Cast Off expansion plan by rapid improvement through Optimization tool design, Tool Parameters and using Six Sigma’s ECRS Technique

NASA Astrophysics Data System (ADS)

Gopalakrishnan, T.; Saravanan, R.

2017-03-01

Powerful management concepts step-up the quality of the product, time saving in producing the product thereby increase the production rate, improves tools and techniques, work culture, work place and employee motivation and morale. In this paper discussed about the case study of optimizing the tool design, tool parameters to cast off expansion plan according ECRS technique. The proposed designs and optimal tool parameters yielded best results and meet the customer demand without expansion plan. Hence the work yielded huge savings of money (direct and indirect cost), time and improved the motivation and more of employees significantly.

Left ventricular assist devices as destination therapy: a new look at survival.

PubMed

Park, Soon J; Tector, Alfred; Piccioni, William; Raines, Edward; Gelijns, Annetine; Moskowitz, Alan; Rose, Eric; Holman, William; Furukawa, Satoshi; Frazier, O Howard; Dembitsky, Walter

2005-01-01

The REMATCH trial compared the use of left ventricular assist devices with optimal medical management for patients with end-stage heart failure. When the trial met its primary end point criteria in July 2001, left ventricular assist device therapy was shown to significantly improve survival and quality of life. With extended follow-up, 2 critical questions emerge: (1) Did these benefits persist, and (2) did outcomes improve over the course of the trial, given the evolving nature of the technology? We analyzed survival in this randomized trial by using the product-limit method of Kaplan and Meier. Changes in the benefits of therapy were analyzed by examining the effect of the enrollment period. The survival rates for patients receiving left ventricular assist devices (n = 68) versus patients receiving optimal medical management (n = 61) were 52% versus 28% at 1 year and 29% versus 13% at 2 years ( P = .008, log-rank test). As of July 2003, 11 patients were alive on left ventricular assist device support out of a total 16 survivors (including 3 patients receiving optimal medical management who crossed over to left ventricular assist device therapy). There was a significant improvement in survival for left ventricular assist device-supported patients who enrolled during the second half of the trial compared with the first half ( P = .03). The Minnesota Living with Heart Failure scores improved significantly over the course of the trial. The extended follow-up confirms the initial observation that left ventricular assist device therapy renders significant survival and quality-of-life benefits compared with optimal medical management for patients with end-stage heart failure. Furthermore, we observed an improvement in the survival of patients receiving left ventricular assist devices over the course of the trial, suggesting the effect of greater clinical experience.

Interleaved segment correction achieves higher improvement factors in using genetic algorithm to optimize light focusing through scattering media

NASA Astrophysics Data System (ADS)

Li, Runze; Peng, Tong; Liang, Yansheng; Yang, Yanlong; Yao, Baoli; Yu, Xianghua; Min, Junwei; Lei, Ming; Yan, Shaohui; Zhang, Chunmin; Ye, Tong

2017-10-01

Focusing and imaging through scattering media has been proved possible with high resolution wavefront shaping. A completely scrambled scattering field can be corrected by applying a correction phase mask on a phase only spatial light modulator (SLM) and thereby the focusing quality can be improved. The correction phase is often found by global searching algorithms, among which Genetic Algorithm (GA) stands out for its parallel optimization process and high performance in noisy environment. However, the convergence of GA slows down gradually with the progression of optimization, causing the improvement factor of optimization to reach a plateau eventually. In this report, we propose an interleaved segment correction (ISC) method that can significantly boost the improvement factor with the same number of iterations comparing with the conventional all segment correction method. In the ISC method, all the phase segments are divided into a number of interleaved groups; GA optimization procedures are performed individually and sequentially among each group of segments. The final correction phase mask is formed by applying correction phases of all interleaved groups together on the SLM. The ISC method has been proved significantly useful in practice because of its ability to achieve better improvement factors when noise is present in the system. We have also demonstrated that the imaging quality is improved as better correction phases are found and applied on the SLM. Additionally, the ISC method lowers the demand of dynamic ranges of detection devices. The proposed method holds potential in applications, such as high-resolution imaging in deep tissue.

Chain alignment for improved properties - Optimization of PLA and PHB-V by crystallization and reinforcement

NASA Astrophysics Data System (ADS)

Moser, K.; Bergmann, B.; Diemert, J.; Elsner, P.

2014-05-01

In this paper two promising ways to improve the material characteristics of PLA and PHB-V are presented by showing their positive effects on mechanical, optical, and thermal properties. The optimization is achieved by increasing the crystallization from the melt of the polymer chains and the other by means of a reinforcement of the matrices by bio-based materials. In the case of crystallization specific nucleating agents and optimized process parameters promote optimized crystallization conditions and lead particularly in toughness to significant improvements. In addition to crystallization the introduction of cellulose-based reinforcing materials is also a good alternative to improve the ductility of a biopolymer matrix considerably. Due to their polar surface structure cellulose fibres are favouring a very good interaction to the also polar biopolymers. In addition, the polar surfaces of both materials results in very homogeneous dispersion within the compound.

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.

Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

NASA Astrophysics Data System (ADS)

Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

2018-03-01

Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Goienetxea Uriarte, A.; Ruiz Zúñiga, E.; Urenda Moris, M.; Ng, A. H. C.

2015-05-01

Discrete Event Simulation (DES) is nowadays widely used to support decision makers in system analysis and improvement. However, the use of simulation for improving stochastic logistic processes is not common among healthcare providers. The process of improving healthcare systems involves the necessity to deal with trade-off optimal solutions that take into consideration a multiple number of variables and objectives. Complementing DES with Multi-Objective Optimization (SMO) creates a superior base for finding these solutions and in consequence, facilitates the decision-making process. This paper presents how SMO has been applied for system improvement analysis in a Swedish Emergency Department (ED). A significant number of input variables, constraints and objectives were considered when defining the optimization problem. As a result of the project, the decision makers were provided with a range of optimal solutions which reduces considerably the length of stay and waiting times for the ED patients. SMO has proved to be an appropriate technique to support healthcare system design and improvement processes. A key factor for the success of this project has been the involvement and engagement of the stakeholders during the whole process.

Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

PubMed

Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

2018-06-12

Particle swarm optimization (PSO) is a powerful metaheuristic population-based global optimization algorithm. However, when it is applied to nonseparable objective functions, its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant PSO algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates superior performance across several nonlinear, multimodal benchmark functions compared with the rotation-invariant PSO algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in the ReaxFF- lg reactive force field was carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents better performance compared to a genetic algorithm optimization method in the optimization of the parameters of a ReaxFF- lg correction model. The computational framework is implemented in a stand-alone C++ code that allows the straightforward development of ReaxFF reactive force fields.

Formulation and characterization of an apigenin-phospholipid phytosome (APLC) for improved solubility, in vivo bioavailability, and antioxidant potential.

PubMed

Telange, Darshan R; Patil, Arun T; Pethe, Anil M; Fegade, Harshal; Anand, Sridhar; Dave, Vivek S

2017-10-15

The apigenin-phospholipid phytosome (APLC) was developed to improve the aqueous solubility, dissolution, in vivo bioavailability, and antioxidant activity of apigenin. The APLC synthesis was guided by a full factorial design strategy, incorporating specific formulation and process variables to deliver an optimized product. The design-optimized formulation was assayed for aqueous solubility, in vitro dissolution, pharmacokinetics, and antioxidant activity. The pharmacological evaluation was carried out by assessing its effects on carbon tetrachloride-induced elevation of liver function marker enzymes in a rat model. The antioxidant activity was assessed by studying its effects on the liver antioxidant marker enzymes. The developed model was validated using the design-optimized levels of formulation and process variables. The physical-chemical characterization confirmed the formation of phytosomes. The optimized formulation demonstrated over 36-fold higher aqueous solubility of apigenin, compared to that of pure apigenin. The formulation also exhibited a significantly higher rate and extent of apigenin release in dissolution studies. The pharmacokinetic analysis revealed a significant enhancement in the oral bioavailability of apigenin from the prepared formulation, compared to pure apigenin. The liver function tests indicated that the prepared phytosome showed a significantly improved restoration of all carbon tetrachloride-elevated rat liver function marker enzymes. The prepared formulation also exhibited antioxidant potential by significantly increasing the levels of glutathione, superoxide dismutase, catalase, and decreasing the levels of lipid peroxidase. The study shows that phospholipid-based phytosome is a promising and viable strategy for improving the delivery of apigenin and similar phytoconstituents with low aqueous solubility. Copyright © 2016 Elsevier B.V. All rights reserved.

Clinical Outcomes of an Optimized Prolate Ablation Procedure for Correcting Residual Refractive Errors Following Laser Surgery.

PubMed

Chung, Byunghoon; Lee, Hun; Choi, Bong Joon; Seo, Kyung Ryul; Kim, Eung Kwon; Kim, Dae Yune; Kim, Tae-Im

2017-02-01

The purpose of this study was to investigate the clinical efficacy of an optimized prolate ablation procedure for correcting residual refractive errors following laser surgery. We analyzed 24 eyes of 15 patients who underwent an optimized prolate ablation procedure for the correction of residual refractive errors following laser in situ keratomileusis, laser-assisted subepithelial keratectomy, or photorefractive keratectomy surgeries. Preoperative ophthalmic examinations were performed, and uncorrected distance visual acuity, corrected distance visual acuity, manifest refraction values (sphere, cylinder, and spherical equivalent), point spread function, modulation transfer function, corneal asphericity (Q value), ocular aberrations, and corneal haze measurements were obtained postoperatively at 1, 3, and 6 months. Uncorrected distance visual acuity improved and refractive errors decreased significantly at 1, 3, and 6 months postoperatively. Total coma aberration increased at 3 and 6 months postoperatively, while changes in all other aberrations were not statistically significant. Similarly, no significant changes in point spread function were detected, but modulation transfer function increased significantly at the postoperative time points measured. The optimized prolate ablation procedure was effective in terms of improving visual acuity and objective visual performance for the correction of persistent refractive errors following laser surgery.

Optimal decision making modeling for copper-matte Peirce-Smith converting process by means of data mining

NASA Astrophysics Data System (ADS)

Song, Yanpo; Peng, Xiaoqi; Tang, Ying; Hu, Zhikun

2013-07-01

To improve the operation level of copper converter, the approach to optimal decision making modeling for coppermatte converting process based on data mining is studied: in view of the characteristics of the process data, such as containing noise, small sample size and so on, a new robust improved ANN (artificial neural network) modeling method is proposed; taking into account the application purpose of decision making model, three new evaluation indexes named support, confidence and relative confidence are proposed; using real production data and the methods mentioned above, optimal decision making model for blowing time of S1 period (the 1st slag producing period) are developed. Simulation results show that this model can significantly improve the converting quality of S1 period, increase the optimal probability from about 70% to about 85%.

Power plant maintenance scheduling using ant colony optimization: an improved formulation

NASA Astrophysics Data System (ADS)

Foong, Wai Kuan; Maier, Holger; Simpson, Angus

2008-04-01

It is common practice in the hydropower industry to either shorten the maintenance duration or to postpone maintenance tasks in a hydropower system when there is expected unserved energy based on current water storage levels and forecast storage inflows. It is therefore essential that a maintenance scheduling optimizer can incorporate the options of shortening the maintenance duration and/or deferring maintenance tasks in the search for practical maintenance schedules. In this article, an improved ant colony optimization-power plant maintenance scheduling optimization (ACO-PPMSO) formulation that considers such options in the optimization process is introduced. As a result, both the optimum commencement time and the optimum outage duration are determined for each of the maintenance tasks that need to be scheduled. In addition, a local search strategy is presented in this article to boost the robustness of the algorithm. When tested on a five-station hydropower system problem, the improved formulation is shown to be capable of allowing shortening of maintenance duration in the event of expected demand shortfalls. In addition, the new local search strategy is also shown to have significantly improved the optimization ability of the ACO-PPMSO algorithm.

SU-E-T-593: Clinical Evaluation of Direct Aperture Optimization in Head/Neck and Prostate IMRT Treatment

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

Hosini, M; GALAL, M; Emam, I

2014-06-01

Purpose: To investigate the planning and dosimetric advantages of direct aperture optimization (DAO) over beam-let optimization in IMRT treatment of head and neck (H/N) and prostate cancers. Methods: Five Head and Neck as well as five prostate patients were planned using the beamlet optimizer in Elekta-Xio ver 4.6 IMRT treatment planning system. Based on our experience in beamlet IMRT optimization, PTVs in H/N plans were prescribed to 70 Gy delivered by 7 fields. While prostate PTVs were prescribed to 76 Gy with 9 fields. In all plans, fields were set to be equally spaced. All cases were re-planed using Directmore » Aperture optimizer in Prowess Panther ver 5.01 IMRT planning system at same configurations and dose constraints. Plans were evaluated according to ICRU criteria, number of segments, number of monitor units and planning time. Results: For H/N plans, the near maximum dose (D2) and the dose that covers 95% D95 of PTV has improved by 4% in DAO. For organs at risk (OAR), DAO reduced the volume covered by 30% (V30) in spinal cord, right parotid, and left parotid by 60%, 54%, and 53% respectively. This considerable dosimetric quality improvement achieved using 25% less planning time and lower number of segments and monitor units by 46% and 51% respectively. In DAO prostate plans, Both D2 and D95 for the PTV were improved by only 2%. The V30 of the right femur, left femur and bladder were improved by 35%, 15% and 3% respectively. On the contrary, the rectum V30 got even worse by 9%. However, number of monitor units, and number of segments decreased by 20% and 25% respectively. Moreover the planning time reduced significantly too. Conclusion: DAO introduces considerable advantages over the beamlet optimization in regards to organs at risk sparing. However, no significant improvement occurred in most studied PTVs.« less

Optimal Control Strategy Design Based on Dynamic Programming for a Dual-Motor Coupling-Propulsion System

PubMed Central

Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui

2014-01-01

A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch. PMID:25540814

Optimal control strategy design based on dynamic programming for a dual-motor coupling-propulsion system.

PubMed

Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui

2014-01-01

A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

PubMed

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-07-14

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

Observation of combined/optimized therapy of Lamivudine and Adefovir Dipivoxyl for hepatitis B-induced decompensated cirrhosis with baseline HBV DNA>1,000 IU/mL.

PubMed

Zhang, D; Zhao, G; Li, L; Li, Z

2017-01-01

This study aimed to observe and compare the efficacy and safety of the combined therapy and two different optimized therapies of lamivudine (LAM) and adefovir dipivoxil (ADV), as well as entecavir (ETV) monotherapy in patients with hepatitis B-induced decompensated cirrhosis. Method : A total of 127 patients with decompensated cirrhosis were divided into four groups, and each group received different doses of regimens: initial combination of LAM and ADV, ADV add-on therapies with previous 12-week LAM, ADV add-on therapies with previous 24-week LAM, and ETV monotherapy. At the end of the treatment, the level of alanine amino-transferase (ALT), albumin (ALB) and total bilirubin (TBIL) in the combination therapy group and 12-week optimized therapy group were significantly improved. For the 24-week optimized therapy group, only ALT levels revealed a significant improvement. There were no obvious differences in the normalization rate of ALT, negative conversion rate of HBV DNA and HBeAg, as well as improvement in Child-Pugh scores among the combination therapy group, 12-week optimized therapy group, and ETV monotherapy group. However, the difference among these three groups and the 24-week optimized therapy group were significant. Differences were not observed in the HBeAg seroconversion between each group. Differences in blood urea nitrogen, serum creatinine, creatine kinase, or other serious adverse effects were not observed in each group at the end of the 96-week treatment. Combination therapy and early ADV addition were the preferred approaches in the antiviral strategy for the treatment of hepatitis B-induced decompensated cirrhosis.

Clinical implementation of a knowledge based planning tool for prostate VMAT.

PubMed

Powis, Richard; Bird, Andrew; Brennan, Matthew; Hinks, Susan; Newman, Hannah; Reed, Katie; Sage, John; Webster, Gareth

2017-05-08

A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency. A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as "optimal" and "sub-optimal" by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly. Plans identified as "sub-optimal" in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as "optimal" observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed. The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data.

An efficient optimization method to improve the measuring accuracy of oxygen saturation by using triangular wave optical signal

NASA Astrophysics Data System (ADS)

Li, Gang; Yu, Yue; Zhang, Cui; Lin, Ling

2017-09-01

The oxygen saturation is one of the important parameters to evaluate human health. This paper presents an efficient optimization method that can improve the accuracy of oxygen saturation measurement, which employs an optical frequency division triangular wave signal as the excitation signal to obtain dynamic spectrum and calculate oxygen saturation. In comparison to the traditional method measured RMSE (root mean square error) of SpO2 which is 0.1705, this proposed method significantly reduced the measured RMSE which is 0.0965. It is notable that the accuracy of oxygen saturation measurement has been improved significantly. The method can simplify the circuit and bring down the demand of elements. Furthermore, it has a great reference value on improving the signal to noise ratio of other physiological signals.

