frequently gets trapped in local minima. We found that the initial intensity distribution obtained from IMRT optimization utilizing objective function parameters, which favor a specific anatomic structure, would lead to a local minimum corresponding to that structure. Our results indicate that from among the gradient algorithms tested, Newton's method appears to be the fastest by far. Different gradient algorithms have the same convergence properties for dose-volume- and EUD-based objective functions. The hybrid dose calculation strategy is valid and can significantly accelerate the optimization process. The degree of acceleration achieved depends on the type of optimization problem being addressed (e.g., IMRT optimization, intensity modulated beam configuration optimization, or objective function parameter optimization). Under special conditions, gradient algorithms will get trapped in local minima, and reoptimization, starting with the results of previous optimization, will lead to solutions that are generally not significantly different from the local minimum.

Modeling of lead air pollution. [Baton Rouge, Louisiana

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

Monteith, C.S.; Henry, J.M.

1982-05-01

A study was performed to determine whether vehicular emissions should be included with industrial emissions when demonstrating attainment of the ambient air quality standard for lead. The impact on ambient lead concentrations of the phaseout of leaded gasoline and improved automobile fuel economy was examined by modeling vehicular emissions for 1972 and 1978. Results show that while automobiles in the Baton Rouge area were a significant source of lead in 1972, the phaseout of leaded gasoline and the increase in fuel economy have resulted in a lower contribution (0.20 ..mu..g/m/sup 3/) by automobiles to the ambient lead concentration in 1978.more » The areas having the greatest potential for exceeding the ambient air quality standard can be identified using CDM (EPA's Climatological Dispersion Model). This information can be used to determine the optimal location for an ambient air monitor to demonstrate compliance with the ambient air quality standard. 9 references, 4 figures, 5 tables. (JMT)« less

Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Farahlina Johari, Nur; Zain, Azlan Mohd; Haszlinna Mustaffa, Noorfa; Udin, Amirmudin

2017-09-01

Firefly Algorithm (FA) is a metaheuristic algorithm that is inspired by the flashing behavior of fireflies and the phenomenon of bioluminescent communication and the algorithm is used to optimize the machining parameters (feed rate, depth of cut, and spindle speed) in this research. The algorithm is hybridized with Particle Swarm Optimization (PSO) to discover better solution in exploring the search space. Objective function of previous research is used to optimize the machining parameters in turning operation. The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

Study Abroad as a Multifaceted Approach to Supporting College Sophomores: Creating Optimal Environments to Promote Intercultural Maturity

ERIC Educational Resources Information Center

Luchesi, Jessica

2014-01-01

Leaders in higher education bear the responsibility of creating educational environments and programming that promote student development and help prepare graduates to work, live, and lead in today's interconnected and global society. Such institutional programming, which fosters "intercultural maturity," defined as the cognitive,…

A Qualitative Analysis of an Advanced Practice Nurse-Directed Transitional Care Model Intervention

ERIC Educational Resources Information Center

Bradway, Christine; Trotta, Rebecca; Bixby, M. Brian; McPartland, Ellen; Wollman, M. Catherine; Kapustka, Heidi; McCauley, Kathleen; Naylor, Mary D.

2012-01-01

Purpose: The purpose of this study was to describe barriers and facilitators to implementing a transitional care intervention for cognitively impaired older adults and their caregivers lead by advanced practice nurses (APNs). Design and Methods: APNs implemented an evidence-based protocol to optimize transitions from hospital to home. An…

Fragment-based virtual screening approach and molecular dynamics simulation studies for identification of BACE1 inhibitor leads.

PubMed

Manoharan, Prabu; Ghoshal, Nanda

2018-05-01

Traditional structure-based virtual screening method to identify drug-like small molecules for BACE1 is so far unsuccessful. Location of BACE1, poor Blood Brain Barrier permeability and P-glycoprotein (Pgp) susceptibility of the inhibitors make it even more difficult. Fragment-based drug design method is suitable for efficient optimization of initial hit molecules for target like BACE1. We have developed a fragment-based virtual screening approach to identify/optimize the fragment molecules as a starting point. This method combines the shape, electrostatic, and pharmacophoric features of known fragment molecules, bound to protein conjugate crystal structure, and aims to identify both chemically and energetically feasible small fragment ligands that bind to BACE1 active site. The two top-ranked fragment hits were subjected for a 53 ns MD simulation. Principle component analysis and free energy landscape analysis reveal that the new ligands show the characteristic features of established BACE1 inhibitors. The potent method employed in this study may serve for the development of potential lead molecules for BACE1-directed Alzheimer's disease therapeutics.

Design, synthesis, in vitro Evaluation and docking studies on dihydropyrimidine-based urease inhibitors.

PubMed

Iftikhar, Fatima; Ali, Yousaf; Ahmad Kiani, Farooq; Fahad Hassan, Syed; Fatima, Tabeer; Khan, Ajmal; Niaz, Basit; Hassan, Abbas; Latif Ansari, Farzana; Rashid, Umer

2017-10-01

In our previous report, we have identified 3,4-dihydropyrimidine scaffold as promising class of urease inhibitor in a structure based virtual screen (SBVS) experiment. In present study, we attempted to optimize the scaffold by varying C-5 substituent. The elongation of the C-5 chain was achieved by the reaction of C-5 ester with hydrazine leading to C-5 carbohydrazides which were further used as building blocks for the synthesis of fifteen new compounds having diverse moieties. A significantly higher in vitro urease inhibitory activity with IC 50 values in submicromolar range was observed for semithiocarbazide derivatives (4a-c, 0.58-0.79µM) and isatin Schiff base derivative 5a (0.23µM). Docking analysis suggests that the synthesized compounds were anchored well in the catalytic site and extending to the entrance of binding pocket and thus restrict the mobility of the flap by interacting with its key amino acid residues. The overall results of urease inhibition have shown that these compounds can be further optimized and developed as lead urease inhibitors. Copyright © 2017 Elsevier Inc. All rights reserved.

Structure-Guided Lead Optimization of Triazolopyrimidine-Ring Substituents Identifies Potent Plasmodium falciparum Dihydroorotate Dehydrogenase Inhibitors with Clinical Candidate Potential

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

Coteron, Jose M.; Marco, Maria; Esquivias, Jorge

2012-02-27

Drug therapy is the mainstay of antimalarial therapy, yet current drugs are threatened by the development of resistance. In an effort to identify new potential antimalarials, we have undertaken a lead optimization program around our previously identified triazolopyrimidine-based series of Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors. The X-ray structure of PfDHODH was used to inform the medicinal chemistry program allowing the identification of a potent and selective inhibitor (DSM265) that acts through DHODH inhibition to kill both sensitive and drug resistant strains of the parasite. This compound has similar potency to chloroquine in the humanized SCID mouse P. falciparum model,more » can be synthesized by a simple route, and rodent pharmacokinetic studies demonstrated it has excellent oral bioavailability, a long half-life and low clearance. These studies have identified the first candidate in the triazolopyrimidine series to meet previously established progression criteria for efficacy and ADME properties, justifying further development of this compound toward clinical candidate status.« less

Effect of glomerular filtration rate at dialysis initiation on survival in patients with advanced chronic kidney disease: what is the effect of lead-time bias?

PubMed Central

Janmaat, Cynthia J; van Diepen, Merel; Krediet, Raymond T; Hemmelder, Marc H; Dekker, Friedo W

2017-01-01

Purpose Current clinical guidelines recommend to initiate dialysis in the presence of symptoms or signs attributable to kidney failure, often with a glomerular filtration rate (GFR) of 5–10 mL/min/1.73 m2. Little evidence exists about the optimal kidney function to start dialysis. Thus far, most observational studies have been limited by lead-time bias. Only a few studies have accounted for lead-time bias, and showed contradictory results. We examined the effect of GFR at dialysis initiation on survival in chronic kidney disease patients, and the role of lead-time bias therein. We used both kidney function based on 24-hour urine collection (measured GFR [mGFR]) and estimated GFR (eGFR). Materials and methods A total of 1,143 patients with eGFR data at dialysis initiation and 852 patients with mGFR data were included from the NECOSAD cohort. Cox regression was used to adjust for potential confounders. To examine the effect of lead-time bias, survival was counted from the time of dialysis initiation or from a common starting point (GFR 20 mL/min/1.73 m2), using linear interpolation models. Results Without lead-time correction, no difference between early and late starters was present based on eGFR (hazard ratio [HR] 1.03, 95% confidence interval [CI] 0.81–1.3). However, after lead-time correction, early initiation showed a survival disadvantage (HR between 1.1 [95% CI 0.82–1.48] and 1.33 [95% CI 1.05–1.68]). Based on mGFR, the potential survival benefit for early starters without lead-time correction (HR 0.8, 95% CI 0.62–1.03) completely disappeared after lead-time correction (HR between 0.94 [95% CI 0.65–1.34] and 1.21 [95% CI 0.95–1.56]). Dialysis start time differed about a year between early and late initiation. Conclusion Lead-time bias is not only a methodological problem but also has clinical impact when assessing the optimal kidney function to start dialysis. Therefore, lead-time bias is extremely important to correct for. Taking account of lead-time bias, this controlled study showed that early dialysis initiation (eGFR >7.9, mGFR >6.6 mL/min/1.73 m2) was not associated with an improvement in survival. Based on kidney function, this study suggests that in some patients, dialysis could be started even later than an eGFR <5.7 and mGFR <4.3 mL/min/1.73 m2. PMID:28442934

Porous NiTi for bone implants: a review.

PubMed

Bansiddhi, A; Sargeant, T D; Stupp, S I; Dunand, D C

2008-07-01

NiTi foams are unique among biocompatible porous metals because of their high recovery strain (due to the shape-memory or superelastic effects) and their low stiffness facilitating integration with bone structures. To optimize NiTi foams for bone implant applications, two key areas are under active study: synthesis of foams with optimal architectures, microstructure and mechanical properties; and tailoring of biological interactions through modifications of pore surfaces. This article reviews recent research on NiTi foams for bone replacement, focusing on three specific topics: (i) surface modifications designed to create bio-inert porous NiTi surfaces with low Ni release and corrosion, as well as bioactive surfaces to enhance and accelerate biological activity; (ii) in vitro and in vivo biocompatibility studies to confirm the long-term safety of porous NiTi implants; and (iii) biological evaluations for specific applications, such as in intervertebral fusion devices and bone tissue scaffolds. Possible future directions for bio-performance and processing studies are discussed that could lead to optimized porous NiTi implants.

Porous NiTi for bone implants: A review

PubMed Central

Bansiddhi, A.; Sargeant, T.D.; Stupp, S.I.; Dunand, D.C.

2011-01-01

NiTi foams are unique among biocompatible porous metals because of their high recovery strain (due to the shape-memory or superelastic effects) and their low stiffness facilitating integration with bone structures. To optimize NiTi foams for bone implant applications, two key areas are under active study: synthesis of foams with optimal architectures, microstructure and mechanical properties; and tailoring of biological interactions through modifications of pore surfaces. This article reviews recent research on NiTi foams for bone replacement, focusing on three specific topics: (i) surface modifications designed to create bio-inert porous NiTi surfaces with low Ni release and corrosion, as well as bioactive surfaces to enhance and accelerate biological activity; (ii) In vitro and in vivo biocompatibility studies to confirm the long-term safety of porous NiTi implants; and (iii) biological evaluations for specific applications, such as in intervertebral fusion devices and bone tissue scaffolds. Possible future directions for bio-performance and processing studies are discussed that could lead to optimized porous NiTi implants. PMID:18348912

Stress for Success: How to Optimize Your Performance.

ERIC Educational Resources Information Center

Gmelch, Walter H.

1983-01-01

This article explores linkages between stress and effective job performance: while too much stress can lead to burnout, too little stressful stimulation can result in boredom. Generating the proper amount of stress for optimal job performance is discussed. (PP)

Application of lean manufacturing concepts to drug discovery: rapid analogue library synthesis.

PubMed

Weller, Harold N; Nirschl, David S; Petrillo, Edward W; Poss, Michael A; Andres, Charles J; Cavallaro, Cullen L; Echols, Martin M; Grant-Young, Katherine A; Houston, John G; Miller, Arthur V; Swann, R Thomas

2006-01-01

The application of parallel synthesis to lead optimization programs in drug discovery has been an ongoing challenge since the first reports of library synthesis. A number of approaches to the application of parallel array synthesis to lead optimization have been attempted over the years, ranging from widespread deployment by (and support of) individual medicinal chemists to centralization as a service by an expert core team. This manuscript describes our experience with the latter approach, which was undertaken as part of a larger initiative to optimize drug discovery. In particular, we highlight how concepts taken from the manufacturing sector can be applied to drug discovery and parallel synthesis to improve the timeliness and thus the impact of arrays on drug discovery.

Development of a simple method for the determination of lead in lipstick using alkaline solubilization and graphite furnace atomic absorption spectrometry.

PubMed

Soares, Aline Rodrigues; Nascentes, Clésia Cristina

2013-02-15

A simple method was developed for determining the total lead content in lipstick samples by graphite furnace atomic absorption spectrometry (GFAAS) after treatment with tetramethylammonium hydroxide (TMAH). Multivariate optimization was used to establish the optimal conditions of sample preparation. The graphite furnace heating program was optimized through pyrolysis and atomization curves. An aliquot containing approximately 50mg of the sample was mixed with TMAH and heated in a water bath at 60°C for 60 min. Using Nb as the permanent modifier and Pd as the chemical modifier, the optimal temperatures were 900°C and 1800°C for pyrolysis and atomization, respectively. Under optimum conditions, the working range was from 1.73 to 50.0 μg L(-1), with detection and quantification limits of 0.20 and 0.34 μg g(-1), respectively. The precision was evaluated under conditions of repeatability and intermediate precision and showed standard deviations of 2.37%-4.61% and 4.93%-9.75%, respectively. The % recovery ranged from 96.2% to 109%, and no significant differences were found between the results obtained using the proposed method and the microwave decomposition method for real samples. Lead was detected in 21 tested lipstick samples; the lead content in these samples ranged from 0.27 to 4.54 μg g(-1). Copyright © 2012 Elsevier B.V. All rights reserved.

Optimal Magnetic Sensor Vests for Cardiac Source Imaging

PubMed Central

Lau, Stephan; Petković, Bojana; Haueisen, Jens

2016-01-01

Magnetocardiography (MCG) non-invasively provides functional information about the heart. New room-temperature magnetic field sensors, specifically magnetoresistive and optically pumped magnetometers, have reached sensitivities in the ultra-low range of cardiac fields while allowing for free placement around the human torso. Our aim is to optimize positions and orientations of such magnetic sensors in a vest-like arrangement for robust reconstruction of the electric current distributions in the heart. We optimized a set of 32 sensors on the surface of a torso model with respect to a 13-dipole cardiac source model under noise-free conditions. The reconstruction robustness was estimated by the condition of the lead field matrix. Optimization improved the condition of the lead field matrix by approximately two orders of magnitude compared to a regular array at the front of the torso. Optimized setups exhibited distributions of sensors over the whole torso with denser sampling above the heart at the front and back of the torso. Sensors close to the heart were arranged predominantly tangential to the body surface. The optimized sensor setup could facilitate the definition of a standard for sensor placement in MCG and the development of a wearable MCG vest for clinical diagnostics. PMID:27231910

Extreme Trust Region Policy Optimization for Active Object Recognition.

PubMed

Liu, Huaping; Wu, Yupei; Sun, Fuchun; Huaping Liu; Yupei Wu; Fuchun Sun; Sun, Fuchun; Liu, Huaping; Wu, Yupei

2018-06-01

In this brief, we develop a deep reinforcement learning method to actively recognize objects by choosing a sequence of actions for an active camera that helps to discriminate between the objects. The method is realized using trust region policy optimization, in which the policy is realized by an extreme learning machine and, therefore, leads to efficient optimization algorithm. The experimental results on the publicly available data set show the advantages of the developed extreme trust region optimization method.

Optimizing Teleportation Cost in Distributed Quantum Circuits

NASA Astrophysics Data System (ADS)

Zomorodi-Moghadam, Mariam; Houshmand, Mahboobeh; Houshmand, Monireh

2018-03-01

The presented work provides a procedure for optimizing the communication cost of a distributed quantum circuit (DQC) in terms of the number of qubit teleportations. Because of technology limitations which do not allow large quantum computers to work as a single processing element, distributed quantum computation is an appropriate solution to overcome this difficulty. Previous studies have applied ad-hoc solutions to distribute a quantum system for special cases and applications. In this study, a general approach is proposed to optimize the number of teleportations for a DQC consisting of two spatially separated and long-distance quantum subsystems. To this end, different configurations of locations for executing gates whose qubits are in distinct subsystems are considered and for each of these configurations, the proposed algorithm is run to find the minimum number of required teleportations. Finally, the configuration which leads to the minimum number of teleportations is reported. The proposed method can be used as an automated procedure to find the configuration with the optimal communication cost for the DQC. This cost can be used as a basic measure of the communication cost for future works in the distributed quantum circuits.

A probabilistic method for the estimation of residual risk in donated blood.

PubMed

Bish, Ebru K; Ragavan, Prasanna K; Bish, Douglas R; Slonim, Anthony D; Stramer, Susan L

2014-10-01

The residual risk (RR) of transfusion-transmitted infections, including the human immunodeficiency virus and hepatitis B and C viruses, is typically estimated by the incidence[Formula: see text]window period model, which relies on the following restrictive assumptions: Each screening test, with probability 1, (1) detects an infected unit outside of the test's window period; (2) fails to detect an infected unit within the window period; and (3) correctly identifies an infection-free unit. These assumptions need not hold in practice due to random or systemic errors and individual variations in the window period. We develop a probability model that accurately estimates the RR by relaxing these assumptions, and quantify their impact using a published cost-effectiveness study and also within an optimization model. These assumptions lead to inaccurate estimates in cost-effectiveness studies and to sub-optimal solutions in the optimization model. The testing solution generated by the optimization model translates into fewer expected infections without an increase in the testing cost. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

PubMed

Hager, Rebecca; Tsiatis, Anastasios A; Davidian, Marie

2018-05-18

Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment options at each decision point, and thus formalizes this process. An optimal regime is one leading to the most beneficial outcome on average if used to select treatment for the patient population. We propose a method for estimation of an optimal regime involving two decision points when the outcome of interest is a censored survival time, which is based on maximizing a locally efficient, doubly robust, augmented inverse probability weighted estimator for average outcome over a class of regimes. By casting this optimization as a classification problem, we exploit well-studied classification techniques such as support vector machines to characterize the class of regimes and facilitate implementation via a backward iterative algorithm. Simulation studies of performance and application of the method to data from a sequential, multiple assignment randomized clinical trial in acute leukemia are presented. © 2018, The International Biometric Society.

Convergence analysis of evolutionary algorithms that are based on the paradigm of information geometry.

PubMed

Beyer, Hans-Georg

2014-01-01

The convergence behaviors of so-called natural evolution strategies (NES) and of the information-geometric optimization (IGO) approach are considered. After a review of the NES/IGO ideas, which are based on information geometry, the implications of this philosophy w.r.t. optimization dynamics are investigated considering the optimization performance on the class of positive quadratic objective functions (the ellipsoid model). Exact differential equations describing the approach to the optimizer are derived and solved. It is rigorously shown that the original NES philosophy optimizing the expected value of the objective functions leads to very slow (i.e., sublinear) convergence toward the optimizer. This is the real reason why state of the art implementations of IGO algorithms optimize the expected value of transformed objective functions, for example, by utility functions based on ranking. It is shown that these utility functions are localized fitness functions that change during the IGO flow. The governing differential equations describing this flow are derived. In the case of convergence, the solutions to these equations exhibit an exponentially fast approach to the optimizer (i.e., linear convergence order). Furthermore, it is proven that the IGO philosophy leads to an adaptation of the covariance matrix that equals in the asymptotic limit-up to a scalar factor-the inverse of the Hessian of the objective function considered.

A multi-objective simulation-optimization model for in situ bioremediation of groundwater contamination: Application of bargaining theory

NASA Astrophysics Data System (ADS)

Raei, Ehsan; Nikoo, Mohammad Reza; Pourshahabi, Shokoufeh

2017-08-01

In the present study, a BIOPLUME III simulation model is coupled with a non-dominating sorting genetic algorithm (NSGA-II)-based model for optimal design of in situ groundwater bioremediation system, considering preferences of stakeholders. Ministry of Energy (MOE), Department of Environment (DOE), and National Disaster Management Organization (NDMO) are three stakeholders in the groundwater bioremediation problem in Iran. Based on the preferences of these stakeholders, the multi-objective optimization model tries to minimize: (1) cost; (2) sum of contaminant concentrations that violate standard; (3) contaminant plume fragmentation. The NSGA-II multi-objective optimization method gives Pareto-optimal solutions. A compromised solution is determined using fallback bargaining with impasse to achieve a consensus among the stakeholders. In this study, two different approaches are investigated and compared based on two different domains for locations of injection and extraction wells. At the first approach, a limited number of predefined locations is considered according to previous similar studies. At the second approach, all possible points in study area are investigated to find optimal locations, arrangement, and flow rate of injection and extraction wells. Involvement of the stakeholders, investigating all possible points instead of a limited number of locations for wells, and minimizing the contaminant plume fragmentation during bioremediation are new innovations in this research. Besides, the simulation period is divided into smaller time intervals for more efficient optimization. Image processing toolbox in MATLAB® software is utilized for calculation of the third objective function. In comparison with previous studies, cost is reduced using the proposed methodology. Dispersion of the contaminant plume is reduced in both presented approaches using the third objective function. Considering all possible points in the study area for determining the optimal locations of the wells in the second approach leads to more desirable results, i.e. decreasing the contaminant concentrations to a standard level and 20% to 40% cost reduction.

Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong

2018-01-01

Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.

SAR Studies on Trisubstituted Benzimidazoles as Inhibitors of Mtb FtsZ for the Development of Novel Antitubercular Agents

PubMed Central

Awasthi, Divya; Kumar, Kunal; Knudson, Susan E.; Slayden, Richard A.; Ojima, Iwao

2014-01-01

FtsZ, an essential protein for bacterial cell division, is a highly promising therapeutic target, especially for the discovery and development of new-generation anti-TB agents. Following up the identification of two lead 2,5,6-trisubstituted benzimidazoles, 1 and 2, targeting Mtb-FtsZ in our previous study, an extensive SAR study for optimization of these lead compounds was performed through systematic modification of the 5 and 6 positions. This study has successfully led to the discovery of a highly potent advanced lead 5f (MIC 0.06 µg/mL) and several other compounds with comparable potencies. These advanced lead compounds possess a dimethylamino group at the 6 position. The functional groups at the 5 position exhibit substantial effects on the antibacterial activity as well. In vitro experiments such as the FtsZ polymerization inhibitory assay and TEM analysis of Mtb-FtsZ treated with 5f and others indicate that Mtb-FtsZ is the molecular target for their antibacterial activity. PMID:24266862

SAR studies on trisubstituted benzimidazoles as inhibitors of Mtb FtsZ for the development of novel antitubercular agents.

PubMed

Awasthi, Divya; Kumar, Kunal; Knudson, Susan E; Slayden, Richard A; Ojima, Iwao

2013-12-12

FtsZ, an essential protein for bacterial cell division, is a highly promising therapeutic target, especially for the discovery and development of new-generation anti-TB agents. Following up the identification of two lead 2,5,6-trisubstituted benzimidazoles, 1 and 2, targeting Mtb-FtsZ in our previous study, an extensive SAR study for optimization of these lead compounds was performed through systematic modification of the 5 and 6 positions. This study has successfully led to the discovery of a highly potent advanced lead 5f (MIC = 0.06 μg/mL) and several other compounds with comparable potencies. These advanced lead compounds possess a dimethylamino group at the 6 position. The functional groups at the 5 position exhibit substantial effects on the antibacterial activity as well. In vitro experiments such as the FtsZ polymerization inhibitory assay and TEM analysis of Mtb-FtsZ treated with 5f and others indicate that Mtb-FtsZ is the molecular target for their antibacterial activity.

Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods.

PubMed

Suleimanov, Yury V; Green, William H

2015-09-08

We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation double- and single-ended transition-state optimization algorithms--the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several single-molecule systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not only "known" reaction pathways, manually detected in the previous studies, but also new, previously "unknown", reaction pathways which involve significant atom rearrangements. We believe that applying such a systematic approach to elementary reaction path finding will greatly accelerate the discovery of new chemistry and will lead to more accurate computer simulations of various chemical processes.

Broken symmetry in a two-qubit quantum control landscape

NASA Astrophysics Data System (ADS)

Bukov, Marin; Day, Alexandre G. R.; Weinberg, Phillip; Polkovnikov, Anatoli; Mehta, Pankaj; Sels, Dries

2018-05-01

We analyze the physics of optimal protocols to prepare a target state with high fidelity in a symmetrically coupled two-qubit system. By varying the protocol duration, we find a discontinuous phase transition, which is characterized by a spontaneous breaking of a Z2 symmetry in the functional form of the optimal protocol, and occurs below the quantum speed limit. We study in detail this phase and demonstrate that even though high-fidelity protocols come degenerate with respect to their fidelity, they lead to final states of different entanglement entropy shared between the qubits. Consequently, while globally both optimal protocols are equally far away from the target state, one is locally closer than the other. An approximate variational mean-field theory which captures the physics of the different phases is developed.

Linear energy transfer incorporated intensity modulated proton therapy optimization

NASA Astrophysics Data System (ADS)

Cao, Wenhua; Khabazian, Azin; Yepes, Pablo P.; Lim, Gino; Poenisch, Falk; Grosshans, David R.; Mohan, Radhe

2018-01-01

The purpose of this study was to investigate the feasibility of incorporating linear energy transfer (LET) into the optimization of intensity modulated proton therapy (IMPT) plans. Because increased LET correlates with increased biological effectiveness of protons, high LETs in target volumes and low LETs in critical structures and normal tissues are preferred in an IMPT plan. However, if not explicitly incorporated into the optimization criteria, different IMPT plans may yield similar physical dose distributions but greatly different LET, specifically dose-averaged LET, distributions. Conventionally, the IMPT optimization criteria (or cost function) only includes dose-based objectives in which the relative biological effectiveness (RBE) is assumed to have a constant value of 1.1. In this study, we added LET-based objectives for maximizing LET in target volumes and minimizing LET in critical structures and normal tissues. Due to the fractional programming nature of the resulting model, we used a variable reformulation approach so that the optimization process is computationally equivalent to conventional IMPT optimization. In this study, five brain tumor patients who had been treated with proton therapy at our institution were selected. Two plans were created for each patient based on the proposed LET-incorporated optimization (LETOpt) and the conventional dose-based optimization (DoseOpt). The optimized plans were compared in terms of both dose (assuming a constant RBE of 1.1 as adopted in clinical practice) and LET. Both optimization approaches were able to generate comparable dose distributions. The LET-incorporated optimization achieved not only pronounced reduction of LET values in critical organs, such as brainstem and optic chiasm, but also increased LET in target volumes, compared to the conventional dose-based optimization. However, on occasion, there was a need to tradeoff the acceptability of dose and LET distributions. Our conclusion is that the inclusion of LET-dependent criteria in the IMPT optimization could lead to similar dose distributions as the conventional optimization but superior LET distributions in target volumes and normal tissues. This may have substantial advantages in improving tumor control and reducing normal tissue toxicities.

Optimal ciliary beating patterns

NASA Astrophysics Data System (ADS)

Vilfan, Andrej; Osterman, Natan

2011-11-01

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

Image gathering and processing - Information and fidelity

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Halyo, N.; Samms, R. W.; Stacy, K.

1985-01-01

In this paper we formulate and use information and fidelity criteria to assess image gathering and processing, combining optical design with image-forming and edge-detection algorithms. The optical design of the image-gathering system revolves around the relationship among sampling passband, spatial response, and signal-to-noise ratio (SNR). Our formulations of information, fidelity, and optimal (Wiener) restoration account for the insufficient sampling (i.e., aliasing) common in image gathering as well as for the blurring and noise that conventional formulations account for. Performance analyses and simulations for ordinary optical-design constraints and random scences indicate that (1) different image-forming algorithms prefer different optical designs; (2) informationally optimized designs maximize the robustness of optimal image restorations and lead to the highest-spatial-frequency channel (relative to the sampling passband) for which edge detection is reliable (if the SNR is sufficiently high); and (3) combining the informationally optimized design with a 3 by 3 lateral-inhibitory image-plane-processing algorithm leads to a spatial-response shape that approximates the optimal edge-detection response of (Marr's model of) human vision and thus reduces the data preprocessing and transmission required for machine vision.

Lead detection using micro/nanocrystalline boron-doped diamond by square-wave anodic stripping voltammetry.

PubMed

Arantes, Tatiane M; Sardinha, André; Baldan, Mauricio R; Cristovan, Fernando H; Ferreira, Neidenei G

2014-10-01

Monitoring heavy metal ion levels in water is essential for human health and safety. Electroanalytical techniques have presented important features to detect toxic trace heavy metals in the environment due to their high sensitivity associated with their easy operational procedures. Square-wave voltammetry is a powerful electrochemical technique that may be applied to both electrokinetic and analytical measurements, and the analysis of the characteristic parameters of this technique also enables the mechanism and kinetic evaluation of the electrochemical process under study. In this work, we present a complete optimized study on the heavy metal detection using diamond electrodes. It was analyzed the influence of the morphology characteristics as well as the doping level on micro/nanocrystalline boron-doped diamond films by means of square-wave anodic stripping voltammetry (SWASV) technique. The SWASV parameters were optimized for all films, considering that their kinetic response is dependent on the morphology and/or doping level. The films presented reversible results for the Lead [Pb (II)] system studied. The Pb (II) analysis was performed in ammonium acetate buffer at pH 4.5, varying the lead concentration in the range from 1 to 10 μg L(-1). The analytical responses were obtained for the four electrodes. However, the best low limit detection and reproducibility was found for boron doped nanocrystalline diamond electrodes (BDND) doped with 2000 mg L(-1) in B/C ratio. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimization of laccase production from Marasmiellus palmivorus LA1 by Taguchi method of Design of experiments.