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.

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

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

Zarepisheh, M; Li, R; Xing, L

Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) andmore » aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves quality of resultant treatment plans as compared with conventional VMAT or IMRT treatments.« less

iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans

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

Breedveld, Sebastiaan; Storchi, Pascal R. M.; Voet, Peter W. J.

2012-02-15

Purpose: To introduce iCycle, a novel algorithm for integrated, multicriterial optimization of beam angles, and intensity modulated radiotherapy (IMRT) profiles. Methods: A multicriterial plan optimization with iCycle is based on a prescription called wish-list, containing hard constraints and objectives with ascribed priorities. Priorities are ordinal parameters used for relative importance ranking of the objectives. The higher an objective priority is, the higher the probability that the corresponding objective will be met. Beam directions are selected from an input set of candidate directions. Input sets can be restricted, e.g., to allow only generation of coplanar plans, or to avoid collisions betweenmore » patient/couch and the gantry in a noncoplanar setup. Obtaining clinically feasible calculation times was an important design criterium for development of iCycle. This could be realized by sequentially adding beams to the treatment plan in an iterative procedure. Each iteration loop starts with selection of the optimal direction to be added. Then, a Pareto-optimal IMRT plan is generated for the (fixed) beam setup that includes all so far selected directions, using a previously published algorithm for multicriterial optimization of fluence profiles for a fixed beam arrangement Breedveld et al.[Phys. Med. Biol. 54, 7199-7209 (2009)]. To select the next direction, each not yet selected candidate direction is temporarily added to the plan and an optimization problem, derived from the Lagrangian obtained from the just performed optimization for establishing the Pareto-optimal plan, is solved. For each patient, a single one-beam, two-beam, three-beam, etc. Pareto-optimal plan is generated until addition of beams does no longer result in significant plan quality improvement. Plan generation with iCycle is fully automated. Results: Performance and characteristics of iCycle are demonstrated by generating plans for a maxillary sinus case, a cervical cancer patient, and a liver patient treated with SBRT. Plans generated with beam angle optimization did better meet the clinical goals than equiangular or manually selected configurations. For the maxillary sinus and liver cases, significant improvements for noncoplanar setups were seen. The cervix case showed that also in IMRT with coplanar setups, beam angle optimization with iCycle may improve plan quality. Computation times for coplanar plans were around 1-2 h and for noncoplanar plans 4-7 h, depending on the number of beams and the complexity of the site. Conclusions: Integrated beam angle and profile optimization with iCycle may result in significant improvements in treatment plan quality. Due to automation, the plan generation workload is minimal. Clinical application has started.« less

Application of genetic algorithm in modeling on-wafer inductors for up to 110 Ghz

NASA Astrophysics Data System (ADS)

Liu, Nianhong; Fu, Jun; Liu, Hui; Cui, Wenpu; Liu, Zhihong; Liu, Linlin; Zhou, Wei; Wang, Quan; Guo, Ao

2018-05-01

In this work, the genetic algorithm has been introducted into parameter extraction for on-wafer inductors for up to 110 GHz millimeter-wave operations, and nine independent parameters of the equivalent circuit model are optimized together. With the genetic algorithm, the model with the optimized parameters gives a better fitting accuracy than the preliminary parameters without optimization. Especially, the fitting accuracy of the Q value achieves a significant improvement after the optimization.

SU-F-T-256: 4D IMRT Planning Using An Early Prototype GPU-Enabled Eclipse Workstation

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

Hagan, A; Modiri, A; Sawant, A

Purpose: True 4D IMRT planning, based on simultaneous spatiotemporal optimization has been shown to significantly improve plan quality in lung radiotherapy. However, the high computational complexity associated with such planning represents a significant barrier to widespread clinical deployment. We introduce an early prototype GPU-enabled Eclipse workstation for inverse planning. To our knowledge, this is the first GPUintegrated Eclipse system demonstrating the potential for clinical translation of GPU computing on a major commercially-available TPS. Methods: The prototype system comprised of four NVIDIA Tesla K80 GPUs, with a maximum processing capability of 8.5 Tflops per K80 card. The system architecture consisted ofmore » three key modules: (i) a GPU-based inverse planning module using a highly-parallelizable, swarm intelligence-based global optimization algorithm, (ii) a GPU-based open-source b-spline deformable image registration module, Elastix, and (iii) a CUDA-based data management module. For evaluation, aperture fluence weights in an IMRT plan were optimized over 9 beams,166 apertures and 10 respiratory phases (14940 variables) for a lung cancer case (GTV = 95 cc, right lower lobe, 15 mm cranio-caudal motion). Sensitivity of the planning time and memory expense to parameter variations was quantified. Results: GPU-based inverse planning was significantly accelerated compared to its CPU counterpart (36 vs 488 min, for 10 phases, 10 search agents and 10 iterations). The optimized IMRT plan significantly improved OAR sparing compared to the original internal target volume (ITV)-based clinical plan, while maintaining prescribed tumor coverage. The dose-sparing improvements were: Esophagus Dmax 50%, Heart Dmax 42% and Spinal cord Dmax 25%. Conclusion: Our early prototype system demonstrates that through massive parallelization, computationally intense tasks such as 4D treatment planning can be accomplished in clinically feasible timeframes. With further optimization, such systems are expected to enable the eventual clinical translation of higher-dimensional and complex treatment planning strategies to significantly improve plan quality. This work was partially supported through research funding from National Institutes of Health (R01CA169102) and Varian Medical Systems, Palo Alto, CA, USA.« less

Time-saving design of experiment protocol for optimization of LC-MS data processing in metabolomic approaches.

PubMed

Zheng, Hong; Clausen, Morten Rahr; Dalsgaard, Trine Kastrup; Mortensen, Grith; Bertram, Hanne Christine

2013-08-06

We describe a time-saving protocol for the processing of LC-MS-based metabolomics data by optimizing parameter settings in XCMS and threshold settings for removing noisy and low-intensity peaks using design of experiment (DoE) approaches including Plackett-Burman design (PBD) for screening and central composite design (CCD) for optimization. A reliability index, which is based on evaluation of the linear response to a dilution series, was used as a parameter for the assessment of data quality. After identifying the significant parameters in the XCMS software by PBD, CCD was applied to determine their values by maximizing the reliability and group indexes. Optimal settings by DoE resulted in improvements of 19.4% and 54.7% in the reliability index for a standard mixture and human urine, respectively, as compared with the default setting, and a total of 38 h was required to complete the optimization. Moreover, threshold settings were optimized by using CCD for further improvement. The approach combining optimal parameter setting and the threshold method improved the reliability index about 9.5 times for a standards mixture and 14.5 times for human urine data, which required a total of 41 h. Validation results also showed improvements in the reliability index of about 5-7 times even for urine samples from different subjects. It is concluded that the proposed methodology can be used as a time-saving approach for improving the processing of LC-MS-based metabolomics data.

Application of resist-profile-aware source optimization in 28 nm full chip optical proximity correction

NASA Astrophysics Data System (ADS)

Zhu, Jun; Zhang, David Wei; Kuo, Chinte; Wang, Qing; Wei, Fang; Zhang, Chenming; Chen, Han; He, Daquan; Hsu, Stephen D.

2017-07-01

As technology node shrinks, aggressive design rules for contact and other back end of line (BEOL) layers continue to drive the need for more effective full chip patterning optimization. Resist top loss is one of the major challenges for 28 nm and below technology nodes, which can lead to post-etch hotspots that are difficult to predict and eventually degrade the process window significantly. To tackle this problem, we used an advanced programmable illuminator (FlexRay) and Tachyon SMO (Source Mask Optimization) platform to make resistaware source optimization possible, and it is proved to greatly improve the imaging contrast, enhance focus and exposure latitude, and minimize resist top loss thus improving the yield.

The influence of optimism on functionality after total hip replacement surgery.

PubMed

Balck, Friedrich; Lippmann, Maike; Jeszenszky, Csilla; Günther, Klaus-Peter; Kirschner, Stephan

2016-08-01

Among other factors, optimism has been shown to significantly influence the course of some diseases (cancer, HIV, coronary heart disease). This study investigated whether optimism of a patient before a total hip replacement can predict the functionality of the lower limbs 3 and 6 months after surgery. A total of 325 patients took part in the study (age: 58.7 years; w: 55%). The functionality was measured with the Western Ontario and McMaster Universities arthrosis index, and optimism with the Life Orientation Test. To analyse the influences of age, gender and optimism, general linear models were calculated. In optimistic patients, functionality improved significantly over time. The study showed a clear influence of dispositional optimism on the recovery after total hip replacement in the first 3 months after surgery. © The Author(s) 2015.

A randomized pilot study of optimization of cardiac resynchronization therapy in sinus rhythm patients using a peak endocardial acceleration sensor vs. standard methods.

PubMed

Ritter, Philippe; Delnoy, Peter Paul H M; Padeletti, Luigi; Lunati, Maurizio; Naegele, Herbert; Borri-Brunetto, Alberto; Silvestre, Jorge

2012-09-01

Non-response rate to cardiac resynchronization therapy (CRT) might be decreased by optimizing device programming. The Clinical Evaluation on Advanced Resynchronization (CLEAR) study aimed to assess the effects of CRT with automatically optimized atrioventricular (AV) and interventricular (VV) delays, based on a Peak Endocardial Acceleration (PEA) signal system. This multicentre, single-blind study randomized patients in a 1 : 1 ratio to CRT optimized either automatically by the PEA-based system, or according to centres' usual practices, mostly by echocardiography. Patients had heart failure (HF) New York Heart Association (NYHA) functional class III/IV, left ventricular ejection fraction (LVEF) <35%, QRS duration >150 or >120 ms with mechanical dyssynchrony. Follow-up was 1 year. The primary endpoint was the proportion of patients who improved their condition at 1 year, based on a composite of all-cause death, HF hospitalizations, NYHA class, and quality of life. In all, 268 patients in sinus rhythm (63% men; mean age: 73.1 ± 9.9 years; mean NYHA: 3.0 ± 0.3; mean LVEF: 27.1 ± 8.1%; and mean QRS duration: 160.1 ± 22.0 ms) were included and 238 patients were randomized, 123 to PEA and 115 to the control group. At 1 year, 76% of patients assigned to PEA were classified as improved, vs. 62% in the control group (P= 0.0285). The percentage of patients with improved NYHA class was significantly (P= 0.0020) higher in the PEA group than in controls. Fatal and non-fatal adverse events were evenly distributed between the groups. PEA-based optimization of CRT in HF patients significantly increased the proportion of patients who improved with therapy, mainly through improved NYHA class, after 1 year of follow-up.

Propulsion system-flight control integration and optimization: Flight evaluation and technology transition

NASA Technical Reports Server (NTRS)

Burcham, Frank W., Jr.; Gilyard, Glenn B.; Myers, Lawrence P.

1990-01-01

Integration of propulsion and flight control systems and their optimization offers significant performance improvements. Research programs were conducted which have developed new propulsion and flight control integration concepts, implemented designs on high-performance airplanes, demonstrated these designs in flight, and measured the performance improvements. These programs, first on the YF-12 airplane, and later on the F-15, demonstrated increased thrust, reduced fuel consumption, increased engine life, and improved airplane performance; with improvements in the 5 to 10 percent range achieved with integration and with no changes to hardware. The design, software and hardware developments, and testing requirements were shown to be practical.

An energy-based perturbation and a taboo strategy for improving the searching ability of stochastic structural optimization methods

NASA Astrophysics Data System (ADS)

Cheng, Longjiu; Cai, Wensheng; Shao, Xueguang

2005-03-01

An energy-based perturbation and a new idea of taboo strategy are proposed for structural optimization and applied in a benchmark problem, i.e., the optimization of Lennard-Jones (LJ) clusters. It is proved that the energy-based perturbation is much better than the traditional random perturbation both in convergence speed and searching ability when it is combined with a simple greedy method. By tabooing the most wide-spread funnel instead of the visited solutions, the hit rate of other funnels can be significantly improved. Global minima of (LJ) clusters up to 200 atoms are found with high efficiency.

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

PubMed

Yi, Xinzhu; Bayen, Stéphane; Kelly, Barry C; Li, Xu; Zhou, Zhi

2015-12-01

A solid-phase extraction/liquid chromatography/electrospray ionization/multi-stage mass spectrometry (SPE-LC-ESI-MS/MS) method was optimized in this study for sensitive and simultaneous detection of multiple antibiotics in urban surface waters and soils. Among the seven classes of tested antibiotics, extraction efficiencies of macrolides, lincosamide, chloramphenicol, and polyether antibiotics were significantly improved under optimized sample extraction pH. Instead of only using acidic extraction in many existing studies, the results indicated that antibiotics with low pK a values (<7) were extracted more efficiently under acidic conditions and antibiotics with high pK a values (>7) were extracted more efficiently under neutral conditions. The effects of pH were more obvious on polar compounds than those on non-polar compounds. Optimization of extraction pH resulted in significantly improved sample recovery and better detection limits. Compared with reported values in the literature, the average reduction of minimal detection limits obtained in this study was 87.6% in surface waters (0.06-2.28 ng/L) and 67.1% in soils (0.01-18.16 ng/g dry wt). This method was subsequently applied to detect antibiotics in environmental samples in a heavily populated urban city, and macrolides, sulfonamides, and lincomycin were frequently detected. Antibiotics with highest detected concentrations were sulfamethazine (82.5 ng/L) in surface waters and erythromycin (6.6 ng/g dry wt) in soils. The optimized sample extraction strategy can be used to improve the detection of a variety of antibiotics in environmental surface waters and soils.

Efficiency improvement of GaN-on-silicon thin-film light-emitting diodes with optimized via-like n-electrodes

NASA Astrophysics Data System (ADS)

Feng, Bo; Deng, Biao; Fu, Yi; Liu, Le Gong; Li, Zeng Cheng; Feng, Mei Xin; Zhao, Han Min; Sun, Qian

2017-07-01

This work reports a significant improvement in efficiency by optimizing the via-like n-electrode architecture design of a GaN-based thin-film LED grown on a 6-inch silicon substrate. The external quantum efficiency of the as-fabricated 1.1 mm × 1.1 mm via-thin-film LED chip at 350 mA was increased by 11.3% compared to that of a vertical thin-film LED chip with a conventional finger-like n-electrode. Detailed analysis of encapsulation gain and false color emission patterns illustrated that the significantly improved LED performance was due to enhanced light extraction efficiency and more uniform current spreading, both of which can be attributed to the optimized via-thin-film chip structure. Minimizing the light loss at the periphery of the Ag mirror was demonstrated to be a critical factor for improving light extraction, rather than simply replacing the finger-like n-electrodes with via-like ones. After encapsulation, the median blue lamp power and the wall-plug efficiency of the via-thin-film LED at 350 mA reached 659 mW and 63.7%, respectively.

SU-D-BRB-02: Combining a Commercial Autoplanning Engine with Database Dose Predictions to Further Improve Plan Quality

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

Robertson, SP; Moore, JA; Hui, X

Purpose: Database dose predictions and a commercial autoplanning engine both improve treatment plan quality in different but complimentary ways. The combination of these planning techniques is hypothesized to further improve plan quality. Methods: Four treatment plans were generated for each of 10 head and neck (HN) and 10 prostate cancer patients, including Plan-A: traditional IMRT optimization using clinically relevant default objectives; Plan-B: traditional IMRT optimization using database dose predictions; Plan-C: autoplanning using default objectives; and Plan-D: autoplanning using database dose predictions. One optimization was used for each planning method. Dose distributions were normalized to 95% of the planning target volumemore » (prostate: 8000 cGy; HN: 7000 cGy). Objectives used in plan optimization and analysis were the larynx (25%, 50%, 90%), left and right parotid glands (50%, 85%), spinal cord (0%, 50%), rectum and bladder (0%, 20%, 50%, 80%), and left and right femoral heads (0%, 70%). Results: All objectives except larynx 25% and 50% resulted in statistically significant differences between plans (Friedman’s χ{sup 2} ≥ 11.2; p ≤ 0.011). Maximum dose to the rectum (Plans A-D: 8328, 8395, 8489, 8537 cGy) and bladder (Plans A-D: 8403, 8448, 8527, 8569 cGy) were significantly increased. All other significant differences reflected a decrease in dose. Plans B-D were significantly different from Plan-A for 3, 17, and 19 objectives, respectively. Plans C-D were also significantly different from Plan-B for 8 and 13 objectives, respectively. In one case (cord 50%), Plan-D provided significantly lower dose than plan C (p = 0.003). Conclusion: Combining database dose predictions with a commercial autoplanning engine resulted in significant plan quality differences for the greatest number of objectives. This translated to plan quality improvements in most cases, although special care may be needed for maximum dose constraints. Further evaluation is warranted in a larger cohort across HN, prostate, and other treatment sites. This work is supported by Philips Radiation Oncology Systems.« less

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

PubMed Central

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-01-01

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971

Design and optimization of self-nanoemulsifying drug delivery systems (SNEDDS) for enhanced dissolution of gemfibrozil.

PubMed

Villar, Ana Maria Sierra; Naveros, Beatriz Clares; Campmany, Ana Cristina Calpena; Trenchs, Monserrat Aróztegui; Rocabert, Coloma Barbé; Bellowa, Lyda Halbaut

2012-07-15

Self-nanoemulsifying drug delivery systems of gemfibrozil were developed under Quality by Design approach for improvement of dissolution and oral absorption. Preliminary screening was performed to select proper components combination. Box-Behnken experimental design was employed as statistical tool to optimize the formulation variables, X(1) (Cremophor(®) EL), X(2) (Capmul(®) MCM-C8), and X(3) (lemon essential oil). Systems were assessed for visual characteristics (emulsification efficacy), turbidity, droplet size, polydispersity index and drug release. Different pH media were also assayed for optimization. Following optimization, the values of formulation components (X(1), X(2), and X(3)) were 32.43%, 29.73% and 21.62%, respectively (16.22% of gemfibrozil). Transmission electron microscopy demonstrated spherical droplet morphology. SNEEDS release study was compared to commercial tablets. Optimized SNEDDS formulation of gemfibrozil showed a significant increase in dissolution rate compared to conventional tablets. Both formulations followed Weibull mathematical model release with a significant difference in t(d) parameter in favor of the SNEDDS. Equally amodelistic parameters were calculated being the dissolution efficiency significantly higher for SNEDDS, confirming that the developed SNEDDS formulation was superior to commercial formulation with respect to in vitro dissolution profile. This paper provides an overview of the SNEDDS of the gemfibrozil as a promising alternative to improve oral absorption. Copyright © 2012 Elsevier B.V. All rights reserved.

Recent Improvements to the Copernicus Trajectory Design and Optimization System

NASA Technical Reports Server (NTRS)

Williams, Jacob; Senent, Juan S.; Ocampo, Cesar; Lee, David E.

2012-01-01

Copernicus is a software tool for spacecraft trajectory design and optimization. The latest version (v3.0.1) was released in October 2011. It is available at no cost to NASA centers, government contractors, and organizations with a contractual affiliation with NASA. This paper is a brief overview of the recent development history of Copernicus. An overview of the evolution of the software and a discussion of significant new features and improvements is given, and how the tool is used to design spacecraft missions

Optimization of municipal pressure pumping station layout and sewage pipe network design

NASA Astrophysics Data System (ADS)

Tian, Jiandong; Cheng, Jilin; Gong, Yi

2018-03-01

Accelerated urbanization places extraordinary demands on sewer networks; thus optimization research to improve the design of these systems has practical significance. In this article, a subsystem nonlinear programming model is developed to optimize pumping station layout and sewage pipe network design. The subsystem model is expanded into a large-scale complex nonlinear programming system model to find the minimum total annual cost of the pumping station and network of all pipe segments. A comparative analysis is conducted using the sewage network in Taizhou City, China, as an example. The proposed method demonstrated that significant cost savings could have been realized if the studied system had been optimized using the techniques described in this article. Therefore, the method has practical value for optimizing urban sewage projects and provides a reference for theoretical research on optimization of urban drainage pumping station layouts.

VDLLA: A virtual daddy-long legs optimization

NASA Astrophysics Data System (ADS)

Yaakub, Abdul Razak; Ghathwan, Khalil I.

2016-08-01

Swarm intelligence is a strong optimization algorithm based on a biological behavior of insects or animals. The success of any optimization algorithm is depending on the balance between exploration and exploitation. In this paper, we present a new swarm intelligence algorithm, which is based on daddy long legs spider (VDLLA) as a new optimization algorithm with virtual behavior. In VDLLA, each agent (spider) has nine positions which represent the legs of spider and each position represent one solution. The proposed VDLLA is tested on four standard functions using average fitness, Medium fitness and standard deviation. The results of proposed VDLLA have been compared against Particle Swarm Optimization (PSO), Differential Evolution (DE) and Bat Inspired Algorithm (BA). Additionally, the T-Test has been conducted to show the significant deference between our proposed and other algorithms. VDLLA showed very promising results on benchmark test functions for unconstrained optimization problems and also significantly improved the original swarm algorithms.

Method of freezing living cells and tissues with improved subsequent survival

DOEpatents

Senkan, Selim M.; Hirsch, Gerald P.

1980-01-01

This invention relates to an improved method for freezing red blood cells, ther living cells, or tissues with improved subsequent survival, wherein constant-volume freezing is utilized that results in significantly improved survival compared with constant-pressure freezing; optimization is attainable through the use of different vessel geometries, cooling baths and warming baths, and sample concentrations.

Optimization of Materials and Interfaces for Spintronic Devices

NASA Astrophysics Data System (ADS)

Clark, Billy

In recent years' Spintronic devices have drawn a significant amount of research attention. This interest comes in large part from their ability to enable interesting and new technology such as Spin Torque Transfer Random Access Memory or improve existing technology such as High Signal Read Heads for Hard Disk Drives. For the former we worked on optimizing and improving magnetic tunnel junctions by optimizing their thermal stability by using Ta insertion layers in the free layer. We further tried to simplify the design of the MTJ stack by attempting to replace the Co/Pd multilayer with CoPd alloy. In this dissertation, we detail its development and examine the switching characteristics. Lastly we look at a highly spin polarized material, Fe2MnGe, for optimizing Hard Drive Disk read heads.

Improvement of electroporation to deliver plasmid DNA into dental follicle cells

PubMed Central

Yao, Shaomian; Rana, Samir; Liu, Dawen; Wise, Gary E.

2010-01-01

Electroporation DNA transfer is a simple and versatile approach to deliver genes. To develop an optimal electroporation protocol to deliver DNA into cells, we conducted square wave electroporation experiments with using rat dental follicle cells as follows: 1) the cells were electroporated at different electric field strengths with lac Z plasmid; 2) plasmid concentrations were tested to determine the optimal doses; 3) various concentrations of bovine serum albumin or fetal bovine serum were added to the pulsing buffer; and, 4) the pulsing durations were studied to determine the optimal duration. These experiments indicated that the optimal electroporation electric field strength was 375 V/cm, and that plasmid concentrations greater than 0.18 μg/μl were required to achieve high transfection efficiency. BSA or FBS in the pulsing buffer significantly improved cell survival and increased the number of transfected cells. The optimal pulsing duration was in the range of 45 to 120 milliseconds (ms) at 375 V/cm. Thus, an improved electroporation protocol was established by optimizing the above parameters. In turn, this electroporation protocol can be used to deliver DNA into dental follicle cells to study the roles of candidate genes in regulating tooth eruption. PMID:19830717

Optimally stopped variational quantum algorithms

NASA Astrophysics Data System (ADS)

Vinci, Walter; Shabani, Alireza

2018-04-01

Quantum processors promise a paradigm shift in high-performance computing which needs to be assessed by accurate benchmarking measures. In this article, we introduce a benchmark for the variational quantum algorithm (VQA), recently proposed as a heuristic algorithm for small-scale quantum processors. In VQA, a classical optimization algorithm guides the processor's quantum dynamics to yield the best solution for a given problem. A complete assessment of the scalability and competitiveness of VQA should take into account both the quality and the time of dynamics optimization. The method of optimal stopping, employed here, provides such an assessment by explicitly including time as a cost factor. Here, we showcase this measure for benchmarking VQA as a solver for some quadratic unconstrained binary optimization. Moreover, we show that a better choice for the cost function of the classical routine can significantly improve the performance of the VQA algorithm and even improve its scaling properties.

Interrelations of stress, optimism and control in older people's psychological adjustment.

PubMed

Bretherton, Susan Jane; McLean, Louise Anne

2015-06-01

To investigate the influence of perceived stress, optimism and perceived control of internal states on the psychological adjustment of older adults. The sample consisted of 212 older adults, aged between 58 and 103 (M = 80.42 years, SD = 7.31 years), living primarily in retirement villages in Melbourne, Victoria. Participants completed the Perceived Stress Scale, Life Orientation Test-Revised, Perceived Control of Internal States Scale and the World Health Organisation Quality of Life-Bref. Optimism significantly mediated the relationship between older people's perceived stress and psychological health, and perceived control of internal states mediated the relationships among stress, optimism and psychological health. The variables explained 49% of the variance in older people's psychological adjustment. It is suggested that strategies to improve optimism and perceived control may improve the psychological adjustment of older people struggling to adapt to life's stressors. © 2014 ACOTA.

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

NASA Astrophysics Data System (ADS)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

Toward an optimal online checkpoint solution under a two-level HPC checkpoint model

DOE PAGES

Di, Sheng; Robert, Yves; Vivien, Frederic; ...

2016-03-29

The traditional single-level checkpointing method suffers from significant overhead on large-scale platforms. Hence, multilevel checkpointing protocols have been studied extensively in recent years. The multilevel checkpoint approach allows different levels of checkpoints to be set (each with different checkpoint overheads and recovery abilities), in order to further improve the fault tolerance performance of extreme-scale HPC applications. How to optimize the checkpoint intervals for each level, however, is an extremely difficult problem. In this paper, we construct an easy-to-use two-level checkpoint model. Checkpoint level 1 deals with errors with low checkpoint/recovery overheads such as transient memory errors, while checkpoint level 2more » deals with hardware crashes such as node failures. Compared with previous optimization work, our new optimal checkpoint solution offers two improvements: (1) it is an online solution without requiring knowledge of the job length in advance, and (2) it shows that periodic patterns are optimal and determines the best pattern. We evaluate the proposed solution and compare it with the most up-to-date related approaches on an extreme-scale simulation testbed constructed based on a real HPC application execution. Simulation results show that our proposed solution outperforms other optimized solutions and can improve the performance significantly in some cases. Specifically, with the new solution the wall-clock time can be reduced by up to 25.3% over that of other state-of-the-art approaches. Lastly, a brute-force comparison with all possible patterns shows that our solution is always within 1% of the best pattern in the experiments.« less

Optimization of capillary zone electrophoresis for charge heterogeneity testing of biopharmaceuticals using enhanced method development principles.

PubMed

Moritz, Bernd; Locatelli, Valentina; Niess, Michele; Bathke, Andrea; Kiessig, Steffen; Entler, Barbara; Finkler, Christof; Wegele, Harald; Stracke, Jan

2017-12-01

CZE is a well-established technique for charge heterogeneity testing of biopharmaceuticals. It is based on the differences between the ratios of net charge and hydrodynamic radius. In an extensive intercompany study, it was recently shown that CZE is very robust and can be easily implemented in labs that did not perform it before. However, individual characteristics of some examined proteins resulted in suboptimal resolution. Therefore, enhanced method development principles were applied here to investigate possibilities for further method optimization. For this purpose, a high number of different method parameters was evaluated with the aim to improve CZE separation. For the relevant parameters, design of experiments (DoE) models were generated and optimized in several ways for different sets of responses like resolution, peak width and number of peaks. In spite of product specific DoE optimization it was found that the resulting combination of optimized parameters did result in significant improvement of separation for 13 out of 16 different antibodies and other molecule formats. These results clearly demonstrate generic applicability of the optimized CZE method. Adaptation to individual molecular properties may sometimes still be required in order to achieve optimal separation but the set screws discussed in this study [mainly pH, identity of the polymer additive (HPC versus HPMC) and the concentrations of additives like acetonitrile, butanolamine and TETA] are expected to significantly reduce the effort for specific optimization. 2017 The Authors. Electrophoresis published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimizing The DSSC Fabrication Process Using Lean Six Sigma

NASA Astrophysics Data System (ADS)

Fauss, Brian

Alternative energy technologies must become more cost effective to achieve grid parity with fossil fuels. Dye sensitized solar cells (DSSCs) are an innovative third generation photovoltaic technology, which is demonstrating tremendous potential to become a revolutionary technology due to recent breakthroughs in cost of fabrication. The study here focused on quality improvement measures undertaken to improve fabrication of DSSCs and enhance process efficiency and effectiveness. Several quality improvement methods were implemented to optimize the seven step individual DSSC fabrication processes. Lean Manufacturing's 5S method successfully increased efficiency in all of the processes. Six Sigma's DMAIC methodology was used to identify and eliminate each of the root causes of defects in the critical titanium dioxide deposition process. These optimizations resulted with the following significant improvements in the production process: 1. fabrication time of the DSSCs was reduced by 54 %; 2. fabrication procedures were improved to the extent that all critical defects in the process were eliminated; 3. the quantity of functioning DSSCs fabricated was increased from 17 % to 90 %.

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

PubMed

Ping, Bo; Su, Fenzhen; Meng, Yunshan

2016-01-01

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

Thermomechanical treatment for improved neutron irradiation resistance of austenitic alloy (Fe-21Cr-32Ni)

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

L. Tan; J. T. Busby; H. J. M. Chichester

2013-06-01

An optimized thermomechanical treatment (TMT) applied to austenitic alloy 800H (Fe-21Cr-32Ni) had shown significant improvements in corrosion resistance and basic mechanical properties. This study examined its effect on radiation resistance by irradiating both the solution-annealed (SA) and TMT samples at 500 degrees C for 3 dpa. Microstructural characterization using transmission electron microscopy revealed that the radiation-induced Frank loops, voids, and y'-Ni3(Ti,Al) precipitates had similar sizes between the SA and TMT samples. The amounts of radiation-induced defects and more significantly y' precipitates, however, were reduced in the TMT samples. These reductions would approximately reduce by 40.9% the radiation hardening compared tomore » the SA samples. This study indicates that optimized-TMT is an economical approach for effective overall property improvements.« less

How to Improve Academic Optimism? an Inquiry from the Perspective of School Resource and Investment

ERIC Educational Resources Information Center

Wu, Jason Hsinchieh; Sheu, Tian-Ming

2015-01-01

Previous studies have identified many school variables which can have significant effect on academic optimism. However, most of these identified variables are leadership or psychological constructs; thus, it is often too abstract for school administrators to translate into real practice. Therefore, this study adopted the perspective of school…

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

Batchelor, D.B.; Carreras, B.A.; Hirshman, S.P.

Significant progress has been made in the development of new modest-size compact stellarator devices that could test optimization principles for the design of a more attractive reactor. These are 3 and 4 field period low-aspect-ratio quasi-omnigenous (QO) stellarators based on an optimization method that targets improved confinement, stability, ease of coil design, low-aspect-ratio, and low bootstrap current.

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.

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

PubMed

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

Improvement of halophilic cellulase production from locally isolated fungal strain.

PubMed

Gunny, Ahmad Anas Nagoor; Arbain, Dachyar; Jamal, Parveen; Gumba, Rizo Edwin

2015-07-01

Halophilic cellulases from the newly isolated fungus, Aspergillus terreus UniMAP AA-6 were found to be useful for in situ saccharification of ionic liquids treated lignocelluloses. Efforts have been taken to improve the enzyme production through statistical optimization approach namely Plackett-Burman design and the Face Centered Central Composite Design (FCCCD). Plackett-Burman experimental design was used to screen the medium components and process conditions. It was found that carboxymethylcellulose (CMC), FeSO4·7H2O, NaCl, MgSO4·7H2O, peptone, agitation speed and inoculum size significantly influence the production of halophilic cellulase. On the other hand, KH2PO4, KOH, yeast extract and temperature had a negative effect on enzyme production. Further optimization through FCCCD revealed that the optimization approach improved halophilic cellulase production from 0.029 U/ml to 0.0625 U/ml, which was approximately 2.2-times greater than before optimization.