PubMed

Chenthamarakshan, Aiswarya; Parambayil, Nayana; Miziriya, Nafeesathul; Soumya, P S; Lakshmi, M S Kiran; Ramgopal, Anala; Dileep, Anuja; Nambisan, Padma

2017-02-13

Fungal laccase has profound applications in different fields of biotechnology due to its broad specificity and high redox potential. Any successful application of the enzyme requires large scale production. As laccase production is highly dependent on medium components and cultural conditions, optimization of the same is essential for efficient product production. Production of laccase by fungal strain Marasmiellus palmivorus LA1 under solid state fermentation was optimized by the Taguchi design of experiments (DOE) methodology. An orthogonal array (L8) was designed using Qualitek-4 software to study the interactions and relative influence of the seven selected factors by one factor at a time approach. The optimum condition formulated was temperature (28 °C), pH (5), galactose (0.8%w/v), cupric sulphate (3 mM), inoculum concentration (number of mycelial agar pieces) (6Nos.) and substrate length (0.05 m). Overall yield increase of 17.6 fold was obtained after optimization. Statistical optimization leads to the elimination of an insignificant medium component ammonium dihydrogen phosphate from the process and contributes to a 1.06 fold increase in enzyme production. A final production of 667.4 ± 13 IU/mL laccase activity paves way for the application of this strain for industrial applications. Study optimized lignin degrading laccases from Marasmiellus palmivorus LA1. This laccases can thus be used for further applications in different scales of production after analyzing the properties of the enzyme. Study also confirmed the use of taguchi method for optimizations of product production.

Design Optimization of Hybrid FRP/RC Bridge

NASA Astrophysics Data System (ADS)

Papapetrou, Vasileios S.; Tamijani, Ali Y.; Brown, Jeff; Kim, Daewon

2018-04-01

The hybrid bridge consists of a Reinforced Concrete (RC) slab supported by U-shaped Fiber Reinforced Polymer (FRP) girders. Previous studies on similar hybrid bridges constructed in the United States and Europe seem to substantiate these hybrid designs for lightweight, high strength, and durable highway bridge construction. In the current study, computational and optimization analyses were carried out to investigate six composite material systems consisting of E-glass and carbon fibers. Optimization constraints are determined by stress, deflection and manufacturing requirements. Finite Element Analysis (FEA) and optimization software were utilized, and a framework was developed to run the complete analyses in an automated fashion. Prior to that, FEA validation of previous studies on similar U-shaped FRP girders that were constructed in Poland and Texas is presented. A finer optimization analysis is performed for the case of the Texas hybrid bridge. The optimization outcome of the hybrid FRP/RC bridge shows the appropriate composite material selection and cross-section geometry that satisfies all the applicable Limit States (LS) and, at the same time, results in the lightest design. Critical limit states show that shear stress criteria determine the optimum design for bridge spans less than 15.24 m and deflection criteria controls for longer spans. Increased side wall thickness can reduce maximum observed shear stresses, but leads to a high weight penalty. A taller cross-section and a thicker girder base can efficiently lower the observed deflections and normal stresses. Finally, substantial weight savings can be achieved by the optimization framework if base and side-wall thickness are treated as independent variables.

Tailor-made heart simulation predicts the effect of cardiac resynchronization therapy in a canine model of heart failure.

PubMed

Panthee, Nirmal; Okada, Jun-ichi; Washio, Takumi; Mochizuki, Youhei; Suzuki, Ryohei; Koyama, Hidekazu; Ono, Minoru; Hisada, Toshiaki; Sugiura, Seiryo

2016-07-01

Despite extensive studies on clinical indices for the selection of patient candidates for cardiac resynchronization therapy (CRT), approximately 30% of selected patients do not respond to this therapy. Herein, we examined whether CRT simulations based on individualized realistic three-dimensional heart models can predict the therapeutic effect of CRT in a canine model of heart failure with left bundle branch block. In four canine models of failing heart with dyssynchrony, individualized three-dimensional heart models reproducing the electromechanical activity of each animal were created based on the computer tomographic images. CRT simulations were performed for 25 patterns of three ventricular pacing lead positions. Lead positions producing the best and the worst therapeutic effects were selected in each model. The validity of predictions was tested in acute experiments in which hearts were paced from the sites identified by simulations. We found significant correlations between the experimentally observed improvement in ejection fraction (EF) and the predicted improvements in ejection fraction (P<0.01) or the maximum value of the derivative of left ventricular pressure (P<0.01). The optimal lead positions produced better outcomes compared with the worst positioning in all dogs studied, although there were significant variations in responses. Variations in ventricular wall thickness among the dogs may have contributed to these responses. Thus CRT simulations using the individualized three-dimensional heart models can predict acute hemodynamic improvement, and help determine the optimal positions of the pacing lead. Copyright © 2016 Elsevier B.V. All rights reserved.

An Insoluble Titanium-Lead Anode for Sulfate Electrolytes

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

Ferdman, Alla

2005-05-11

The project is devoted to the development of novel insoluble anodes for copper electrowinning and electrolytic manganese dioxide (EMD) production. The anodes are made of titanium-lead composite material produced by techniques of powder metallurgy, compaction of titanium powder, sintering and subsequent lead infiltration. The titanium-lead anode combines beneficial electrochemical behavior of a lead anode with high mechanical properties and corrosion resistance of a titanium anode. In the titanium-lead anode, the titanium stabilizes the lead, preventing it from spalling, and the lead sheathes the titanium, protecting it from passivation. Interconnections between manufacturing process, structure, composition and properties of the titanium-lead compositemore » material were investigated. The material containing 20-30 vol.% of lead had optimal combination of mechanical and electrochemical properties. Optimal process parameters to manufacture the anodes were identified. Prototypes having optimized composition and structure were produced for testing in operating conditions of copper electrowinning and EMD production. Bench-scale, mini-pilot scale and pilot scale tests were performed. The test anodes were of both a plate design and a flow-through cylindrical design. The cylindrical anodes were composed of cylinders containing titanium inner rods and fitting over titanium-lead bushings. The cylindrical design allows the electrolyte to flow through the anode, which enhances diffusion of the electrolyte reactants. The cylindrical anodes demonstrate higher mass transport capabilities and increased electrical efficiency compared to the plate anodes. Copper electrowinning represents the primary target market for the titanium-lead anode. A full-size cylindrical anode performance in copper electrowinning conditions was monitored over a year. The test anode to cathode voltage was stable in the 1.8 to 2.0 volt range. Copper cathode morphology was very smooth and uniform. There was no measurable anode weight loss during this time period. Quantitative chemical analysis of the anode surface showed that the lead content after testing remained at its initial level. No lead dissolution or transfer from the anode to the product occurred.A key benefit of the titanium-lead anode design is that cobalt additions to copper electrolyte should be eliminated. Cobalt is added to the electrolyte to help stabilize the lead oxide surface of conventional lead anodes. The presence of the titanium intimately mixed with the lead should eliminate the need for cobalt stabilization of the lead surface. The anode should last twice as long as the conventional lead anode. Energy savings should be achieved due to minimizing and stabilizing the anode-cathode distance in the electrowinning cells. The anode is easily substitutable into existing tankhouses without a rectifier change.The copper electrowinning test data indicate that the titanium-lead anode is a good candidate for further testing as a possible replacement for a conventional lead anode. A key consideration is the cost. Titanium costs have increased. One of the ways to get the anode cost down is manufacturing the anodes with fewer cylinders. Additional prototypes having different number of cylinders were constructed for a long-term commercial testing in a circuit without cobalt. The objective of the testing is to evaluate the need for cobalt, investigate the effect of decreasing the number of cylinders on the anode performance, and to optimize further the anode design in order to meet the operating requirements, minimize the voltage, maximize the life of the anode, and to balance this against a reasonable cost for the anode. It is anticipated that after testing of the additional prototypes, a whole cell commercial test will be conducted to complete evaluation of the titanium-lead anode costs/benefits.« less

Identification and hit-to-lead optimization of a novel class of CB1 antagonists.

PubMed

Letourneau, Jeffrey J; Jokiel, Patrick; Olson, John; Riviello, Christopher M; Ho, Koc-Kan; McAleer, Lihong; Yang, Jingchun; Swanson, Robert N; Baker, James; Cowley, Phillip; Edwards, Darren; Ward, Nick; Ohlmeyer, Michael H J; Webb, Maria L

2010-09-15

The discovery, synthesis and preliminary structure-activity relationships (SARs) of a novel class of CB1 antagonists is described. Initial optimization of benzimidazole-based screening hit 4 led to the identification of 'inverted' indole-based lead compound 18c with improved properties versus compound 4 including reduced AlogP, improved microsomal stability and improved aqueous solubility. Compound 18c demonstrates in vivo CB1 antagonist efficacy (CB1 agonist induced hypothermia model) and is orally bioavailable in rat. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

The application of defaults to optimize parents' health-based choices for children.

PubMed

Loeb, Katharine L; Radnitz, Cynthia; Keller, Kathleen; Schwartz, Marlene B; Marcus, Sue; Pierson, Richard N; Shannon, Michael; DeLaurentis, Danielle

2017-06-01

Optimal defaults is a compelling model from behavioral economics and the psychology of human decision-making, designed to shape or "nudge" choices in a positive direction without fundamentally restricting options. The current study aimed to test the effectiveness of optimal (less obesogenic) defaults and parent empowerment priming on health-based decisions with parent-child (ages 3-8) dyads in a community-based setting. Two proof-of-concept experiments (one on breakfast food selections and one on activity choice) were conducted comparing the main and interactive effects of optimal versus suboptimal defaults, and parent empowerment priming versus neutral priming, on parents' health-related choices for their children. We hypothesized that in each experiment, making the default option more optimal will lead to more frequent health-oriented choices, and that priming parents to be the ultimate decision-makers on behalf of their child's health will potentiate this effect. Results show that in both studies, default condition, but not priming condition or the interaction between default and priming, significantly predicted choice (healthier vs. less healthy option). There was also a significant main effect for default condition (and no effect for priming condition or the interaction term) on the quantity of healthier food children consumed in the breakfast experiment. These pilot studies demonstrate that optimal defaults can be practicably implemented to improve parents' food and activity choices for young children. Results can inform policies and practices pertaining to obesogenic environmental factors in school, restaurant, and home environments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimizing conservation practices in watersheds: Do community preferences matter?

NASA Astrophysics Data System (ADS)

Piemonti, Adriana D.; Babbar-Sebens, Meghna; Jane Luzar, E.

2013-10-01

This paper focuses on investigating (a) how landowner tenure and attitudes of farming communities affect the preference of individual conservation practices in agricultural watersheds, (b) how spatial distribution of landowner tenure affects the spatial optimization of conservation practices on a watershed scale, and (c) how the different attitudes and preferences of stakeholders can modify the effectiveness of alternatives obtained via classic optimization approaches that do not include the influence of existing social attitudes in a watershed during the search process. Results show that for Eagle Creek Watershed in central Indiana, USA, the most optimal alternatives (i.e., highest benefits for minimum economic costs) are for a scenario when the watershed consists of landowners who operate as farmers on their own land. When a different land-tenure scenario was used for the watershed (e.g., share renters and cash renters), the optimized alternatives had similar nitrate reduction benefits and sediment reduction benefits, but at higher economic costs. Our experiments also demonstrated that social attitudes can lead to alteration of optimized alternatives found via typical optimization approaches. For example, when certain practices were rejected by landowner operators whose attitudes toward practices were driven by economic profits, removal of these practices from the optimized alternatives led to a setback of nitrates reduction by 2-50%, peak flow reductions by 11-98 %, and sediments reduction by 20-77%. In conclusion, this study reveals the potential loss in optimality of optimized alternatives possible, when socioeconomic data on farmer preferences and land tenure are not incorporated within watershed optimization investigations.

On a New Optimization Approach for the Hydroforming of Defects-Free Tubular Metallic Parts

NASA Astrophysics Data System (ADS)

Caseiro, J. F.; Valente, R. A. F.; Andrade-Campos, A.; Jorge, R. M. Natal

2011-05-01

In the hydroforming of tubular metallic components, process parameters (internal pressure, axial feed and counter-punch position) must be carefully set in order to avoid defects in the final part. If, on one hand, excessive pressure may lead to thinning and bursting during forming, on the other hand insufficient pressure may lead to an inadequate filling of the die. Similarly, an excessive axial feeding may lead to the formation of wrinkles, whilst an inadequate one may cause thinning and, consequentially, bursting. These apparently contradictory targets are virtually impossible to achieve without trial-and-error procedures in industry, unless optimization approaches are formulated and implemented for complex parts. In this sense, an optimization algorithm based on differentialevolutionary techniques is presented here, capable of being applied in the determination of the adequate process parameters for the hydroforming of metallic tubular components of complex geometries. The Hybrid Differential Evolution Particle Swarm Optimization (HDEPSO) algorithm, combining the advantages of a number of well-known distinct optimization strategies, acts along with a general purpose implicit finite element software, and is based on the definition of a wrinkling and thinning indicators. If defects are detected, the algorithm automatically corrects the process parameters and new numerical simulations are performed in real time. In the end, the algorithm proved to be robust and computationally cost-effective, thus providing a valid design tool for the conformation of defects-free components in industry [1].

Design and development of bio-inspired framework for reservoir operation optimization

NASA Astrophysics Data System (ADS)

Asvini, M. Sakthi; Amudha, T.

2017-12-01

Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

Factorization and the synthesis of optimal feedback kernels for differential-delay systems

NASA Technical Reports Server (NTRS)

Milman, Mark M.; Scheid, Robert E.

1987-01-01

A combination of ideas from the theories of operator Riccati equations and Volterra factorizations leads to the derivation of a novel, relatively simple set of hyperbolic equations which characterize the optimal feedback kernel for the finite-time regulator problem for autonomous differential-delay systems. Analysis of these equations elucidates the underlying structure of the feedback kernel and leads to the development of fast and accurate numerical methods for its computation. Unlike traditional formulations based on the operator Riccati equation, the gain is characterized by means of classical solutions of the derived set of equations. This leads to the development of approximation schemes which are analogous to what has been accomplished for systems of ordinary differential equations with given initial conditions.

Optimization of cathodic arc deposition and pulsed plasma melting techniques for growing smooth superconducting Pb photoemissive films for SRF injectors

DOE PAGES

Nietubyc, Robert; Lorkiewicz, Jerzy; Sekutowicz, Jacek; ...

2018-02-14

Superconducting photoinjectors have a potential to be the optimal solution for moderate and high current cw operating free electron lasers. For this application, a superconducting lead (Pb) cathode has been proposed to simplify the cathode integration into a 1.3 GHz, TESLA-type, 1.6-cell long purely superconducting gun cavity. In the proposed design, a lead film several micrometres thick is deposited onto a niobium plug attached to the cavity back wall. Traditional lead deposition techniques usually produce very non-uniform emission surfaces and often result in a poor adhesion of the layer. A pulsed plasma melting procedure reducing the non-uniformity of the leadmore » photocathodes is presented. In order to determine the parameters optimal for this procedure, heat transfer from plasma to the film was first modelled to evaluate melting front penetration range and liquid state duration. The obtained results were verified by surface inspection of witness samples. The optimal procedure was used to prepare a photocathode plug, which was then tested in an electron gun. In conclusion, the quantum efficiency and the value of cavity quality factor have been found to satisfy the requirements for an injector of the European-XFEL facility.« less

Optimization of cathodic arc deposition and pulsed plasma melting techniques for growing smooth superconducting Pb photoemissive films for SRF injectors

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

Nietubyc, Robert; Lorkiewicz, Jerzy; Sekutowicz, Jacek

Superconducting photoinjectors have a potential to be the optimal solution for moderate and high current cw operating free electron lasers. For this application, a superconducting lead (Pb) cathode has been proposed to simplify the cathode integration into a 1.3 GHz, TESLA-type, 1.6-cell long purely superconducting gun cavity. In the proposed design, a lead film several micrometres thick is deposited onto a niobium plug attached to the cavity back wall. Traditional lead deposition techniques usually produce very non-uniform emission surfaces and often result in a poor adhesion of the layer. A pulsed plasma melting procedure reducing the non-uniformity of the leadmore » photocathodes is presented. In order to determine the parameters optimal for this procedure, heat transfer from plasma to the film was first modelled to evaluate melting front penetration range and liquid state duration. The obtained results were verified by surface inspection of witness samples. The optimal procedure was used to prepare a photocathode plug, which was then tested in an electron gun. In conclusion, the quantum efficiency and the value of cavity quality factor have been found to satisfy the requirements for an injector of the European-XFEL facility.« less

Image-guided optimization of the ECG trace in cardiac MRI.

PubMed

Barnwell, James D; Klein, J Larry; Stallings, Cliff; Sturm, Amanda; Gillespie, Michael; Fine, Jason; Hyslop, W Brian

2012-03-01

Improper electrocardiogram (ECG) lead placement resulting in suboptimal gating may lead to reduced image quality in cardiac magnetic resonance imaging (CMR). A patientspecific systematic technique for rapid optimization of lead placement may improve CMR image quality. A rapid 3 dimensional image of the thorax was used to guide the realignment of ECG leads relative to the cardiac axis of the patient in forty consecutive adult patients. Using our novel approach and consensus reading of pre- and post-correction ECG traces, seventy-three percent of patients had a qualitative improvement in their ECG tracings, and no patient had a decrease in quality of their ECG tracing following the correction technique. Statistically significant improvement was observed independent of gender, body mass index, and cardiac rhythm. This technique provides an efficient option to improve the quality of the ECG tracing in patients who have a poor quality ECG with standard techniques.

Optimization of spin-torque switching using AC and DC pulses

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

Dunn, Tom; Kamenev, Alex; Fine Theoretical Physics Institute, University of Minnesota, Minneapolis, Minnesota 55455

2014-06-21

We explore spin-torque induced magnetic reversal in magnetic tunnel junctions using combined AC and DC spin-current pulses. We calculate the optimal pulse times and current strengths for both AC and DC pulses as well as the optimal AC signal frequency, needed to minimize the Joule heat lost during the switching process. The results of this optimization are compared against numeric simulations. Finally, we show how this optimization leads to different dynamic regimes, where switching is optimized by either a purely AC or DC spin-current, or a combination AC/DC spin-current, depending on the anisotropy energies and the spin-current polarization.

WE-H-207A-03: The Universality of the Lognormal Behavior of [F-18]FLT PET SUV Measurements

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

Scarpelli, M; Eickhoff, J; Perlman, S

Purpose: Log transforming [F-18]FDG PET standardized uptake values (SUVs) has been shown to lead to normal SUV distributions, which allows utilization of powerful parametric statistical models. This study identified the optimal transformation leading to normally distributed [F-18]FLT PET SUVs from solid tumors and offers an example of how normal distributions permits analysis of non-independent/correlated measurements. Methods: Forty patients with various metastatic diseases underwent up to six FLT PET/CT scans during treatment. Tumors were identified by nuclear medicine physician and manually segmented. Average uptake was extracted for each patient giving a global SUVmean (gSUVmean) for each scan. The Shapiro-Wilk test wasmore » used to test distribution normality. One parameter Box-Cox transformations were applied to each of the six gSUVmean distributions and the optimal transformation was found by selecting the parameter that maximized the Shapiro-Wilk test statistic. The relationship between gSUVmean and a serum biomarker (VEGF) collected at imaging timepoints was determined using a linear mixed effects model (LMEM), which accounted for correlated/non-independent measurements from the same individual. Results: Untransformed gSUVmean distributions were found to be significantly non-normal (p<0.05). The optimal transformation parameter had a value of 0.3 (95%CI: −0.4 to 1.6). Given the optimal parameter was close to zero (which corresponds to log transformation), the data were subsequently log transformed. All log transformed gSUVmean distributions were normally distributed (p>0.10 for all timepoints). Log transformed data were incorporated into the LMEM. VEGF serum levels significantly correlated with gSUVmean (p<0.001), revealing log-linear relationship between SUVs and underlying biology. Conclusion: Failure to account for correlated/non-independent measurements can lead to invalid conclusions and motivated transformation to normally distributed SUVs. The log transformation was found to be close to optimal and sufficient for obtaining normally distributed FLT PET SUVs. These transformations allow utilization of powerful LMEMs when analyzing quantitative imaging metrics.« less

Transonic Wing Shape Optimization Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.; Kwak, Dochan (Technical Monitor)

2002-01-01

A method for aerodynamic shape optimization based on a genetic algorithm approach is demonstrated. The algorithm is coupled with a transonic full potential flow solver and is used to optimize the flow about transonic wings including multi-objective solutions that lead to the generation of pareto fronts. The results indicate that the genetic algorithm is easy to implement, flexible in application and extremely reliable.

Memo Addressing Lead and Copper Rule Requirements for Optimal Corrosion Control Treatment

EPA Pesticide Factsheets

EPA has recently published a memo to address the requirements pertaining to maintenance of optimal corrosion control treatment, in situations in which a large water system ceases to purchase treated water and switches to a new drinking water source.

Optimization on Fc for Improvement of Stability and Aggregation Resistance.

PubMed

Chen, Xiaobo; Zeng, Fang; Huang, Tao; Cheng, Liang; Liu, Huan; Gong, Rui

2016-01-01

Fc-based therapeutics including therapeutic full-size monoclonal antibodies (mAbs) and Fcfusion proteins represent fastest-growing market in biopharmaceutical industrial. However, one major challenge during development of Fc-based therapeutics is how to maintain their efficacy in clinic use. Many factors may lead to failure in final marketing. For example, the stability and aggregation resistance might not be high enough for bearing the disadvantages during fermentation, purification, formulation, storage, shipment and other steps in manufacture and sale. Low stability and high aggregation tendency lead to decreased bioactivity and increased risk of immunogenicity resulting in serious side effect. Because Fc is one of the major parts in monoclonal antibodies and Fc-fusion proteins, engineering of Fc to increase its stability and reduce or eliminate aggregation due to incorrect association are of great importance and could further extend the potential of Fc-based therapeutics. Lots of studies focus on Fc optimization for better physical and chemical characteristics and function by structured-based computer-aid rational design, high-throughput screening expression system selection and other methods. The identification of optimized Fc mutants increases the clinic potential of currently existed therapeutics mAbs and Fc-fusion proteins, and accelerates the development of new Fc-based therapeutics. Here we provide an overview of the related field, and discuss recent advances and future directions in optimization of Fc-based therapeutics with modified stability and aggregation resistance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The benefit of using additional hydrological information from earth observations and reanalysis data on water allocation decisions in irrigation districts

NASA Astrophysics Data System (ADS)

Kaune, Alexander; López, Patricia; Werner, Micha; de Fraiture, Charlotte

2017-04-01

Hydrological information on water availability and demand is vital for sound water allocation decisions in irrigation districts, particularly in times of water scarcity. However, sub-optimal water allocation decisions are often taken with incomplete hydrological information, which may lead to agricultural production loss. In this study we evaluate the benefit of additional hydrological information from earth observations and reanalysis data in supporting decisions in irrigation districts. Current water allocation decisions were emulated through heuristic operational rules for water scarce and water abundant conditions in the selected irrigation districts. The Dynamic Water Balance Model based on the Budyko framework was forced with precipitation datasets from interpolated ground measurements, remote sensing and reanalysis data, to determine the water availability for irrigation. Irrigation demands were estimated based on estimates of potential evapotranspiration and coefficient for crops grown, adjusted with the interpolated precipitation data. Decisions made using both current and additional hydrological information were evaluated through the rate at which sub-optimal decisions were made. The decisions made using an amended set of decision rules that benefit from additional information on demand in the districts were also evaluated. Results show that sub-optimal decisions can be reduced in the planning phase through improved estimates of water availability. Where there are reliable observations of water availability through gauging stations, the benefit of the improved precipitation data is found in the improved estimates of demand, equally leading to a reduction of sub-optimal decisions.

Economic optimization of natural hazard protection - conceptual study of existing approaches

NASA Astrophysics Data System (ADS)

Spackova, Olga; Straub, Daniel

2013-04-01

Risk-based planning of protection measures against natural hazards has become a common practice in many countries. The selection procedure aims at identifying an economically efficient strategy with regard to the estimated costs and risk (i.e. expected damage). A correct setting of the evaluation methodology and decision criteria should ensure an optimal selection of the portfolio of risk protection measures under a limited state budget. To demonstrate the efficiency of investments, indicators such as Benefit-Cost Ratio (BCR), Marginal Costs (MC) or Net Present Value (NPV) are commonly used. However, the methodologies for efficiency evaluation differ amongst different countries and different hazard types (floods, earthquakes etc.). Additionally, several inconsistencies can be found in the applications of the indicators in practice. This is likely to lead to a suboptimal selection of the protection strategies. This study provides a general formulation for optimization of the natural hazard protection measures from a socio-economic perspective. It assumes that all costs and risks can be expressed in monetary values. The study regards the problem as a discrete hierarchical optimization, where the state level sets the criteria and constraints, while the actual optimization is made on the regional level (towns, catchments) when designing particular protection measures and selecting the optimal protection level. The study shows that in case of an unlimited budget, the task is quite trivial, as it is sufficient to optimize the protection measures in individual regions independently (by minimizing the sum of risk and cost). However, if the budget is limited, the need for an optimal allocation of resources amongst the regions arises. To ensure this, minimum values of BCR or MC can be required by the state, which must be achieved in each region. The study investigates the meaning of these indicators in the optimization task at the conceptual level and compares their suitability. To illustrate the theoretical findings, the indicators are tested on a hypothetical example of five regions with different risk levels. Last but not least, political and societal aspects and limitations in the use of the risk-based optimization framework are discussed.

The Management of Lead Concentrate Acquisition in "Trepca"

NASA Astrophysics Data System (ADS)

Haxhiaj, Ahmet; Fan, Maoming; Haxhiaj, Bajram

Based on the placement of lead and its consumption in industry branches, the paper deals with the composition of lead in the ores of Kopaonik, grinding and flotation recovery of galena. In the flotation process, the flotation machine, the flotation reagents, chemical composition of the flotation concentrates and tailings were discussed in this paper. Verification of the chemical composition of Pb concentrates with Pb, Zn, and Ag, etc. was conducted in this study. It is special that the ratio of Pb to Zn in Kopaonik massive composition is 1.4:1.0. During the flotation, lead tends to float with concentrate more than allowed. In this investigation, effects have been made to minimize the loss of Pb to concentrates. This paper as such gave the first effects in optimizing of these parameters with positive effects in the flotation process in Trepca.

eWorkbooks for Mathematics: Mapping the Independent Learning Experiences of Elementary Students with Learning Disabilities

ERIC Educational Resources Information Center

Kaczorowski, Tara; Raimondi, Sharon

2014-01-01

In this paper, we describe a small case study exploring how four elementary students with mathematics learning disabilities utilized mobile technology (the eWorkbook) during core math instruction in a general education setting. The lead author designed the eWorkbook intervention to provide a flexible learning experience optimized for diverse…

Vitamin D Status and Optimal Supplementation in Institutionalized Adults with Intellectual Disability

ERIC Educational Resources Information Center

Kilpinen-Loisa, P.; Arvio, M.; Ilvesmaki, V.; Makitie, O.

2009-01-01

Background: Adults with intellectual disability (ID) have several risk factors for osteoporosis. Feeding problems with consequent nutritive deficiencies, and lack of sunshine exposure may lead to vitamin D deficiency. The purpose of this study was to evaluate vitamin D status in adults with ID living in nursing homes and to compare two different…

A Study of Flow Theory in the Foreign Language Classroom

ERIC Educational Resources Information Center

Egbert, Joy

2004-01-01

This article focuses on the relationship between flow experiences and language learning. Flow Theory suggests that flow experiences (characterized by a balance between challenge and skills and by a person's interest, control, and focused attention during a task) can lead to optimal learning. This theory has not yet been tested in the area of…

Optimal control problems of epidemic systems with parameter uncertainties: application to a malaria two-age-classes transmission model with asymptomatic carriers.

PubMed

Mwanga, Gasper G; Haario, Heikki; Capasso, Vicenzo

2015-03-01

The main scope of this paper is to study the optimal control practices of malaria, by discussing the implementation of a catalog of optimal control strategies in presence of parameter uncertainties, which is typical of infectious diseases data. In this study we focus on a deterministic mathematical model for the transmission of malaria, including in particular asymptomatic carriers and two age classes in the human population. A partial qualitative analysis of the relevant ODE system has been carried out, leading to a realistic threshold parameter. For the deterministic model under consideration, four possible control strategies have been analyzed: the use of Long-lasting treated mosquito nets, indoor residual spraying, screening and treatment of symptomatic and asymptomatic individuals. The numerical results show that using optimal control the disease can be brought to a stable disease free equilibrium when all four controls are used. The Incremental Cost-Effectiveness Ratio (ICER) for all possible combinations of the disease-control measures is determined. The numerical simulations of the optimal control in the presence of parameter uncertainty demonstrate the robustness of the optimal control: the main conclusions of the optimal control remain unchanged, even if inevitable variability remains in the control profiles. The results provide a promising framework for the designing of cost-effective strategies for disease controls with multiple interventions, even under considerable uncertainty of model parameters. Copyright © 2014 Elsevier Inc. All rights reserved.

Complaint-adaptive power density optimization as a tool for HTP-guided steering in deep hyperthermia treatment of pelvic tumors

NASA Astrophysics Data System (ADS)

Canters, R. A. M.; Franckena, M.; van der Zee, J.; Van Rhoon, G. C.

2008-12-01

For an efficient clinical use of HTP (hyperthermia treatment planning), optimization methods are needed. In this study, a complaint-adaptive PD (power density) optimization as a tool for HTP-guided steering in deep hyperthermia of pelvic tumors is developed and tested. PD distribution in patients is predicted using FE-models. Two goal functions, Opt1 and Opt2, are applied to optimize PD distributions. Optimization consists of three steps: initial optimization, adaptive optimization after a first complaint and increasing the weight of a region after recurring complaints. Opt1 initially considers only target PD whereas Opt2 also takes into account hot spots. After patient complaints though, both limit PD in a region. Opt1 and Opt2 are evaluated in a phantom test, using patient models and during hyperthermia treatment. The phantom test and a sensitivity study in ten patient models, show that HTP-guided steering is most effective in peripheral complaint regions. Clinical evaluation in two groups of five patients shows that time between complaints is longer using Opt2 (p = 0.007). However, this does not lead to significantly different temperatures (T50s of 40.3 (Opt1) versus 40.1 °C (Opt2) (p = 0.898)). HTP-guided steering is feasible in terms of PD reduction in complaint regions and in time consumption. Opt2 is preferable in future use, because of better complaint reduction and control.