Improvement of halophilic cellulase production from locally isolated fungal strain

PubMed Central

Gunny, Ahmad Anas Nagoor; Arbain, Dachyar; Jamal, Parveen; Gumba, Rizo Edwin

2014-01-01

Halophilic cellulases from the newly isolated fungus, Aspergillus terreus UniMAP AA-6 were found to be useful for in situ saccharification of ionic liquids treated lignocelluloses. Efforts have been taken to improve the enzyme production through statistical optimization approach namely Plackett–Burman design and the Face Centered Central Composite Design (FCCCD). Plackett–Burman experimental design was used to screen the medium components and process conditions. It was found that carboxymethylcellulose (CMC), FeSO4·7H2O, NaCl, MgSO4·7H2O, peptone, agitation speed and inoculum size significantly influence the production of halophilic cellulase. On the other hand, KH2PO4, KOH, yeast extract and temperature had a negative effect on enzyme production. Further optimization through FCCCD revealed that the optimization approach improved halophilic cellulase production from 0.029 U/ml to 0.0625 U/ml, which was approximately 2.2-times greater than before optimization. PMID:26150755

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

PubMed

Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

2017-07-19

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

WE-DE-201-01: BEST IN PHYSICS (THERAPY): A Fast Multi-Target Inverse Treatment Planning Strategy Optimizing Dosimetric Measures for High-Dose-Rate (HDR) Brachytherapy

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

Guthier, C; University Medical Center Mannheim, Mannheim; Harvard Medical School, Boston, MA

Purpose: Inverse treatment planning (ITP) for interstitial HDR brachytherapy of gynecologic cancers seeks to maximize coverage of the clinical target volumes (tumor and vagina) while respecting dose-volume-histogram related dosimetric measures (DMs) for organs at risk (OARs). Commercially available ITP tools do not support DM-based planning because it is computationally too expensive to solve. In this study we present a novel approach that allows fast ITP for gynecologic cancers based on DMs for the first time. Methods: This novel strategy is an optimization model based on a smooth DM-based objective function. The smooth approximation is achieved by utilizing a logistic functionmore » for the evaluation of DMs. The resulting nonconvex and constrained optimization problem is then optimized with a BFGS algorithm. The model was evaluated using the implant geometry extracted from 20 patient treatment plans under an IRB-approved retrospective study. For each plan, the final DMs were evaluated and compared to the original clinical plans. The CTVs were the contoured tumor volume and the contoured surface of the vagina. Statistical significance was evaluated with a one-sided paired Wilcoxon signed-rank test. Results: As did the clinical plans, all generated plans fulfilled the defined DMs for OARs. The proposed strategy showed a statistically significant improvement (p<0.001) in coverage of the tumor and vagina, with absolute improvements of related DMs of (6.9 +/− 7.9)% and (28.2 +/− 12.0)%, respectively. This was achieved with a statistically significant (p<0.01) decrease of the high-dose-related DM for the tumor. The runtime of the optimization was (2.3 +/− 2.0) seconds. Conclusion: We demonstrated using clinical data that our novel approach allows rapid DM-based optimization with improved coverage of CTVs with fewer hot spots. Being up to three orders of magnitude faster than the current clinical practice, the method dramatically shortens planning time.« less

Optimal redistribution of an urban air quality monitoring network using atmospheric dispersion model and genetic algorithm

NASA Astrophysics Data System (ADS)

Hao, Yufang; Xie, Shaodong

2018-03-01

Air quality monitoring networks play a significant role in identifying the spatiotemporal patterns of air pollution, and they need to be deployed efficiently, with a minimum number of sites. The revision and optimal adjustment of existing monitoring networks is crucial for cities that have undergone rapid urban expansion and experience temporal variations in pollution patterns. The approach based on the Weather Research and Forecasting-California PUFF (WRF-CALPUFF) model and genetic algorithm (GA) was developed to design an optimal monitoring network. The maximization of coverage with minimum overlap and the ability to detect violations of standards were developed as the design objectives for redistributed networks. The non-dominated sorting genetic algorithm was applied to optimize the network size and site locations simultaneously for Shijiazhuang city, one of the most polluted cities in China. The assessment on the current network identified the insufficient spatial coverage of SO2 and NO2 monitoring for the expanding city. The optimization results showed that significant improvements were achieved in multiple objectives by redistributing the original network. Efficient coverage of the resulting designs improved to 60.99% and 76.06% of the urban area for SO2 and NO2, respectively. The redistributing design for multi-pollutant including 8 sites was also proposed, with the spatial representation covered 52.30% of the urban area and the overlapped areas decreased by 85.87% compared with the original network. The abilities to detect violations of standards were not improved as much as the other two objectives due to the conflicting nature between the multiple objectives. Additionally, the results demonstrated that the algorithm was slightly sensitive to the parameter settings, with the number of generations presented the most significant effect. Overall, our study presents an effective and feasible procedure for air quality network optimization at a city scale.

Experimental and Numerical Optimization of a High-Lift System to Improve Low-Speed Performance, Stability, and Control of an Arrow-Wing Supersonic Transport

NASA Technical Reports Server (NTRS)

Hahne, David E.; Glaab, Louis J.

1999-01-01

An investigation was performed to evaluate leading-and trailing-edge flap deflections for optimal aerodynamic performance of a High-Speed Civil Transport concept during takeoff and approach-to-landing conditions. The configuration used for this study was designed by the Douglas Aircraft Company during the 1970's. A 0.1-scale model of this configuration was tested in the Langley 30- by 60-Foot Tunnel with both the original leading-edge flap system and a new leading-edge flap system, which was designed with modem computational flow analysis and optimization tools. Leading-and trailing-edge flap deflections were generated for the original and modified leading-edge flap systems with the computational flow analysis and optimization tools. Although wind tunnel data indicated improvements in aerodynamic performance for the analytically derived flap deflections for both leading-edge flap systems, perturbations of the analytically derived leading-edge flap deflections yielded significant additional improvements in aerodynamic performance. In addition to the aerodynamic performance optimization testing, stability and control data were also obtained. An evaluation of the crosswind landing capability of the aircraft configuration revealed that insufficient lateral control existed as a result of high levels of lateral stability. Deflection of the leading-and trailing-edge flaps improved the crosswind landing capability of the vehicle considerably; however, additional improvements are required.

Biventricular pacemaker optimization guided by comprehensive echocardiography-preliminary observations regarding the effects on systolic and diastolic ventricular function and third heart sound.

PubMed

Taha, Nima; Zhang, Jing; Ranjan, Rupesh; Daneshvar, Samuel; Castillo, Edilzar; Guillen, Elizabeth; Montoya, Martha C; Velasquez, Giovanna; Naqvi, Tasneem Z

2010-08-01

Doppler echocardiography of mitral inflow or aortic outflow or both has been validated and advocated to guide biventricular (Biv) pacemaker optimization. A comprehensive and tailored Doppler echocardiographic evaluation may be required in patients with heart failure to assist with Biv pacemaker optimization. The third heart sound (S(3)), an acoustic cardiographic parameter, has been demonstrated to be a highly specific finding for hemodynamic evaluation in patients with heart failure. The aims of this study were to evaluate the use of comprehensive Doppler echocardiography as a guide during Biv pacemaker optimization in patients after cardiac resynchronization therapy and to evaluate the feasibility of S(3) intensity to be a cost-efficient parameter for Biv pacemaker optimization compared with Doppler echocardiography. Comprehensive Doppler echocardiographic evaluations were performed during Biv pacemaker optimization in 44 patients referred for pacemaker optimization (mean age, 71 + or - 12 years; mean left ventricular ejection fraction, 34 + or - 11%). Blinded assessment of S(3) intensity was performed simultaneously using acoustic cardiography. The correlation and improvement in cardiac hemodynamics were analyzed between the methods. Echocardiographically guided optimization resulted in significant improvements in the left ventricular outflow velocity-time integral (15.92 + or - 4.77 to 18.51 + or - 5.19 cm, P < .001), ejection time (278 + or - 40 to 293 + or - 40 ms, P < .001), myocardial performance index (0.57 + or - 0.19 to 0.44 + or - 0.14, P < .002), and peak pulmonary artery systolic pressure (42 + or - 13 to 36 + or - 11 mm Hg, P < .04) and decreased S(3) intensity from 4.81 + or - 1.84 at baseline to 3.96 + or - 1.22 after optimization (P < .02) for the overall study group and from 6.63 + or - 1.37 to 4.85 + or - 1.13 (P < .001) in the 18 patients with baseline S(3) intensity > 5.0. The correlation between echocardiographic and acoustic cardiographic S(3) intensity for optimal atrioventricular delay was 0.86 (P < .001) and for optimal interventricular delay was 0.64 (P < .001). Optimal atrioventricular delay was identical by echocardiographic and acoustic cardiographic S(3) intensity in 56%, and optimal interventricular delay was identical in 75% of patients. Pacemakers were permanently programmed on the basis of echocardiographic evaluation. In 35 patients available for follow up, the mean New York Heart Association class reduced from 2.55 + or - 0.81 to 1.77 + or - 0.90 (P < .001) and the mean quality-of-life score as assessed by Minnesota Living With Heart Failure Questionnaire improved from 45 + or - 28 to 32 + or - 28 (P = .08) at 2.5 + or - 2.1 months. Comprehensive echocardiographically guided Biv pacemaker optimization produces significant improvement in Doppler echocardiographic hemodynamics, a reduction in S(3) intensity, and an improvement in functional class in patients after cardiac resynchronization therapy. Copyright 2010 American Society of Echocardiography. Published by Mosby, Inc. All rights reserved.

Subjective audio quality evaluation of embedded-optimization-based distortion precompensation algorithms.

PubMed

Defraene, Bruno; van Waterschoot, Toon; Diehl, Moritz; Moonen, Marc

2016-07-01

Subjective audio quality evaluation experiments have been conducted to assess the performance of embedded-optimization-based precompensation algorithms for mitigating perceptible linear and nonlinear distortion in audio signals. It is concluded with statistical significance that the perceived audio quality is improved by applying an embedded-optimization-based precompensation algorithm, both in case (i) nonlinear distortion and (ii) a combination of linear and nonlinear distortion is present. Moreover, a significant positive correlation is reported between the collected subjective and objective PEAQ audio quality scores, supporting the validity of using PEAQ to predict the impact of linear and nonlinear distortion on the perceived audio quality.

People efficiently explore the solution space of the computationally intractable traveling salesman problem to find near-optimal tours.

PubMed

Acuña, Daniel E; Parada, Víctor

2010-07-29

Humans need to solve computationally intractable problems such as visual search, categorization, and simultaneous learning and acting, yet an increasing body of evidence suggests that their solutions to instantiations of these problems are near optimal. Computational complexity advances an explanation to this apparent paradox: (1) only a small portion of instances of such problems are actually hard, and (2) successful heuristics exploit structural properties of the typical instance to selectively improve parts that are likely to be sub-optimal. We hypothesize that these two ideas largely account for the good performance of humans on computationally hard problems. We tested part of this hypothesis by studying the solutions of 28 participants to 28 instances of the Euclidean Traveling Salesman Problem (TSP). Participants were provided feedback on the cost of their solutions and were allowed unlimited solution attempts (trials). We found a significant improvement between the first and last trials and that solutions are significantly different from random tours that follow the convex hull and do not have self-crossings. More importantly, we found that participants modified their current better solutions in such a way that edges belonging to the optimal solution ("good" edges) were significantly more likely to stay than other edges ("bad" edges), a hallmark of structural exploitation. We found, however, that more trials harmed the participants' ability to tell good from bad edges, suggesting that after too many trials the participants "ran out of ideas." In sum, we provide the first demonstration of significant performance improvement on the TSP under repetition and feedback and evidence that human problem-solving may exploit the structure of hard problems paralleling behavior of state-of-the-art heuristics.

People Efficiently Explore the Solution Space of the Computationally Intractable Traveling Salesman Problem to Find Near-Optimal Tours

PubMed Central

Acuña, Daniel E.; Parada, Víctor

2010-01-01

Humans need to solve computationally intractable problems such as visual search, categorization, and simultaneous learning and acting, yet an increasing body of evidence suggests that their solutions to instantiations of these problems are near optimal. Computational complexity advances an explanation to this apparent paradox: (1) only a small portion of instances of such problems are actually hard, and (2) successful heuristics exploit structural properties of the typical instance to selectively improve parts that are likely to be sub-optimal. We hypothesize that these two ideas largely account for the good performance of humans on computationally hard problems. We tested part of this hypothesis by studying the solutions of 28 participants to 28 instances of the Euclidean Traveling Salesman Problem (TSP). Participants were provided feedback on the cost of their solutions and were allowed unlimited solution attempts (trials). We found a significant improvement between the first and last trials and that solutions are significantly different from random tours that follow the convex hull and do not have self-crossings. More importantly, we found that participants modified their current better solutions in such a way that edges belonging to the optimal solution (“good” edges) were significantly more likely to stay than other edges (“bad” edges), a hallmark of structural exploitation. We found, however, that more trials harmed the participants' ability to tell good from bad edges, suggesting that after too many trials the participants “ran out of ideas.” In sum, we provide the first demonstration of significant performance improvement on the TSP under repetition and feedback and evidence that human problem-solving may exploit the structure of hard problems paralleling behavior of state-of-the-art heuristics. PMID:20686597

Simultaneous optimization of micro-heliostat geometry and field layout using a genetic algorithm

NASA Astrophysics Data System (ADS)

Lazardjani, Mani Yousefpour; Kronhardt, Valentina; Dikta, Gerhard; Göttsche, Joachim

2016-05-01

A new optimization tool for micro-heliostat (MH) geometry and field layout is presented. The method intends simultaneous performance improvement and cost reduction through iteration of heliostat geometry and field layout parameters. This tool was developed primarily for the optimization of a novel micro-heliostat concept, which was developed at Solar-Institut Jülich (SIJ). However, the underlying approach for the optimization can be used for any heliostat type. During the optimization the performance is calculated using the ray-tracing tool SolCal. The costs of the heliostats are calculated by use of a detailed cost function. A genetic algorithm is used to change heliostat geometry and field layout in an iterative process. Starting from an initial setup, the optimization tool generates several configurations of heliostat geometries and field layouts. For each configuration a cost-performance ratio is calculated. Based on that, the best geometry and field layout can be selected in each optimization step. In order to find the best configuration, this step is repeated until no significant improvement in the results is observed.

Multi-objective optimization in quantum parameter estimation

NASA Astrophysics Data System (ADS)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

Application of Genetic Algorithm and Particle Swarm Optimization techniques for improved image steganography systems

NASA Astrophysics Data System (ADS)

Jude Hemanth, Duraisamy; Umamaheswari, Subramaniyan; Popescu, Daniela Elena; Naaji, Antoanela

2016-01-01

Image steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT) and Finite Ridgelet Transform (FRIT) are used in combination with GA and PSO to improve the efficiency of the image steganography system.

Efficient amplitude-modulated pulses for triple- to single-quantum coherence conversion in MQMAS NMR.

PubMed

Colaux, Henri; Dawson, Daniel M; Ashbrook, Sharon E

2014-08-07

The conversion between multiple- and single-quantum coherences is integral to many nuclear magnetic resonance (NMR) experiments of quadrupolar nuclei. This conversion is relatively inefficient when effected by a single pulse, and many composite pulse schemes have been developed to improve this efficiency. To provide the maximum improvement, such schemes typically require time-consuming experimental optimization. Here, we demonstrate an approach for generating amplitude-modulated pulses to enhance the efficiency of the triple- to single-quantum conversion. The optimization is performed using the SIMPSON and MATLAB packages and results in efficient pulses that can be used without experimental reoptimisation. Most significant signal enhancements are obtained when good estimates of the inherent radio-frequency nutation rate and the magnitude of the quadrupolar coupling are used as input to the optimization, but the pulses appear robust to reasonable variations in either parameter, producing significant enhancements compared to a single-pulse conversion, and also comparable or improved efficiency over other commonly used approaches. In all cases, the ease of implementation of our method is advantageous, particularly for cases with low sensitivity, where the improvement is most needed (e.g., low gyromagnetic ratio or high quadrupolar coupling). Our approach offers the potential to routinely improve the sensitivity of high-resolution NMR spectra of nuclei and systems that would, perhaps, otherwise be deemed "too challenging".