Optimization of Systems with Uncertainty: Initial Developments for Performance, Robustness and Reliability Based Designs

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

This paper presents a study on the optimization of systems with structured uncertainties, whose inputs and outputs can be exhaustively described in the probabilistic sense. By propagating the uncertainty from the input to the output in the space of the probability density functions and the moments, optimization problems that pursue performance, robustness and reliability based designs are studied. Be specifying the desired outputs in terms of desired probability density functions and then in terms of meaningful probabilistic indices, we settle a computationally viable framework for solving practical optimization problems. Applications to static optimization and stability control are used to illustrate the relevance of incorporating uncertainty in the early stages of the design. Several examples that admit a full probabilistic description of the output in terms of the design variables and the uncertain inputs are used to elucidate the main features of the generic problem and its solution. Extensions to problems that do not admit closed form solutions are also evaluated. Concrete evidence of the importance of using a consistent probabilistic formulation of the optimization problem and a meaningful probabilistic description of its solution is provided in the examples. In the stability control problem the analysis shows that standard deterministic approaches lead to designs with high probability of running into instability. The implementation of such designs can indeed have catastrophic consequences.

Improving hot region prediction by parameter optimization of density clustering in PPI.

PubMed

Hu, Jing; Zhang, Xiaolong

2016-11-01

This paper proposed an optimized algorithm which combines density clustering of parameter selection with feature-based classification for hot region prediction. First, all the residues are classified by SVM to remove non-hot spot residues, then density clustering of parameter selection is used to find hot regions. In the density clustering, this paper studies how to select input parameters. There are two parameters radius and density in density-based incremental clustering. We firstly fix density and enumerate radius to find a pair of parameters which leads to maximum number of clusters, and then we fix radius and enumerate density to find another pair of parameters which leads to maximum number of clusters. Experiment results show that the proposed method using both two pairs of parameters provides better prediction performance than the other method, and compare these two predictive results, the result by fixing radius and enumerating density have slightly higher prediction accuracy than that by fixing density and enumerating radius. Copyright © 2016. Published by Elsevier Inc.

Primary gamma ray selection in a hybrid timing/imaging Cherenkov array

NASA Astrophysics Data System (ADS)

Postnikov, E. B.; Grinyuk, A. A.; Kuzmichev, L. A.; Sveshnikova, L. G.

2017-06-01

This work is a methodical study on hybrid reconstruction techniques for hybrid imaging/timing Cherenkov observations. This type of hybrid array is to be realized at the gamma-observatory TAIGA intended for very high energy gamma-ray astronomy (> 30 TeV). It aims at combining the cost-effective timing-array technique with imaging telescopes. Hybrid operation of both of these techniques can lead to a relatively cheap way of development of a large area array. The joint approach of gamma event selection was investigated on both types of simulated data: the image parameters from the telescopes, and the shower parameters reconstructed from the timing array. The optimal set of imaging parameters and shower parameters to be combined is revealed. The cosmic ray background suppression factor depending on distance and energy is calculated. The optimal selection technique leads to cosmic ray background suppression of about 2 orders of magnitude on distances up to 450 m for energies greater than 50 TeV.

Structure-Guided Design of EED Binders Allosterically Inhibiting the Epigenetic Polycomb Repressive Complex 2 (PRC2) Methyltransferase

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

Lingel, Andreas; Sendzik, Martin; Huang, Ying

2017-01-12

PRC2 is a multisubunit methyltransferase involved in epigenetic regulation of early embryonic development and cell growth. The catalytic subunit EZH2 methylates primarily lysine 27 of histone H3, leading to chromatin compaction and repression of tumor suppressor genes. Inhibiting this activity by small molecules targeting EZH2 was shown to result in antitumor efficacy. Here, we describe the optimization of a chemical series representing a new class of PRC2 inhibitors which acts allosterically via the trimethyllysine pocket of the noncatalytic EED subunit. Deconstruction of a larger and complex screening hit to a simple fragment-sized molecule followed by structure-guided regrowth and careful propertymore » modulation were employed to yield compounds which achieve submicromolar inhibition in functional assays and cellular activity. The resulting molecules can serve as a simplified entry point for lead optimization and can be utilized to study this new mechanism of PRC2 inhibition and the associated biology in detail.« less

Optimal (R, Q) policy and pricing for two-echelon supply chain with lead time and retailer's service-level incomplete information

NASA Astrophysics Data System (ADS)

Esmaeili, M.; Naghavi, M. S.; Ghahghaei, A.

2018-03-01

Many studies focus on inventory systems to analyze different real-world situations. This paper considers a two-echelon supply chain that includes one warehouse and one retailer with stochastic demand and an up-to-level policy. The retailer's lead time includes the transportation time from the warehouse to the retailer that is unknown to the retailer. On the other hand, the warehouse is unaware of retailer's service level. The relationship between the retailer and the warehouse is modeled based on the Stackelberg game with incomplete information. Moreover, their relationship is presented when the warehouse and the retailer reveal their private information using the incentive strategies. The optimal inventory and pricing policies are obtained using an algorithm based on bi-level programming. Numerical examples, including sensitivity analysis of some key parameters, will compare the results between the Stackelberg models. The results show that information sharing is more beneficial to the warehouse rather than the retailer.

Enhancement of Automatization through Vocabulary Learning Using CALL: Can Prompt Language Processing Lead to Better Comprehension in L2 Reading?

ERIC Educational Resources Information Center

Sato, Takeshi; Matsunuma, Mitsuyasu; Suzuki, Akio

2013-01-01

Our study aims to optimize a multimedia application for vocabulary learning for English as a Foreign Language (EFL). Our study is based on the concept that difficulty in reading a text in a second language is due to the need for more working memory for word decoding skills, although the working memory must also be used for text comprehension…

Optimal design of solenoid valve to minimize cavitation by numerical analysis

NASA Astrophysics Data System (ADS)

Ko, Seungbin; Jang, Ilhoon; Song, Simon

2012-11-01

Keeping pace with the development of clean energy, hybrid cars and electric vehicles are getting extensive attention recently. In an electronic-control brake system which is essential to those vehicles, a solenoid valve is used to control external hydraulic pressure that boosts up the driver's braking force. However, strong cavitation occurs at the narrow passage between the ball and seat of a solenoid valve due to sudden decrease in pressure, leading to severe damage to the valve. In this study, we investigate the cavitation numerically to discover geometric parameters to affect the cavitation, and an optimal design to minimize the cavitation using optimization technique. As a result, we found four parameters: seat inner radius, seat angle, seat length, and ball radius. Among them, the seat inner radius affects the cavitation most. Also, we found that preventing a sudden reduction in a flow passage is important to reduce cavitation. Finally using an evolutionary algorithm for optimization we minimized cavitation. The optimal design resulted in the maximum vapor volume of fraction of 0.04 while it was 0.7 for reference geometry.

Unraveling the potential of a combined nitritation-anammox biomass towards the biodegradation of pharmaceutically active compounds.

PubMed

Kassotaki, Elissavet; Pijuan, Maite; Joss, Adriano; Borrego, Carles M; Rodriguez-Roda, Ignasi; Buttiglieri, Gianluigi

2018-05-15

In the past few years, anaerobic ammonium oxidation-based processes have attracted a lot of attention for their implementation at the mainstream line of wastewater treatment plants, due to the possibility of leading to energy autarky if combined with anaerobic digestion. However, little is known about the potential degradation of micropollutants by the microbial groups responsible of these processes and the few results available are inconclusive. This study aimed to assess the degradation capability of biomass withdrawn from a combined nitritation/anaerobic ammonium oxidation (combined N/A) pilot plant towards five pharmaceutically active compounds (ibuprofen, sulfamethoxazole, metoprolol, venlafaxine and carbamazepine). Batch experiments were performed under different conditions by selectively activating or inhibiting different microbial groups: i) regular combined N/A operation, ii) aerobic (optimal for nitrifying bacteria), iii) aerobic with allylthiourea (an inhibitor of ammonia monooxygenase, enzyme of ammonia oxidizing bacteria), iv) anoxic (optimal for anaerobic ammonium oxidizing bacteria), v) aerobic with acetate (optimal for heterotrophic bacteria) and vi) anoxic with acetate (optimal for heterotrophic denitrifying bacteria). Ibuprofen was the most biodegradable compound being significantly degraded (49-100%) under any condition except heterotrophic denitrification. Sulfamethoxazole, exhibited the highest removal (70%) under optimal conditions for nitrifying bacteria but in the rest of the experiments anoxic conditions were found to be slightly more favorable (up to 58%). For metoprolol the highest performance was obtained under anoxic conditions favoring anammox bacteria (62%). Finally, carbamazepine and venlafaxine were hardly removed (≤10% in the majority of cases). Taken together, these results suggest the specificity of different microbial groups that in combination with alternating operational parameters can lead to enhanced removal of some micropollutants. Copyright © 2017 Elsevier B.V. All rights reserved.

Study and optimization of the ultrasound-enhanced cleaning of an ultrafiltration ceramic membrane through a combined experimental-statistical approach.

PubMed

Alventosa-deLara, E; Barredo-Damas, S; Alcaina-Miranda, M I; Iborra-Clar, M I

2014-05-01

Membrane fouling is one of the main drawbacks of ultrafiltration technology during the treatment of dye-containing effluents. Therefore, the optimization of the membrane cleaning procedure is essential to improve the overall efficiency. In this work, a study of the factors affecting the ultrasound-assisted cleaning of an ultrafiltration ceramic membrane fouled by dye particles was carried out. The effect of transmembrane pressure (0.5, 1.5, 2.5 bar), cross-flow velocity (1, 2, 3 ms(-1)), ultrasound power level (40%, 70%, 100%) and ultrasound frequency mode (37, 80 kHz and mixed wave) on the cleaning efficiency was evaluated. The lowest frequency showed better results, although the best cleaning performance was obtained using the mixed wave mode. A Box-Behnken Design was used to find the optimal conditions for the cleaning procedure through a response surface study. The optimal operating conditions leading to the maximum cleaning efficiency predicted (32.19%) were found to be 1.1 bar, 3 ms(-1) and 100% of power level. Finally, the optimized response was compared to the efficiency of a chemical cleaning with NaOH solution, with and without the use of ultrasound. By using NaOH, cleaning efficiency nearly triples, and it improves up to 25% by adding ultrasound. Copyright © 2013 Elsevier B.V. All rights reserved.

A comparative study on stress and compliance based structural topology optimization

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

New system for digital to analog transformation and reconstruction of 12-lead ECGs.

PubMed

Kothadia, Roshni; Kulecz, Walter B; Kofman, Igor S; Black, Adam J; Grier, James W; Schlegel, Todd T

2013-01-01

We describe initial validation of a new system for digital to analog conversion (DAC) and reconstruction of 12-lead ECGs. The system utilizes an open and optimized software format with a commensurately optimized DAC hardware configuration to accurately reproduce, from digital files, the original analog electrocardiographic signals of previously instrumented patients. By doing so, the system also ultimately allows for transmission of data collected on one manufacturer's 12-lead ECG hardware/software into that of any other. To initially validate the system, we compared original and post-DAC re-digitized 12-lead ECG data files (∼5-minutes long) in two types of validation studies in 10 patients. The first type quantitatively compared the total waveform voltage differences between the original and re-digitized data while the second type qualitatively compared the automated electrocardiographic diagnostic statements generated by the original versus re-digitized data. The grand-averaged difference in root mean squared voltage between the original and re-digitized data was 20.8 µV per channel when re-digitization involved the same manufacturer's analog to digital converter (ADC) as the original digitization, and 28.4 µV per channel when it involved a different manufacturer's ADC. Automated diagnostic statements generated by the original versus reconstructed data did not differ when using the diagnostic algorithm from the same manufacturer on whose device the original data were collected, and differed only slightly for just 1 of 10 patients when using a third-party diagnostic algorithm throughout. Original analog 12-lead ECG signals can be reconstructed from digital data files with accuracy sufficient for clinical use. Such reconstructions can readily enable automated second opinions for difficult-to-interpret 12-lead ECGs, either locally or remotely through the use of dedicated or cloud-based servers.

Frequency and change mechanisms of psychotherapy among depressed patients: study protocol for a multicenter randomized trial comparing twice-weekly versus once-weekly sessions of CBT and IPT.

PubMed

Bruijniks, Sanne J E; Bosmans, Judith; Peeters, Frenk P M L; Hollon, Steven D; van Oppen, Patricia; van den Boogaard, Michael; Dingemanse, Pieter; Cuijpers, Pim; Arntz, Arnoud; Franx, Gerdien; Huibers, Marcus J H

2015-06-30

Cognitive behavioral therapy (CBT) and interpersonal therapy (IPT) are among the most well established therapies for the treatment of depression. However, some major questions remain unanswered. First, it is unknown what session frequency results in the most optimal (cost) effectiveness in psychotherapy. Second, the debate as to what mechanisms underlie the effect of psychotherapy has not yet been resolved. Enhancing knowledge about the optimal session frequency and mechanisms of change seems crucial in order to optimize the (cost) effectiveness of psychotherapy for depression. This study aims to compare treatment outcome of twice-weekly versus once-weekly sessions of CBT and IPT. We expect twice-weekly sessions to be more effective and lead to more rapid recovery of depressive symptoms in comparison to once-weekly sessions. Both therapy-specific and non-specific process measures will be included to unravel the mechanisms of change in psychotherapy for depression. Besides the use of self-reports and behavioral observations, this study will also examine underlying biological processes by collecting blood samples. In a multicenter randomized trial, two hundred depressed patients will be recruited from Dutch specialized mental healthcare centers and randomized into one of the following groups, all receiving a maximum of 20 sessions in different frequencies: a) twice-weekly sessions at the start of CBT, b) twice-weekly sessions at the start of IPT, c) once-weekly sessions at the start of CBT, d) once-weekly sessions at the start of IPT. Primary outcome measures are depression severity, cost-effectiveness and quality of life. Process measures include therapeutic alliance, recall, therapy-specific skills, motivation and compliance. Assessments will take place during baseline, monthly during treatment and follow-up at month 9, 12 and 24. In addition, at 12 and 24 months, the frequency of depressive episodes in the previous year will be assessed. Blood samples will be taken pre- and post-treatment. The study has been ethically approved and registered. Finding that twice-weekly sessions are more effective or lead to more rapid recovery of depressive symptoms could lead to treatment adaptations that have the potential to reduce the personal and societal burden of depression. In addition, insight into the mechanisms of change and physiological processes in psychotherapy will enable us to optimize treatments and may help to understand human functioning beyond the context of treatment. The study has been registered on October 21th, 2014 at the Netherlands Trial Register, part of the Dutch Cochrane Centre ( NTR4856 ).

Improvement of glass-forming ability and phase separation in Cu Ti-rich

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

Park, E S; Chang, H J; Kim, D H

2010-01-01

Present study reports improvement of glass-forming ability (GFA) and phase separation in Cu Ti-rich Cu Ti Zr Ni Si bulk metallic glasses (BMGs) by tailoring the constituent elements. The MA of metalloid element, Sn having relatively large negative enthalpy of mixing can lead to improve GFA (up to 8mm in diameter) as well as thermal stability (up toTx = 48K) by optimizing the substitution element. And the addition of elements having relatively large positive enthalpy of mixing (partial substitution of Zr or Ti with Y) can lead to the liquid state phase separation in Cu Ti Sn Zr Ni Simore » BMG, although the addition lead to drastic deterioration of the GFA.« less

Treatment of lead contaminated water by a PVDF membrane that is modified by zirconium, phosphate and PVA.

PubMed

Zhao, Dandan; Yu, Yang; Chen, J Paul

2016-09-15

Lead contamination is one of the most serious problems in drinking water facing humans. In this study, a novel zirconium phosphate modified polyvinyl alcohol (PVA)-PVDF membrane was developed for lead removal. The zirconium ions and PVA were firstly coated onto a PVDF membrane through crosslinking reactions with glutaraldehyde, which was then modified by phosphate. The adsorption kinetics study showed that most of ultimate uptake occurred in 5 h. The adsorption increased with an increase in pH; the optimal adsorption was achieved at pH 5.5. The experimental data were better described by Langmuir equation than Freundlich equation; the maximum adsorption capacity was 121.2 mg-Pb/g at pH 5.5, much higher than other reported adsorptive membranes. The membrane exhibited a higher selectivity for lead over zinc with a relative selectivity coefficient (Pb(2+)/Zn(2+)) of 9.92. The filtration study showed that the membrane with an area of 12.56 cm(2) could treat 13.9 L (equivalent to 73,000 bed volumes) of lead containing wastewater with an influent concentration of 224.5 μ g/L to meet the maximum contaminant level of 15 μ g/L. It was demonstrated that the membrane did well in the removal of lead in both simulated wastewater and lead-spiked reservoir water and had a good reusability in its applications. The XPS studies revealed that the lead uptake was mainly due to cation exchange between hydrogen ions and lead ions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic analysis of concentrated solar supercritical CO2-based power generation closed-loop cycle

DOE PAGES

Osorio, Julian D.; Hovsapian, Rob; Ordonez, Juan C.

2016-01-01

Here, the dynamic behavior of a concentrated solar power (CSP) supercritical CO 2 cycle is studied under different seasonal conditions. The system analyzed is composed of a central receiver, hot and cold thermal energy storage units, a heat exchanger, a recuperator, and multi-stage compression-expansion subsystems with intercoolers and reheaters between compressors and turbines respectively. Energy models for each component of the system are developed in order to optimize operating and design parameters such as mass flow rate, intermediate pressures and the effective area of the recuperator to lead to maximum efficiency. Our results show that the parametric optimization leads themore » system to a process efficiency of about 21 % and a maximum power output close to 1.5 MW. The thermal energy storage allows the system to operate for several hours after sunset. This operating time is approximately increased from 220 to 480 minutes after optimization. The hot and cold thermal energy storage also lessens the temperature fluctuations by providing smooth changes of temperatures at the turbines and compressors inlets. Our results indicate that concentrated solar systems using supercritical CO 2 could be a viable alternative to satisfying energy needs in desert areas with scarce water and fossil fuel resources.« less

Maximizing neotissue growth kinetics in a perfusion bioreactor: An in silico strategy using model reduction and Bayesian optimization.

PubMed

Mehrian, Mohammad; Guyot, Yann; Papantoniou, Ioannis; Olofsson, Simon; Sonnaert, Maarten; Misener, Ruth; Geris, Liesbet

2018-03-01

In regenerative medicine, computer models describing bioreactor processes can assist in designing optimal process conditions leading to robust and economically viable products. In this study, we started from a (3D) mechanistic model describing the growth of neotissue, comprised of cells, and extracellular matrix, in a perfusion bioreactor set-up influenced by the scaffold geometry, flow-induced shear stress, and a number of metabolic factors. Subsequently, we applied model reduction by reformulating the problem from a set of partial differential equations into a set of ordinary differential equations. Comparing the reduced model results to the mechanistic model results and to dedicated experimental results assesses the reduction step quality. The obtained homogenized model is 10 5 fold faster than the 3D version, allowing the application of rigorous optimization techniques. Bayesian optimization was applied to find the medium refreshment regime in terms of frequency and percentage of medium replaced that would maximize neotissue growth kinetics during 21 days of culture. The simulation results indicated that maximum neotissue growth will occur for a high frequency and medium replacement percentage, a finding that is corroborated by reports in the literature. This study demonstrates an in silico strategy for bioprocess optimization paying particular attention to the reduction of the associated computational cost. © 2017 Wiley Periodicals, Inc.

Joint Optimization of Distribution Network Design and Two-Echelon Inventory Control with Stochastic Demand and CO2 Emission Tax Charges

PubMed Central

Li, Shuangyan; Li, Xialian; Zhang, Dezhi; Zhou, Lingyun

2017-01-01

This study develops an optimization model to integrate facility location and inventory control for a three-level distribution network consisting of a supplier, multiple distribution centers (DCs), and multiple retailers. The integrated model addressed in this study simultaneously determines three types of decisions: (1) facility location (optimal number, location, and size of DCs); (2) allocation (assignment of suppliers to located DCs and retailers to located DCs, and corresponding optimal transport mode choices); and (3) inventory control decisions on order quantities, reorder points, and amount of safety stock at each retailer and opened DC. A mixed-integer programming model is presented, which considers the carbon emission taxes, multiple transport modes, stochastic demand, and replenishment lead time. The goal is to minimize the total cost, which covers the fixed costs of logistics facilities, inventory, transportation, and CO2 emission tax charges. The aforementioned optimal model was solved using commercial software LINGO 11. A numerical example is provided to illustrate the applications of the proposed model. The findings show that carbon emission taxes can significantly affect the supply chain structure, inventory level, and carbon emission reduction levels. The delay rate directly affects the replenishment decision of a retailer. PMID:28103246

To the theory of high-power gyrotrons with uptapered resonators

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

Dumbrajs, O.; Nusinovich, G. S.

In high-power gyrotrons it is desirable to combine an optimal resonator length with the optimal value of the resonator quality factor. In resonators with the constant radius of the central part, the possibilities of this combination are limited because the quality factor of the resonator sharply increases with its length. Therefore the attempts to increase the length for maximizing the efficiency leads to such increase in the quality factor which makes the optimal current too small. Resonators with slightly uptapered profiles offer more flexibility in this regard. In such resonators, one can separate optimization of the interaction length from optimizationmore » of the quality factor because the quality factor determined by diffractive losses can be reduced by increasing the angle of uptapering. In the present paper, these issues are analyzed by studying as a typical high-power 17 GHz gyrotron which is currently under development in Europe for ITER (http://en.wikipedia.org/wiki/ITER). The effect of a slight uptapering of the resonator wall on the efficiency enhancement and the purity of the radiation spectrum in the process of the gyrotron start-up and power modulation are studied. Results show that optimal modification of the shape of a slightly uptapered resonator may result in increasing the gyrotron power from 1052 to 1360 kW.« less

Study on residual discharge time of lead-acid battery based on fitting method

NASA Astrophysics Data System (ADS)

Liu, Bing; Yu, Wangwang; Jin, Yueqiang; Wang, Shuying

2017-05-01

This paper use the method of fitting to discuss the data of C problem of mathematical modeling in 2016, the residual discharge time model of lead-acid battery with 20A,30A,…,100A constant current discharge is obtained, and the discharge time model of discharge under arbitrary constant current is presented. The mean relative error of the model is calculated to be about 3%, which shows that the model has high accuracy. This model can provide a basis for optimizing the adaptation of power system to the electrical motor vehicle.

Study of low energy neutron beam formation based on GEANT4 simulations

NASA Astrophysics Data System (ADS)

Avagyan, R.; Avetisyan, R.; Ivanyan, V.; Kerobyan, I.

2017-07-01

The possibility of obtaining thermal/epithermal energy neutron beams using external protons from cyclotron C18/18 is studied based on GEANT4 simulations. This study will be the basis of the Beam Shaped Assembly (BSA) development for future Boron Neutron Capture Therapy (BNCT). Proton induced reactions on 9Be target are considered as a neutron source, and dependence of neutron yield on target thickness is investigated. The problem of reducing the ratio of gamma to neutron yields by inserting a lead sheet after the beryllium target is studied as well. By GEANT4 modeling the optimal thicknesses of 9Be target and lead absorber are determined and the design characteristics of beam shaping assembly, including the materials and thicknesses of reflector and moderator are considered.

Focusing light through random photonic layers by four-element division algorithm

NASA Astrophysics Data System (ADS)

Fang, Longjie; Zhang, Xicheng; Zuo, Haoyi; Pang, Lin

2018-02-01

The propagation of waves in turbid media is a fundamental problem of optics with vast applications. Optical phase optimization approaches for focusing light through turbid media using phase control algorithm have been widely studied in recent years due to the rapid development of spatial light modulator. The existing approaches include element-based algorithms - stepwise sequential algorithm, continuous sequential algorithm and whole element optimization approaches - partitioning algorithm, transmission matrix approach and genetic algorithm. The advantage of element-based approaches is that the phase contribution of each element is very clear; however, because the intensity contribution of each element to the focal point is small especially for the case of large number of elements, the determination of the optimal phase for a single element would be difficult. In other words, the signal to noise ratio of the measurement is weak, leading to possibly local maximal during the optimization. As for whole element optimization approaches, all elements are employed for the optimization. Of course, signal to noise ratio during the optimization is improved. However, because more random processings are introduced into the processing, optimizations take more time to converge than the single element based approaches. Based on the advantages of both single element based approaches and whole element optimization approaches, we propose FEDA approach. Comparisons with the existing approaches show that FEDA only takes one third of measurement time to reach the optimization, which means that FEDA is promising in practical application such as for deep tissue imaging.

An analytic model for footprint dispersions and its application to mission design

NASA Technical Reports Server (NTRS)

Rao, J. R. Jagannatha; Chen, Yi-Chao

1992-01-01

This is the final report on our recent research activities that are complementary to those conducted by our colleagues, Professor Farrokh Mistree and students, in the context of the Taguchi method. We have studied the mathematical model that forms the basis of the Simulation and Optimization of Rocket Trajectories (SORT) program and developed an analytic method for determining mission reliability with a reduced number of flight simulations. This method can be incorporated in a design algorithm to mathematically optimize different performance measures of a mission, thus leading to a robust and easy-to-use methodology for mission planning and design.

Hit to Lead optimization of a novel class of squarate-containing polo-like kinases inhibitors.

PubMed

Zhang, Qingwei; Xia, Zhiren; Mitten, Michael J; Lasko, Loren M; Klinghofer, Vered; Bouska, Jennifer; Johnson, Eric F; Penning, Thomas D; Luo, Yan; Giranda, Vincent L; Shoemaker, Alexander R; Stewart, Kent D; Djuric, Stevan W; Vasudevan, Anil

2012-12-15

A high throughput screening (HTS) hit, 1 (Plk1 K(i)=2.2 μM) was optimized and evaluated for the enzymatic inhibition of Plk-1 kinase. Molecular modeling suggested the importance of adding a hydrophobic aromatic amine side chain in order to improve the potency by a classic kinase H-donor-acceptor binding mode. Extensive SAR studies led to the discovery of 49 (Plk1 K(i)=5 nM; EC(50)=1.05 μM), which demonstrated moderate efficacy at 100 mpk in a MiaPaCa tumor model, with no overt toxicity. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Design Problem of Assembly Line Systems using Genetic Algorithm under the BTO Environment

NASA Astrophysics Data System (ADS)

Abe, Kazuaki; Yamada, Tetsuo; Matsui, Masayuki

Under the BTO environment, stochastic assembly lines require design methods which shorten not only the production lead time but also the ready time for the line design. We propose a design method for Assembly Line Systems (ALS) in Yamada et al. (2001) by using Genetic Algorithm (GA) and Adam-Eve GA, in which all design variables are determined in consideration of constraints such as line length related to the production lead time. First, an ALS model with a line length constraint is introduced, and an optimal design problem is set to maximize the net reward under shorter lead time. Next, a simulation optimization method is developed using Adam-Eve GA and traditional GA. Finally, an optimal design example is shown and discussed by comparing the 2-stage design by Yamada et al. (2001) and both the GA designs. It is shown that the Adam-Eve GA is superior to the traditional GA design in terms of computational time though there is only a slight difference in terms of net reward.

Optimal technology investment strategies for a reusable launch vehicle

NASA Technical Reports Server (NTRS)

Moore, A. A.; Braun, R. D.; Powell, R. W.

1995-01-01

Within the present budgetary environment, developing the technology that leads to an operationally efficient space transportation system with the required performance is a challenge. The present research focuses on a methodology to determine high payoff technology investment strategies. Research has been conducted at Langley Research Center in which design codes for the conceptual analysis of space transportation systems have been integrated in a multidisciplinary design optimization approach. The current study integrates trajectory, propulsion, weights and sizing, and cost disciplines where the effect of technology maturation on the development cost of a single stage to orbit reusable launch vehicle is examined. Results show that the technology investment prior to full-scale development has a significant economic payoff. The design optimization process is used to determine strategic allocations of limited technology funding to maximize the economic payoff.

Characterization of classical static noise via qubit as probe

NASA Astrophysics Data System (ADS)

Javed, Muhammad; Khan, Salman; Ullah, Sayed Arif

2018-03-01

The dynamics of quantum Fisher information (QFI) of a single qubit coupled to classical static noise is investigated. The analytical relation for QFI fixes the optimal initial state of the qubit that maximizes it. An approximate limit for the time of coupling that leads to physically useful results is identified. Moreover, using the approach of quantum estimation theory and the analytical relation for QFI, the qubit is used as a probe to precisely estimate the disordered parameter of the environment. Relation for optimal interaction time with the environment is obtained, and condition for the optimal measurement of the noise parameter of the environment is given. It is shown that all values, in the mentioned range, of the noise parameter are estimable with equal precision. A comparison of our results with the previous studies in different classical environments is made.

Targeting blood–brain barrier changes during inflammatory pain: an opportunity for optimizing CNS drug delivery

PubMed Central

Ronaldson, Patrick T; Davis, Thomas P

2012-01-01

The blood–brain barrier (BBB) is the most significant obstacle to effective CNS drug delivery. It possesses structural and biochemical features (i.e., tight-junction protein complexes and, influx and efflux transporters) that restrict xenobiotic permeation. Pathophysiological stressors (i.e., peripheral inflammatory pain) can alter BBB tight junctions and transporters, which leads to drug-permeation changes. This is especially critical for opioids, which require precise CNS concentrations to be safe and effective analgesics. Recent studies have identified molecular targets (i.e., endogenous transporters and intracellular signaling systems) that can be exploited for optimization of CNS drug delivery. This article summarizes current knowledge in this area and emphasizes those targets that present the greatest opportunity for controlling drug permeation and/or drug transport across the BBB in an effort to achieve optimal CNS opioid delivery. PMID:22468221

Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning

PubMed Central

Brković, Milenko; Simić, Mirjana

2014-01-01

Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443

Contributions on Optimizing Approximations in the Study of Melting and Solidification Processes That Occur in Processing by Electro-Erosion

NASA Astrophysics Data System (ADS)

Potra, F. L.; Potra, T.; Soporan, V. F.