Efficient Amplitude-Modulated Pulses for Triple- to Single-Quantum Coherence Conversion in MQMAS NMR

PubMed Central

2014-01-01

The conversion between multiple- and single-quantum coherences is integral to many nuclear magnetic resonance (NMR) experiments of quadrupolar nuclei. This conversion is relatively inefficient when effected by a single pulse, and many composite pulse schemes have been developed to improve this efficiency. To provide the maximum improvement, such schemes typically require time-consuming experimental optimization. Here, we demonstrate an approach for generating amplitude-modulated pulses to enhance the efficiency of the triple- to single-quantum conversion. The optimization is performed using the SIMPSON and MATLAB packages and results in efficient pulses that can be used without experimental reoptimisation. Most significant signal enhancements are obtained when good estimates of the inherent radio-frequency nutation rate and the magnitude of the quadrupolar coupling are used as input to the optimization, but the pulses appear robust to reasonable variations in either parameter, producing significant enhancements compared to a single-pulse conversion, and also comparable or improved efficiency over other commonly used approaches. In all cases, the ease of implementation of our method is advantageous, particularly for cases with low sensitivity, where the improvement is most needed (e.g., low gyromagnetic ratio or high quadrupolar coupling). Our approach offers the potential to routinely improve the sensitivity of high-resolution NMR spectra of nuclei and systems that would, perhaps, otherwise be deemed “too challenging”. PMID:25047226

Improving Emergency Department flow through optimized bed utilization

PubMed Central

Chartier, Lucas Brien; Simoes, Licinia; Kuipers, Meredith; McGovern, Barb

2016-01-01

Over the last decade, patient volumes in the emergency department (ED) have grown disproportionately compared to the increase in staffing and resources at the Toronto Western Hospital, an academic tertiary care centre in Toronto, Canada. The resultant congestion has spilled over to the ED waiting room, where medically undifferentiated and potentially unstable patients must wait until a bed becomes available. The aim of this quality improvement project was to decrease the 90th percentile of wait time between triage and bed assignment (time-to-bed) by half, from 120 to 60 minutes, for our highest acuity patients. We engaged key stakeholders to identify barriers and potential strategies to achieve optimal flow of patients into the ED. We first identified multiple flow-interrupting challenges, including operational bottlenecks and cultural issues. We then generated change ideas to address two main underlying causes of ED congestion: unnecessary patient utilization of ED beds and communication breakdown causing bed turnaround delays. We subsequently performed seven tests of change through sequential plan-do-study-act (PDSA) cycles. The most significant gains were made by improving communication strategies: small gains were achieved through the optimization of in-house digital information management systems, while significant improvements were achieved through the implementation of a low-tech direct contact mechanism (a two-way radio or walkie-talkie). In the post-intervention phase, time-to-bed for the 90th percentile of high-acuity patients decreased from 120 minutes to 66 minutes, with special cause variation showing a significant shift in the weekly measurements. PMID:27752312

Improving Emergency Department flow through optimized bed utilization.

PubMed

Chartier, Lucas Brien; Simoes, Licinia; Kuipers, Meredith; McGovern, Barb

2016-01-01

Over the last decade, patient volumes in the emergency department (ED) have grown disproportionately compared to the increase in staffing and resources at the Toronto Western Hospital, an academic tertiary care centre in Toronto, Canada. The resultant congestion has spilled over to the ED waiting room, where medically undifferentiated and potentially unstable patients must wait until a bed becomes available. The aim of this quality improvement project was to decrease the 90th percentile of wait time between triage and bed assignment (time-to-bed) by half, from 120 to 60 minutes, for our highest acuity patients. We engaged key stakeholders to identify barriers and potential strategies to achieve optimal flow of patients into the ED. We first identified multiple flow-interrupting challenges, including operational bottlenecks and cultural issues. We then generated change ideas to address two main underlying causes of ED congestion: unnecessary patient utilization of ED beds and communication breakdown causing bed turnaround delays. We subsequently performed seven tests of change through sequential plan-do-study-act (PDSA) cycles. The most significant gains were made by improving communication strategies: small gains were achieved through the optimization of in-house digital information management systems, while significant improvements were achieved through the implementation of a low-tech direct contact mechanism (a two-way radio or walkie-talkie). In the post-intervention phase, time-to-bed for the 90th percentile of high-acuity patients decreased from 120 minutes to 66 minutes, with special cause variation showing a significant shift in the weekly measurements.

Narrative Performance of Optimal Outcome Children and Adolescents with a History of an Autism Spectrum Disorder (ASD)

ERIC Educational Resources Information Center

Suh, Joyce; Eigsti, Inge-Marie; Naigles, Letitia; Barton, Marianne; Kelley, Elizabeth; Fein, Deborah

2014-01-01

Autism Spectrum Disorders (ASDs) have traditionally been considered a lifelong condition; however, a subset of people makes such significant improvements that they no longer meet diagnostic criteria for an ASD. The current study examines whether these "optimal outcome" (OO) children and adolescents continue to have subtle pragmatic…

MO-FG-CAMPUS-TeP2-05: Optimizing Stereotactic Radiosurgery Treatment of Multiple Brain Metastasis Lesions with Individualized Rotational Arc Trajectories

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

Dong, P; Xing, L; Ma, L

Purpose: Radiosurgery of multiple (n>4) brain metastasis lesions requires 3–4 noncoplanar VMAT arcs with excessively high monitor units and long delivery time. We investigated whether an improved optimization technique would decrease the needed arc numbers and increase the delivery efficiency, while improving or maintaining the plan quality. Methods: The proposed 4pi arc space optimization algorithm consists of two steps: automatic couch angle selection followed by aperture generation for each arc with optimized control points distribution. We use a greedy algorithm to select the couch angles. Starting from a single coplanar arc plan we search through the candidate noncoplanar arcs tomore » pick a single noncoplanar arc that will bring the best plan quality when added into the existing treatment plan. Each time, only one additional noncoplanar arc is considered making the calculation time tractable. This process repeats itself until desired number of arc is reached. The technique is first evaluated in coplanar arc delivery scheme with testing cases and then applied to noncoplanar treatments of a case with 12 brain metastasis lesions. Results: Clinically acceptable plans are created within minutes. For the coplanar testing cases the algorithm yields singlearc plans with better dose distributions than that of two-arc VMAT, simultaneously with a 12–17% reduction in the delivery time and a 14–21% reduction in MUs. For the treatment of 12 brain mets while Paddick conformity indexes of the two plans were comparable the SCG-optimization with 2 arcs (1 noncoplanar and 1 coplanar) significantly improved the conventional VMAT with 3 arcs (2 noncoplanar and 1 coplanar). Specifically V16 V10 and V5 of the brain were reduced by 11%, 11% and 12% respectively. The beam delivery time was shortened by approximately 30%. Conclusion: The proposed 4pi arc space optimization technique promises to significantly reduce the brain toxicity while greatly improving the treatment efficiency.« less

In vitro validation of a shape-optimized fiber-reinforced dental bridge.

PubMed

Chen, YungChung; Li, Haiyan; Fok, Alex

2011-12-01

To improve its mechanical performance, structural optimization had been used in a previous study to obtain an alternative design for a 3-unit inlay-retained fiber-reinforced composite (FRC) dental bridge. In that study, an optimized layout of the FRC substructure had been proposed to minimize stresses in the veneering composite and interfacial stresses between the composite and substructure. The current work aimed to validate in vitro the improved fracture resistance of the optimized design. All samples for the 3-unit inlay-retained FRC dental bridge were made with glass-fibers (FibreKor) as the substructure, surrounded by a veneering composite (GC Gradia). Two different FRC substructure designs were prepared: a conventional (n=20) and an optimized design (n=21). The conventional design was a straight beam linking one proximal box to the other, while the optimized design was a curved beam following the lower outline of the pontic. All samples were loaded to 400N on a universal test machine (MTS 810) with a loading speed of 0.2mm/min. During loading, the force and displacement were recorded. Meanwhile, a two-channel acoustic emission (AE) system was used to monitor the development of cracks during loading. The load-displacement curves of the two groups displayed significant differences. For the conventional design, there were numerous drops in load corresponding to local damage of the sample. For the optimized design, the load curves were much smoother. Cracks were clearly visible on the surface of the conventional group only, and the directions of those cracks were perpendicular to those of the most tensile stresses. Results from the more sensitive AE measurement also showed that the optimized design had, on average, fewer cracking events: 38 versus 2969 in the conventional design. The much lower number of AE events and smoother load-displacement curves indicated that the optimized FRC bridge design had a higher fracture resistance. It is expected that the optimized design will significantly improve the clinical performance of FRC bridges. Copyright © 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Improvements in the order, isotropy and electron density of glypican-1 crystals by controlled dehydration

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

Awad, Wael; Cairo University, Cairo; Svensson Birkedal, Gabriel

The anisotropy of crystals of glypican-1 was significantly reduced by controlled dehydration using the HC1 device, allowing the building of previously disordered parts of the structure. The use of controlled dehydration for improvement of protein crystal diffraction quality is increasing in popularity, although there are still relatively few documented examples of success. A study has been carried out to establish whether controlled dehydration could be used to improve the anisotropy of crystals of the core protein of the human proteoglycan glypican-1. Crystals were subjected to controlled dehydration using the HC1 device. The optimal protocol for dehydration was developed by carefulmore » investigation of the following parameters: dehydration rate, final relative humidity and total incubation time T{sub inc}. Of these, the most important was shown to be T{sub inc}. After dehydration using the optimal protocol the crystals showed significantly reduced anisotropy and improved electron density, allowing the building of previously disordered parts of the structure.« less

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.

Improving Learning Performance Through Rational Resource Allocation

NASA Technical Reports Server (NTRS)

Gratch, J.; Chien, S.; DeJong, G.

1994-01-01

This article shows how rational analysis can be used to minimize learning cost for a general class of statistical learning problems. We discuss the factors that influence learning cost and show that the problem of efficient learning can be cast as a resource optimization problem. Solutions found in this way can be significantly more efficient than the best solutions that do not account for these factors. We introduce a heuristic learning algorithm that approximately solves this optimization problem and document its performance improvements on synthetic and real-world problems.

Hemp-Fiber-Reinforced Unsaturated Polyester Composites: Optimization of Processing and Improvement of Interfacial Adhesion

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

Qui, Renhui; Ren, Xiaofeng; Fifield, Leonard S.

2011-02-25

The processing variables for making hemp-fiber-reinforced unsaturated polyester (UPE) composites were optimized through orthogonal experiments. It was found that the usage of initiator, methyl ethyl ketone peroxide, had the most significant effect on the tensile strength of the composites. The treatment of hemp fibers with a combination of 1, 6-diisocyanatohexane (DIH) and 2-hydroxylethyl acrylate (HEA) significantly increased tensile strength, flexural modulus of rupture and flexural modulus of elasticity, and water resistance of the resulting hemp-UPE composites. FTIR spectra revealed that DIH and HEA were covalently bonded to hemp fibers. Scanning electronic microscopy graphs of the fractured hemp-UPE composites demonstrated thatmore » treatment of hemp fibers with a combination of DIH and HEA greatly improved the interfacial adhesion between hemp fibers and UPE. The mechanism of improving the interfacial adhesion is proposed.« less

Process Design and Techno-economic Analysis for Materials to Treat Produced Waters.

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

Heimer, Brandon Walter; Paap, Scott M; Sasan, Koroush

Significant quantities of water are produced during enhanced oil recovery making these “produced water” streams attractive candidates for treatment and reuse. However, high concentrations of dissolved silica raise the propensity for fouling. In this paper, we report the design and economic analysis for a new ion exchange process using calcined hydrotalcite (HTC) to remove silica from water. This process improves upon known technologies by minimizing sludge product, reducing process fouling, and lowering energy use. Process modeling outputs included raw material requirements, energy use, and the minimum water treatment price (MWTP). Monte Carlo simulations quantified the impact of uncertainty and variabilitymore » in process inputs on MWTP. These analyses showed that cost can be significantly reduced if the HTC materials are optimized. Specifically, R&D improving HTC reusability, silica binding capacity, and raw material price can reduce MWTP by 40%, 13%, and 20%, respectively. Optimizing geographic deployment further improves cost competitiveness.« less

Integrated multidisciplinary optimization of rotorcraft: A plan for development

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

A prospective comparison of phakic collamer lenses and wavefront-optimized laser-assisted in situ keratomileusis for correction of myopia

PubMed Central

Parkhurst, Gregory D

2016-01-01

Purpose The aim of this study was to evaluate and compare night vision and low-luminance contrast sensitivity (CS) in patients undergoing implantation of phakic collamer lenses or wavefront-optimized laser-assisted in situ keratomileusis (LASIK). Patients and methods This is a nonrandomized, prospective study, in which 48 military personnel were recruited. Rabin Super Vision Test was used to compare the visual acuity and CS of Visian implantable collamer lens (ICL) and LASIK groups under normal and low light conditions, using a filter for simulated vision through night vision goggles. Results Preoperative mean spherical equivalent was −6.10 D in the ICL group and −6.04 D in the LASIK group (P=0.863). Three months postoperatively, super vision acuity (SVa), super vision acuity with (low-luminance) goggles (SVaG), super vision contrast (SVc), and super vision contrast with (low luminance) goggles (SVcG) significantly improved in the ICL and LASIK groups (P<0.001). Mean improvement in SVaG at 3 months postoperatively was statistically significantly greater in the ICL group than in the LASIK group (mean change [logarithm of the minimum angle of resolution, LogMAR]: ICL =−0.134, LASIK =−0.085; P=0.032). Mean improvements in SVc and SVcG were also statistically significantly greater in the ICL group than in the LASIK group (SVc mean change [logarithm of the CS, LogCS]: ICL =0.356, LASIK =0.209; P=0.018 and SVcG mean change [LogCS]: ICL =0.390, LASIK =0.259; P=0.024). Mean improvement in SVa at 3 months was comparable in both groups (P=0.154). Conclusion Simulated night vision improved with both ICL implantation and wavefront-optimized LASIK, but improvements were significantly greater with ICLs. These differences may be important in a military setting and may also affect satisfaction with civilian vision correction. PMID:27418804

A prospective comparison of phakic collamer lenses and wavefront-optimized laser-assisted in situ keratomileusis for correction of myopia.

PubMed

Parkhurst, Gregory D

2016-01-01

The aim of this study was to evaluate and compare night vision and low-luminance contrast sensitivity (CS) in patients undergoing implantation of phakic collamer lenses or wavefront-optimized laser-assisted in situ keratomileusis (LASIK). This is a nonrandomized, prospective study, in which 48 military personnel were recruited. Rabin Super Vision Test was used to compare the visual acuity and CS of Visian implantable collamer lens (ICL) and LASIK groups under normal and low light conditions, using a filter for simulated vision through night vision goggles. Preoperative mean spherical equivalent was -6.10 D in the ICL group and -6.04 D in the LASIK group (P=0.863). Three months postoperatively, super vision acuity (SVa), super vision acuity with (low-luminance) goggles (SVaG), super vision contrast (SVc), and super vision contrast with (low luminance) goggles (SVcG) significantly improved in the ICL and LASIK groups (P<0.001). Mean improvement in SVaG at 3 months postoperatively was statistically significantly greater in the ICL group than in the LASIK group (mean change [logarithm of the minimum angle of resolution, LogMAR]: ICL =-0.134, LASIK =-0.085; P=0.032). Mean improvements in SVc and SVcG were also statistically significantly greater in the ICL group than in the LASIK group (SVc mean change [logarithm of the CS, LogCS]: ICL =0.356, LASIK =0.209; P=0.018 and SVcG mean change [LogCS]: ICL =0.390, LASIK =0.259; P=0.024). Mean improvement in SVa at 3 months was comparable in both groups (P=0.154). Simulated night vision improved with both ICL implantation and wavefront-optimized LASIK, but improvements were significantly greater with ICLs. These differences may be important in a military setting and may also affect satisfaction with civilian vision correction.

Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1

NASA Astrophysics Data System (ADS)

Langenbrunner, B.; Neelin, J. D.

2017-09-01

Global climate models (GCMs) are examples of high-dimensional input-output systems, where model output is a function of many variables, and an update in model physics commonly improves performance in one objective function (i.e., measure of model performance) at the expense of degrading another. Here concepts from multiobjective optimization in the engineering literature are used to investigate parameter sensitivity and optimization in the face of such trade-offs. A metamodeling technique called cut high-dimensional model representation (cut-HDMR) is leveraged in the context of multiobjective optimization to improve GCM simulation of the tropical Pacific climate, focusing on seasonal precipitation, column water vapor, and skin temperature. An evolutionary algorithm is used to solve for Pareto fronts, which are surfaces in objective function space along which trade-offs in GCM performance occur. This approach allows the modeler to visualize trade-offs quickly and identify the physics at play. In some cases, Pareto fronts are small, implying that trade-offs are minimal, optimal parameter value choices are more straightforward, and the GCM is well-functioning. In all cases considered here, the control run was found not to be Pareto-optimal (i.e., not on the front), highlighting an opportunity for model improvement through objectively informed parameter selection. Taylor diagrams illustrate that these improvements occur primarily in field magnitude, not spatial correlation, and they show that specific parameter updates can improve fields fundamental to tropical moist processes—namely precipitation and skin temperature—without significantly impacting others. These results provide an example of how basic elements of multiobjective optimization can facilitate pragmatic GCM tuning processes.

Simultaneous beam sampling and aperture shape optimization for SPORT.

PubMed

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

2015-02-01

Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. The authors build a mathematical model with the fundamental station point parameters as the decision variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%. The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.

Simultaneous beam sampling and aperture shape optimization for SPORT

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

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

Purpose: Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: The authors build a mathematical model with the fundamental station point parameters as the decisionmore » variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution. Results: A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%. Conclusions: The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.« less

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.