We propose two optimization methods of the processes which appear in EDM (Electrical Discharge Machining). First refers to the introduction of a new function approximating the thermal flux energy in EDM machine. Classical researches approximate this energy with the Gauss' function. In the case of unconventional technology the Gauss' bell became null only for r → +∞, where r is the radius of crater produced by EDM. We introduce a cubic spline regression which descends to zero at the crater's boundary. In the second optimization we propose modifications in technologies' work regarding the displacement of the tool electrode to the piece electrode such that the material melting to be realized in optimal time and the feeding speed with dielectric liquid regarding the solidification of the expulsed material. This we realize using the FAHP algorithm based on the theory of eigenvalues and eigenvectors, which lead to mean values of best approximation. [6

Management of Occupational Exposure to Engineered Nanoparticles Through a Chance-Constrained Nonlinear Programming Approach

PubMed Central

Chen, Zhi; Yuan, Yuan; Zhang, Shu-Shen; Chen, Yu; Yang, Feng-Lin

2013-01-01

Critical environmental and human health concerns are associated with the rapidly growing fields of nanotechnology and manufactured nanomaterials (MNMs). The main risk arises from occupational exposure via chronic inhalation of nanoparticles. This research presents a chance-constrained nonlinear programming (CCNLP) optimization approach, which is developed to maximize the nanaomaterial production and minimize the risks of workplace exposure to MNMs. The CCNLP method integrates nonlinear programming (NLP) and chance-constrained programming (CCP), and handles uncertainties associated with both the nanomaterial production and workplace exposure control. The CCNLP method was examined through a single-walled carbon nanotube (SWNT) manufacturing process. The study results provide optimal production strategies and alternatives. It reveal that a high control measure guarantees that environmental health and safety (EHS) standards regulations are met, while a lower control level leads to increased risk of violating EHS regulations. The CCNLP optimization approach is a decision support tool for the optimization of the increasing MNMS manufacturing with workplace safety constraints under uncertainties. PMID:23531490

Self-extinction through optimizing selection.

PubMed

Parvinen, Kalle; Dieckmann, Ulf

2013-09-21

Evolutionary suicide is a process in which selection drives a viable population to extinction. So far, such selection-driven self-extinction has been demonstrated in models with frequency-dependent selection. This is not surprising, since frequency-dependent selection can disconnect individual-level and population-level interests through environmental feedback. Hence it can lead to situations akin to the tragedy of the commons, with adaptations that serve the selfish interests of individuals ultimately ruining a population. For frequency-dependent selection to play such a role, it must not be optimizing. Together, all published studies of evolutionary suicide have created the impression that evolutionary suicide is not possible with optimizing selection. Here we disprove this misconception by presenting and analyzing an example in which optimizing selection causes self-extinction. We then take this line of argument one step further by showing, in a further example, that selection-driven self-extinction can occur even under frequency-independent selection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Management of occupational exposure to engineered nanoparticles through a chance-constrained nonlinear programming approach.

PubMed

Chen, Zhi; Yuan, Yuan; Zhang, Shu-Shen; Chen, Yu; Yang, Feng-Lin

2013-03-26

Critical environmental and human health concerns are associated with the rapidly growing fields of nanotechnology and manufactured nanomaterials (MNMs). The main risk arises from occupational exposure via chronic inhalation of nanoparticles. This research presents a chance-constrained nonlinear programming (CCNLP) optimization approach, which is developed to maximize the nanaomaterial production and minimize the risks of workplace exposure to MNMs. The CCNLP method integrates nonlinear programming (NLP) and chance-constrained programming (CCP), and handles uncertainties associated with both the nanomaterial production and workplace exposure control. The CCNLP method was examined through a single-walled carbon nanotube (SWNT) manufacturing process. The study results provide optimal production strategies and alternatives. It reveal that a high control measure guarantees that environmental health and safety (EHS) standards regulations are met, while a lower control level leads to increased risk of violating EHS regulations. The CCNLP optimization approach is a decision support tool for the optimization of the increasing MNMS manufacturing with workplace safety constraints under uncertainties.

Premium cost optimization of operational and maintenance of green building in Indonesia using life cycle assessment method

NASA Astrophysics Data System (ADS)

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

2017-06-01

Building has a big impact on the environmental developments. There are three general motives in building, namely the economy, society, and environment. Total completed building construction in Indonesia increased by 116% during 2009 to 2011. It made the energy consumption increased by 11% within the last three years. In fact, 70% of energy consumption is used for electricity needs on commercial buildings which leads to an increase of greenhouse gas emissions by 25%. Green Building cycle costs is known as highly building upfront cost in Indonesia. The purpose of optimization in this research improves building performance with some of green concept alternatives. Research methodology is mixed method of qualitative and quantitative approaches through questionnaire surveys and case study. Assessing the successful of optimization functions in the existing green building is based on the operational and maintenance phase with the Life Cycle Assessment Method. Choosing optimization results were based on the largest efficiency of building life cycle and the most effective cost to refund.

Meshes optimized for discrete exterior calculus (DEC).

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

Mousley, Sarah C.; Deakin, Michael; Knupp, Patrick

We study the optimization of an energy function used by the meshing community to measure and improve mesh quality. This energy is non-traditional because it is dependent on both the primal triangulation and its dual Voronoi (power) diagram. The energy is a measure of the mesh's quality for usage in Discrete Exterior Calculus (DEC), a method for numerically solving PDEs. In DEC, the PDE domain is triangulated and this mesh is used to obtain discrete approximations of the continuous operators in the PDE. The energy of a mesh gives an upper bound on the error of the discrete diagonal approximationmore » of the Hodge star operator. In practice, one begins with an initial mesh and then makes adjustments to produce a mesh of lower energy. However, we have discovered several shortcomings in directly optimizing this energy, e.g. its non-convexity, and we show that the search for an optimized mesh may lead to mesh inversion (malformed triangles). We propose a new energy function to address some of these issues.« less

Optimism bias leads to inconclusive results - an empirical study

PubMed Central

Djulbegovic, Benjamin; Kumar, Ambuj; Magazin, Anja; Schroen, Anneke T.; Soares, Heloisa; Hozo, Iztok; Clarke, Mike; Sargent, Daniel; Schell, Michael J.

2010-01-01

Objective Optimism bias refers to unwarranted belief in the efficacy of new therapies. We assessed the impact of optimism bias on a proportion of trials that did not answer their research question successfully, and explored whether poor accrual or optimism bias is responsible for inconclusive results. Study Design Systematic review Setting Retrospective analysis of a consecutive series phase III randomized controlled trials (RCTs) performed under the aegis of National Cancer Institute Cooperative groups. Results 359 trials (374 comparisons) enrolling 150,232 patients were analyzed. 70% (262/374) of the trials generated conclusive results according to the statistical criteria. Investigators made definitive statements related to the treatment preference in 73% (273/374) of studies. Investigators’ judgments and statistical inferences were concordant in 75% (279/374) of trials. Investigators consistently overestimated their expected treatment effects, but to a significantly larger extent for inconclusive trials. The median ratio of expected over observed hazard ratio or odds ratio was 1.34 (range 0.19 – 15.40) in conclusive trials compared to 1.86 (range 1.09 – 12.00) in inconclusive studies (p<0.0001). Only 17% of the trials had treatment effects that matched original researchers’ expectations. Conclusion Formal statistical inference is sufficient to answer the research question in 75% of RCTs. The answers to the other 25% depend mostly on subjective judgments, which at times are in conflict with statistical inference. Optimism bias significantly contributes to inconclusive results. PMID:21163620

Fuel optimization for low-thrust Earth-Moon transfer via indirect optimal control

NASA Astrophysics Data System (ADS)

Pérez-Palau, Daniel; Epenoy, Richard

2018-02-01

The problem of designing low-energy transfers between the Earth and the Moon has attracted recently a major interest from the scientific community. In this paper, an indirect optimal control approach is used to determine minimum-fuel low-thrust transfers between a low Earth orbit and a Lunar orbit in the Sun-Earth-Moon Bicircular Restricted Four-Body Problem. First, the optimal control problem is formulated and its necessary optimality conditions are derived from Pontryagin's Maximum Principle. Then, two different solution methods are proposed to overcome the numerical difficulties arising from the huge sensitivity of the problem's state and costate equations. The first one consists in the use of continuation techniques. The second one is based on a massive exploration of the set of unknown variables appearing in the optimality conditions. The dimension of the search space is reduced by considering adapted variables leading to a reduction of the computational time. The trajectories found are classified in several families according to their shape, transfer duration and fuel expenditure. Finally, an analysis based on the dynamical structure provided by the invariant manifolds of the two underlying Circular Restricted Three-Body Problems, Earth-Moon and Sun-Earth is presented leading to a physical interpretation of the different families of trajectories.

Exocharmic Reactions up Close

ERIC Educational Resources Information Center

Ramette, R. W.

2007-01-01

The exocharmic reactions that can be observed microscopically are discussed. The students can discover the optimal concentration of an acidic lead nitrate solution, so that a crystal of potassium iodide, nudged to the edge of a drop, results in glinting golden hexagons of lead iodide.

Robust design of (s, S) inventory policy parameters in supply chains with demand and lead time uncertainties

NASA Astrophysics Data System (ADS)

Karimi Movahed, Kamran; Zhang, Zhi-Hai

2015-09-01

Demand and lead time uncertainties have significant effects on supply chain behaviour. In this paper, we present a single-product three-level multi-period supply chain with uncertain demands and lead times by using robust techniques to study the managerial insights of the supply chain inventory system under uncertainty. We formulate this problem as a robust mixed-integer linear program with minimised expected cost and total cost variation to determine the optimal (s, S) values of the inventory parameters. Several numerical studies are performed to investigate the supply chain behaviour. Useful guidelines for the design of a robust supply chain are also provided. Results show that the order variance and the expected cost in a supply chain significantly increase when the manufacturer's review period is an integer ratio of the distributor's and the retailer's review periods.

Study on Pyroelectric Harvesters with Various Geometry

PubMed Central

Siao, An-Shen; Chao, Ching-Kong; Hsiao, Chun-Ching

2015-01-01

Pyroelectric harvesters convert time-dependent temperature variations into electric current. The appropriate geometry of the pyroelectric cells, coupled with the optimal period of temperature fluctuations, is key to driving the optimal load resistance, which enhances the performance of pyroelectric harvesters. The induced charge increases when the thickness of the pyroelectric cells decreases. Moreover, the induced charge is extremely reduced for the thinner pyroelectric cell when not used for the optimal period. The maximum harvested power is achieved when a 100 μm-thick PZT (Lead zirconate titanate) cell is used to drive the optimal load resistance of about 40 MΩ. Moreover, the harvested power is greatly reduced when the working resistance diverges even slightly from the optimal load resistance. The stored voltage generated from the 75 μm-thick PZT cell is less than that from the 400 μm-thick PZT cell for a period longer than 64 s. Although the thinner PZT cell is advantageous in that it enhances the efficiency of the pyroelectric harvester, the much thinner 75 μm-thick PZT cell and the divergence from the optimal period further diminish the performance of the pyroelectric cell. Therefore, the designers of pyroelectric harvesters need to consider the coupling effect between the geometry of the pyroelectric cells and the optimal period of temperature fluctuations to drive the optimal load resistance. PMID:26270666

Lead optimization of 2-(piperidin-3-yl)-1H-benzimidazoles: identification of 2-morpholin- and 2-thiomorpholin-2-yl-1H-benzimidazoles as selective and CNS penetrating H₁-antihistamines for insomnia.

PubMed

Ravula, Satheesh Babu; Yu, Jinghua; Tran, Joe A; Arellano, Melissa; Tucci, Fabio C; Moree, Wilna J; Li, Bin-Feng; Petroski, Robert E; Wen, Jianyun; Malany, Siobhan; Hoare, Samuel R J; Madan, Ajay; Crowe, Paul D; Beaton, Graham

2012-01-01

The structure-activity relationships of 2-(piperidin-3-yl)-1H-benzimidazoles, 2-morpholine and 2-thiomorpholin-2-yl-1H-benzimidazoles are described. In the lead optimization process, the pK(a) and/or logP of benzimidazole analogs were reduced either by attachment of polar substituents to the piperidine nitrogen or incorporation of heteroatoms into the piperidine heterocycle. Compounds 9a and 9b in the morpholine series and 10g in the thiomorpholine series demonstrated improved selectivity and CNS profiles compared to lead compound 2 and these are potential candidates for evaluation as sedative hypnotics. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Petit, Johan; Lallemant, Lucile

2017-05-01

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

Controlled supercontinua via spatial beam shaping

NASA Astrophysics Data System (ADS)

Zhdanova, Alexandra A.; Shen, Yujie; Thompson, Jonathan V.; Scully, Marlan O.; Yakovlev, Vladislav V.; Sokolov, Alexei V.

2018-06-01

Recently, optimization techniques have had a significant impact in a variety of fields, leading to a higher signal-to-noise and more streamlined techniques. We consider the possibility for using programmable phase-only spatial optimization of the pump beam to influence the supercontinuum generation process. Preliminary results show that significant broadening and rough control of the supercontinuum spectrum in the visible region are possible without loss of input energy. This serves as a proof-of-concept demonstration that spatial effects can controllably influence the supercontinuum spectrum, leading to possibilities for utilizing supercontinuum power more efficiently and achieving excellent spectral control.

The Mass-Longevity Triangle: Pareto Optimality and the Geometry of Life-History Trait Space

PubMed Central

Szekely, Pablo; Korem, Yael; Moran, Uri; Mayo, Avi; Alon, Uri

2015-01-01

When organisms need to perform multiple tasks they face a fundamental tradeoff: no phenotype can be optimal at all tasks. This situation was recently analyzed using Pareto optimality, showing that tradeoffs between tasks lead to phenotypes distributed on low dimensional polygons in trait space. The vertices of these polygons are archetypes—phenotypes optimal at a single task. This theory was applied to examples from animal morphology and gene expression. Here we ask whether Pareto optimality theory can apply to life history traits, which include longevity, fecundity and mass. To comprehensively explore the geometry of life history trait space, we analyze a dataset of life history traits of 2105 endothermic species. We find that, to a first approximation, life history traits fall on a triangle in log-mass log-longevity space. The vertices of the triangle suggest three archetypal strategies, exemplified by bats, shrews and whales, with specialists near the vertices and generalists in the middle of the triangle. To a second approximation, the data lies in a tetrahedron, whose extra vertex above the mass-longevity triangle suggests a fourth strategy related to carnivory. Each animal species can thus be placed in a coordinate system according to its distance from the archetypes, which may be useful for genome-scale comparative studies of mammalian aging and other biological aspects. We further demonstrate that Pareto optimality can explain a range of previous studies which found animal and plant phenotypes which lie in triangles in trait space. This study demonstrates the applicability of multi-objective optimization principles to understand life history traits and to infer archetypal strategies that suggest why some mammalian species live much longer than others of similar mass. PMID:26465336

Parameter Optimization for Feature and Hit Generation in a General Unknown Screening Method-Proof of Concept Study Using a Design of Experiment Approach for a High Resolution Mass Spectrometry Procedure after Data Independent Acquisition.

PubMed

Elmiger, Marco P; Poetzsch, Michael; Steuer, Andrea E; Kraemer, Thomas

2018-03-06

High resolution mass spectrometry and modern data independent acquisition (DIA) methods enable the creation of general unknown screening (GUS) procedures. However, even when DIA is used, its potential is far from being exploited, because often, the untargeted acquisition is followed by a targeted search. Applying an actual GUS (including untargeted screening) produces an immense amount of data that must be dealt with. An optimization of the parameters regulating the feature detection and hit generation algorithms of the data processing software could significantly reduce the amount of unnecessary data and thereby the workload. Design of experiment (DoE) approaches allow a simultaneous optimization of multiple parameters. In a first step, parameters are evaluated (crucial or noncrucial). Second, crucial parameters are optimized. The aim in this study was to reduce the number of hits, without missing analytes. The obtained parameter settings from the optimization were compared to the standard settings by analyzing a test set of blood samples spiked with 22 relevant analytes as well as 62 authentic forensic cases. The optimization lead to a marked reduction of workload (12.3 to 1.1% and 3.8 to 1.1% hits for the test set and the authentic cases, respectively) while simultaneously increasing the identification rate (68.2 to 86.4% and 68.8 to 88.1%, respectively). This proof of concept study emphasizes the great potential of DoE approaches to master the data overload resulting from modern data independent acquisition methods used for general unknown screening procedures by optimizing software parameters.

Parallel Radiofrequency Transmission for the Reduction of Heating in Deep Brain Stimulation Leads at 3T

NASA Astrophysics Data System (ADS)

McElcheran, Clare

Deep Brain Stimulation (DBS) is increasingly used to treat a variety of brain diseases by sending electrical impulses to deep brain nuclei through long, electrically conductive leads. Magnetic resonance imaging (MRI) of patients pre- and post-implantation is desirable to target and position the implant, to evaluate possible side-effects and to examine DBS patients who have other health conditions. Although MRI is the preferred modality for pre-operative planning, MRI post-implantation is limited due to the risk of high local power deposition, and therefore tissue heating, at the tip of the lead. The localized power deposition arises from currents induced in the leads caused by coupling with the radiofrequency (RF) transmission field during imaging. In this thesis, parallel RF transmission (pTx) is used to tailor the RF electric field to suppress coupling effects. Three pTx coil configurations with 2-elements, 4-elements, and 8-elements, respectively, were investigated. Optimal input voltages to minimize coupling, while maintaining RF magnetic field homogeneity, were determined using a Nelder-Mead optimization algorithm. Resulting electric and magnetic fields were compared to that of a 16-rung birdcage coil. Experimental validation was performed with a custom-built 4-element pTx coil. Three cases were investigated to develop and evaluate this technique. First, a Proof-of-Concept study was performed to investigate the case of a simple, uniform cylindrical phantom with a straight, perfectly conducting wire. Second, a heterogeneous subject with bilateral, curved implanted wires was investigated. Finally, the third case investigated realistic patient lead-trajectories obtained from intra-operative CT scans. In all three cases, specific absorption rate (SAR), a metric used to quantify power deposition which results in heating, was reduced by over 90%. Maximal reduction in SAR was obtained with the 8-element pTx coil. Magnetic field homogeneity was comparable to the birdcage coil for the 4- and 8-element pTx configurations. Although further research is required before clinical implementation, these initial results suggest that the concept of optimizing pTx to reduce DBS heating effects holds considerable promise.

Prediction of pH dependent absorption using in vitro, in silico, and in vivo rat models: Early liability assessment during lead optimization.

PubMed

Saxena, Ajay; Shah, Devang; Padmanabhan, Shweta; Gautam, Shashyendra Singh; Chowan, Gajendra Singh; Mandlekar, Sandhya; Desikan, Sridhar

2015-08-30

Weakly basic compounds which have pH dependent solubility are liable to exhibit pH dependent absorption. In some cases, a subtle change in gastric pH can significantly modulate the plasma concentration of the drug and can lead to sub-therapeutic exposure of the drug. Evaluating the risk of pH dependent absorption and potential drug-drug interaction with pH modulators are important aspects of drug discovery and development. In order to assess the risk around the extent of decrease in the systemic exposure of drugs co-administered with pH modulators in the clinic, a pH effect study is carried out, typically in higher species, mostly dog. The major limitation of a higher species pH effect study is the resource and material requirement to assess this risk. Hence, these studies are mostly restricted to promising or advanced leads. In our current work, we have used in vitro aqueous solubility, in silico simulations using GastroPlus™ and an in vivo rat pH effect model to provide a qualitative assessment of the pH dependent absorption liability. Here, we evaluate ketoconazole and atazanavir with different pH dependent solubility profiles and based on in vitro, in silico and in vivo results, a different extent of gastric pH effect on absorption is predicted. The prediction is in alignment with higher species and human pH effect study results. This in vitro, in silico and in vivo (IVISIV) correlation is then extended to assess pH absorption mitigation strategy. The IVISIV predicts pH dependent absorption for BMS-582949 whereas its solubility enhancing prodrug, BMS-751324 is predicted to mitigate this liability. Overall, the material requirement for this assessment is substantially low which makes this approach more practical to screen multiple compounds during lead optimization. Copyright © 2015 Elsevier B.V. All rights reserved.

Gait training strategies to optimize walking ability in people with stroke: A synthesis of the evidence

PubMed Central

Tang, Pei Fang

2011-01-01

Stroke is a leading cause of long-term disability. Impairments resulting from stroke lead to persistent difficulties with walking and subsequently, improved walking ability is one of the highest priorities for people living with a stroke. In addition, walking ability has important health implications in providing protective effects against secondary complications common after a stroke such as heart disease or osteoporosis. This paper systematically reviews common gait training strategies (neurodevelopmental techniques, muscle strengthening, treadmill training, intensive mobility exercises) to improve walking ability. The results (descriptive summaries as well as pooled effect sizes) from randomized controlled trials are presented and implications for optimal gait training strategies are discussed. Novel and emerging gait training strategies are highlighted and research directions proposed to enable the optimal recovery and maintenance of walking ability. PMID:17939776

Guidance and flight control law development for hypersonic vehicles

NASA Technical Reports Server (NTRS)

Calise, A. J.; Markopoulos, N.

1993-01-01

During the third reporting period our efforts were focused on a reformulation of the optimal control problem involving active state-variable inequality constraints. In the reformulated problem the optimization is carried out not with respect to all controllers, but only with respect to asymptotic controllers leading to the state constraint boundary. Intimately connected with the traditional formulation is the fact that when the reduced solution for such problems lies on a state constraint boundary, the corresponding boundary layer transitions are of finite time in the stretched time scale. Thus, it has been impossible so far to apply the classical asymptotic boundary layer theory to such problems. Moreover, the traditional formulation leads to optimal controllers that are one-sided, that is, they break down when a disturbance throws the system on the prohibited side of the state constraint boundary.

Optimized mid-infrared thermal emitters for applications in aircraft countermeasures

NASA Astrophysics Data System (ADS)

Lorenzo, Simón G.; You, Chenglong; Granier, Christopher H.; Veronis, Georgios; Dowling, Jonathan P.

2017-12-01

We introduce an optimized aperiodic multilayer structure capable of broad angle and high temperature thermal emission over the 3 μm to 5 μm atmospheric transmission band. This aperiodic multilayer structure composed of alternating layers of silicon carbide and graphite on top of a tungsten substrate exhibits near maximal emittance in a 2 μm wavelength range centered in the mid-wavelength infrared band traditionally utilized for atmospheric transmission. We optimize the layer thicknesses using a hybrid optimization algorithm coupled to a transfer matrix code to maximize the power emitted in this mid-infrared range normal to the structure's surface. We investigate possible applications for these structures in mimicking 800-1000 K aircraft engine thermal emission signatures and in improving countermeasure effectiveness against hyperspectral imagers. We find these structures capable of matching the Planck blackbody curve in the selected infrared range with relatively sharp cutoffs on either side, leading to increased overall efficiency of the structures. Appropriately optimized multilayer structures with this design could lead to matching a variety of mid-infrared thermal emissions. For aircraft countermeasure applications, this method could yield a flare design capable of mimicking engine spectra and breaking the lock of hyperspectral imaging systems.

Battery management systems (BMS) optimization for electric vehicles (EVs) in Malaysia

NASA Astrophysics Data System (ADS)

Salehen, P. M. W.; Su'ait, M. S.; Razali, H.; Sopian, K.

2017-04-01

Following the UN Climate Change Conference 2009 in Copenhagen, Denmark, Malaysia seriously committed on "Go Green" campaign with the aim to reduce 40% GHG emission by the year 2020. Therefore, the National Green Technology Policy has been legalised in 2009 with transportation as one of its focused sectors, which include hybrid (HEVs), electric vehicles (EVs) and fuel cell vehicles with the purpose of to keep up with the worst scenario. While the number of registered cars has been increasing by 1 million yearly, the amount has doubled in the last two decades. Consequently, CO2 emission in Malaysia reaches up to 97.1% and will continue to increase mainly due to the activities in the transportation sector. Nevertheless, Malaysia is now moving towards on green car which battery-based EVs. This type of transportation mainly needs power performance optimization, which is controlled by the Batteries Management System (BMS). BMS is an essential module which leads to reliable power management, optimal power performance and safe vehicle that lead back for power optimization in EVs. Thus, this paper proposes power performance optimization for various setups of lithium-ion cathode with graphene anode using MATLAB/SIMULINK software for better management performance and extended EVs driving range.

Most-Critical Transient Disturbances in an Incompressible Flat-Plate Boundary Layer

NASA Astrophysics Data System (ADS)

Monschke, Jason; White, Edward

2015-11-01

Transient growth is a linear disturbance growth mechanism that plays a key role in roughness-induced boundary-layer transition. It occurs when superposed stable, non-orthogonal continuous spectrum modes experience algebraic disturbance growth followed by exponential decay. Algebraic disturbance growth can modify the basic state making it susceptible to secondary instabilities rapidly leading to transition. Optimal disturbance theory was developed to model the most-dangerous disturbances. However, evidence suggests roughness-induced transient growth is sub-optimal yet leads to transition earlier than optimal theory suggests. This research computes initial disturbances most unstable to secondary instabilities to further develop the applicability of transient growth theory to surface roughness. The main approach is using nonlinear adjoint optimization with solutions of the parabolized Navier-Stokes and BiGlobal stability equations. Two objective functions were considered: disturbance kinetic energy growth and sinuous instability growth rate. The first objective function was used as validation of the optimization method. Counter-rotating streamwise vortices located low in the boundary layer maximize the sinuous instability growth rate. The authors would like to acknowledge NASA and the AFOSR for funding this work through AFOSR Grant FA9550-09-1-0341.

An Examination of the Professional Development of Experienced Principals and Aspiring Principals in Long Island, New York Public Schools

ERIC Educational Resources Information Center

Bullock, Gay

2012-01-01

Principals are being asked to create optimal learning conditions that will "lead to improved results for students, long-term gains in school system capacity, and increased productivity and effectiveness" (RTTT, 2009). The purpose of this study was to examine the professional development offered to and sought by experienced principals and…

Forest inventories generate scientifically sound information on the forest resource, but do our data and information really matter?

Treesearch

Christoph Keinn; Goran Stahl

2009-01-01

Current research in forest inventory focuses very much on technical-statistical problems geared mainly to the optimization of data collection and information generation. The basic assumption is that better information leads to better decisions and, therefore, to better forest management and forest policy. Not many studies, however, strive to explicitly establish the...

Design, economic and system considerations of large wind-driven generators

NASA Technical Reports Server (NTRS)

Jorgensen, G. E.; Lotker, M.; Meier, R. C.; Brierley, D.

1976-01-01

The increased search for alternative energy sources has lead to renewed interest and studies of large wind-driven generators. This paper presents the results and considerations of such an investigation. The paper emphasizes the concept selection of wind-driven generators, system optimization, control system design, safety aspects, economic viability on electric utility systems and potential electric system interfacing problems.

The discovery of tricyclic pyridone JAK2 inhibitors. Part 1: hit to lead.

PubMed

Siu, Tony; Kozina, Ekaterina S; Jung, Joon; Rosenstein, Craig; Mathur, Anjili; Altman, Michael D; Chan, Grace; Xu, Lin; Bachman, Eric; Mo, Jan-Rung; Bouthillette, Melaney; Rush, Thomas; Dinsmore, Christopher J; Marshall, C Gary; Young, Jonathan R

2010-12-15

This paper describes the discovery and design of a novel class of JAK2 inhibitors. Furthermore, we detail the optimization of a screening hit using ligand binding efficiency and log D. These efforts led to the identification of compound 41, which demonstrates in vivo activity in our study. Copyright © 2010 Elsevier Ltd. All rights reserved.

Strategic targeting of advance care planning interventions: the Goldilocks phenomenon.

PubMed

Billings, J Andrew; Bernacki, Rachelle

2014-04-01

Strategically selecting patients for discussions and documentation about limiting life-sustaining treatments-choosing the right time along the end-of-life trajectory for such an intervention and identifying patients at high risk of facing end-of-life decisions-can have a profound impact on the value of advance care planning (ACP) efforts. Timing is important because the completion of an advance directive (AD) too far from or too close to the time of death can lead to end-of-life decisions that do not optimally reflect the patient's values, goals, and preferences: a poorly chosen target patient population that is unlikely to need an AD in the near future may lead to patients making unrealistic, hypothetical choices, while assessing preferences in the emergency department or hospital in the face of a calamity is notoriously inadequate. Because much of the currently studied ACP efforts have led to a disappointingly small proportion of patients eventually benefitting from an AD, careful targeting of the intervention should also improve the efficacy of such projects. A key to optimal timing and strategic selection of target patients for an ACP program is prognostication, and we briefly highlight prognostication tools and studies that may point us toward high-value AD interventions.

In vitro reconstruction of branched tubular structures from lung epithelial cells in high cell concentration gradient environment.

PubMed

Hagiwara, Masaya; Peng, Fei; Ho, Chih-Ming

2015-01-27

We have succeeded in developing hollow branching structure in vitro commonly observed in lung airway using primary lung airway epithelial cells. Cell concentration gradient is the key factor that determines production of the branching cellular structures, as optimization of this component removes the need for heterotypic culture. The higher cell concentration leads to the more production of morphogens and increases the growth rate of cells. However, homogeneous high cell concentration does not make a branching structure. Branching requires sufficient space in which cells can grow from a high concentration toward a low concentration. Simulation performed using a reaction-diffusion model revealed that long-range inhibition prevents cells from branching when they are homogeneously spread in culture environments, while short-range activation from neighboring cells leads to positive feedback. Thus, a high cell concentration gradient is required to make branching structures. Spatial distributions of morphogens, such as BMP-4, play important roles in the pattern formation. This simple yet robust system provides an optimal platform for the further study and understanding of branching mechanisms in the lung airway, and will facilitate chemical and genetic studies of lung morphogenesis programs.