Layout design-based research on optimization and assessment method for shipbuilding workshop

NASA Astrophysics Data System (ADS)

Liu, Yang; Meng, Mei; Liu, Shuang

2013-06-01

The research study proposes to examine a three-dimensional visualization program, emphasizing on improving genetic algorithms through the optimization of a layout design-based standard and discrete shipbuilding workshop. By utilizing a steel processing workshop as an example, the principle of minimum logistic costs will be implemented to obtain an ideological equipment layout, and a mathematical model. The objectiveness is to minimize the total necessary distance traveled between machines. An improved control operator is implemented to improve the iterative efficiency of the genetic algorithm, and yield relevant parameters. The Computer Aided Tri-Dimensional Interface Application (CATIA) software is applied to establish the manufacturing resource base and parametric model of the steel processing workshop. Based on the results of optimized planar logistics, a visual parametric model of the steel processing workshop is constructed, and qualitative and quantitative adjustments then are applied to the model. The method for evaluating the results of the layout is subsequently established through the utilization of AHP. In order to provide a mode of reference to the optimization and layout of the digitalized production workshop, the optimized discrete production workshop will possess a certain level of practical significance.

Dissolved oxygen content prediction in crab culture using a hybrid intelligent method

PubMed Central

Yu, Huihui; Chen, Yingyi; Hassan, ShahbazGul; Li, Daoliang

2016-01-01

A precise predictive model is needed to obtain a clear understanding of the changing dissolved oxygen content in outdoor crab ponds, to assess how to reduce risk and to optimize water quality management. The uncertainties in the data from multiple sensors are a significant factor when building a dissolved oxygen content prediction model. To increase prediction accuracy, a new hybrid dissolved oxygen content forecasting model based on the radial basis function neural networks (RBFNN) data fusion method and a least squares support vector machine (LSSVM) with an optimal improved particle swarm optimization(IPSO) is developed. In the modelling process, the RBFNN data fusion method is used to improve information accuracy and provide more trustworthy training samples for the IPSO-LSSVM prediction model. The LSSVM is a powerful tool for achieving nonlinear dissolved oxygen content forecasting. In addition, an improved particle swarm optimization algorithm is developed to determine the optimal parameters for the LSSVM with high accuracy and generalizability. In this study, the comparison of the prediction results of different traditional models validates the effectiveness and accuracy of the proposed hybrid RBFNN-IPSO-LSSVM model for dissolved oxygen content prediction in outdoor crab ponds. PMID:27270206

Dissolved oxygen content prediction in crab culture using a hybrid intelligent method.

PubMed

Yu, Huihui; Chen, Yingyi; Hassan, ShahbazGul; Li, Daoliang

2016-06-08

A precise predictive model is needed to obtain a clear understanding of the changing dissolved oxygen content in outdoor crab ponds, to assess how to reduce risk and to optimize water quality management. The uncertainties in the data from multiple sensors are a significant factor when building a dissolved oxygen content prediction model. To increase prediction accuracy, a new hybrid dissolved oxygen content forecasting model based on the radial basis function neural networks (RBFNN) data fusion method and a least squares support vector machine (LSSVM) with an optimal improved particle swarm optimization(IPSO) is developed. In the modelling process, the RBFNN data fusion method is used to improve information accuracy and provide more trustworthy training samples for the IPSO-LSSVM prediction model. The LSSVM is a powerful tool for achieving nonlinear dissolved oxygen content forecasting. In addition, an improved particle swarm optimization algorithm is developed to determine the optimal parameters for the LSSVM with high accuracy and generalizability. In this study, the comparison of the prediction results of different traditional models validates the effectiveness and accuracy of the proposed hybrid RBFNN-IPSO-LSSVM model for dissolved oxygen content prediction in outdoor crab ponds.

Investigating the effects of PDC cutters geometry on ROP using the Taguchi technique

NASA Astrophysics Data System (ADS)

Jamaludin, A. A.; Mehat, N. M.; Kamaruddin, S.

2017-10-01

At times, the polycrystalline diamond compact (PDC) bit’s performance dropped and affects the rate of penetration (ROP). The objective of this project is to investigate the effect of PDC cutter geometry and optimize them. An intensive study in cutter geometry would further enhance the ROP performance. The relatively extended analysis was carried out and four significant geometry factors have been identified that directly improved the ROP. Cutter size, back rake angle, side rake angle and chamfer angle are the stated geometry factors. An appropriate optimization technique that effectively controls all influential geometry factors during cutters manufacturing is introduced and adopted in this project. By adopting L9 Taguchi OA, simulation experiment is conducted by using explicit dynamics finite element analysis. Through a structure Taguchi analysis, ANOVA confirms that the most significant geometry to improve ROP is cutter size (99.16% percentage contribution). The optimized cutter is expected to drill with high ROP that can reduce the rig time, which in its turn, may reduce the total drilling cost.

Quantitative learning strategies based on word networks

NASA Astrophysics Data System (ADS)

Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

2018-02-01

Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

The optimization of iloprost inhalation under moderate flow of oxygen therapy in severe pulmonary arterial hypertension.

PubMed

Nakayama, Kazuhiko; Emoto, Noriaki; Tamada, Naoki; Okano, Mitsumasa; Shinkura, Yuto; Yanaka, Kenichi; Onishi, Hiroyuki; Hiraishi, Mana; Yamada, Shinichiro; Tanaka, Hidekazu; Shinke, Toshiro; Hirata, Ken-Ichi

2018-01-01

Inhaled iloprost efficiently improves pulmonary hemodynamics, exercise capacity, and quality of life in patients with pulmonary arterial hypertension (PAH). However, the process of inhalation is laborious for patients suffering from resting dyspnea. We describe a 75-year-old man with idiopathic PAH and a low gas transfer. Investigations excluded significant parenchymal lung disease and airflow obstruction (presuming FEV1/FVC ration > 70%). The patient struggled to complete iloprost inhalation due to severe dyspnea and hypoxemia. As such, we optimized the methods of oxygen supply from the nasal cannula to the trans-inhalator during the inhalation. We successfully shortened the inhalation duration that effectively reduced the laborious efforts required of patients. We also recorded pulmonary hemodynamics during inhalation of nebulized iloprost. This revealed significant hemodynamic improvement immediately following inhalation but hemodynamics returned to baseline within 2 hours. We hope that this optimization will enable patients with severe PAH to undergo iloprost inhalation.

Design and optimization of self-nanoemulsifying drug delivery systems for improved bioavailability of cyclovirobuxine D

PubMed Central

Ke, Zhongcheng; Hou, Xuefeng; Jia, Xiao-bin

2016-01-01

Background The main purpose of this research was to design a self-nanoemulsifying drug delivery system (SNEDDS) for improving the bioavailability of cyclovirobuxine D as a poorly water-soluble drug. Materials and methods Solubility trials, emulsifying studies, and pseudo-ternary phase diagrams were used to screen the SNEDDS formulations. The optimized drug-loaded SNEDDS was prepared at a mass ratio of 3:24:38:38 for cyclovirobuxine D, oleic acid, Solutol SH15, and propylene glycol, respectively. The optimized formulation was characterized in terms of physicochemical and pharmacokinetic parameters compared with marketed cyclovirobuxine D tablets. Results The optimized cyclovirobuxine-D-loaded SNEDDS was spontaneously dispersed to form a nanoemulsion with a globule size of 64.80±3.58 nm, which exhibited significant improvement of drug solubility, rapid absorption rate, and enhanced area under the curve, together with increased permeation and decreased efflux. Fortunately, there was a nonsignificant cytotoxic effect toward Caco-2 cells. The relative bioavailability of SNEDDS was 200.22% in comparison with market tablets, in rabbits. Conclusion SNEDDS could be a potential candidate for an oral dosage form of cyclovirobuxine D with improved bioavailability. PMID:27418807

Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market

NASA Astrophysics Data System (ADS)

Sun, Xuelian; Liu, Zixian

2016-02-01

In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.

Fabrication and Optimization of Self-Microemulsions to Improve the Oral Bioavailability of Total Flavones of Hippophaë rhamnoides L.

PubMed

Guo, Ruixue; Guo, Xinbo; Hu, Xiaodan; Abbasi, Arshad Mehmood; Zhou, Lin; Li, Tong; Fu, Xiong; Liu, Rui Hai

2017-12-01

The purpose of this work was to improve the oral bioavailability of a poorly soluble functional food ingredient, the total flavones of Hippophaë rhamnoides L. (TFH). A self-microemulsion drug delivery system (SMEDDS) was developed to overcome the problems of poor absorption of TFH in vivo. The optimal SMEDDS significantly enhanced the solubility of TFH up to 530 times compared to that in water. The mean droplet size was 61.76 nm with uniform distribution. And the loaded system was stable at 25 °C for 3 mo with transparent appearance. The in vitro release of TFH from SMEDDS was faster and more complete than that from suspension. After oral administration of TFH-SMEDDS in rats, the relative bioavailability of TFH was dramatically improved for 3.09 times compared with the unencapsulated form. The investigation indicated the potential application of SMEDDS as a vehicle to improve the oral bioavailability of TFH. The lipid-based nanotechnology, namely self-microemulsion drug delivery system (SMEDDS) was used to improve the bioavailability and oral delivery of total flavones of Hippophaë rhamnoides L. (TFH). The relevant bioavailability of TFH could be remarkably 3-fold improved by the optimized SMEDDS. The SMEDDS produced via a simple one-step process for poorly soluble TFH to achieve a significant improvement in the bioavailability, may endorse the promising utilization of TFH in functional foods as well as pharmaceutical fields with an enhanced absorption in vivo. © 2017 Institute of Food Technologists®.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks

PubMed Central

Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Li, Baoqing; Yuan, Xiaobing

2017-01-01

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum–minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms. PMID:28753962

Waste-Activated Sludge Fermentation for Polyacrylamide Biodegradation Improved by Anaerobic Hydrolysis and Key Microorganisms Involved in Biological Polyacrylamide Removal.

PubMed

Dai, Xiaohu; Luo, Fan; Zhang, Dong; Dai, Lingling; Chen, Yinguang; Dong, Bin

2015-07-06

During the anaerobic digestion of dewatered sludge, polyacrylamide (PAM), a chemical conditioner, can usually be consumed as a carbon and nitrogen source along with other organic matter (e.g., proteins and carbohydrates in the sludge). However, a significant accumulation of acrylamide monomers (AMs) was observed during the PAM biodegradation process. To improve the anaerobic hydrolysis of PAM, especially the amide hydrolysis process, and to avoid the generation of the intermediate product AM, a new strategy is reported herein that uses an initial pH of 9, 200 mg COD/L of PAM and a fermentation time of 17 d. First, response surface methodology (RSM) was applied to optimize PAM removal in the anaerobic digestion of the sludge. The biological hydrolysis of PAM reached 86.64% under the optimal conditions obtained from the RSM. Then, the mechanisms for the optimized parameters that significantly improved the biological hydrolysis of PAM were investigated by the synergistic effect of the main organic compounds in the sludge, the floc size distribution, and the enzymatic activities. Finally, semi-continuous-flow experiments for a microbial community study were investigated based on the determination of key microorganisms involved in the biological hydrolysis of PAM.

Sensitivity-Based Guided Model Calibration

NASA Astrophysics Data System (ADS)

Semnani, M.; Asadzadeh, M.

2017-12-01

A common practice in automatic calibration of hydrologic models is applying the sensitivity analysis prior to the global optimization to reduce the number of decision variables (DVs) by identifying the most sensitive ones. This two-stage process aims to improve the optimization efficiency. However, Parameter sensitivity information can be used to enhance the ability of the optimization algorithms to find good quality solutions in a fewer number of solution evaluations. This improvement can be achieved by increasing the focus of optimization on sampling from the most sensitive parameters in each iteration. In this study, the selection process of the dynamically dimensioned search (DDS) optimization algorithm is enhanced by utilizing a sensitivity analysis method to put more emphasis on the most sensitive decision variables for perturbation. The performance of DDS with the sensitivity information is compared to the original version of DDS for different mathematical test functions and a model calibration case study. Overall, the results show that DDS with sensitivity information finds nearly the same solutions as original DDS, however, in a significantly fewer number of solution evaluations.

The optimal code searching method with an improved criterion of coded exposure for remote sensing image restoration

NASA Astrophysics Data System (ADS)

He, Lirong; Cui, Guangmang; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

2015-03-01

Coded exposure photography makes the motion de-blurring a well-posed problem. The integration pattern of light is modulated using the method of coded exposure by opening and closing the shutter within the exposure time, changing the traditional shutter frequency spectrum into a wider frequency band in order to preserve more image information in frequency domain. The searching method of optimal code is significant for coded exposure. In this paper, an improved criterion of the optimal code searching is proposed by analyzing relationship between code length and the number of ones in the code, considering the noise effect on code selection with the affine noise model. Then the optimal code is obtained utilizing the method of genetic searching algorithm based on the proposed selection criterion. Experimental results show that the time consuming of searching optimal code decreases with the presented method. The restoration image is obtained with better subjective experience and superior objective evaluation values.

Memetic Algorithm-Based Multi-Objective Coverage Optimization for Wireless Sensor Networks

PubMed Central

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-01-01

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms. PMID:25360579

Memetic algorithm-based multi-objective coverage optimization for wireless sensor networks.

PubMed

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-10-30

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms.

Production optimization of a heat-tolerant alkaline pectinase from Bacillus subtilis ZGL14 and its purification and characterization.

PubMed

Yu, Ping; Zhang, Yishu; Gu, Donglu

2017-09-03

Alkaline pectinase has important applications in the pretreatment of waste water from food processing and in both the fabric and paper industries. In this study, a 2-level factorial design was used to screen significant factors that affect the activity of alkaline pectinase, and the response surface methodology (RSM) with a Box-Behnken design (BBD) was used to optimize their concentrations. Starch, peptone, KH 2 PO 4 and K 2 HPO 4 ·3H 2 O were found to significantly affect the activity of alkaline pectinase. Their optimal concentrations were as follows: 4.68% starch, 1.6% peptone, 0.26% KH 2 PO 4 and 0.68% K 2 HPO 4 ·3H 2 O. Under the above conditions, the activity of alkaline pectinase was significantly improved to 734.11 U/mL. Alkaline pectinase was purified to homogeneity with a recovery rate of 9.6% and a specific activity of 52372.52 U/mg. Its optimal temperature and pH were 50°C and 8.6, respectively. The purified enzyme showed strong thermo-stability and good alkali resistance. In addition, the activity of alkaline pectinase was improved in the presence of Mg 2+ . Cu 2+ , Mn 2+ , and Co 2+ significantly inhibited its activity. This study provides an important basis for the future development and use of a heat-tolerant alkaline pectinase from B. subtilis ZGL14.

Production optimization of a heat-tolerant alkaline pectinase from Bacillus subtilis ZGL14 and its purification and characterization

PubMed Central

Yu, Ping; Zhang, Yishu; Gu, Donglu

2017-01-01

ABSTRACT Alkaline pectinase has important applications in the pretreatment of waste water from food processing and in both the fabric and paper industries. In this study, a 2-level factorial design was used to screen significant factors that affect the activity of alkaline pectinase, and the response surface methodology (RSM) with a Box-Behnken design (BBD) was used to optimize their concentrations. Starch, peptone, KH2PO4 and K2HPO4·3H2O were found to significantly affect the activity of alkaline pectinase. Their optimal concentrations were as follows: 4.68% starch, 1.6% peptone, 0.26% KH2PO4 and 0.68% K2HPO4·3H2O. Under the above conditions, the activity of alkaline pectinase was significantly improved to 734.11 U/mL. Alkaline pectinase was purified to homogeneity with a recovery rate of 9.6% and a specific activity of 52372.52 U/mg. Its optimal temperature and pH were 50°C and 8.6, respectively. The purified enzyme showed strong thermo-stability and good alkali resistance. In addition, the activity of alkaline pectinase was improved in the presence of Mg2+. Cu2+, Mn2+, and Co2+ significantly inhibited its activity. This study provides an important basis for the future development and use of a heat-tolerant alkaline pectinase from B. subtilis ZGL14. PMID:28282260

Discovery and Optimization of 5-Amino-1,2,3-triazole-4-carboxamide Series against Trypanosoma cruzi.

PubMed

Brand, Stephen; Ko, Eun Jung; Viayna, Elisabet; Thompson, Stephen; Spinks, Daniel; Thomas, Michael; Sandberg, Lars; Francisco, Amanda F; Jayawardhana, Shiromani; Smith, Victoria C; Jansen, Chimed; De Rycker, Manu; Thomas, John; MacLean, Lorna; Osuna-Cabello, Maria; Riley, Jennifer; Scullion, Paul; Stojanovski, Laste; Simeons, Frederick R C; Epemolu, Ola; Shishikura, Yoko; Crouch, Sabrinia D; Bakshi, Tania S; Nixon, Christopher J; Reid, Iain H; Hill, Alan P; Underwood, Tim Z; Hindley, Sean J; Robinson, Sharon A; Kelly, John M; Fiandor, Jose M; Wyatt, Paul G; Marco, Maria; Miles, Timothy J; Read, Kevin D; Gilbert, Ian H

2017-09-14

Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi, is the most common cause of cardiac-related deaths in endemic regions of Latin America. There is an urgent need for new safer treatments because current standard therapeutic options, benznidazole and nifurtimox, have significant side effects and are only effective in the acute phase of the infection with limited efficacy in the chronic phase. Phenotypic high content screening against the intracellular parasite in infected VERO cells was used to identify a novel hit series of 5-amino-1,2,3-triazole-4-carboxamides (ATC). Optimization of the ATC series gave improvements in potency, aqueous solubility, and metabolic stability, which combined to give significant improvements in oral exposure. Mitigation of a potential Ames and hERG liability ultimately led to two promising compounds, one of which demonstrated significant suppression of parasite burden in a mouse model of Chagas' disease.