Longitudinal relaxation optimized amide 1H-CEST experiments for studying slow chemical exchange processes in fully protonated proteins.

PubMed

Yuwen, Tairan; Kay, Lewis E

2017-04-01

Chemical Exchange Saturation Transfer (CEST) experiments are increasingly used to study slow timescale exchange processes in biomolecules. Although 15 N- and 13 C-CEST have been the approaches of choice, the development of spin state selective 1 H-CEST pulse sequences that separate the effects of chemical and dipolar exchange [T. Yuwen, A. Sekhar and L. E. Kay, Angew Chem Int Ed Engl 2016 doi: 10.1002/anie.201610759 (Yuwen et al. 2017)] significantly increases the utility of 1 H-based experiments. Pulse schemes have been described previously for studies of highly deuterated proteins. We present here longitudinal-relaxation optimized amide 1 H-CEST experiments for probing chemical exchange in protonated proteins. Applications involving a pair of proteins are presented establishing that accurate 1 H chemical shifts of sparsely populated conformers can be obtained from simple analyses of 1 H-CEST profiles. A discussion of the inherent differences between 15 N-/ 13 C- and 1 H-CEST experiments is presented, leading to an optimal strategy for recording 1 H-CEST experiments.

A Hamiltonian approach to the planar optimization of mid-course corrections

NASA Astrophysics Data System (ADS)

Iorfida, E.; Palmer, P. L.; Roberts, M.

2016-04-01

Lawden's primer vector theory gives a set of necessary conditions that characterize the optimality of a transfer orbit, defined accordingly to the possibility of adding mid-course corrections. In this paper a novel approach is proposed where, through a polar coordinates transformation, the primer vector components decouple. Furthermore, the case when transfer, departure and arrival orbits are coplanar is analyzed using a Hamiltonian approach. This procedure leads to approximate analytic solutions for the in-plane components of the primer vector. Moreover, the solution for the circular transfer case is proven to be the Hill's solution. The novel procedure reduces the mathematical and computational complexity of the original case study. It is shown that the primer vector is independent of the semi-major axis of the transfer orbit. The case with a fixed transfer trajectory and variable initial and final thrust impulses is studied. The acquired related optimality maps are presented and analyzed and they express the likelihood of a set of trajectories to be optimal. Furthermore, it is presented which kind of requirements have to be fulfilled by a set of departure and arrival orbits to have the same profile of primer vector.

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Multi-parameter geometrical scaledown study for energy optimization of MTJ and related spintronics nanodevices

NASA Astrophysics Data System (ADS)

Farhat, I. A. H.; Alpha, C.; Gale, E.; Atia, D. Y.; Stein, A.; Isakovic, A. F.

The scaledown of magnetic tunnel junctions (MTJ) and related nanoscale spintronics devices poses unique challenges for energy optimization of their performance. We demonstrate the dependence of the switching current on the scaledown variable, while considering the influence of geometric parameters of MTJ, such as the free layer thickness, tfree, lateral size of the MTJ, w, and the anisotropy parameter of the MTJ. At the same time, we point out which values of the saturation magnetization, Ms, and anisotropy field, Hk, can lead to lowering the switching current and overall decrease of the energy needed to operate an MTJ. It is demonstrated that scaledown via decreasing the lateral size of the MTJ, while allowing some other parameters to be unconstrained, can improve energy performance by a measurable factor, shown to be the function of both geometric and physical parameters above. Given the complex interdependencies among both families of parameters, we developed a particle swarm optimization (PSO) algorithm that can simultaneously lower energy of operation and the switching current density. Results we obtained in scaledown study and via PSO optimization are compared to experimental results. Support by Mubadala-SRC 2012-VJ-2335 is acknowledged, as are staff at Cornell-CNF and BNL-CFN.

Optimization of LDL targeted nanostructured lipid carriers of 5-FU by a full factorial design.

PubMed

Andalib, Sare; Varshosaz, Jaleh; Hassanzadeh, Farshid; Sadeghi, Hojjat

2012-01-01

Nanostructured lipid carriers (NLC) are a mixture of solid and liquid lipids or oils as colloidal carrier systems that lead to an imperfect matrix structure with high ability for loading water soluble drugs. The aim of this study was to find the best proportion of liquid and solid lipids of different types for optimization of the production of LDL targeted NLCs used in carrying 5-Fu by the emulsification-solvent evaporation method. The influence of the lipid type, cholesterol or cholesteryl stearate for targeting LDL receptors, oil type (oleic acid or octanol), lipid and oil% on particle size, surface charge, drug loading efficiency, and drug released percent from the NLCs were studied by a full factorial design. The NLCs prepared by 54.5% cholesterol and 25% of oleic acid, showed optimum results with particle size of 105.8 nm, relatively high zeta potential of -25 mV, drug loading efficiency of 38% and release efficiency of about 40%. Scanning electron microscopy of nanoparticles confirmed the results of dynamic light scattering method used in measuring the particle size of NLCs. The optimization method by a full factorial statistical design is a useful optimization method for production of nanostructured lipid carriers.

Detonation energies of explosives by optimized JCZ3 procedures

NASA Astrophysics Data System (ADS)

Stiel, Leonard I.; Baker, Ernest L.

1998-07-01

Procedures for the detonation properties of explosives have been extended for the calculation of detonation energies at adiabatic expansion conditions. The use of the JCZ3 equation of state with optimized Exp-6 potential parameters leads to lower errors in comparison to JWL detonation energies than for other methods tested.

NREL Leads Energy Systems Integration - Continuum Magazine | NREL

Science.gov Websites

performance data to manage and optimize campus energy use. Integrated Solutions for a Complex Energy World 03 Integrated Solutions for a Complex Energy World Energy systems integration optimizes the design and efficient data centers in the world. Sustainability through Dynamic Energy Management Sustainability through

Pilot Project to Optimize Ground Water Remediation Systems at RCRA Corrective Action Facilities: Summary Report and Lessons Learned

EPA Pesticide Factsheets

Based on previous success with conducting independent optimization evaluations at Fund-lead pump and treat sites (i.e., those sites with pump and treat systems funded and managed by Superfund and the States), the EPA Office of Superfund .....

Experimental study on the optimal purge duration of a proton exchange membrane fuel cell with a dead-ended anode

NASA Astrophysics Data System (ADS)

Lin, Yu-Fen; Chen, Yong-Song

2017-02-01

When a proton exchange membrane fuel cell (PEMFC) is operated with a dead-ended anode, impurities gradually accumulate within the anode, resulting in a performance drop. An anode purge is thereby ultimately required to remove impurities within the anode. A purge strategy comprises purge interval (valve closed) and purge duration (valve is open). A short purge interval causes frequent and unnecessary activation of the valve, whereas a long purge interval leads to excessive impurity accumulation. A short purge duration causes an incomplete performance recovery, whereas a long purge duration results in low hydrogen utilization. In this study, a series of experimental trials was conducted to simultaneously measure the hydrogen supply rate and power generation of a PEMFC at a frequency of 50 Hz for various operating current density levels and purge durations. The effect of purge duration on the cell's energy efficiency was subsequently analyzed and discussed. The results showed that the optimal purge duration for the PEMFC was approximately 0.2 s. Based on the results of this study, a methodical process for determining optimal purge durations was ultimately proposed for widespread application. Purging approximately one-fourth of anode gas can obtain optimal energy efficiency for a PEMFC with a dead-ended anode.

Structure change of β-hairpin induced by turn optimization: an enhanced sampling molecular dynamics simulation study.

PubMed

Shao, Qiang; Yang, Lijiang; Gao, Yi Qin

2011-12-21

Our previous study showed that for the tested polypeptides which have similar β-hairpin structures but different sequences, their folding free energy pathways are dominantly determined by the turn conformational propensity. In this study, we study how the turn conformational propensity affects the structure of hairpins. The folding of two mutants of GB1p peptide (GB1m2 and GB1m3), which have the optimized turn sequence ((6)DDATK(11)T → (6)NPATG(11)K) with native structures unsolved, were simulated using integrated tempering sampling molecular dynamics simulations and the predicted stable structures were compared to wild-type GB1p. It was observed that the turn optimization of GB1p generates a more favored 5-residue type I(') turn in addition to the 6-residue type I turn in wild-type GB1p. As a result two distinctly different hairpin structures are formed corresponding to the "misfolded" (M) and the "folded" (F) states. M state is a one-residue-shifted asymmetric β-hairpin structure whereas F state has the similar symmetric hairpin structure as wild-type GB1p. The formation of the favored type I(') turn has a small free energy barrier and leads to the shifted β-hairpin structure, following the modified "zipping" model. The presence of disfavored type I turn structure makes the folding of a β-hairpin consistent with the "hydrophobic-core-centric" model. On the other hand, the folding simulations on other two GB1p mutants (GB1r1 and GBr2), which have the position of the hydrophobic core cluster further away from the turn compared to wild-type GB1p, showed that moving the hydrophobic core cluster away from the turn region destabilizes but does not change the hairpin structure. Therefore, the present study showed that the turn conformational propensity is a key factor in affecting not only the folding pathways but also the stable structure of β-hairpins, and the turn conformational change induced by the turn optimization leads to significant changes of β-hairpin structure.

Zirconium-based highly porous metal-organic framework (MOF-545) as an efficient adsorbent for vortex assisted-solid phase extraction of lead from cereal, beverage and water samples.

PubMed

Tokalıoğlu, Şerife; Yavuz, Emre; Demir, Selçuk; Patat, Şaban

2017-12-15

In this study, zirconium-based highly porous metal-organic framework, MOF-545, was synthesized and characterized. The surface area of MOF-545 was found to be 2192m 2 /g. This adsorbent was used for the first time as an adsorbent for the vortex assisted-solid phase extraction of Pb(II) from cereal, beverage and water samples. Lead in solutions was determined by FAAS. The optimal experimental conditions were as follows: the amount of MOF-545, 10mg; pH of sample, 7; adsorption and elution time, 15min; and elution solvent, 2mL of 1molL -1 HCl. Under the optimal conditions of the method, the limit of detection, preconcentration factor and precision as RSD% were found to be 1.78μgL -1 , 125 and 2.6%, respectively. The adsorption capacity of the adsorbent for lead was found to be 73mgg -1 . The method was successfully verified by analyzing two certified reference materials (BCR-482 Lichen and SPS-WW1 Batch 114) and spiked chickpea, bean, wheat, lentil, cherry juice, mineral water, well water and wastewater samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapid optimization of multiple-burn rocket flights.

NASA Technical Reports Server (NTRS)

Brown, K. R.; Harrold, E. F.; Johnson, G. W.

1972-01-01

Different formulations of the fuel optimization problem for multiple burn trajectories are considered. It is shown that certain customary idealizing assumptions lead to an ill-posed optimization problem for which no solution exists. Several ways are discussed for avoiding such difficulties by more realistic problem statements. An iterative solution of the boundary value problem is presented together with efficient coast arc computations, the right end conditions for various orbital missions, and some test results.

Topology optimization analysis based on the direct coupling of the boundary element method and the level set method

NASA Astrophysics Data System (ADS)

Vitório, Paulo Cezar; Leonel, Edson Denner

2017-12-01

The structural design must ensure suitable working conditions by attending for safe and economic criteria. However, the optimal solution is not easily available, because these conditions depend on the bodies' dimensions, materials strength and structural system configuration. In this regard, topology optimization aims for achieving the optimal structural geometry, i.e. the shape that leads to the minimum requirement of material, respecting constraints related to the stress state at each material point. The present study applies an evolutionary approach for determining the optimal geometry of 2D structures using the coupling of the boundary element method (BEM) and the level set method (LSM). The proposed algorithm consists of mechanical modelling, topology optimization approach and structural reconstruction. The mechanical model is composed of singular and hyper-singular BEM algebraic equations. The topology optimization is performed through the LSM. Internal and external geometries are evolved by the LS function evaluated at its zero level. The reconstruction process concerns the remeshing. Because the structural boundary moves at each iteration, the body's geometry change and, consequently, a new mesh has to be defined. The proposed algorithm, which is based on the direct coupling of such approaches, introduces internal cavities automatically during the optimization process, according to the intensity of Von Mises stress. The developed optimization model was applied in two benchmarks available in the literature. Good agreement was observed among the results, which demonstrates its efficiency and accuracy.

Optimal designs for prediction studies of whiplash.

PubMed

Kamper, Steven J; Hancock, Mark J; Maher, Christopher G

2011-12-01

Commentary. To provide guidance for the design and interpretation of predictive studies of whiplash associated disorders (WAD). Numerous studies have sought to define and explain the clinical course and response to treatment of people with WAD. Design of these studies is often suboptimal, which can lead to biased findings and issues with interpreting the results. Literature review and commentary. Predictive studies can be grouped into four broad categories; studies of symptomatic course, studies that aim to identify factors that predict outcome, studies that aim to isolate variables that are causally responsible for outcome, and studies that aim to identify patients who respond best to particular treatments. Although the specific research question will determine the optimal methods, there are a number of generic features that should be incorporated into design of such studies. The aim of these features is to minimize bias, generate adequately precise prognostic estimates, and ensure generalizability of the findings. This paper provides a summary of important considerations in the design, conduct, and reporting of prediction studies in the field of whiplash.

Optimization Of PVDF-TrFE Processing Conditions For The Fabrication Of Organic MEMS Resonators

PubMed Central

Ducrot, Pierre-Henri; Dufour, Isabelle; Ayela, Cédric

2016-01-01

This paper reports a systematic optimization of processing conditions of PVDF-TrFE piezoelectric thin films, used as integrated transducers in organic MEMS resonators. Indeed, despite data on electromechanical properties of PVDF found in the literature, optimized processing conditions that lead to these properties remain only partially described. In this work, a rigorous optimization of parameters enabling state-of-the-art piezoelectric properties of PVDF-TrFE thin films has been performed via the evaluation of the actuation performance of MEMS resonators. Conditions such as annealing duration, poling field and poling duration have been optimized and repeatability of the process has been demonstrated. PMID:26792224

Optimization Of PVDF-TrFE Processing Conditions For The Fabrication Of Organic MEMS Resonators.

PubMed

Ducrot, Pierre-Henri; Dufour, Isabelle; Ayela, Cédric

2016-01-21

This paper reports a systematic optimization of processing conditions of PVDF-TrFE piezoelectric thin films, used as integrated transducers in organic MEMS resonators. Indeed, despite data on electromechanical properties of PVDF found in the literature, optimized processing conditions that lead to these properties remain only partially described. In this work, a rigorous optimization of parameters enabling state-of-the-art piezoelectric properties of PVDF-TrFE thin films has been performed via the evaluation of the actuation performance of MEMS resonators. Conditions such as annealing duration, poling field and poling duration have been optimized and repeatability of the process has been demonstrated.

Optimization of the protocols for the use of contrast agents in PET/CT studies.

PubMed

Pelegrí Martínez, L; Kohan, A A; Vercher Conejero, J L

The introduction of PET/CT scanners in clinical practice in 1998 has improved care for oncologic patients throughout the clinical pathway, from the initial diagnosis of disease through the evaluation of the response to treatment to screening for possible recurrence. The CT component of a PET/CT study is used to correct the attenuation of PET studies; CT also provides anatomic information about the distribution of the radiotracer. CT is especially useful in situations where PET alone can lead to false positives and false negatives, and CT thereby improves the diagnostic performance of PET. The use of intravenous or oral contrast agents and optimal CT protocols have improved the detection and characterization of lesions. However, there are circumstances in which the systematic use of contrast agents is not justified. The standard acquisition in PET/CT scanners is the whole body protocol, but this can lead to artifacts due to the position of patients and respiratory movements between the CT and PET acquisitions. This article discusses these aspects from a constructive perspective with the aim of maximizing the diagnostic potential of PET/CT and providing better care for patients. Copyright © 2016 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets.

PubMed

Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

PubMed Central

Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817

Computed Tomography 3-D Imaging of the Metal Deformation Flow Path in Friction Stir Welding

NASA Technical Reports Server (NTRS)

Schneider, Judy; Beshears, Ronald; Nunes, Arthur C., Jr.

2005-01-01

In friction stir welding (FSW), a rotating threaded pin tool is inserted into a weld seam and literally stirs the edges of the seam together. To determine optimal processing parameters for producing a defect free weld, a better understanding of the resulting metal deformation flow path is required. Marker studies are the principal method of studying the metal deformation flow path around the FSW pin tool. In our study, we have used computed tomography (CT) scans to reveal the flow pattern of a lead wire embedded in a FSW weld seam. At the welding temperature of aluminum, the lead becomes molten and is carried with the macro-flow of the weld metal. By using CT images, a 3-dimensional (3D) image of the lead flow pattern can be reconstructed. CT imaging was found to be a convenient and comprehensive way of collecting and displaying tracer data. It marks an advance over previous more tedious and ambiguous radiographic/metallographic data collection methods.

Rapid and Highly Sensitive Detection of Lead Ions in Drinking Water Based on a Strip Immunosensor

PubMed Central

Kuang, Hua; Xing, Changrui; Hao, Changlong; Liu, Liqiang; Wang, Libing; Xu, Chuanlai

2013-01-01

In this study, we have first developed a rapid and sensitive strip immunosensor based on two heterogeneously-sized gold nanoparticles (Au NPs) probes for the detection of trace lead ions in drinking water. The sensitivity was 4-fold higher than that of the conventional LFA under the optimized conditions. The visual limit of detection (LOD) of the amplified method for qualitative detection lead ions was 2 ng/mL and the LOD for semi-quantitative detection could go down to 0.19 ng/mL using a scanning reader. The method suffered from no interference from other metal ions and could be used to detect trace lead ions in drinking water without sample enrichment. The recovery of the test samples ranged from 96% to 103%. As the detection method could be accomplished within 15 min, this method could be used as a potential tool for preliminary monitoring of lead contamination in drinking water. PMID:23539028

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

Jimenez, O.; Roa, Luis; Delgado, A.

We study the probabilistic cloning of equidistant states. These states are such that the inner product between them is a complex constant or its conjugate. Thereby, it is possible to study their cloning in a simple way. In particular, we are interested in the behavior of the cloning probability as a function of the phase of the overlap among the involved states. We show that for certain families of equidistant states Duan and Guo's cloning machine leads to cloning probabilities lower than the optimal unambiguous discrimination probability of equidistant states. We propose an alternative cloning machine whose cloning probability ismore » higher than or equal to the optimal unambiguous discrimination probability for any family of equidistant states. Both machines achieve the same probability for equidistant states whose inner product is a positive real number.« less

Cloud, Aerosol, and Volcanic Ash Retrievals Using ASTR and SLSTR with ORAC

NASA Astrophysics Data System (ADS)

McGarragh, Gregory; Poulsen, Caroline; Povey, Adam; Thomas, Gareth; Christensen, Matt; Sus, Oliver; Schlundt, Cornelia; Stapelberg, Stefan; Stengel, Martin; Grainger, Don

2015-12-01

The Optimal Retrieval of Aerosol and Cloud (ORAC) is a generalized optimal estimation system that retrieves cloud, aerosol and volcanic ash parameters using satellite imager measurements in the visible to infrared. Use of the same algorithm for different sensors and parameters leads to consistency that facilitates inter-comparison and interaction studies. ORAC currently supports ATSR, AVHRR, MODIS and SEVIRI. In this proceeding we discuss the ORAC retrieval algorithm applied to ATSR data including the retrieval methodology, the forward model, uncertainty characterization and discrimination/classification techniques. Application of ORAC to SLSTR data is discussed including the additional features that SLSTR provides relative to the ATSR heritage. The ORAC level 2 and level 3 results are discussed and an application of level 3 results to the study of cloud/aerosol interactions is presented.

The WOMEN study: what is the optimal method for ischemia evaluation in women? A multi-center, prospective, randomized study to establish the optimal method for detection of coronary artery disease (CAD) risk in women at an intermediate-high pretest likelihood of CAD: study design.

PubMed

Mieres, Jennifer H; Shaw, Leslee J; Hendel, Robert C; Heller, Gary V

2009-01-01

Coronary artery disease remains the leading cause of morbidity and mortality in women. The optimal non-invasive test for evaluation of ischemic heart disease in women is unknown. Although current guidelines support the choice of the exercise tolerance test (ETT) as a first line test for women with a normal baseline ECG and adequate exercise capabilities, supportive data for this recommendation are controversial. The what is the optimal method for ischemia evaluation in women? (WOMEN) study was designed to determine the optimal non-invasive strategy for CAD risk detection of intermediate and high risk women presenting with chest pain or equivalent symptoms suggestive of ischemic heart disease. The study will prospectively compare the 2-year event rates in women capable of performing exercise treadmill testing or Tc-99 m tetrofosmin SPECT myocardial perfusion imaging (MPI). The study will enroll women presenting for the evaluation of chest pain or anginal equivalent symptoms who are capable of performing >5 METs of exercise while at intermediate-high pretest risk for ischemic heart disease who will be randomized to either ETT testing alone or with Tc-99 m tetrofosmin SPECT MPI. The null hypothesis for this project is that the exercise ECG has the same negative predictive value for risk detection as gated myocardial perfusion SPECT in women. The primary aim is to compare 2-year cardiac event rates in women randomized to SPECT MPI to those randomized to ETT. The WOMEN study seeks to provide objective information for guidelines for the evaluation of symptomatic women with an intermediate-high likelihood for CAD.

Homotopy method for optimization of variable-specific-impulse low-thrust trajectories

NASA Astrophysics Data System (ADS)

Chi, Zhemin; Yang, Hongwei; Chen, Shiyu; Li, Junfeng

2017-11-01

The homotopy method has been used as a useful tool in solving fuel-optimal trajectories with constant-specific-impulse low thrust. However, the specific impulse is often variable for many practical solar electric power-limited thrusters. This paper investigates the application of the homotopy method for optimization of variable-specific-impulse low-thrust trajectories. Difficulties arise when the two commonly-used homotopy functions are employed for trajectory optimization. The optimal power throttle level and the optimal specific impulse are coupled with the commonly-used quadratic and logarithmic homotopy functions. To overcome these difficulties, a modified logarithmic homotopy function is proposed to serve as a gateway for trajectory optimization, leading to decoupled expressions of both the optimal power throttle level and the optimal specific impulse. The homotopy method based on this homotopy function is proposed. Numerical simulations validate the feasibility and high efficiency of the proposed method.

SU-D-12A-07: Optimization of a Moving Blocker System for Cone-Beam Computed Tomography Scatter Correction

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

Ouyang, L; Yan, H; Jia, X

2014-06-01

Purpose: A moving blocker based strategy has shown promising results for scatter correction in cone-beam computed tomography (CBCT). Different parameters of the system design affect its performance in scatter estimation and image reconstruction accuracy. The goal of this work is to optimize the geometric design of the moving block system. Methods: In the moving blocker system, a blocker consisting of lead strips is inserted between the x-ray source and imaging object and moving back and forth along rotation axis during CBCT acquisition. CT image of an anthropomorphic pelvic phantom was used in the simulation study. Scatter signal was simulated bymore » Monte Carlo calculation with various combinations of the lead strip width and the gap between neighboring lead strips, ranging from 4 mm to 80 mm (projected at the detector plane). Scatter signal in the unblocked region was estimated by cubic B-spline interpolation from the blocked region. Scatter estimation accuracy was quantified as relative root mean squared error by comparing the interpolated scatter to the Monte Carlo simulated scatter. CBCT was reconstructed by total variation minimization from the unblocked region, under various combinations of the lead strip width and gap. Reconstruction accuracy in each condition is quantified by CT number error as comparing to a CBCT reconstructed from unblocked full projection data. Results: Scatter estimation error varied from 0.5% to 2.6% as the lead strip width and the gap varied from 4mm to 80mm. CT number error in the reconstructed CBCT images varied from 12 to 44. Highest reconstruction accuracy is achieved when the blocker lead strip width is 8 mm and the gap is 48 mm. Conclusions: Accurate scatter estimation can be achieved in large range of combinations of lead strip width and gap. However, image reconstruction accuracy is greatly affected by the geometry design of the blocker.« less

Modeling, hybridization, and optimal charging of electrical energy storage systems

NASA Astrophysics Data System (ADS)

Parvini, Yasha

The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems analytically. Efficiency analysis for constant power (CP) and optimal charging strategies under different charging times (slow and fast) was performed. In case of the lithium ion battery, the model included the electronic as well as polarization resistance. Furthermore, in order to investigate the influence of temperature on the internal resistance of the lithium ion battery, the optimal charging problem for a three state electro-thermal model was solved using dynamic programming (DP). The ability to charge electric vehicles is a pace equivalent to fueling a gasoline car will be a game changer in the widespread acceptability and feasibility of the electric vehicles. Motivated by the knowledge gained from the optimal charging study, the challenges facing the fast charging of lithium ion batteries are investigated. In this context, the suitable models for the study of fast charging, high rate anode materials, and different charging strategies are studied. The side effects of fast charging such as lithium plating and mechanical failure are also discussed. This dissertation has targeted some of the most challenging questions in the field of electrical energy storage systems and the reported results are applicable to a wide range of applications such as in electronic gadgets, medical devices, electricity grid, and electric vehicles.

Flight style optimization in ski jumping on normal, large, and ski flying hills.

PubMed

Jung, Alexander; Staat, Manfred; Müller, Wolfram

2014-02-07

In V-style ski jumping, aerodynamic forces are predominant performance factors and athletes have to solve difficult optimization problems in parts of a second in order to obtain their jump length maximum and to keep the flight stable. Here, a comprehensive set of wind tunnel data was used for optimization studies based on Pontryagin's minimum principle with both the angle of attack α and the body-ski angle β as controls. Various combinations of the constraints αmax and βmin(t) were analyzed in order to compare different optimization strategies. For the computer simulation studies, the Olympic hill profiles in Esto-Sadok, Russia (HS 106m, HS 140m), and in Harrachov, Czech Republic, host of the Ski Flying World Championships 2014 (HS 205m) were used. It is of high importance for ski jumping practice that various aerodynamic strategies, i.e. combinations of α- and β-time courses, can lead to similar jump lengths which enables athletes to win competitions using individual aerodynamic strategies. Optimization results also show that aerodynamic behavior has to be different at different hill sizes (HS). Optimized time courses of α and β using reduced drag and lift areas in order to mimic recent equipment regulations differed only in a negligible way. This indicates that optimization results presented here are not very sensitive to minor changes of the aerodynamic equipment features when similar jump length are obtained by using adequately higher in-run velocities. However, wind tunnel measurements with athletes including take-off and transition to stabilized flight, flight, and landing behavior would enable a more detailed understanding of individual flight style optimization. © 2013 Published by Elsevier Ltd.

Reducing the metabolic cost of walking with an ankle exoskeleton: interaction between actuation timing and power.

PubMed

Galle, Samuel; Malcolm, Philippe; Collins, Steven Hartley; De Clercq, Dirk

2017-04-27

Powered ankle-foot exoskeletons can reduce the metabolic cost of human walking to below normal levels, but optimal assistance properties remain unclear. The purpose of this study was to test the effects of different assistance timing and power characteristics in an experiment with a tethered ankle-foot exoskeleton. Ten healthy female subjects walked on a treadmill with bilateral ankle-foot exoskeletons in 10 different assistance conditions. Artificial pneumatic muscles assisted plantarflexion during ankle push-off using one of four actuation onset timings (36, 42, 48 and 54% of the stride) and three power levels (average positive exoskeleton power over a stride, summed for both legs, of 0.2, 0.4 and 0.5 W∙kg -1 ). We compared metabolic rate, kinematics and electromyography (EMG) between conditions. Optimal assistance was achieved with an onset of 42% stride and average power of 0.4 W∙kg -1 , leading to 21% reduction in metabolic cost compared to walking with the exoskeleton deactivated and 12% reduction compared to normal walking without the exoskeleton. With suboptimal timing or power, the exoskeleton still reduced metabolic cost, but substantially less so. The relationship between timing, power and metabolic rate was well-characterized by a two-dimensional quadratic function. The assistive mechanisms leading to these improvements included reducing muscular activity in the ankle plantarflexors and assisting leg swing initiation. These results emphasize the importance of optimizing exoskeleton actuation properties when assisting or augmenting human locomotion. Our optimal assistance onset timing and average power levels could be used for other exoskeletons to improve assistance and resulting benefits.

High-Intensity Interval Training After Stroke: An Opportunity to Promote Functional Recovery, Cardiovascular Health, and Neuroplasticity.

PubMed

Crozier, Jennifer; Roig, Marc; Eng, Janice J; MacKay-Lyons, Marilyn; Fung, Joyce; Ploughman, Michelle; Bailey, Damian M; Sweet, Shane N; Giacomantonio, Nicholas; Thiel, Alexander; Trivino, Michael; Tang, Ada

2018-04-01

Stroke is the leading cause of adult disability. Individuals poststroke possess less than half of the cardiorespiratory fitness (CRF) as their nonstroke counterparts, leading to inactivity, deconditioning, and an increased risk of cardiovascular events. Preserving cardiovascular health is critical to lower stroke risk; however, stroke rehabilitation typically provides limited opportunity for cardiovascular exercise. Optimal cardiovascular training parameters to maximize recovery in stroke survivors also remains unknown. While stroke rehabilitation recommendations suggest the use of moderate-intensity continuous exercise (MICE) to improve CRF, neither is it routinely implemented in clinical practice, nor is the intensity always sufficient to elicit a training effect. High-intensity interval training (HIIT) has emerged as a potentially effective alternative that encompasses brief high-intensity bursts of exercise interspersed with bouts of recovery, aiming to maximize cardiovascular exercise intensity in a time-efficient manner. HIIT may provide an alternative exercise intervention and invoke more pronounced benefits poststroke. To provide an updated review of HIIT poststroke through ( a) synthesizing current evidence; ( b) proposing preliminary considerations of HIIT parameters to optimize benefit; ( c) discussing potential mechanisms underlying changes in function, cardiovascular health, and neuroplasticity following HIIT; and ( d) discussing clinical implications and directions for future research. Preliminary evidence from 10 studies report HIIT-associated improvements in functional, cardiovascular, and neuroplastic outcomes poststroke; however, optimal HIIT parameters remain unknown. Larger randomized controlled trials are necessary to establish ( a) effectiveness, safety, and optimal training parameters within more heterogeneous poststroke populations; (b) potential mechanisms of HIIT-associated improvements; and ( c) adherence and psychosocial outcomes.