The effect of a multidisciplinary regional educational programme on the quality of colon cancer resection.

PubMed

Sheehan-Dare, G E; Marks, K M; Tinkler-Hundal, E; Ingeholm, P; Bertelsen, C A; Quirke, P; West, N P

2018-02-01

Mesocolic plane surgery with central vascular ligation produces an oncologically superior specimen following colon cancer resection and appears to be related to optimal outcomes. We aimed to assess whether a regional educational programme in optimal mesocolic surgery led to an improvement in the quality of specimens. Following an educational programme in the Capital and Zealand areas of Denmark, 686 cases of primary colon cancer resected across six hospitals were assessed by grading the plane of surgery and undertaking tissue morphometry. These were compared to 263 specimens resected prior to the educational programme. Across the region, the mesocolic plane rate improved from 58% to 77% (P < 0.001). One hospital had previously implemented optimal surgery as standard prior to the educational programme and continued to produce a high rate of mesocolic plane specimens (68%) with a greater distance between the tumour and the high tie (median for all fresh cases: 113 vs 82 mm) and lymph node yield (33 vs 18) compared to the other hospitals. Three of the other hospitals showed a significant improvement in the plane of surgical resection. A multidisciplinary regional educational programme in optimal mesocolic surgery improved the oncological quality of colon cancer specimens as assessed by mesocolic planes; however, there was no significant effect on the amount of tissue resected centrally. Surgeons who attempt central vascular ligation continue to produce more radical specimens suggesting that such educational programmes alone are not sufficient to increase the amount of tissue resected around the tumour. Colorectal Disease © 2017 The Association of Coloproctology of Great Britain and Ireland.

Significantly enhancing recombinant alkaline amylase production in Bacillus subtilis by integration of a novel mutagenesis-screening strategy with systems-level fermentation optimization.

PubMed

Ma, Yingfang; Shen, Wei; Chen, Xianzhong; Liu, Long; Zhou, Zhemin; Xu, Fei; Yang, Haiquan

2016-01-01

Alkaline amylase has significant potential for applications in the textile, paper and detergent industries, however, low yield of which cannot meet the requirement of industrial application. In this work, a novel ARTP mutagenesis-screening method and fermentation optimization strategies were used to significantly improve the expression level of recombinant alkaline amylase in B. subtilis 168. The activity of alkaline amylase in mutant B. subtilis 168 mut-16# strain was 1.34-fold greater than that in the wild-type, and the highest specific production rate was improved from 1.31 U/(mg·h) in the wild-type strain to 1.57 U/(mg·h) in the mutant strain. Meanwhile, the growth of B. subtilis was significantly enhanced by ARTP mutagenesis. When the agitation speed was 550 rpm, the highest activity of recombinant alkaline amylase was 1.16- and 1.25-fold of the activities at 450 and 650 rpm, respectively. When the concentration of soluble starch and soy peptone in the initial fermentation medium was doubled, alkaline amylase activity was increased 1.29-fold. Feeding hydrolyzed starch and soy peptone mixture or glucose significantly improved cell growth, but inhibited the alkaline amylase production in B. subtilis 168 mut-16#. The highest alkaline amylase activity by feeding hydrolyzed starch reached 591.4 U/mL, which was 1.51-fold the activity by feeding hydrolyzed starch and soy peptone mixture. Single pulse feeding-based batch feeding at 10 h favored the production of alkaline amylase in B. subtilis 168 mut-16#. The results indicated that this novel ARTP mutagenesis-screening method could significantly improve the yield of recombinant proteins in B. subtilis . Meanwhile, fermentation optimization strategies efficiently promoted expression of recombinant alkaline amylase in B. subtilis 168 mut-16#. These findings have great potential for facilitating the industrial-scale production of alkaline amylase and other enzymes, using B. subtilis cultures as microbial cell factories.

Advanced in-duct sorbent injection for SO{sub 2} control. Topical report No. 2, Subtask 2.2: Design optimization

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

Rosenhoover, W.A.; Stouffer, M.R.; Withum, J.A.

1994-12-01

The objective of this research project is to develop second-generation duct injection technology as a cost-effective SO{sub 2} control option for the 1990 Clean Air Act Amendments. Research is focused on the Advanced Coolside process, which has shown the potential for achieving the performance targets of 90% SO{sub 2} removal and 60% sorbent utilization. In Subtask 2.2, Design Optimization, process improvement was sought by optimizing sorbent recycle and by optimizing process equipment for reduced cost. The pilot plant recycle testing showed that 90% SO{sub 2} removal could be achieved at sorbent utilizations up to 75%. This testing also showed thatmore » the Advanced Coolside process has the potential to achieve very high removal efficiency (90 to greater than 99%). Two alternative contactor designs were developed, tested and optimized through pilot plant testing; the improved designs will reduce process costs significantly, while maintaining operability and performance essential to the process. Also, sorbent recycle handling equipment was optimized to reduce cost.« less

Alloy and structural optimization of a directionally solidified lamellar eutectic alloy

NASA Technical Reports Server (NTRS)

Sheffler, K. D.

1976-01-01

Mechanical property characterization tests of a directionally solidified Ni-20 percent Cb-2.5 percent Al-6 percent Cr cellular eutectic turbine blade alloy demonstrated excellent long time creep stability and indicated intermediate temperature transverse tensile ductility and shear strength to be somewhat low for turbine blade applications. Alloy and structural optimization significantly improves these off-axis properties with no loss of longitudinal creep strength or stability. The optimized alloy-structure combination is a carbon modified Ni-20.1 percent Cb-2.5 percent Al-6.0 percent Cr-0.06 percent C composition processed under conditions producing plane front solidification and a fully-lamellar microstructure. With current processing technology, this alloy exhibits a creep-rupture advantage of 39 C over the best available nickel base superalloy, directionally solidified MAR M200+ Hf. While improved by about 20 percent, shear strength of the optimized alloy remains well below typical superalloy values.

Fireworks Algorithm with Enhanced Fireworks Interaction.

PubMed

Zhang, Bei; Zheng, Yu-Jun; Zhang, Min-Xia; Chen, Sheng-Yong

2017-01-01

As a relatively new metaheuristic in swarm intelligence, fireworks algorithm (FWA) has exhibited promising performance on a wide range of optimization problems. This paper aims to improve FWA by enhancing fireworks interaction in three aspects: 1) Developing a new Gaussian mutation operator to make sparks learn from more exemplars; 2) Integrating the regular explosion operator of FWA with the migration operator of biogeography-based optimization (BBO) to increase information sharing; 3) Adopting a new population selection strategy that enables high-quality solutions to have high probabilities of entering the next generation without incurring high computational cost. The combination of the three strategies can significantly enhance fireworks interaction and thus improve solution diversity and suppress premature convergence. Numerical experiments on the CEC 2015 single-objective optimization test problems show the effectiveness of the proposed algorithm. The application to a high-speed train scheduling problem also demonstrates its feasibility in real-world optimization problems.

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.

Optimization Performance of a CO[subscript 2] Pulsed Tuneable Laser

ERIC Educational Resources Information Center

Ribeiro, J. H. F.; Lobo, R. F. M.

2009-01-01

In this paper, a procedure is presented that will allow (i) the power and (ii) the energy of a pulsed and tuneable TEA CO[subscript 2] laser to be optimized. This type of laser represents a significant improvement in performance and portability. Combining a pulse mode with a grating tuning facility, it enables us to scan the working wavelength…

Modelling and optimization of semi-solid processing of 7075 Al alloy

NASA Astrophysics Data System (ADS)

Binesh, B.; Aghaie-Khafri, M.

2017-09-01

The new modified strain-induced melt activation (SIMA) process presented by Binesh and Aghaie-Khafri was optimized using a response surface methodology to improve the thixotropic characteristics of semi-solid 7075 alloy. The responses, namely the average grain size and the shape factor, were considered as functions of three independent input variables: effective strain, isothermal holding temperature and time. Mathematical models for the responses were developed using the regression analysis technique, and the adequacy of the models was validated by the analysis of variance method. The calculated results correlated fairly well with the experiments. It was found that all the first- and second-order terms of the independent parameters and the interactive terms of the effective strain and holding time were statistically significant for the responses. In order to simultaneously optimize the responses, the desirable values for the effective strain, holding temperature and time were predicted to be 5.1, 609 °C and 14 min, respectively, when employing the desirability function approach. Based on the optimization results, a significant improvement in the average grain size and shape factor of the semi-solid slurry prepared by the new modified SIMA process was observed.

Optimum outlier model for potential improvement of environmental cleaning and disinfection.

PubMed

Rupp, Mark E; Huerta, Tomas; Cavalieri, R J; Lyden, Elizabeth; Van Schooneveld, Trevor; Carling, Philip; Smith, Philip W

2014-06-01

The effectiveness and efficiency of 17 housekeepers in terminal cleaning 292 hospital rooms was evaluated through adenosine triphosphate detection. A subgroup of housekeepers was identified who were significantly more effective and efficient than their coworkers. These optimum outliers may be used in performance improvement to optimize environmental cleaning.

Holistic, model-based optimization of edge leveling as an enabler for lithographic focus control: application to a memory use case

NASA Astrophysics Data System (ADS)

Hasan, T.; Kang, Y.-S.; Kim, Y.-J.; Park, S.-J.; Jang, S.-Y.; Hu, K.-Y.; Koop, E. J.; Hinnen, P. C.; Voncken, M. M. A. J.

2016-03-01

Advancement of the next generation technology nodes and emerging memory devices demand tighter lithographic focus control. Although the leveling performance of the latest-generation scanners is state of the art, challenges remain at the wafer edge due to large process variations. There are several customer configurable leveling control options available in ASML scanners, some of which are application specific in their scope of leveling improvement. In this paper, we assess the usability of leveling non-correctable error models to identify yield limiting edge dies. We introduce a novel dies-inspec based holistic methodology for leveling optimization to guide tool users in selecting an optimal configuration of leveling options. Significant focus gain, and consequently yield gain, can be achieved with this integrated approach. The Samsung site in Hwaseong observed an improved edge focus performance in a production of a mid-end memory product layer running on an ASML NXT 1960 system. 50% improvement in focus and a 1.5%p gain in edge yield were measured with the optimized configurations.

Optimization methods applied to hybrid vehicle design

NASA Technical Reports Server (NTRS)

Donoghue, J. F.; Burghart, J. H.

1983-01-01

The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.

Optimizing outcome after cardiac arrest.

PubMed

Nolan, Jerry P

2011-10-01

To discuss recent data relating to survival rates after cardiac arrest and interventions that can be used to optimize outcome. A recent analysis of 70 studies indicates that following out-of-hospital cardiac arrest (OHCA), 7.6% of patients will survive to hospital discharge (95% confidence interval 6.7-8.4). Following in-hospital cardiac arrest, 18% of patients will survive to hospital discharge. Survival may be optimized by increasing the rate of bystander cardiopulmonary resuscitation (CPR), which can be achieved by improving recognition of cardiac arrest, simplifying CPR and training more of the community. Feedback systems improve the quality of CPR but this has yet to be translated into improved outcome. One study has shown improved survival following OHCA with active compression-decompression CPR combined with an impedance-threshold device. In those who have no obvious extracardiac cause of OHCA, 70% have at least one significant coronary lesion demonstrable by coronary angiography. Although generally reserved for those with ST-elevation myocardial infarction, primary percutaneous coronary intervention may also benefit OHCA survivors with ECG patterns other than ST elevation. The term 'mild therapeutic hypothermia' has been replaced by the term 'targeted temperature management'; its role in optimizing outcome after cardiac arrest continues to be defined. In several centres, survival rates following OHCA are increasing. All links in the chain of survival must be optimized if a good-quality neurological outcome is to be achieved.

Optimization of Process Parameters of Pulsed Electro Deposition Technique for Nanocrystalline Nickel Coating Using Gray Relational Analysis (GRA)

NASA Astrophysics Data System (ADS)

Venkatesh, C.; Sundara Moorthy, N.; Venkatesan, R.; Aswinprasad, V.

The moving parts of any mechanism and machine parts are always subjected to a significant wear due to the development of friction. It is an utmost important aspect to address the wear problems in present environment. But the complexity goes on increasing to replace the worn out parts if they are very precise. Technology advancement in surface engineering ensures the minimum surface wear with the introduction of polycrystalline nano nickel coating. The enhanced tribological property of the nano nickel coating was achieved by the development of grain size and hardness of the surface. In this study, it has been decided to focus on the optimized parameters of the pulsed electro deposition to develop such a coating. Taguchi’s method coupled gray relational analysis was employed by considering the pulse frequency, average current density and duty cycle as the chief process parameters. The grain size and hardness were considered as responses. Totally, nine experiments were conducted as per L9 design of experiment. Additionally, response graph method has been applied to determine the most significant parameter to influence both the responses. In order to improve the degree of validation, confirmation test and predicted gray grade were carried out with the optimized parameters. It has been observed that there was significant improvement in gray grade for the optimal parameters.

The effect of spectral filters on visual search in stroke patients.

PubMed

Beasley, Ian G; Davies, Leon N

2013-01-01

Visual search impairment can occur following stroke. The utility of optimal spectral filters on visual search in stroke patients has not been considered to date. The present study measured the effect of optimal spectral filters on visual search response time and accuracy, using a task requiring serial processing. A stroke and control cohort undertook the task three times: (i) using an optimally selected spectral filter; (ii) the subjects were randomly assigned to two groups with group 1 using an optimal filter for two weeks, whereas group 2 used a grey filter for two weeks; (iii) the groups were crossed over with group 1 using a grey filter for a further two weeks and group 2 given an optimal filter, before undertaking the task for the final time. Initial use of an optimal spectral filter improved visual search response time but not error scores in the stroke cohort. Prolonged use of neither an optimal nor a grey filter improved response time or reduced error scores. In fact, response times increased with the filter, regardless of its type, for stroke and control subjects; this outcome may be due to contrast reduction or a reflection of task design, given that significant practice effects were noted.

Shape optimization techniques for musical instrument design

NASA Astrophysics Data System (ADS)

Henrique, Luis; Antunes, Jose; Carvalho, Joao S.

2002-11-01

The design of musical instruments is still mostly based on empirical knowledge and costly experimentation. One interesting improvement is the shape optimization of resonating components, given a number of constraints (allowed parameter ranges, shape smoothness, etc.), so that vibrations occur at specified modal frequencies. Each admissible geometrical configuration generates an error between computed eigenfrequencies and the target set. Typically, error surfaces present many local minima, corresponding to suboptimal designs. This difficulty can be overcome using global optimization techniques, such as simulated annealing. However these methods are greedy, concerning the number of function evaluations required. Thus, the computational effort can be unacceptable if complex problems, such as bell optimization, are tackled. Those issues are addressed in this paper, and a method for improving optimization procedures is proposed. Instead of using the local geometric parameters as searched variables, the system geometry is modeled in terms of truncated series of orthogonal space-funcitons, and optimization is performed on their amplitude coefficients. Fourier series and orthogonal polynomials are typical such functions. This technique reduces considerably the number of searched variables, and has a potential for significant computational savings in complex problems. It is illustrated by optimizing the shapes of both current and uncommon marimba bars.

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

Lafleur, Adrienne M.; Ulrich, Timothy J. II; Menlove, Howard O.