Does training under consistent mapping conditions lead to automatic attention attraction to targets in search tasks?

PubMed

Lefebvre, Christine; Cousineau, Denis; Larochelle, Serge

2008-11-01

Schneider and Shiffrin (1977) proposed that training under consistent stimulus-response mapping (CM) leads to automatic target detection in search tasks. Other theories, such as Treisman and Gelade's (1980) feature integration theory, consider target-distractor discriminability as the main determinant of search performance. The first two experiments pit these two principles against each other. The results show that CM training is neither necessary nor sufficient to achieve optimal search performance. Two other experiments examine whether CM trained targets, presented as distractors in unattended display locations, attract attention away from current targets. The results are again found to vary with target-distractor similarity. Overall, the present study strongly suggests that CM training does not invariably lead to automatic attention attraction in search tasks.

An integrated production-inventory model for the singlevendor two-buyer problem with partial backorder, stochastic demand, and service level constraints

NASA Astrophysics Data System (ADS)

Arfawi Kurdhi, Nughthoh; Adi Diwiryo, Toray; Sutanto

2016-02-01

This paper presents an integrated single-vendor two-buyer production-inventory model with stochastic demand and service level constraints. Shortage is permitted in the model, and partial backordered partial lost sale. The lead time demand is assumed follows a normal distribution and the lead time can be reduced by adding crashing cost. The lead time and ordering cost reductions are interdependent with logaritmic function relationship. A service level constraint policy corresponding to each buyer is considered in the model in order to limit the level of inventory shortages. The purpose of this research is to minimize joint total cost inventory model by finding the optimal order quantity, safety stock, lead time, and the number of lots delivered in one production run. The optimal production-inventory policy gained by the Lagrange method is shaped to account for the service level restrictions. Finally, a numerical example and effects of the key parameters are performed to illustrate the results of the proposed model.

The clinical benefit of cardiac resynchronization therapy optimization using a device-based hemodynamic sensor in a patient with dilated cardiomyopathy: a case report.

PubMed

Volpicelli, Mario; Covino, Gregorio; Capogrosso, Paolo

2015-12-19

Results on the evolution of the clinical status of patients undergoing cardiac resynchronization therapy with a defibrillator after automatic optimization of their cardiac resynchronization therapy are scarce. We observed a rapid and important change in the clinical status of our non-responding patient following activation of a sensor capable of weekly atrioventricular and interventricular delays' optimization. A 78-year-old Caucasian man presented with dilated cardiomyopathy, left bundle branch block, a left ventricular ejection fraction of 35 %, New York Heart Association class III/IV heart failure, and paroxysmal atrial fibrillation. Our patient was implanted with a cardiac resynchronization device with a defibrillator and the SonRtip atrial lead. Right ventricular and left ventricular leads were also implanted. Because of the recurrence of atrial fibrillation, the automatic optimization was set off at discharge. Consequently, the device did not optimize atrioventricular and interventricular delays (programming at discharge: 125 ms for the atrioventricular delay and 0 ms for the interventriculardelay). Our patient was treated with an anti-arrhythmic drug. Five months after implantation, his clinical status remained impaired (left ventricular ejection fraction = 30 %). The SonR signal amplitude had also decreased from 0.52 g to 0.29 g. Nevertheless, because our patient was no longer presenting with atrial fibrillation, the anti-arrhythmic treatment was stopped and the SonR optimization system was activated. After 2 months of automatic cardiac resynchronization therapy with defibrillator optimization, our patient's clinical status had significantly improved (left ventricular ejection fraction = 60 %, New York Heart Association class II) and the SonR signal amplitude had doubled shortly after the first weekly automatic optimization. In this non-responding patient, device-based automatic cardiac resynchronization therapy optimization was shown to significantly improve his clinical status.

Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks.

PubMed

Dilkina, Bistra; Houtman, Rachel; Gomes, Carla P; Montgomery, Claire A; McKelvey, Kevin S; Kendall, Katherine; Graves, Tabitha A; Bernstein, Richard; Schwartz, Michael K

2017-02-01

Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs and by allowing derived corridors to more closely reflect conservation priorities. © 2016 Society for Conservation Biology.

Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks

USGS Publications Warehouse

Dilkina, Bistra; Houtman, Rachel; Gomes, Carla P.; Montgomery, Claire A.; McKelvey, Kevin; Kendall, Katherine; Graves, Tabitha A.; Bernstein, Richard; Schwartz, Michael K.

2017-01-01

Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs and by allowing derived corridors to more closely reflect conservation priorities.

Functional and Structural Optimality in Plant Growth: A Crop Modelling Case Study

NASA Astrophysics Data System (ADS)

Caldararu, S.; Purves, D. W.; Smith, M. J.

2014-12-01

Simple mechanistic models of vegetation processes are essential both to our understanding of plant behaviour and to our ability to predict future changes in vegetation. One concept that can take us closer to such models is that of plant optimality, the hypothesis that plants aim to achieve an optimal state. Conceptually, plant optimality can be either structural or functional optimality. A structural constraint would mean that plants aim to achieve a certain structural characteristic such as an allometric relationship or nutrient content that allows optimal function. A functional condition refers to plants achieving optimal functionality, in most cases by maximising carbon gain. Functional optimality conditions are applied on shorter time scales and lead to higher plasticity, making plants more adaptable to changes in their environment. In contrast, structural constraints are optimal given the specific environmental conditions that plants are adapted to and offer less flexibility. We exemplify these concepts using a simple model of crop growth. The model represents annual cycles of growth from sowing date to harvest, including both vegetative and reproductive growth and phenology. Structural constraints to growth are represented as an optimal C:N ratio in all plant organs, which drives allocation throughout the vegetative growing stage. Reproductive phenology - i.e. the onset of flowering and grain filling - is determined by a functional optimality condition in the form of maximising final seed mass, so that vegetative growth stops when the plant reaches maximum nitrogen or carbon uptake. We investigate the plants' response to variations in environmental conditions within these two optimality constraints and show that final yield is most affected by changes during vegetative growth which affect the structural constraint.

Thermodynamic Behavior Research Analysis of Twin-roll Casting Lead Alloy Strip Process

NASA Astrophysics Data System (ADS)

Jiang, Chengcan; Rui, Yannian

2017-03-01

The thermodynamic behavior of twin-roll casting (TRC) lead alloy strip process directly affects the forming of the lead strip, the quality of the lead strip and the production efficiency. However, there is little research on the thermodynamics of lead alloy strip at home and abroad. The TRC lead process is studied in four parameters: the pouring temperature of molten lead, the depth of molten pool, the roll casting speed, and the rolling thickness of continuous casting. Firstly, the thermodynamic model for TRC lead process is built. Secondly, the thermodynamic behavior of the TRC process is simulated with the use of Fluent. Through the thermodynamics research and analysis, the process parameters of cast rolling lead strip can be obtained: the pouring temperature of molten lead: 360-400 °C, the depth of molten pool: 250-300 mm, the roll casting speed: 2.5-3 m/min, the rolling thickness: 8-9 mm. Based on the above process parameters, the optimal parameters(the pouring temperature of molten lead: 375-390 °C, the depth of molten pool: 285-300 mm, the roll casting speed: 2.75-3 m/min, the rolling thickness: 8.5-9 mm) can be gained with the use of the orthogonal experiment. Finally, the engineering test of TRC lead alloy strip is carried out and the test proves the thermodynamic model is scientific, necessary and correct. In this paper, a detailed study on the thermodynamic behavior of lead alloy strip is carried out and the process parameters of lead strip forming are obtained through the research, which provide an effective theoretical guide for TRC lead alloy strip process.

In silico optimization of pharmacokinetic properties and receptor binding affinity simultaneously: a 'parallel progression approach to drug design' applied to β-blockers.

PubMed

Advani, Poonam; Joseph, Blessy; Ambre, Premlata; Pissurlenkar, Raghuvir; Khedkar, Vijay; Iyer, Krishna; Gabhe, Satish; Iyer, Radhakrishnan P; Coutinho, Evans

2016-01-01

The present work exploits the potential of in silico approaches for minimizing attrition of leads in the later stages of drug development. We propose a theoretical approach, wherein 'parallel' information is generated to simultaneously optimize the pharmacokinetics (PK) and pharmacodynamics (PD) of lead candidates. β-blockers, though in use for many years, have suboptimal PKs; hence are an ideal test series for the 'parallel progression approach'. This approach utilizes molecular modeling tools viz. hologram quantitative structure activity relationships, homology modeling, docking, predictive metabolism, and toxicity models. Validated models have been developed for PK parameters such as volume of distribution (log Vd) and clearance (log Cl), which together influence the half-life (t1/2) of a drug. Simultaneously, models for PD in terms of inhibition constant pKi have been developed. Thus, PK and PD properties of β-blockers were concurrently analyzed and after iterative cycling, modifications were proposed that lead to compounds with optimized PK and PD. We report some of the resultant re-engineered β-blockers with improved half-lives and pKi values comparable with marketed β-blockers. These were further analyzed by the docking studies to evaluate their binding poses. Finally, metabolic and toxicological assessment of these molecules was done through in silico methods. The strategy proposed herein has potential universal applicability, and can be used in any drug discovery scenario; provided that the data used is consistent in terms of experimental conditions, endpoints, and methods employed. Thus the 'parallel progression approach' helps to simultaneously fine-tune various properties of the drug and would be an invaluable tool during the drug development process.

CO2 Mitigation Measures of Power Sector and Its Integrated Optimization in China

PubMed Central

Dai, Pan; Chen, Guang; Zhou, Hao; Su, Meirong; Bao, Haixia

2012-01-01

Power sector is responsible for about 40% of the total CO2 emissions in the world and plays a leading role in climate change mitigation. In this study, measures that lower CO2 emissions from the supply side, demand side, and power grid are discussed, based on which, an integrated optimization model of CO2 mitigation (IOCM) is proposed. Virtual energy, referring to energy saving capacity in both demand side and the power grid, together with conventional energy in supply side, is unified planning for IOCM. Consequently, the optimal plan of energy distribution, considering both economic benefits and mitigation benefits, is figured out through the application of IOCM. The results indicate that development of demand side management (DSM) and smart grid can make great contributions to CO2 mitigation of power sector in China by reducing the CO2 emissions by 10.02% and 12.59%, respectively, in 2015, and in 2020. PMID:23213305

Electronic and geometric properties of ETS-10: QM/MM studies of cluster models.

PubMed

Zimmerman, Anne Marie; Doren, Douglas J; Lobo, Raul F

2006-05-11

Hybrid DFT/MM methods have been used to investigate the electronic and geometric properties of the microporous titanosilicate ETS-10. A comparison of finite length and periodic models demonstrates that band gap energies for ETS-10 can be well represented with relatively small cluster models. Optimization of finite clusters leads to different local geometries for bulk and end sites, where the local bulk TiO6 geometry is in good agreement with recent experimental results. Geometry optimizations reveal that any asymmetry within the axial O-Ti-O chain is negligible. The band gap in the optimized model corresponds to a O(2p) --> Tibulk(3d) transition. The results suggest that the three Ti atom, single chain, symmetric, finite cluster is an effective model for the geometric and electronic properties of bulk and end TiO6 groups in ETS-10.

Optimizing Dense Plasma Focus Neutron Yields with Fast Gas Jets

NASA Astrophysics Data System (ADS)

McMahon, Matthew; Kueny, Christopher; Stein, Elizabeth; Link, Anthony; Schmidt, Andrea

2016-10-01

We report a study using the particle-in-cell code LSP to perform fully kinetic simulations modeling dense plasma focus (DPF) devices with high density gas jets on axis. The high density jet models fast gas puffs which allow for more mass on axis while maintaining the optimal pressure for the DPF. As the density of the jet compared to the background fill increases we find the neutron yield increases, as does the variability in the neutron yield. Introducing perturbations in the jet density allow for consistent seeding of the m =0 instability leading to more consistent ion acceleration and higher neutron yields with less variability. Jets with higher on axis density are found to have the greatest yield. The optimal jet configuration is explored. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Optimal programming management of ventricular tachycardia storm in ICD patients

PubMed Central

Qian, Zhiyong; Guo, Jianghong; Zhang, Zhiyong; Wang, Yao; Hou, Xiaofeng; Zou, Jiangang

2015-01-01

Abstract Ventricular tachycardia storm (VTS) is defined as a life-threatening syndrome of three or more separate episodes of ventricular tachycardia (VT) leading to implantable cardioverter defibrillator (ICD) therapy within 24 hours. Patients with VTS have poor outcomes and require immediate medical attention. ICD shocks have been shown to be associated with increased mortality in several studies. Optimal programming in minimization of ICD shocks may decrease mortality. Large controlled trials showed that long detection time and high heart rate detection threshold reduced ICD shock burden without an increase in syncope or death. As a fundamental therapy of ICD, antitachycardia pacing (ATP) can terminate most slow VT with a low risk of acceleration. For fast VT, burst pacing is more effective and less likely to result in acceleration than ramp pacing. One algorithm of optimal programming management during a VTS is presented in the review. PMID:25745473

Optimal Portfolio Selection Under Concave Price Impact

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

Ma Jin, E-mail: jinma@usc.edu; Song Qingshuo, E-mail: songe.qingshuo@cityu.edu.hk; Xu Jing, E-mail: xujing8023@yahoo.com.cn

2013-06-15

In this paper we study an optimal portfolio selection problem under instantaneous price impact. Based on some empirical analysis in the literature, we model such impact as a concave function of the trading size when the trading size is small. The price impact can be thought of as either a liquidity cost or a transaction cost, but the concavity nature of the cost leads to some fundamental difference from those in the existing literature. We show that the problem can be reduced to an impulse control problem, but without fixed cost, and that the value function is a viscosity solutionmore » to a special type of Quasi-Variational Inequality (QVI). We also prove directly (without using the solution to the QVI) that the optimal strategy exists and more importantly, despite the absence of a fixed cost, it is still in a 'piecewise constant' form, reflecting a more practical perspective.« less

Generalized filtering of laser fields in optimal control theory: application to symmetry filtering of quantum gate operations

NASA Astrophysics Data System (ADS)

Schröder, Markus; Brown, Alex

2009-10-01

We present a modified version of a previously published algorithm (Gollub et al 2008 Phys. Rev. Lett.101 073002) for obtaining an optimized laser field with more general restrictions on the search space of the optimal field. The modification leads to enforcement of the constraints on the optimal field while maintaining good convergence behaviour in most cases. We demonstrate the general applicability of the algorithm by imposing constraints on the temporal symmetry of the optimal fields. The temporal symmetry is used to reduce the number of transitions that have to be optimized for quantum gate operations that involve inversion (NOT gate) or partial inversion (Hadamard gate) of the qubits in a three-dimensional model of ammonia.

Urban Forest Ecosystem Service Optimization, Tradeoffs, and Disparities

NASA Astrophysics Data System (ADS)

Bodnaruk, E.; Kroll, C. N.; Endreny, T. A.; Hirabayashi, S.; Yang, Y.

2014-12-01

Urban land area and the proportion of humanity living in cities is growing, leading to increased urban air pollution, temperature, and stormwater runoff. These changes can exacerbate respiratory and heat-related illnesses and affect ecosystem functioning. Urban trees can help mitigate these threats by removing air pollutants, mitigating urban heat island effects, and infiltrating and filtering stormwater. The urban environment is highly heterogeneous, and there is no tool to determine optimal locations to plant or protect trees. Using spatially explicit land cover, weather, and demographic data within biophysical ecosystem service models, this research expands upon the iTree urban forest tools to produce a new decision support tool (iTree-DST) that will explore the development and impacts of optimal tree planting. It will also heighten awareness of environmental justice by incorporating the Atkinson Index to quantify disparities in health risks and ecosystem services across vulnerable and susceptible populations. The study area is Baltimore City, a location whose urban forest and environmental justice concerns have been studied extensively. The iTree-DST is run at the US Census block group level and utilizes a local gradient approach to calculate the change in ecosystem services with changing tree cover across the study area. Empirical fits provide ecosystem service gradients for possible tree cover scenarios, greatly increasing the speed and efficiency of the optimization procedure. Initial results include an evaluation of the performance of the gradient method, optimal planting schemes for individual ecosystem services, and an analysis of tradeoffs and synergies between competing objectives.

Optimism bias leads to inconclusive results-an empirical study.

PubMed

Djulbegovic, Benjamin; Kumar, Ambuj; Magazin, Anja; Schroen, Anneke T; Soares, Heloisa; Hozo, Iztok; Clarke, Mike; Sargent, Daniel; Schell, Michael J

2011-06-01

Optimism bias refers to unwarranted belief in the efficacy of new therapies. We assessed the impact of optimism bias on a proportion of trials that did not answer their research question successfully and explored whether poor accrual or optimism bias is responsible for inconclusive results. Systematic review. Retrospective analysis of a consecutive-series phase III randomized controlled trials (RCTs) performed under the aegis of National Cancer Institute Cooperative groups. Three hundred fifty-nine trials (374 comparisons) enrolling 150,232 patients were analyzed. Seventy percent (262 of 374) of the trials generated conclusive results according to the statistical criteria. Investigators made definitive statements related to the treatment preference in 73% (273 of 374) of studies. Investigators' judgments and statistical inferences were concordant in 75% (279 of 374) of trials. Investigators consistently overestimated their expected treatment effects but to a significantly larger extent for inconclusive trials. The median ratio of expected and observed hazard ratio or odds ratio was 1.34 (range: 0.19-15.40) in conclusive trials compared with 1.86 (range: 1.09-12.00) in inconclusive studies (P<0.0001). Only 17% of the trials had treatment effects that matched original researchers' expectations. Formal statistical inference is sufficient to answer the research question in 75% of RCTs. The answers to the other 25% depend mostly on subjective judgments, which at times are in conflict with statistical inference. Optimism bias significantly contributes to inconclusive results. Copyright © 2011 Elsevier Inc. All rights reserved.

Consensus definitions and application guidelines for control groups in cerebrospinal fluid biomarker studies in multiple sclerosis.

PubMed

Teunissen, Charlotte; Menge, Til; Altintas, Ayse; Álvarez-Cermeño, José C; Bertolotto, Antonio; Berven, Frode S; Brundin, Lou; Comabella, Manuel; Degn, Matilde; Deisenhammer, Florian; Fazekas, Franz; Franciotta, Diego; Frederiksen, Jette L; Galimberti, Daniela; Gnanapavan, Sharmilee; Hegen, Harald; Hemmer, Bernhard; Hintzen, Rogier; Hughes, Steve; Iacobaeus, Ellen; Kroksveen, Ann C; Kuhle, Jens; Richert, John; Tumani, Hayrettin; Villar, Luisa M; Drulovic, Jelena; Dujmovic, Irena; Khalil, Michael; Bartos, Ales

2013-11-01

The choice of appropriate control group(s) is critical in cerebrospinal fluid (CSF) biomarker research in multiple sclerosis (MS). There is a lack of definitions and nomenclature of different control groups and a rationalized application of different control groups. We here propose consensus definitions and nomenclature for the following groups: healthy controls (HCs), spinal anesthesia subjects (SASs), inflammatory neurological disease controls (INDCs), peripheral inflammatory neurological disease controls (PINDCs), non-inflammatory neurological controls (NINDCs), symptomatic controls (SCs). Furthermore, we discuss the application of these control groups in specific study designs, such as for diagnostic biomarker studies, prognostic biomarker studies and therapeutic response studies. Application of these uniform definitions will lead to better comparability of biomarker studies and optimal use of available resources. This will lead to improved quality of CSF biomarker research in MS and related disorders.

Multiobjective optimization of urban water resources: Moving toward more practical solutions

NASA Astrophysics Data System (ADS)

Mortazavi, Mohammad; Kuczera, George; Cui, Lijie

2012-03-01

The issue of drought security is of paramount importance for cities located in regions subject to severe prolonged droughts. The prospect of "running out of water" for an extended period would threaten the very existence of the city. Managing drought security for an urban water supply is a complex task involving trade-offs between conflicting objectives. In this paper a multiobjective optimization approach for urban water resource planning and operation is developed to overcome practically significant shortcomings identified in previous work. A case study based on the headworks system for Sydney (Australia) demonstrates the approach and highlights the potentially serious shortcomings of Pareto optimal solutions conditioned on short climate records, incomplete decision spaces, and constraints to which system response is sensitive. Where high levels of drought security are required, optimal solutions conditioned on short climate records are flawed. Our approach addresses drought security explicitly by identifying approximate optimal solutions in which the system does not "run dry" in severe droughts with expected return periods up to a nominated (typically large) value. In addition, it is shown that failure to optimize the full mix of interacting operational and infrastructure decisions and to explore the trade-offs associated with sensitive constraints can lead to significantly more costly solutions.

Pharmacodynamically optimized erythropoietin treatment combined with phlebotomy reduction predicted to eliminate blood transfusions in selected preterm infants.

PubMed

Rosebraugh, Matthew R; Widness, John A; Nalbant, Demet; Cress, Gretchen; Veng-Pedersen, Peter

2014-02-01

Preterm very-low-birth-weight (VLBW) infants weighing <1.5 kg at birth develop anemia, often requiring multiple red blood cell transfusions (RBCTx). Because laboratory blood loss is a primary cause of anemia leading to RBCTx in VLBW infants, our purpose was to simulate the extent to which RBCTx can be reduced or eliminated by reducing laboratory blood loss in combination with pharmacodynamically optimized erythropoietin (Epo) treatment. Twenty-six VLBW ventilated infants receiving RBCTx were studied during the first month of life. RBCTx simulations were based on previously published RBCTx criteria and data-driven Epo pharmacodynamic optimization of literature-derived RBC life span and blood volume data corrected for phlebotomy loss. Simulated pharmacodynamic optimization of Epo administration and reduction in phlebotomy by ≥ 55% predicted a complete elimination of RBCTx in 1.0-1.5 kg infants. In infants <1.0 kg with 100% reduction in simulated phlebotomy and optimized Epo administration, a 45% reduction in RBCTx was predicted. The mean blood volume drawn from all infants was 63 ml/kg: 33% required for analysis and 67% discarded. When reduced laboratory blood loss and optimized Epo treatment are combined, marked reductions in RBCTx in ventilated VLBW infants were predicted, particularly among those with birth weights >1.0 kg.

The solution space of sorting by DCJ.

PubMed

Braga, Marília D V; Stoye, Jens

2010-09-01

In genome rearrangements, the double cut and join (DCJ) operation, introduced by Yancopoulos et al. in 2005, allows one to represent most rearrangement events that could happen in multichromosomal genomes, such as inversions, translocations, fusions, and fissions. No restriction on the genome structure considering linear and circular chromosomes is imposed. An advantage of this general model is that it leads to considerable algorithmic simplifications compared to other genome rearrangement models. Recently, several works concerning the DCJ operation have been published, and in particular, an algorithm was proposed to find an optimal DCJ sequence for sorting one genome into another one. Here we study the solution space of this problem and give an easy-to-compute formula that corresponds to the exact number of optimal DCJ sorting sequences for a particular subset of instances of the problem. We also give an algorithm to count the number of optimal sorting sequences for any instance of the problem. Another interesting result is the demonstration of the possibility of obtaining one optimal sorting sequence by properly replacing any pair of consecutive operations in another optimal sequence. As a consequence, any optimal sorting sequence can be obtained from one other by applying such replacements successively, but the problem of finding the shortest number of replacements between two sorting sequences is still open.

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

Determination of lead in flour samples directly by solid sampling high resolution continuum source graphite furnace atomic absorption spectrometry

NASA Astrophysics Data System (ADS)

Tinas, Hande; Ozbek, Nil; Akman, Suleyman

2018-02-01

In this study, lead concentrations in various flour samples were determined by high-resolution continuum source graphite furnace atomic absorption spectrometry with solid sampling. Since samples were analyzed directly, the risks and disadvantages of sample digestion were eliminated. Solid flour samples were dried, weighed on the platforms, Pd was added as a modifier and introduced directly into a graphite tube using a manual solid sampler. Platforms and tubes were coated with Zr. The optimized pyrolysis and atomization temperatures were 800 °C and 2200 °C, respectively. The sensitivities of lead in various flour certified reference materials (CRMs) and aqueous standards were not significantly different. Therefore, aqueous standards were safely used for calibration. The absolute limit of detection and characteristic mass were 7.2 pg and 9.0 pg of lead, respectively. The lead concentrations in different types of flour samples were found in the range of 25-52 μg kg- 1. Finally, homogeneity factors representing the heterogeneity of analyte distribution for lead in flour samples were determined.

The Effect of Aerodynamic Evaluators on the Multi-Objective Optimization of Flatback Airfoils

NASA Astrophysics Data System (ADS)

Miller, M.; Slew, K. Lee; Matida, E.

2016-09-01

With the long lengths of today's wind turbine rotor blades, there is a need to reduce the mass, thereby requiring stiffer airfoils, while maintaining the aerodynamic efficiency of the airfoils, particularly in the inboard region of the blade where structural demands are highest. Using a genetic algorithm, the multi-objective aero-structural optimization of 30% thick flatback airfoils was systematically performed for a variety of aerodynamic evaluators such as lift-to-drag ratio (Cl/Cd), torque (Ct), and torque-to-thrust ratio (Ct/Cn) to determine their influence on airfoil shape and performance. The airfoil optimized for Ct possessed a 4.8% thick trailing-edge, and a rather blunt leading-edge region which creates high levels of lift and correspondingly, drag. It's ability to maintain similar levels of lift and drag under forced transition conditions proved it's insensitivity to roughness. The airfoil optimized for Cl/Cd displayed relatively poor insensitivity to roughness due to the rather aft-located free transition points. The Ct/Cn optimized airfoil was found to have a very similar shape to that of the Cl/Cd airfoil, with a slightly more blunt leading-edge which aided in providing higher levels of lift and moderate insensitivity to roughness. The influence of the chosen aerodynamic evaluator under the specified conditions and constraints in the optimization of wind turbine airfoils is shown to have a direct impact on the airfoil shape and performance.

A review on fracture prevention of stent in femoropopliteal artery

NASA Astrophysics Data System (ADS)

Atan, Bainun Akmal Mohd; Ismail, Al Emran; Taib, Ishkrizat; Lazim, Zulfaqih

2017-01-01

Heavily calcific lesions, total occlusions, tortuous blood vessels, variable lengths of arteries, various dynamic loads and deformations in the femoropopliteal (FP) arterial segment make stenosis treatments are complicated. The dynamic forces in FP artery including bending, torsion and radial compression may lead to stent fracture (SF) and eventually to in-stent restenosis (ISR). Stent design specifically geometrical configurations are a major factor need to be improved to optimize stent expansion and flexibility both bending and torsion during stent deployment into the diseased FP artery. Previous studies discovered the influence of various stent geometrical designs resulted different structural behaviour. Optimizing stent design can improve stent performances: flexibility and radial strength to prevent SF in FP arterial segment

Novel methodology for wide-ranged multistage morphing waverider based on conical theory

NASA Astrophysics Data System (ADS)

Liu, Zhen; Liu, Jun; Ding, Feng; Xia, Zhixun

2017-11-01

This study proposes the wide-ranged multistage morphing waverider design method. The flow field structure and aerodynamic characteristics of multistage waveriders are also analyzed. In this method, the multistage waverider is generated in the same conical flowfield, which contains a free-stream surface and different compression-stream surfaces. The obtained results show that the introduction of the multistage waverider design method can solve the problem of aerodynamic performance deterioration in the off-design state and allow the vehicle to always maintain the optimal flight state. The multistage waverider design method, combined with transfiguration flight strategy, can lead to greater design flexibility and the optimization of hypersonic wide-ranged waverider vehicles.

Optimization of Ballast Design: A Case Study of the Physics Entrepreneurship Program

NASA Astrophysics Data System (ADS)

Ding, Jun; Cheng, Norman; Lamouri, Abbas; Sulcs, Juris; Brown, Robert; Taylor, Cyrus

2001-10-01

This talk presents a typical internship project for students in the Physics Entrepreneurship Program at Case Western Reserve University. As part of their overall strategy, Advanced Lighting International (ADLT) is involved in the production of magnetic ballasts for metal halide lamps. The systems in which these ballasts function is undergoing rapid evolution, leading to the question of how the design of the ballasts can be optimized in order to deliver superior performance for lower cost. Addressing this question requires a full understanding of a variety of issues ranging from the basic modeling of the physics of the magnetic ballasts to questions of overall market strategy, manufacturing considerations, and the competitive environment.

Development of Simultaneous Corrosion Barrier and Optimized Microstructure in FeCrAl Heat-Resistant Alloy for Energy Applications. Part II: The Optimized Creep-Resistant Microstructure

NASA Astrophysics Data System (ADS)

Pimentel, G.; Aranda, M. M.; Chao, J.; González-Carrasco, J. L.; Capdevila, C.

2015-09-01

The first part of this two-part study reported the possibility of simultaneously generating a dense, self-healing α-alumina layer by thermal oxidation and a coarse-grained microstructure with a potential goodness for high-temperature creep resistance in a FeCrAl oxide dispersion-strengthened ferritic alloy that was cold deformed after hot rolling and extrusion. In this second part, the factors affecting the formation of the coarse-grained microstructure such as strain gradients induced during the rolling process are analyzed. It is concluded that larger strain gradients lead to more refined and more isotropic grain structures.

Study on optimized algorithm for mileage wheel of magnetic flux leakage detector

NASA Astrophysics Data System (ADS)

Y Sun, L.; Li, Y. B.; Wu, Y. T.; Y Xu, Q.; Cai, Y.

2017-07-01

Pipeline integrity is significant to safe operation of long-range pipeline. To avoid critical failure of the pipeline, which may lead to great loss of property and life, MFL_PIG is often used to detect the corrosion and leakage of the pipeline. To accurately locate the defects, mileage pulses emitted by the mileage wheel are used to and emit signal to single-chip microcomputer for position. This paper investigates the factors that may affect the precision of mileage wheel, an important part of pipeline corrosion and leakage detector (MFL_PIG), investigate its working principle and present an optimized algorithm for mileage wheel to increase the precision of detection.

Fragment-based hit discovery and structure-based optimization of aminotriazoloquinazolines as novel Hsp90 inhibitors.

PubMed

Casale, Elena; Amboldi, Nadia; Brasca, Maria Gabriella; Caronni, Dannica; Colombo, Nicoletta; Dalvit, Claudio; Felder, Eduard R; Fogliatto, Gianpaolo; Galvani, Arturo; Isacchi, Antonella; Polucci, Paolo; Riceputi, Laura; Sola, Francesco; Visco, Carlo; Zuccotto, Fabio; Casuscelli, Francesco

2014-08-01

In the last decade the heat shock protein 90 (Hsp90) has emerged as a major therapeutic target and many efforts have been dedicated to the discovery of Hsp90 inhibitors as new potent anticancer agents. Here we report the identification of a novel class of Hsp90 inhibitors by means of a biophysical FAXS-NMR based screening of a library of fragments. The use of X-ray structure information combined with modeling studies enabled the fragment evolution of the initial triazoloquinazoline hit to a class of compounds with nanomolar potency and drug-like properties suited for further lead optimization. Copyright © 2014 Elsevier Ltd. All rights reserved.

Stochastic control and the second law of thermodynamics

NASA Technical Reports Server (NTRS)

Brockett, R. W.; Willems, J. C.

1979-01-01

The second law of thermodynamics is studied from the point of view of stochastic control theory. We find that the feedback control laws which are of interest are those which depend only on average values, and not on sample path behavior. We are lead to a criterion which, when satisfied, permits one to assign a temperature to a stochastic system in such a way as to have Carnot cycles be the optimal trajectories of optimal control problems. Entropy is also defined and we are able to prove an equipartition of energy theorem using this definition of temperature. Our formulation allows one to treat irreversibility in a quite natural and completely precise way.

Lead aVR: beyond 'No man's land'.

PubMed

Singh, Bhupinder; Ali, Amjad; Singla, Vivek; Gowda, Sadananda K

2014-04-25

Coronary artery disease (CAD) is one of the leading causes of mortality in the world. Treadmill test is a very useful non-invasive test to diagnose and stratify the risk of CAD. Lead aVR is usually a neglected lead while reading the ECG. We describe a case demonstrating the importance of subtle changes in lead aVR that has got a direct angiographic correlation with left main CAD. Therefore picking up the subtle clues on ECG may help in stratifying the risk and optimal treatment of the patient in a timely fashion.

Monitoring of International Space Station Telemetry Using Shewhart Control Charts

NASA Technical Reports Server (NTRS)

Fitch, Jeffery T.; Simon, Alan L.; Gouveia, John A.; Hillin, Andrew M.; Hernandez, Steve A.

2012-01-01

Shewhart control charts have been established as an expedient method for analyzing dynamic, trending data in order to identify anomalous subsystem performance as soon as such performance would exceed a statistically established baseline. Additionally, this leading indicator tool integrates a selection methodology that reduces false positive indications, optimizes true leading indicator events, minimizes computer processor unit duty cycles, and addresses human factor concerns (i.e., the potential for flight-controller data overload). This innovation leverages statistical process control, and provides a relatively simple way to allow flight controllers to focus their attention on subtle system changes that could lead to dramatic off-nominal system performance. Finally, this capability improves response time to potential hardware damage and/or crew injury, thereby improving space flight safety. Shewhart control charts require normalized data. However, the telemetry from the ISS Early External Thermal Control System (EETCS) was not normally distributed. A method for normalizing the data was implemented, as was a means of selecting data windows, the number of standard deviations (Sigma Level), the number of consecutive points out of limits (Sequence), and direction (increasing or decreasing trend data). By varying these options, and treating them like dial settings, the number of nuisance alerts and leading indicators were optimized. The goal was to capture all leading indicators while minimizing the number of nuisances. Lean Six Sigma (L6S) design of experiment methodologies were employed. To optimize the results, Perl programming language was used to automate the massive amounts of telemetry data, control chart plots, and the data analysis.

Optimal Chebyshev polynomials on ellipses in the complex plane

NASA Technical Reports Server (NTRS)

Fischer, Bernd; Freund, Roland

1989-01-01

The design of iterative schemes for sparse matrix computations often leads to constrained polynomial approximation problems on sets in the complex plane. For the case of ellipses, we introduce a new class of complex polynomials which are in general very good approximations to the best polynomials and even optimal in most cases.

Optimizing inhomogeneous spin ensembles for quantum memory

NASA Astrophysics Data System (ADS)

Bensky, Guy; Petrosyan, David; Majer, Johannes; Schmiedmayer, Jörg; Kurizki, Gershon

2012-07-01

We propose a method to maximize the fidelity of quantum memory implemented by a spectrally inhomogeneous spin ensemble. The method is based on preselecting the optimal spectral portion of the ensemble by judiciously designed pulses. This leads to significant improvement of the transfer and storage of quantum information encoded in the microwave or optical field.

Enhanced Solubility and Dissolution Rate of Lacidipine Nanosuspension: Formulation Via Antisolvent Sonoprecipitation Technique and Optimization Using Box-Behnken Design.

PubMed

Kassem, Mohamed A A; ElMeshad, Aliaa N; Fares, Ahmed R

2017-05-01

Lacidipine (LCDP) is a highly lipophilic calcium channel blocker of poor aqueous solubility leading to poor oral absorption. This study aims to prepare and optimize LCDP nanosuspensions using antisolvent sonoprecipitation technique to enhance the solubility and dissolution of LCDP. A three-factor, three-level Box-Behnken design was employed to optimize the formulation variables to obtain LCDP nanosuspension of small and uniform particle size. Formulation variables were as follows: stabilizer to drug ratio (A), sodium deoxycholate percentage (B), and sonication time (C). LCDP nanosuspensions were assessed for particle size, zeta potential, and polydispersity index. The formula with the highest desirability (0.969) was chosen as the optimized formula. The values of the formulation variables (A, B, and C) in the optimized nanosuspension were 1.5, 100%, and 8 min, respectively. Optimal LCDP nanosuspension had particle size (PS) of 273.21 nm, zeta potential (ZP) of -32.68 mV and polydispersity index (PDI) of 0.098. LCDP nanosuspension was characterized using x-ray powder diffraction, differential scanning calorimetry, and transmission electron microscopy. LCDP nanosuspension showed saturation solubility 70 times that of raw LCDP in addition to significantly enhanced dissolution rate due to particle size reduction and decreased crystallinity. These results suggest that the optimized LCDP nanosuspension could be promising to improve oral absorption of LCDP.

High-Efficiency Nonfullerene Polymer Solar Cell Enabling by Integration of Film-Morphology Optimization, Donor Selection, and Interfacial Engineering.

PubMed

Zhang, Xin; Li, Weiping; Yao, Jiannian; Zhan, Chuanlang

2016-06-22

Carrier mobility is a vital factor determining the electrical performance of organic solar cells. In this paper we report that a high-efficiency nonfullerene organic solar cell (NF-OSC) with a power conversion efficiency of 6.94 ± 0.27% was obtained by optimizing the hole and electron transportations via following judicious selection of polymer donor and engineering of film-morphology and cathode interlayers: (1) a combination of solvent annealing and solvent vapor annealing optimizes the film morphology and hence both hole and electron mobilities, leading to a trade-off of fill factor and short-circuit current density (Jsc); (2) the judicious selection of polymer donor affords a higher hole and electron mobility, giving a higher Jsc; and (3) engineering the cathode interlayer affords a higher electron mobility, which leads to a significant increase in electrical current generation and ultimately the power conversion efficiency (PCE).

Development of optimized PPP insulated pipe-cable systems in the commercial voltage range

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

Allam, E.M.; McKean, A.L.

1992-05-01

The primary objectives of this project included the development of an alternate domestic source of Paper-Polypropylene-Paper (PPP) laminate and the development of optimized designs for PPP-insulated pipe-type cable systems in the commercial voltage range. The development of a domestic source of PPP laminate was successfully completed. This laminate was utilized throughout the program for fabrication of full-size prototype cables submitted for laboratory qualification tests. Selected cables at rated voltages of 138, 230 and 345kV have been designed, fabricated and subjected to the series of qualification tests leading to full laboratory qualification. An optimized design of 2000 kcmil, 345kV cable insulatedmore » with 600 mils of domestic PPP laminate was fabricated and successfully passed all laboratory qualification tests. This cable design was subsequently installed at Waltz Mill to undergo the series of field tests leading to full commercial qualification.« less

Development of optimized PPP insulated pipe-cable systems in the commercial voltage range. Final report

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

Allam, E.M.; McKean, A.L.

1992-05-01

The primary objectives of this project included the development of an alternate domestic source of Paper-Polypropylene-Paper (PPP) laminate and the development of optimized designs for PPP-insulated pipe-type cable systems in the commercial voltage range. The development of a domestic source of PPP laminate was successfully completed. This laminate was utilized throughout the program for fabrication of full-size prototype cables submitted for laboratory qualification tests. Selected cables at rated voltages of 138, 230 and 345kV have been designed, fabricated and subjected to the series of qualification tests leading to full laboratory qualification. An optimized design of 2000 kcmil, 345kV cable insulatedmore » with 600 mils of domestic PPP laminate was fabricated and successfully passed all laboratory qualification tests. This cable design was subsequently installed at Waltz Mill to undergo the series of field tests leading to full commercial qualification.« less

Fluorination-enabled optimal morphology leads to over 11% efficiency for inverted small-molecule organic solar cells

PubMed Central

Deng, Dan; Zhang, Yajie; Zhang, Jianqi; Wang, Zaiyu; Zhu, Lingyun; Fang, Jin; Xia, Benzheng; Wang, Zhen; Lu, Kun; Ma, Wei; Wei, Zhixiang

2016-01-01

Solution-processable small molecules for organic solar cells have attracted intense attention for their advantages of definite molecular structures compared with their polymer counterparts. However, the device efficiencies based on small molecules are still lower than those of polymers, especially for inverted devices, the highest efficiency of which is <9%. Here we report three novel solution-processable small molecules, which contain π-bridges with gradient-decreased electron density and end acceptors substituted with various fluorine atoms (0F, 1F and 2F, respectively). Fluorination leads to an optimal active layer morphology, including an enhanced domain purity, the formation of hierarchical domain size and a directional vertical phase gradation. The optimal morphology balances charge separation and transfer, and facilitates charge collection. As a consequence, fluorinated molecules exhibit excellent inverted device performance, and an average power conversion efficiency of 11.08% is achieved for a two-fluorine atom substituted molecule. PMID:27991486

Cardiopulmonary resuscitation quality and beyond: the need to improve real-time feedback and physiologic monitoring.

PubMed

Lin, Steve; Scales, Damon C

2016-06-28

High-quality cardiopulmonary resuscitation (CPR) has been shown to improve survival outcomes after cardiac arrest. The current standard in studies evaluating CPR quality is to measure CPR process measures-for example, chest compression rate, depth, and fraction. Published studies evaluating CPR feedback devices have yielded mixed results. Newer approaches that seek to optimize CPR by measuring physiological endpoints during the resuscitation may lead to individualized patient care and improved patient outcomes.

Pattern formations and optimal packing.

PubMed

Mityushev, Vladimir

2016-04-01

Patterns of different symmetries may arise after solution to reaction-diffusion equations. Hexagonal arrays, layers and their perturbations are observed in different models after numerical solution to the corresponding initial-boundary value problems. We demonstrate an intimate connection between pattern formations and optimal random packing on the plane. The main study is based on the following two points. First, the diffusive flux in reaction-diffusion systems is approximated by piecewise linear functions in the framework of structural approximations. This leads to a discrete network approximation of the considered continuous problem. Second, the discrete energy minimization yields optimal random packing of the domains (disks) in the representative cell. Therefore, the general problem of pattern formations based on the reaction-diffusion equations is reduced to the geometric problem of random packing. It is demonstrated that all random packings can be divided onto classes associated with classes of isomorphic graphs obtained from the Delaunay triangulation. The unique optimal solution is constructed in each class of the random packings. If the number of disks per representative cell is finite, the number of classes of isomorphic graphs, hence, the number of optimal packings is also finite. Copyright © 2016 Elsevier Inc. All rights reserved.

Transungual Gel of Terbinafine Hydrochloride for the Management of Onychomycosis: Formulation, Optimization, and Evaluation.

PubMed

Thatai, Purva; Sapra, Bharti

2017-08-01

The present study was aimed to optimize, develop, and evaluate microemulsion and microemulsion-based gel as a vehicle for transungual drug delivery of terbinafine hydrochloride for the treatment of onychomycosis. D-optimal mixture experimental design was adopted to optimize the composition of microemulsion having amount of oil (X 1 ), Smix (mixture of surfactant and cosurfactant; X 2 ), and water (X 3 ) as the independent variables. The formulations were assessed for permeation (micrograms per square centimeter per hour; Y 1 ), particle size (nanometer; Y 2 ), and solubility of the drug in the formulation (milligrams per milliliter; Y 3 ). The microemulsion containing 3.05% oil, 24.98% Smix, and 71.96% water was selected as the optimized formulation. The microemulsion-based gel showed better penetration (∼5 folds) as well as more retention (∼9 fold) in the animal hoof as compared to the commercial cream. The techniques used to screen penetration enhancers (hydration enhancement factor, ATR-FTIR, SEM, and DSC) revealed the synergistic effect of combination of urea and n-acetyl cysteine in disruption of the structure of hoof and hence, leading to enhanced penetration of drug.

Gradient descent for robust kernel-based regression

NASA Astrophysics Data System (ADS)

Guo, Zheng-Chu; Hu, Ting; Shi, Lei

2018-06-01

In this paper, we study the gradient descent algorithm generated by a robust loss function over a reproducing kernel Hilbert space (RKHS). The loss function is defined by a windowing function G and a scale parameter σ, which can include a wide range of commonly used robust losses for regression. There is still a gap between theoretical analysis and optimization process of empirical risk minimization based on loss: the estimator needs to be global optimal in the theoretical analysis while the optimization method can not ensure the global optimality of its solutions. In this paper, we aim to fill this gap by developing a novel theoretical analysis on the performance of estimators generated by the gradient descent algorithm. We demonstrate that with an appropriately chosen scale parameter σ, the gradient update with early stopping rules can approximate the regression function. Our elegant error analysis can lead to convergence in the standard L 2 norm and the strong RKHS norm, both of which are optimal in the mini-max sense. We show that the scale parameter σ plays an important role in providing robustness as well as fast convergence. The numerical experiments implemented on synthetic examples and real data set also support our theoretical results.

Delayed lead perforation: a disturbing trend.

PubMed

Khan, Mohammed N; Joseph, George; Khaykin, Yaariv; Ziada, Khaled M; Wilkoff, Bruce L

2005-03-01

Delayed lead perforation (occurring more than 1 month after implantation) is a rare complication. Its pathophysiology and optimal management are currently unclear. Three cases of delayed lead perforation (6-10 month) were identified in patients with low-profile active fixation leads. All cases presented in a subacute fashion with pleuritic chest pain with confirmatory chest x-ray and device interrogation. Given the potential complications of a perforated lead, all cases had the lead extracted under TEE observation with cardiac surgery backup in the operating room. All patients tolerated extraction without complication. Based on these cases, we recommend a management scheme for patients who present with delayed lead perforation.

A New Mathematical Framework for Design Under Uncertainty

DTIC Science & Technology

2016-05-05

blending multiple information sources via auto-regressive stochastic modeling. A computationally efficient machine learning framework is developed based on...sion and machine learning approaches; see Fig. 1. This will lead to a comprehensive description of system performance with less uncertainty than in the...Bayesian optimization of super-cavitating hy- drofoils The goal of this study is to demonstrate the capabilities of statistical learning and

The role of information and communication technology in planning the digital hospital.

PubMed

Lacanna, Giuseppe

2013-01-01

Hospital structure is undergoing radical changes, forced by contemporary market trends, new demands from different stakeholders and a common interest in innovation. Health care expenditure around the globe continues to rise at unsustainable levels. In this context efficiency and optimization become the keywords of the process aimed at lowering costs and increasing the quality of care services. Efficiency and optimization leads to innovation, and innovation in the contemporary age leads to the power of information and communication technology (ICT). This paper discusses how ICT became the new shaping tool for hospital environments and highlights one of the best examples of its implementation.

Numerical algorithm for optimization of positive electrode in lead-acid batteries

NASA Astrophysics Data System (ADS)

Murariu, Ancuta Teodora; Buimaga-Iarinca, Luiza; Morari, Cristian

2017-12-01

The positive electrode in lead-acid batteries is one of the most sensitive parts of the whole battery, since it is affected by various aggresive chemical processes during its life. Therefore, an optimal design of the positive electrode of the battery may have as efect a dramatic improvement of the properties of the battery - such as total capacity or endurance during its life. Our efforts dedicated to this goal cover a range of rather complex tasks, from the design based on numerical analysis to statistic analysis. We present the structure of the software implementation and the results obtained for three types of positive electrodes.

Lead optimization mapper: automating free energy calculations for lead optimization.

PubMed

Liu, Shuai; Wu, Yujie; Lin, Teng; Abel, Robert; Redmann, Jonathan P; Summa, Christopher M; Jaber, Vivian R; Lim, Nathan M; Mobley, David L

2013-09-01

Alchemical free energy calculations hold increasing promise as an aid to drug discovery efforts. However, applications of these techniques in discovery projects have been relatively few, partly because of the difficulty of planning and setting up calculations. Here, we introduce lead optimization mapper, LOMAP, an automated algorithm to plan efficient relative free energy calculations between potential ligands within a substantial library of perhaps hundreds of compounds. In this approach, ligands are first grouped by structural similarity primarily based on the size of a (loosely defined) maximal common substructure, and then calculations are planned within and between sets of structurally related compounds. An emphasis is placed on ensuring that relative free energies can be obtained between any pair of compounds without combining the results of too many different relative free energy calculations (to avoid accumulation of error) and by providing some redundancy to allow for the possibility of error and consistency checking and provide some insight into when results can be expected to be unreliable. The algorithm is discussed in detail and a Python implementation, based on both Schrödinger's and OpenEye's APIs, has been made available freely under the BSD license.

Design and implementation of an automated compound management system in support of lead optimization.

PubMed

Quintero, Catherine; Kariv, Ilona

2009-06-01

To meet the needs of the increasingly rapid and parallelized lead optimization process, a fully integrated local compound storage and liquid handling system was designed and implemented to automate the generation of assay-ready plates directly from newly submitted and cherry-picked compounds. A key feature of the system is the ability to create project- or assay-specific compound-handling methods, which provide flexibility for any combination of plate types, layouts, and plate bar-codes. Project-specific workflows can be created by linking methods for processing new and cherry-picked compounds and control additions to produce a complete compound set for both biological testing and local storage in one uninterrupted workflow. A flexible cherry-pick approach allows for multiple, user-defined strategies to select the most appropriate replicate of a compound for retesting. Examples of custom selection parameters include available volume, compound batch, and number of freeze/thaw cycles. This adaptable and integrated combination of software and hardware provides a basis for reducing cycle time, fully automating compound processing, and ultimately increasing the rate at which accurate, biologically relevant results can be produced for compounds of interest in the lead optimization process.

Discovery of N6-phenyl-1H-pyrazolo[3,4-d]pyrimidine-3,6-diamine derivatives as novel CK1 inhibitors using common-feature pharmacophore model based virtual screening and hit-to-lead optimization.

PubMed

Yang, Ling-Ling; Li, Guo-Bo; Yan, Heng-Xiu; Sun, Qi-Zheng; Ma, Shuang; Ji, Pan; Wang, Ze-Rong; Feng, Shan; Zou, Jun; Yang, Sheng-Yong

2012-10-01

Aberrant activation of casein kinase 1 (CK1) has been demonstrated to be implicated in the pathogenesis of cancer and various central nervous system disorders. Discovery of CK1 inhibitors has thus attracted much attention in recent years. In this account, we describe the discovery of N6-phenyl-1H-pyrazolo[3,4-d]pyrimidine-3,6-diamine derivatives as novel CK1 inhibitors. An optimal common-feature pharmacophore hypothesis, termed Hypo2, was firstly generated, followed by virtual screening using Hypo2 against several chemical databases. One of the best hit compounds, N6-(4-chlorophenyl)-1H-pyrazolo[3,4-d]pyrimidine-3,6-diamine, was chosen for the subsequent hit-to-lead optimization under the guide of Hypo2, which led to the discovery of a new lead compound (1-(3-(3-amino-1H-pyrazolo[3,4-d]pyrimidin-6-ylamino)phenyl)-3-(3-chloro-4-fluorophenyl)urea) that potently inhibits CK1 with an IC(50) value of 78 nM. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Atrial septal pacing in small dogs: a pilot study.

PubMed

Jones, Ashley E; Estrada, Amara H; Pariaut, Romain; Sosa-Samper, Ivan; Shih, Andre C; Mincey, Brandy D; Moïse, N Sydney

2014-09-01

To determine the feasibility of atrial septal pacing via a delivery catheter-guided small non-retracting helix pacing lead. Six healthy beagles (8.3-12.9 kg). Using single plane fluoroscopic guidance, Medtronic(®) 3830 SelectSecure leads were connected to the atrial septum via Medtronic® Attain Select® II standard 90 Left Heart delivery catheter. Pacing threshold and lead impedance were measured at implantation. The Wenckebach point was tested via atrial pacing up to 220 paced pulses per minute (ppm). Thoracic radiographs were performed following implantation to identify the lead position, and repeated at 24 h, 1 month, and 3 months post-operatively. Macro-lead dislodgement occurred in two dogs at 24 h and in three dogs at one-month post-implantation. Lead impedance, measured at the time of implantation, ranged from 583 to 1421 Ω. The Wenckebach point was >220 ppm in four of the six dogs. The remaining two dogs had Wenckebach points of 120 and 190 ppm. This pilot study suggests the selected implantation technique and lead system were inadequate for secure placement in the atrial septum of these dogs. The possible reasons for inadequate stability include unsuitable lead design for this location, inadequate lead slack at the time of implantation and inadequate seating of the lead as evidenced by low impedance at the time of implantation. Other implantation techniques and/or pacing leads should be investigated to determine the optimal way of pacing the atria in small breed dogs that are prone to sinus node dysfunction. Copyright © 2014 Elsevier B.V. All rights reserved.

Universality of optimal measurements

NASA Astrophysics Data System (ADS)

Tarrach, Rolf; Vidal, Guifré

1999-11-01

We present optimal and minimal measurements on identical copies of an unknown state of a quantum bit when the quality of measuring strategies is quantified with the gain of information (Kullback-or mutual information-of probability distributions). We also show that the maximal gain of information occurs, among isotropic priors, when the state is known to be pure. Universality of optimal measurements follows from our results: using the fidelity or the gain of information, two different figures of merits, leads to exactly the same conclusions for isotropic distributions. We finally investigate the optimal capacity of N copies of an unknown state as a quantum channel of information.

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations.

PubMed

Saxena, Shalini; Abdullah, Maaged; Sriram, Dharmarajan; Guruprasad, Lalitha

2017-10-17

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

The key to success: Gelled-electrolyte and optimized separators for stationary lead-acid batteries

NASA Astrophysics Data System (ADS)

Toniazzo, Valérie

The lead acid technology is nowadays considered one of the best suited for stationary applications. Both gel and AGM batteries are complementary technologies and can provide reliability and efficiency due to the constant optimization of the battery design and components. However, gelled-electrolyte batteries remain the preferred technology due to a better manufacturing background and show better performance mainly at low and moderate discharge rates. Especially, using the gel technology allows to get rid of the numerous problems encountered in most AGM batteries: drainage, stratification, short circuits due to dendrites, and mostly premature capacity loss due to the release of internal cell compression. These limitations are the result of the evident lack of an optimal separation system. In gel batteries, on the contrary, highly efficient polymeric separators are nowadays available. Especially, microporous separators based on PVC and silica have shown the best efficiency for nearly 30 years all over the world, and especially in Europe, where the gel technology was born. The improved performance of these separators is explained by the unique extrusion process, which leads to excellent wettability, and optimized physical properties. Because they are the key for the battery success, continuous research and development on separators have led to improved properties, which render the separator even better adapted to the more recent gel technology: the pore size distribution has been optimized to allow good oxygen transfer while avoiding dendrite growth, the pore volume has been increased, the electrical resistance and acid displacement reduced to such an extent that the electrical output of batteries has been raised both in terms of higher capacity and longer cycle life.

Batch sorption dynamics and equilibrium for the removal of lead ions from aqueous phase using activated carbon developed from coffee residue activated with zinc chloride.

PubMed

Boudrahem, F; Aissani-Benissad, F; Aït-Amar, H

2009-07-01

Lignocellulosic materials are good precursors for the production of activated carbon. In this work, coffee residue has been used as raw material in the preparation of powder activated carbon by the method of chemical activation with zinc chloride for the sorption of Pb(II) from dilute aqueous solutions. The influence of impregnation ratio (ZnCl2/coffee residue) on the physical and chemical properties of the prepared carbons was studied in order to optimize this parameter. The optimum experimental condition for preparing predominantly microporous activated carbons with high pore surface area (890 m2/g) and micropore volume (0.772 cm3/g) is an impregnation ratio of 100%. The developed activated carbon shows substantial capability to sorb lead(II) ions from aqueous solutions and for relative impregnation ratios of 75 and 100%, the maximum uptake is practically the same. Thus, 75% represents the optimal impregnation ratio. Batch experiments were conducted to study the effects of the main parameters such as contact time, initial concentration of Pb(II), solution pH, ionic strength and temperature. The maximum uptake of lead(II) at 25 degrees C was about 63 mg/g of adsorbent at pH 5.8, initial Pb(II) concentration of 10 mg/L, agitation speed of 200 rpm and ionic strength of 0.005 M. The kinetic data were fitted to the models of pseudo-first order and pseudo-second order, and follow closely the pseudo-second order model. Equilibrium sorption isotherms of Pb(II) were analyzed by the Langmuir, Freundlich and Temkin isotherm models. The Freundlich model gives a better fit than the others. Results from this study suggest that activated carbon produced from coffee residue is an effective adsorbent for the removal of lead from aqueous solutions and that ZnCl2 is a suitable activating agent for the preparation of high-porosity carbons.

The influence of push-off timing in a robotic ankle-foot prosthesis on the energetics and mechanics of walking.

PubMed

Malcolm, Philippe; Quesada, Roberto E; Caputo, Joshua M; Collins, Steven H

2015-02-22

Robotic ankle-foot prostheses that provide net positive push-off work can reduce the metabolic rate of walking for individuals with amputation, but benefits might be sensitive to push-off timing. Simple walking models suggest that preemptive push-off reduces center-of-mass work, possibly reducing metabolic rate. Studies with bilateral exoskeletons have found that push-off beginning before leading leg contact minimizes metabolic rate, but timing was not varied independently from push-off work, and the effects of push-off timing on biomechanics were not measured. Most lower-limb amputations are unilateral, which could also affect optimal timing. The goal of this study was to vary the timing of positive prosthesis push-off work in isolation and measure the effects on energetics, mechanics and muscle activity. We tested 10 able-bodied participants walking on a treadmill at 1.25 m · s(-1). Participants wore a tethered ankle-foot prosthesis emulator on one leg using a rigid boot adapter. We programmed the prosthesis to apply torque bursts that began between 46% and 56% of stride in different conditions. We iteratively adjusted torque magnitude to maintain constant net positive push-off work. When push-off began at or after leading leg contact, metabolic rate was about 10% lower than in a condition with Spring-like prosthesis behavior. When push-off began before leading leg contact, metabolic rate was not different from the Spring-like condition. Early push-off led to increased prosthesis-side vastus medialis and biceps femoris activity during push-off and increased variability in step length and prosthesis loading during push-off. Prosthesis push-off timing had no influence on intact-side leg center-of-mass collision work. Prosthesis push-off timing, isolated from push-off work, strongly affected metabolic rate, with optimal timing at or after intact-side heel contact. Increased thigh muscle activation and increased human variability appear to have caused the lack of reduction in metabolic rate when push-off was provided too early. Optimal timing with respect to opposite heel contact was not different from normal walking, but the trends in metabolic rate and center-of-mass mechanics were not consistent with simple model predictions. Optimal push-off timing should also be characterized for individuals with amputation, since meaningful benefits might be realized with improved timing.

Life cycle thinking and assessment tools on environmentally-benign electronics: Convergent optimization of materials use, end-of-life strategy and environmental policies

NASA Astrophysics Data System (ADS)

Zhou, Xiaoying

The purpose of this study is to integrate the quantitative environmental performance assessment tools and the theory of multi-objective optimization within the boundary of electronic product systems to support the selection among design alternatives in terms of environmental impact, technical criteria, and economic feasibility. To meet with the requirements that result from emerging environmental legislation targeting electronics products, the research addresses an important analytical methodological approach to facilitate environmentally conscious design and end-of-life management with a life cycle viewpoint. A synthesis of diverse assessment tools is applied on a set of case studies: lead-free solder materials selection, cellular phone design, and desktop display technology assessment. In the first part of this work, an in-depth industrial survey of the status and concerns of the U.S. electronics industry on the elimination of lead (Pb) in solders is described. The results show that the trade-offs among environmental consequences, technology challenges, business risks, legislative compliance and stakeholders' preferences must be explicitly, simultaneously, and systematically addressed in the decision-making process used to guide multi-faceted planning of environmental solutions. In the second part of this work, the convergent optimization of the technical cycle, economic cycle and environmental cycle is addressed in a coherent and systematic way using the application of environmentally conscious design of cellular phones. The technical understanding of product structure, components analysis, and materials flow facilitates the development of "Design for Disassembly" guidelines. A bottom-up disassembly analysis on a "bill of materials" based structure at a micro-operational level is utilized to select optimal end-of-life strategies on the basis of economic feasibility. A macro-operational level life cycle model is used to investigate the environmental consequences linking environmental impact with the cellular phone production activities focusing on the upstream manufacturing and end-of-life life cycle stages. The last part of this work, the quantitative elicitation of weighting factors facilitates the comparison of trade-offs in the context of a multi-attribute problem. An integrated analytical approach, Integrated Industrial Ecology Function Deployment (I2-EFD), is proposed to assess alternatives at the design phase of a product system and is validated with the assessment of desktop display technologies and lead-free solder alternatives.

Statistical optimization for enhanced yields of probiotic Bacillus coagulans and its phage resistant mutants followed by kinetic modelling of the process.

PubMed

Pandey, Kavita R; Joshi, Chetan; Vakil, Babu V

2016-01-01

Probiotics are microorganisms which when administered in adequate amounts confer health benefits to the host. A leading pharmaceutical company producing Bacillus coagulans as a probiotic was facing the problem of recurring phage attacks. Two mutants viz. B. co PIII and B. co MIII that were isolated as phage resistant mutants after UV irradiation and MMS treatment of phage sensitive B. coagulans parental culture were characterized at functional and molecular level and were noted to have undergone interesting genetic changes. The non-specific genetic alterations induced by mutagenesis can also lead to alterations in cell performance. Hence, in the current study the parental strain and the two mutants were selected for shake flask optimization. Plackett-Burman design was used to select the significant culture variables affecting biomass production. Evolutionary operation method was applied for further optimization. The study showed wide variations in the nutritional requirements of phage resistant mutants, post exposure to mutagens. An increment of 150, 134 and 152 % was observed in the biomass productions of B. coagulans (parental type) and mutants B.co PIII and B.co MIII respectively, compared to the yield from one-factor-at-a-time technique. Using Logistic and modified Leudeking-Piret equations, biomass accumulation and substrate utilization efficiency of the bioprocess were determined. The experimental data was in agreement with the results predicted by statistical analysis and modelling. The developed model may be useful for controlling the growth and substrate consumption kinetics in large scale fermentation using B. coagulans .

Use of the Hotelling observer to optimize image reconstruction in digital breast tomosynthesis

PubMed Central

Sánchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

2015-01-01

Abstract. We propose an implementation of the Hotelling observer that can be applied to the optimization of linear image reconstruction algorithms in digital breast tomosynthesis. The method is based on considering information within a specific region of interest, and it is applied to the optimization of algorithms for detectability of microcalcifications. Several linear algorithms are considered: simple back-projection, filtered back-projection, back-projection filtration, and Λ-tomography. The optimized algorithms are then evaluated through the reconstruction of phantom data. The method appears robust across algorithms and parameters and leads to the generation of algorithm implementations which subjectively appear optimized for the task of interest. PMID:26702408

An assessment of Gallistel's (2012) rationalistic account of extinction phenomena.

PubMed

Miller, Ralph R

2012-05-01

Gallistel (2012) asserts that animals use rationalistic reasoning (i.e., information theory and Bayesian inference) to make decisions that underlie select extinction phenomena. Rational processes are presumed to lead to evolutionarily optimal behavior. Thus, Gallistel's model is a type of optimality theory. But optimality theory is only a theory, a theory about an ideal organism, and its predictions frequently deviate appreciably from observed behavior of animals in the laboratory and the real world. That is, behavior of animals is often far from optimal, as is evident in many behavioral phenomena. Hence, appeals to optimality theory to explain, rather than illuminate, actual behavior are misguided. Copyright © 2012 Elsevier B.V. All rights reserved.

Probes for investigating the effect of magnetic field, field orientation, temperature and strain on the critical current density of anisotropic high-temperature superconducting tapes in a split-pair 15 T horizontal magnet.

PubMed

Sunwong, P; Higgins, J S; Hampshire, D P

2014-06-01

We present the designs of probes for making critical current density (Jc) measurements on anisotropic high-temperature superconducting tapes as a function of field, field orientation, temperature and strain in our 40 mm bore, split-pair 15 T horizontal magnet. Emphasis is placed on the design of three components: the vapour-cooled current leads, the variable temperature enclosure, and the springboard-shaped bending beam sample holder. The vapour-cooled brass critical-current leads used superconducting tapes and in operation ran hot with a duty cycle (D) of ~0.2. This work provides formulae for optimising cryogenic consumption and calculating cryogenic boil-off, associated with current leads used to make J(c) measurements, made by uniformly ramping the current up to a maximum current (I(max)) and then reducing the current very quickly to zero. They include consideration of the effects of duty cycle, static helium boil-off from the magnet and Dewar (b'), and the maximum safe temperature for the critical-current leads (T(max)). Our optimized critical-current leads have a boil-off that is about 30% less than leads optimized for magnet operation at the same maximum current. Numerical calculations show that the optimum cross-sectional area (A) for each current lead can be parameterized by LI(max)/A = [1.46D(-0.18)L(0.4)(T(max) - 300)(0.25D(-0.09)) + 750(b'/I(max))D(10(-3)I(max)-2.87b') × 10⁶ A m⁻¹ where L is the current lead's length and the current lead is operated in liquid helium. An optimum A of 132 mm(2) is obtained when I(max) = 1000 A, T(max) = 400 K, D = 0.2, b' = 0.3 l h(-1) and L = 1.0 m. The optimized helium consumption was found to be 0.7 l h(-1). When the static boil-off is small, optimized leads have a boil-off that can be roughly parameterized by: b/I(max)  ≈ (1.35 × 10(-3))D(0.41) l h(‑1) A(-1). A split-current-lead design is employed to minimize the rotation of the probes during the high current measurements in our high-field horizontal magnet. The variable-temperature system is based on the use of an inverted insulating cup that operates above 4.2 K in liquid helium and above 77.4 K in liquid nitrogen, with a stability of ±80 mK to ±150 mK. Uniaxial strains of -1.4% to 1.0% can be applied to the sample, with a total uncertainty of better than ±0.02%, using a modified bending beam apparatus which includes a copper beryllium springboard-shaped sample holder.

Gas turbine bucket wall thickness control

DOEpatents

Stathopoulos, Dimitrios; Xu, Liming; Lewis, Doyle C.

2002-01-01

A core for use in casting a turbine bucket including serpentine cooling passages is divided into two pieces including a leading edge core section and a trailing edge core section. Wall thicknesses at the leading edge and the trailing edge of the turbine bucket can be controlled independent of each other by separately positioning the leading edge core section and the trailing edge core section in the casting die. The controlled leading and trailing edge thicknesses can thus be optimized for efficient cooling, resulting in more efficient turbine operation.

Perspectives of human verification via binary QRS template matching of single-lead and 12-lead electrocardiogram.

PubMed

Krasteva, Vessela; Jekova, Irena; Schmid, Ramun

2018-01-01

This study aims to validate the 12-lead electrocardiogram (ECG) as a biometric modality based on two straightforward binary QRS template matching characteristics. Different perspectives of the human verification problem are considered, regarding the optimal lead selection and stability over sample size, gender, age, heart rate (HR). A clinical 12-lead resting ECG database, including a population of 460 subjects with two-session recordings (>1 year apart) is used. Cost-effective strategies for extraction of personalized QRS patterns (100ms) and binary template matching estimate similarity in the time scale (matching time) and dissimilarity in the amplitude scale (mismatch area). The two-class person verification task, taking the decision to validate or to reject the subject identity is managed by linear discriminant analysis (LDA). Non-redundant LDA models for different lead configurations (I,II,III,aVF,aVL,aVF,V1-V6) are trained on the first half of 230 subjects by stepwise feature selection until maximization of the area under the receiver operating characteristic curve (ROC AUC). The operating point on the training ROC at equal error rate (EER) is tested on the independent dataset (second half of 230 subjects) to report unbiased validation of test-ROC AUC and true verification rate (TVR = 100-EER). The test results are further evaluated in groups by sample size, gender, age, HR. The optimal QRS pattern projection for single-lead ECG biometric modality is found in the frontal plane sector (60°-0°) with best (Test-AUC/TVR) for lead II (0.941/86.8%) and slight accuracy drop for -aVR (-0.017/-1.4%), I (-0.01/-1.5%). Chest ECG leads have degrading accuracy from V1 (0.885/80.6%) to V6 (0.799/71.8%). The multi-lead ECG improves verification: 6-chest (0.97/90.9%), 6-limb (0.986/94.3%), 12-leads (0.995/97.5%). The QRS pattern matching model shows stable performance for verification of 10 to 230 individuals; insignificant degradation of TVR in women by (1.2-3.6%), adults ≥70 years (3.7%), younger <40 years (1.9%), HR<60bpm (1.2%), HR>90bpm (3.9%), no degradation for HR change (0 to >20bpm).

Minimization of lumen depreciation in LED lamps using thermal transient behavior analysis and design optimizations.

PubMed

Khan, M Nisa

2016-02-10

We expansively investigate thermal behaviors of various general-purpose light-emitting diode (LED) lamps and apply our measured results, validated by simulation, to establish lamp design rules for optimizing their optical and thermal properties. These design rules provide the means to minimize lumen depreciation over time by minimizing the periods for lamps to reach thermal steady-state while maintaining their high luminous efficacy and omnidirectional light distribution capability. While it is well known that minimizing the junction temperature of an LED leads to a longer lifetime and an increased lumen output, our study demonstrates, for the first time, to the best of our knowledge, that it is also important to minimize the time it takes to reach thermal equilibrium because doing so minimizes lumen depreciation and enhances light output and color stability during operation. Specifically, we have found that, in addition to inadequate heat-sink fin areas for a lamp configuration, LEDs mounted on multiple boards, as opposed to a single board, lead to longer periods for reaching thermal equilibrium contributing to larger lumen depreciation.

Kalman filter based control for Adaptive Optics

NASA Astrophysics Data System (ADS)

Petit, Cyril; Quiros-Pacheco, Fernando; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Fusco, Thierry

2004-12-01

Classical Adaptive Optics suffer from a limitation of the corrected Field Of View. This drawback has lead to the development of MultiConjugated Adaptive Optics. While the first MCAO experimental set-ups are presently under construction, little attention has been paid to the control loop. This is however a key element in the optimization process especially for MCAO systems. Different approaches have been proposed in recent articles for astronomical applications : simple integrator, Optimized Modal Gain Integrator and Kalman filtering. We study here Kalman filtering which seems a very promising solution. Following the work of Brice Leroux, we focus on a frequential characterization of kalman filters, computing a transfer matrix. The result brings much information about their behaviour and allows comparisons with classical controllers. It also appears that straightforward improvements of the system models can lead to static aberrations and vibrations filtering. Simulation results are proposed and analysed thanks to our frequential characterization. Related problems such as model errors, aliasing effect reduction or experimental implementation and testing of Kalman filter control loop on a simplified MCAO experimental set-up could be then discussed.

A challenge for theranostics: is the optimal particle for therapy also optimal for diagnostics?

NASA Astrophysics Data System (ADS)

Dreifuss, Tamar; Betzer, Oshra; Shilo, Malka; Popovtzer, Aron; Motiei, Menachem; Popovtzer, Rachela

2015-09-01

Theranostics is defined as the combination of therapeutic and diagnostic capabilities in the same agent. Nanotechnology is emerging as an efficient platform for theranostics, since nanoparticle-based contrast agents are powerful tools for enhancing in vivo imaging, while therapeutic nanoparticles may overcome several limitations of conventional drug delivery systems. Theranostic nanoparticles have drawn particular interest in cancer treatment, as they offer significant advantages over both common imaging contrast agents and chemotherapeutic drugs. However, the development of platforms for theranostic applications raises critical questions; is the optimal particle for therapy also the optimal particle for diagnostics? Are the specific characteristics needed to optimize diagnostic imaging parallel to those required for treatment applications? This issue is examined in the present study, by investigating the effect of the gold nanoparticle (GNP) size on tumor uptake and tumor imaging. A series of anti-epidermal growth factor receptor conjugated GNPs of different sizes (diameter range: 20-120 nm) was synthesized, and then their uptake by human squamous cell carcinoma head and neck cancer cells, in vitro and in vivo, as well as their tumor visualization capabilities were evaluated using CT. The results showed that the size of the nanoparticle plays an instrumental role in determining its potential activity in vivo. Interestingly, we found that although the highest tumor uptake was obtained with 20 nm C225-GNPs, the highest contrast enhancement in the tumor was obtained with 50 nm C225-GNPs, thus leading to the conclusion that the optimal particle size for drug delivery is not necessarily optimal for imaging. These findings stress the importance of the investigation and design of optimal nanoparticles for theranostic applications.Theranostics is defined as the combination of therapeutic and diagnostic capabilities in the same agent. Nanotechnology is emerging as an efficient platform for theranostics, since nanoparticle-based contrast agents are powerful tools for enhancing in vivo imaging, while therapeutic nanoparticles may overcome several limitations of conventional drug delivery systems. Theranostic nanoparticles have drawn particular interest in cancer treatment, as they offer significant advantages over both common imaging contrast agents and chemotherapeutic drugs. However, the development of platforms for theranostic applications raises critical questions; is the optimal particle for therapy also the optimal particle for diagnostics? Are the specific characteristics needed to optimize diagnostic imaging parallel to those required for treatment applications? This issue is examined in the present study, by investigating the effect of the gold nanoparticle (GNP) size on tumor uptake and tumor imaging. A series of anti-epidermal growth factor receptor conjugated GNPs of different sizes (diameter range: 20-120 nm) was synthesized, and then their uptake by human squamous cell carcinoma head and neck cancer cells, in vitro and in vivo, as well as their tumor visualization capabilities were evaluated using CT. The results showed that the size of the nanoparticle plays an instrumental role in determining its potential activity in vivo. Interestingly, we found that although the highest tumor uptake was obtained with 20 nm C225-GNPs, the highest contrast enhancement in the tumor was obtained with 50 nm C225-GNPs, thus leading to the conclusion that the optimal particle size for drug delivery is not necessarily optimal for imaging. These findings stress the importance of the investigation and design of optimal nanoparticles for theranostic applications. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03119b

Social networks in primates: smart and tolerant species have more efficient networks.

PubMed

Pasquaretta, Cristian; Levé, Marine; Claidière, Nicolas; van de Waal, Erica; Whiten, Andrew; MacIntosh, Andrew J J; Pelé, Marie; Bergstrom, Mackenzie L; Borgeaud, Christèle; Brosnan, Sarah F; Crofoot, Margaret C; Fedigan, Linda M; Fichtel, Claudia; Hopper, Lydia M; Mareno, Mary Catherine; Petit, Odile; Schnoell, Anna Viktoria; di Sorrentino, Eugenia Polizzi; Thierry, Bernard; Tiddi, Barbara; Sueur, Cédric

2014-12-23

Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities.

Social networks in primates: smart and tolerant species have more efficient networks

PubMed Central

Pasquaretta, Cristian; Levé, Marine; Claidière, Nicolas; van de Waal, Erica; Whiten, Andrew; MacIntosh, Andrew J. J.; Pelé, Marie; Bergstrom, Mackenzie L.; Borgeaud, Christèle; Brosnan, Sarah F.; Crofoot, Margaret C.; Fedigan, Linda M.; Fichtel, Claudia; Hopper, Lydia M.; Mareno, Mary Catherine; Petit, Odile; Schnoell, Anna Viktoria; di Sorrentino, Eugenia Polizzi; Thierry, Bernard; Tiddi, Barbara; Sueur, Cédric

2014-01-01

Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities. PMID:25534964

A Novel Computer-Aided Approach for Parametric Investigation of Custom Design of Fracture Fixation Plates.

PubMed

Chen, Xiaozhong; He, Kunjin; Chen, Zhengming

2017-01-01

The present study proposes an integrated computer-aided approach combining femur surface modeling, fracture evidence recover plate creation, and plate modification in order to conduct a parametric investigation of the design of custom plate for a specific patient. The study allows for improving the design efficiency of specific plates on the patients' femur parameters and the fracture information. Furthermore, the present approach will lead to exploration of plate modification and optimization. The three-dimensional (3D) surface model of a detailed femur and the corresponding fixation plate were represented with high-level feature parameters, and the shape of the specific plate was recursively modified in order to obtain the optimal plate for a specific patient. The proposed approach was tested and verified on a case study, and it could be helpful for orthopedic surgeons to design and modify the plate in order to fit the specific femur anatomy and the fracture information.

Practical Implications from Observed Lead Pipe Scale Mineralogy in a Blended Phosphate Treated System - slides

EPA Science Inventory

Many water utilities in the United States rely on the addition of phosphate-based corrosion inhibitors to optimize their corrosion control and comply with requirements of the Lead and Copper Rule. Orthophosphate is used on the theory of forming low solubility Pb(II)-orthophosphat...

Design of alumina forming FeCrAl steels for lead or lead-bismuth cooled fast reactors

NASA Astrophysics Data System (ADS)

Lim, Jun; Hwang, Il Soon; Kim, Ji Hyun

2013-10-01

Iron-chromium-aluminum alloys containing 15-20 wt.% Cr and 4-6 wt.% Al have shown excellent corrosion resistance in the temperature range up to 600 °C or higher in liquid lead and lead-bismuth eutectic environments by the formation of protective Al2O3 layers. However, the higher Cr and Al concentrations in ferritic alloys could be problematic because of severe embrittlement in the manufacturing process as well as in service, caused by the formation of brittle phases. For this reason, efforts worldwide have so far mainly focused on the development of aluminizing surface treatments. However, aluminizing surface treatments have major disadvantages of cost, processing difficulties and reliability issues. In this study, a new FeCrAl alloy is proposed for structural materials in lead and lead-bismuth cooled nuclear applications. The alloy design relied on corrosion experiments in high temperature lead and lead-bismuth eutectic environments and computational thermodynamic calculations using the commercial software, JMatPro. The design of new alloys has focused on the optimization of Cr and Al levels for the formation of an external Al2O3 layer which can provide excellent oxidation and corrosion resistance in liquid lead alloys in the temperature range 300-600 °C while still retaining workable mechanical properties.

Retrospective Cost Adaptive Control with Concurrent Closed-Loop Identification

NASA Astrophysics Data System (ADS)

Sobolic, Frantisek M.

Retrospective cost adaptive control (RCAC) is a discrete-time direct adaptive control algorithm for stabilization, command following, and disturbance rejection. RCAC is known to work on systems given minimal modeling information which is the leading numerator coefficient and any nonminimum-phase (NMP) zeros of the plant transfer function. This information is normally needed a priori and is key in the development of the filter, also known as the target model, within the retrospective performance variable. A novel approach to alleviate the need for prior modeling of both the leading coefficient of the plant transfer function as well as any NMP zeros is developed. The extension to the RCAC algorithm is the use of concurrent optimization of both the target model and the controller coefficients. Concurrent optimization of the target model and controller coefficients is a quadratic optimization problem in the target model and controller coefficients separately. However, this optimization problem is not convex as a joint function of both variables, and therefore nonconvex optimization methods are needed. Finally, insights within RCAC that include intercalated injection between the controller numerator and the denominator, unveil the workings of RCAC fitting a specific closed-loop transfer function to the target model. We exploit this interpretation by investigating several closed-loop identification architectures in order to extract this information for use in the target model.

Optimizing Associative Experimental Design for Protein Crystallization Screening

PubMed Central

Dinç, Imren; Pusey, Marc L.; Aygün, Ramazan S.

2016-01-01

The goal of protein crystallization screening is the determination of the main factors of importance to crystallizing the protein under investigation. One of the major issues about determining these factors is that screening is often expanded to many hundreds or thousands of conditions to maximize combinatorial chemical space coverage for maximizing the chances of a successful (crystalline) outcome. In this paper, we propose an experimental design method called “Associative Experimental Design (AED)” and an optimization method includes eliminating prohibited combinations and prioritizing reagents based on AED analysis of results from protein crystallization experiments. AED generates candidate cocktails based on these initial screening results. These results are analyzed to determine those screening factors in chemical space that are most likely to lead to higher scoring outcomes, crystals. We have tested AED on three proteins derived from the hyperthermophile Thermococcus thioreducens, and we applied an optimization method to these proteins. Our AED method generated novel cocktails (count provided in parentheses) leading to crystals for three proteins as follows: Nucleoside diphosphate kinase (4), HAD superfamily hydrolase (2), Nucleoside kinase (1). After getting promising results, we have tested our optimization method on four different proteins. The AED method with optimization yielded 4, 3, and 20 crystalline conditions for holo Human Transferrin, archaeal exosome protein, and Nucleoside diphosphate kinase, respectively. PMID:26955046

Optimized open-flow mixing: insights from microbubble streaming

NASA Astrophysics Data System (ADS)

Rallabandi, Bhargav; Wang, Cheng; Guo, Lin; Hilgenfeldt, Sascha

2015-11-01

Microbubble streaming has been developed into a robust and powerful flow actuation technique in microfluidics. Here, we study it as a paradigmatic system for microfluidic mixing under a continuous throughput of fluid (open-flow mixing), providing a systematic optimization of the device parameters in this practically important situation. Focusing on two-dimensional advective stirring (neglecting diffusion), we show through numerical simulation and analytical theory that mixing in steady streaming vortices becomes ineffective beyond a characteristic time scale, necessitating the introduction of unsteadiness. By duty cycling the streaming, such unsteadiness is introduced in a controlled fashion, leading to exponential refinement of the advection structures. The rate of refinement is then optimized for particular parameters of the time modulation, i.e. a particular combination of times for which the streaming is turned ``on'' and ``off''. The optimized protocol can be understood theoretically using the properties of the streaming vortices and the throughput Poiseuille flow. We can thus infer simple design principles for practical open flow micromixing applications, consistent with experiments. Current Address: Mechanical and Aerospace Engineering, Princeton University.

Robustness-Based Design Optimization Under Data Uncertainty

NASA Technical Reports Server (NTRS)

Zaman, Kais; McDonald, Mark; Mahadevan, Sankaran; Green, Lawrence

2010-01-01

This paper proposes formulations and algorithms for design optimization under both aleatory (i.e., natural or physical variability) and epistemic uncertainty (i.e., imprecise probabilistic information), from the perspective of system robustness. The proposed formulations deal with epistemic uncertainty arising from both sparse and interval data without any assumption about the probability distributions of the random variables. A decoupled approach is proposed in this paper to un-nest the robustness-based design from the analysis of non-design epistemic variables to achieve computational efficiency. The proposed methods are illustrated for the upper stage design problem of a two-stage-to-orbit (TSTO) vehicle, where the information on the random design inputs are only available as sparse point and/or interval data. As collecting more data reduces uncertainty but increases cost, the effect of sample size on the optimality and robustness of the solution is also studied. A method is developed to determine the optimal sample size for sparse point data that leads to the solutions of the design problem that are least sensitive to variations in the input random variables.

Uncertainty in the analysis of the overall equipment effectiveness on the shop floor

NASA Astrophysics Data System (ADS)

Rößler, M. P.; Abele, E.

2013-06-01

In this article an approach will be presented which supports transparency regarding the effectiveness of manufacturing equipment by combining the fuzzy set theory with the method of the overall equipment effectiveness analysis. One of the key principles of lean production and also a fundamental task in production optimization projects is the prior analysis of the current state of a production system by the use of key performance indicators to derive possible future states. The current state of the art in overall equipment effectiveness analysis is usually performed by cumulating different machine states by means of decentralized data collection without the consideration of uncertainty. In manual data collection or semi-automated plant data collection systems the quality of derived data often diverges and leads optimization teams to distorted conclusions about the real optimization potential of manufacturing equipment. The method discussed in this paper is to help practitioners to get more reliable results in the analysis phase and so better results of optimization projects. Under consideration of a case study obtained results are discussed.

Energy-optimal electrical excitation of nerve fibers.

PubMed

Jezernik, Saso; Morari, Manfred

2005-04-01

We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.

An Automated DAKOTA and VULCAN-CFD Framework with Application to Supersonic Facility Nozzle Flowpath Optimization

NASA Technical Reports Server (NTRS)

Axdahl, Erik L.

2015-01-01

Removing human interaction from design processes by using automation may lead to gains in both productivity and design precision. This memorandum describes efforts to incorporate high fidelity numerical analysis tools into an automated framework and applying that framework to applications of practical interest. The purpose of this effort was to integrate VULCAN-CFD into an automated, DAKOTA-enabled framework with a proof-of-concept application being the optimization of supersonic test facility nozzles. It was shown that the optimization framework could be deployed on a high performance computing cluster with the flow of information handled effectively to guide the optimization process. Furthermore, the application of the framework to supersonic test facility nozzle flowpath design and optimization was demonstrated using multiple optimization algorithms.

Detection of highly toxic elements (lead and chromium) in commercially available eyeliner (kohl) using laser induced break down spectroscopy

NASA Astrophysics Data System (ADS)

Gondal, M. A.; Dastageer, M. A.; Al-Adel, F. F.; Naqvi, A. A.; Habibullah, Y. B.

2015-12-01

A sensitive laser induced breakdown spectroscopic system was developed and optimized for using it as a sensor for the detection of trace levels of lead and chromium present in the cosmetic eyeliner (kohl) of different price ranges (brands) available in the local market. Kohl is widely used in developing countries for babies as well adults for beautification as well eyes protection. The atomic transition lines at 405.7 nm and 425.4 nm were used as the marker lines for the detection of lead and chromium respectively. The detection system was optimized by finding the appropriate gate delay between the laser excitation and the data acquisition system and also by achieving optically thin plasma near the target by establishing the local thermodynamic equilibrium condition. The detection system was calibrated for these two hazardous elements and the kohl samples under investigation showed 8-15 ppm by mass of lead and 4-9 ppm by mass of Chromium, which are higher than the safe permissible levels of these elements. The limits of detection of the LIBS system for lead and chromium were found to be 1 and 2 ppm respectively.

Optimization of a Two Stage Pulse Tube Refrigerator for the Integrated Current Lead System

NASA Astrophysics Data System (ADS)

Maekawa, R.; Matsubara, Y.; Okada, A.; Takami, S.; Konno, M.; Tomioka, A.; Imayoshi, T.; Hayashi, H.; Mito, T.

2008-03-01

Implementation of a conventional current lead with a pulse tube refrigerator has been validated to be working as an Integrated Current Lead (ICL) system for the Superconducting Magnetic Energy Storage (SMES). Realization of the system is primarily accounted for the flexibility of a pulse tube refrigerator, which does not posses any mechanical piston and/or displacer. As for an ultimate version of the ICL system, a High Temperature Superconducting (HTS) lead links a superconducting coil with a conventional copper lead. To ensure the minimization of heat loads to the superconducting coil, a pulse tube refrigerator has been upgraded to have a second cooling stage. This arrangement reduces not only the heat loads to the superconducting coil but also the operating cost for a SMES system. A prototype two-stage pulse tube refrigerator, series connected arrangement, was designed and fabricated to satisfy the requirements for the ICL system. Operation of the first stage refrigerator is a four-valve mode, while the second stage utilizes a double inlet configuration to ensure its confined geometry. The paper discusses the optimization of second stage cooling to validate the conceptual design

Efficient swimming of an assembly of rigid spheres at low Reynolds number.

PubMed

Felderhof, B U

2015-08-01

The swimming of an assembly of rigid spheres immersed in a viscous fluid of infinite extent is studied in low-Reynolds-number hydrodynamics. The instantaneous swimming velocity and rate of dissipation are expressed in terms of the time-dependent displacements of sphere centers about their collective motion. For small-amplitude swimming with periodically oscillating displacements, optimization of the mean swimming speed at given mean power leads to an eigenvalue problem involving a velocity matrix and a power matrix. The corresponding optimal stroke permits generalization to large-amplitude motion in a model of spheres with harmonic interactions and corresponding actuating forces. The method allows straightforward calculation of the swimming performance of structures modeled as assemblies of interacting rigid spheres. A model of three collinear spheres with motion along the common axis is studied as an example.

Project HyBuJET

NASA Technical Reports Server (NTRS)

Ramsay, Tom; Collet, Bill; Igar, Karyn; Kendall, Dewayne; Miklosovic, Dave; Reuss, Robyn; Ringer, Mark; Scheidt, Tony

1990-01-01

A conceptual Hypersonic Business Jet (HyBuJet) was examined. The main areas of concentration include: aerodynamics, propulsion, stability and control, mission profile, and atmospheric heating. In order to optimize for cruise conditions, a waverider configuration was chosen for the high lift drag ratio and low wave drag. The leading edge and lower surface of a waverider was mapped out from a known flow field and optimized for cruising at Mach 6 and at high altitudes. The shockwave generated by a waverider remains attached along the entire leading edge, allowing for a larger compression along the lower surface. Three turbofan ramjets were chosen as the propulsion of the aircraft due to the combination of good subsonic performance along with high speed propulsive capabilities. A combination of liquid silicon convective cooling for the leading edges with a highly radiative outer skin material was chosen to reduce the atmospheric heating to acceptable level.

Guiding lead optimization with GPCR structure modeling and molecular dynamics.

PubMed

Heifetz, Alexander; James, Tim; Morao, Inaki; Bodkin, Michael J; Biggin, Philip C

2016-10-01

G-protein coupled receptor (GPCR) modeling approaches are widely used in the hit-to-lead and lead optimization stages of drug discovery. Modern protocols that involve molecular dynamics simulation can address key issues such as the free energy of binding (affinity), ligand-induced GPCR flexibility, ligand binding kinetics, conserved water positions and their role in ligand binding and the effects of mutations. The goals of these calculations are to predict the structures of the complexes between existing ligands and their receptors, to understand the key interactions and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this review we present a brief survey of various computational approaches illustrated through a hierarchical GPCR modeling protocol and its prospective application in three industrial drug discovery projects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization of a pyrazole hit from FBDD into a novel series of indazoles as ketohexokinase inhibitors.

PubMed

Zhang, Xuqing; Song, Fengbing; Kuo, Gee-Hong; Xiang, Amy; Gibbs, Alan C; Abad, Marta C; Sun, Weimei; Kuo, Lawrence C; Sui, Zhihua

2011-08-15

A series of indazoles have been discovered as KHK inhibitors from a pyrazole hit identified through fragment-based drug discovery (FBDD). The optimization process guided by both X-ray crystallography and solution activity resulted in lead-like compounds with good pharmaceutical properties. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Dynamic Process Model for Optimizing the Hospital Environment Cash-Flow

NASA Astrophysics Data System (ADS)

Pater, Flavius; Rosu, Serban

2011-09-01

In this article is presented a new approach to some fundamental techniques of solving dynamic programming problems with the use of functional equations. We will analyze the problem of minimizing the cost of treatment in a hospital environment. Mathematical modeling of this process leads to an optimal control problem with a finite horizon.