Objective is to investigate the use of Passive Neutron Albedo Reactivity (PNAR) and Self-Interrogation Neutron Resonance Densitometry (SINRD) to quantify fissile content in FUGEN spent fuel assemblies (FAs). Methodology used is: (1) Detector was designed using fission chambers (FCs); (2) Optimized design via MCNPX simulations; and (3) Plan to build and field test instrument in FY13. Significance was to improve safeguards verification of spent fuel assemblies in water and increase sensitivity to partial defects. MCNPX simulations were performed to optimize the design of the SINRD+PNAR detector. PNAR ratio was less sensitive to FA positioning than SINRD and SINRD ratio wasmore » more sensitive to Pu fissile mass than PNAR. Significance was that the integration of these techniques can be used to improve verification of spent fuel assemblies in water.« less

ZT Optimization: An Application Focus

PubMed Central

Tuley, Richard; Simpson, Kevin

2017-01-01

Significant research has been performed on the challenge of improving thermoelectric materials, with maximum peak figure of merit, ZT, the most common target. We use an approximate thermoelectric material model, matched to real materials, to demonstrate that when an application is known, average ZT is a significantly better optimization target. We quantify this difference with some examples, with one scenario showing that changing the doping to increase peak ZT by 19% can lead to a performance drop of 16%. The importance of average ZT means that the temperature at which the ZT peak occurs should be given similar weight to the value of the peak. An ideal material for an application operates across the maximum peak ZT, otherwise maximum performance occurs when the peak value is reduced in order to improve the peak position. PMID:28772668

Optimization of Deep Drilling Performance - Development and Benchmark Testing of Advanced Diamond Product Drill Bits & HP/HT Fluids to Significantly Improve Rates of Penetration

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

Alan Black; Arnis Judzis

2005-09-30

This document details the progress to date on the OPTIMIZATION OF DEEP DRILLING PERFORMANCE--DEVELOPMENT AND BENCHMARK TESTING OF ADVANCED DIAMOND PRODUCT DRILL BITS AND HP/HT FLUIDS TO SIGNIFICANTLY IMPROVE RATES OF PENETRATION contract for the year starting October 2004 through September 2005. The industry cost shared program aims to benchmark drilling rates of penetration in selected simulated deep formations and to significantly improve ROP through a team development of aggressive diamond product drill bit--fluid system technologies. Overall the objectives are as follows: Phase 1--Benchmark ''best in class'' diamond and other product drilling bits and fluids and develop concepts for amore » next level of deep drilling performance; Phase 2--Develop advanced smart bit-fluid prototypes and test at large scale; and Phase 3--Field trial smart bit--fluid concepts, modify as necessary and commercialize products. As of report date, TerraTek has concluded all Phase 1 testing and is planning Phase 2 development.« less

Improved cellulase production by Botryosphaeria rhodina from OPEFB at low level moisture condition through statistical optimization.

PubMed

Bahrin, E K; Ibrahim, M F; Abd Razak, M N; Abd-Aziz, S; Shah, U K Md; Alitheen, N; Salleh, M Md

2012-01-01

The response surface method was applied in this study to improve cellulase production from oil palm empty fruit bunch (OPEFB) by Botryosphaeria rhodina. An experimental design based on a two-level factorial was employed to screen the significant environmental factors for cellulase production. The locally isolated fungus Botryosphaeria rhodina was cultivated on OPEFB under solid-state fermentation (SSF). From the analysis of variance (ANOVA), the initial moisture content, amount of substrate, and initial pH of nutrient supplied in the SSF system significantly influenced cellulase production. Then the optimization of the variables was done using the response surface method according to central composite design (CCD). Botryosphaeria rhodina exhibited its best performance with a high predicted value of FPase enzyme production (17.95 U/g) when the initial moisture content was at 24.32%, initial pH of nutrient was 5.96, and 3.98 g of substrate was present. The statistical optimization from actual experiment resulted in a significant increment of FPase production from 3.26 to 17.91 U/g (5.49-fold). High cellulase production at low moisture content is a very rare condition for fungi cultured in solid-state fermentation.

Improvements in the order, isotropy and electron density of glypican-1 crystals by controlled dehydration.

PubMed

Awad, Wael; Svensson Birkedal, Gabriel; Thunnissen, Marjolein M G M; Mani, Katrin; Logan, Derek T

2013-12-01

The use of controlled dehydration for improvement of protein crystal diffraction quality is increasing in popularity, although there are still relatively few documented examples of success. A study has been carried out to establish whether controlled dehydration could be used to improve the anisotropy of crystals of the core protein of the human proteoglycan glypican-1. Crystals were subjected to controlled dehydration using the HC1 device. The optimal protocol for dehydration was developed by careful investigation of the following parameters: dehydration rate, final relative humidity and total incubation time Tinc. Of these, the most important was shown to be Tinc. After dehydration using the optimal protocol the crystals showed significantly reduced anisotropy and improved electron density, allowing the building of previously disordered parts of the structure.

King’s College Hospital criteria for non-acetaminophen induced acute liver failure in an international cohort of children

PubMed Central

Sundaram, Vinay; Shneider, Benjamin L.; Dhawan, Anil; Ng, Vicky L.; Im, Kyungah; Belle, Steven; Squires, Robert H.

2012-01-01

Objective To validate King’s College Hospital criteria (KCHC) in children with non-acetaminophen (APAP) induced pediatric acute liver failure (PALF) and to determine whether re-optimizing the KCHC would improve predictive accuracy. Study design We utilized the PALF study group database. Primary outcomes were survival without liver transplantation (LT) versus death at 21 days following enrollment. Classification and Regression Tree (CART) analysis was used to determine if modification of KCHC parameters would improve classification of death versus survival. Results Among 163 patients who met KCHC, 54 patients (33.1%) died within 21 days. Sensitivity of KCHC in this cohort was significantly lower than in the original study (61% vs 91%, p=0.002), and specificity did not differ significantly. The positive predictive value (PPV) and negative predictive value (NPV) of KCHC for this cohort was 33% and 88% respectively. CART analysis yielded the following optimized parameters to predict death: grade 2–4 encephalopathy, international normalized ratio >4.02 and total bilirubin >2.02 mg/dL. These parameters did not improve PPV, but NPV was significantly better (88% vs. 92%, p<0.0001). Conclusions KCHC does not reliably predict death in PALF. With a PPV of 33%, twice as many participants who met KCHC recovered spontaneously than died, indicating that using KCHC may cause over utilization of LT. Re-optimized cutpoints for KCHC parameters improved NPV, but not PPV. Parameters beyond the KCHC should be evaluated to create a predictive model for PALF. PMID:22906509

Optimization of ADME Properties for Sulfonamides Leading to the Discovery of a T-Type Calcium Channel Blocker, ABT-639

PubMed Central

2015-01-01

The discovery of a novel peripherally acting and selective Cav3.2 T-type calcium channel blocker, ABT-639, is described. HTS hits 1 and 2, which have poor metabolic stability, were optimized to obtain 4, which has improved stability and oral bioavailability. Modification of 4 to further improve ADME properties led to the discovery of ABT-639. Following oral administration, ABT-639 produces robust antinociceptive activity in experimental pain models at doses that do not significantly alter psychomotor or hemodynamic function in the rat. PMID:26101566

Optimization of ADME Properties for Sulfonamides Leading to the Discovery of a T-Type Calcium Channel Blocker, ABT-639.

PubMed

Zhang, Qingwei; Xia, Zhiren; Joshi, Shailen; Scott, Victoria E; Jarvis, Michael F

2015-06-11

The discovery of a novel peripherally acting and selective Cav3.2 T-type calcium channel blocker, ABT-639, is described. HTS hits 1 and 2, which have poor metabolic stability, were optimized to obtain 4, which has improved stability and oral bioavailability. Modification of 4 to further improve ADME properties led to the discovery of ABT-639. Following oral administration, ABT-639 produces robust antinociceptive activity in experimental pain models at doses that do not significantly alter psychomotor or hemodynamic function in the rat.

In vitro optimization of non-small cell lung cancer activity with troxacitabine, L-1,3-dioxolane-cytidine, prodrugs.

PubMed

Radi, Marco; Adema, Auke D; Daft, Jonathan R; Cho, Jong H; Hoebe, Eveline K; Alexander, Lou-Ella M M; Peters, Godefridus J; Chu, Chung K

2007-05-03

l-1,3-Dioxolane-cytidine, a potent anticancer agent against leukemia, has limited efficacy against solid tumors, perhaps due to its hydrophilicity. Herein, a library of prodrugs were synthesized to optimize in vitro antitumor activity against non-small cell lung cancer. N4-Substituted fatty acid amide prodrugs of 10-16 carbon chain length demonstrated significantly improved antitumor activity over l-1,3-dioxolane-cytidine. These in vitro results suggest that the in vivo therapeutic efficacy of l-1,3-dioxolane-cytidine against solid tumors may be improved with prodrug strategies.

Application of Taguchi Design and Response Surface Methodology for Improving Conversion of Isoeugenol into Vanillin by Resting Cells of Psychrobacter sp. CSW4.

PubMed

Ashengroph, Morahem; Nahvi, Iraj; Amini, Jahanshir

2013-01-01

For all industrial processes, modelling, optimisation and control are the keys to enhance productivity and ensure product quality. In the current study, the optimization of process parameters for improving the conversion of isoeugenol to vanillin by Psychrobacter sp. CSW4 was investigated by means of Taguchi approach and Box-Behnken statistical design under resting cell conditions. Taguchi design was employed for screening the significant variables in the bioconversion medium. Sequentially, Box-Behnken design experiments under Response Surface Methodology (RSM) was used for further optimization. Four factors (isoeugenol, NaCl, biomass and tween 80 initial concentrations), which have significant effects on vanillin yield, were selected from ten variables by Taguchi experimental design. With the regression coefficient analysis in the Box-Behnken design, a relationship between vanillin production and four significant variables was obtained, and the optimum levels of the four variables were as follows: initial isoeugenol concentration 6.5 g/L, initial tween 80 concentration 0.89 g/L, initial NaCl concentration 113.2 g/L and initial biomass concentration 6.27 g/L. Under these optimized conditions, the maximum predicted concentration of vanillin was 2.25 g/L. These optimized values of the factors were validated in a triplicate shaking flask study and an average of 2.19 g/L for vanillin, which corresponded to a molar yield 36.3%, after a 24 h bioconversion was obtained. The present work is the first one reporting the application of Taguchi design and Response surface methodology for optimizing bioconversion of isoeugenol into vanillin under resting cell conditions.

An Improved Syringe Agroinfiltration Protocol to Enhance Transformation Efficiency by Combinative Use of 5-Azacytidine, Ascorbate Acid and Tween-20.

PubMed

Zhao, Huimin; Tan, Zilong; Wen, Xuejing; Wang, Yucheng

2017-02-14

Syringe infiltration is an important transient transformation method that is widely used in many molecular studies. Owing to the wide use of syringe agroinfiltration, it is important and necessary to improve its transformation efficiency. Here, we studied the factors influencing the transformation efficiency of syringe agroinfiltration. The pCAMBIA1301 was transformed into Nicotiana benthamiana leaves for investigation. The effects of 5-azacytidine (AzaC), Ascorbate acid (ASC) and Tween-20 on transformation were studied. The β-glucuronidase ( GUS ) expression and GUS activity were respectively measured to determine the transformation efficiency. AzaC, ASC and Tween-20 all significantly affected the transformation efficiency of agroinfiltration, and the optimal concentrations of AzaC, ASC and Tween-20 for the transgene expression were identified. Our results showed that 20 μM AzaC, 0.56 mM ASC and 0.03% ( v / v ) Tween-20 is the optimal concentration that could significantly improve the transformation efficiency of agroinfiltration. Furthermore, a combined supplement of 20 μM AzaC, 0.56 mM ASC and 0.03% Tween-20 improves the expression of transgene better than any one factor alone, increasing the transgene expression by more than 6-fold. Thus, an optimized syringe agroinfiltration was developed here, which might be a powerful method in transient transformation analysis.

Optimization of the production process using virtual model of a workspace

NASA Astrophysics Data System (ADS)

Monica, Z.

2015-11-01

Optimization of the production process is an element of the design cycle consisting of: problem definition, modelling, simulation, optimization and implementation. Without the use of simulation techniques, the only thing which could be achieved is larger or smaller improvement of the process, not the optimization (i.e., the best result it is possible to get for the conditions under which the process works). Optimization is generally management actions that are ultimately bring savings in time, resources, and raw materials and improve the performance of a specific process. It does not matter whether it is a service or manufacturing process. Optimizing the savings generated by improving and increasing the efficiency of the processes. Optimization consists primarily of organizational activities that require very little investment, or rely solely on the changing organization of work. Modern companies operating in a market economy shows a significant increase in interest in modern methods of production management and services. This trend is due to the high competitiveness among companies that want to achieve success are forced to continually modify the ways to manage and flexible response to changing demand. Modern methods of production management, not only imply a stable position of the company in the sector, but also influence the improvement of health and safety within the company and contribute to the implementation of more efficient rules for standardization work in the company. This is why in the paper is presented the application of such developed environment like Siemens NX to create the virtual model of a production system and to simulate as well as optimize its work. The analyzed system is the robotized workcell consisting of: machine tools, industrial robots, conveyors, auxiliary equipment and buffers. In the program could be defined the control program realizing the main task in the virtual workcell. It is possible, using this tool, to optimize both the object trajectory and the cooperation process.

Medium optimization for pyrroloquinoline quinone (PQQ) production by Methylobacillus sp. zju323 using response surface methodology and artificial neural network-genetic algorithm.

PubMed

Wei, Peilian; Si, Zhenjun; Lu, Yao; Yu, Qingfei; Huang, Lei; Xu, Zhinan

2017-08-09

Methylobacillus sp. zju323 was adopted to improve the biosynthesis of pyrroloquinoline quinone (PQQ) by systematic optimization of the fermentation medium. The Plackett-Burman design was implemented to screen for the key medium components for the PQQ production. CoCl 2  · 6H 2 O, ρ-amino benzoic acid, and MgSO 4  · 7H 2 O were found capable of enhancing the PQQ production most significantly. A five-level three-factor central composite design was used to investigate the direct and interactive effects of these variables. Both response surface methodology (RSM) and artificial neural network-genetic algorithm (ANN-GA) were used to predict the PQQ production and to optimize the medium composition. The results showed that the medium optimized by ANN-GA was better than that by RSM in maximizing PQQ production and the experimental PQQ concentration in the ANN-GA-optimized medium was improved by 44.3% compared with that in the unoptimized medium. Further study showed that this ANN-GA-optimized medium was also effective in improving PQQ production by fed-batch mode, reaching the highest PQQ accumulation of 232.0 mg/L, which was about 47.6% increase relative to that in the original medium. The present work provided an optimized medium and developed a fed-batch strategy which might be potentially applicable in industrial PQQ production.

Optimal Design of River Monitoring Network in Taizihe River by Matter Element Analysis

PubMed Central

Wang, Hui; Liu, Zhe; Sun, Lina; Luo, Qing

2015-01-01

The objective of this study is to optimize the river monitoring network in Taizihe River, Northeast China. The situation of the network and water characteristics were studied in this work. During this study, water samples were collected once a month during January 2009 - December 2010 from seventeen sites. Futhermore, the 16 monitoring indexes were analyzed in the field and laboratory. The pH value of surface water sample was found to be in the range of 6.83 to 9.31, and the average concentrations of NH4 +-N, chemical oxygen demand (COD), volatile phenol and total phosphorus (TP) were found decreasing significantly. The water quality of the river has been improved from 2009 to 2010. Through the calculation of the data availability and the correlation between adjacent sections, it was found that the present monitoring network was inefficient as well as the optimization was indispensable. In order to improve the situation, the matter element analysis and gravity distance were applied in the optimization of river monitoring network, which were proved to be a useful method to optimize river quality monitoring network. The amount of monitoring sections were cut from 17 to 13 for the monitoring network was more cost-effective after being optimized. The results of this study could be used in developing effective management strategies to improve the environmental quality of Taizihe River. Also, the results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems. PMID:26023785

Lean and Efficient Software: Whole-Program Optimization of Executables

DTIC Science & Technology

2015-09-30

libraries. Many levels of library interfaces—where some libraries are dynamically linked and some are provided in binary form only—significantly limit...software at build time. The opportunity: Our objective in this project is to substantially improve the performance, size, and robustness of binary ...executables by using static and dynamic binary program analysis techniques to perform whole-program optimization directly on compiled programs

Selection and evaluation of optimal two-dimensional CAIPIRINHA kernels applied to time-resolved three-dimensional CE-MRA.

PubMed

Weavers, Paul T; Borisch, Eric A; Riederer, Stephen J

2015-06-01

To develop and validate a method for choosing the optimal two-dimensional CAIPIRINHA kernel for subtraction contrast-enhanced MR angiography (CE-MRA) and estimate the degree of image quality improvement versus that of some reference acceleration parameter set at R ≥ 8. A metric based on patient-specific coil calibration information was defined for evaluating optimality of CAIPIRINHA kernels as applied to subtraction CE-MRA. Evaluation in retrospective studies using archived coil calibration data from abdomen, calf, foot, and hand CE-MRA exams was accomplished with an evaluation metric comparing the geometry factor (g-factor) histograms. Prospective calf, foot, and hand CE-MRA studies were evaluated with vessel signal-to-noise ratio (SNR). Retrospective studies show g-factor improvement for the selected CAIPIRINHA kernels was significant in the feet, moderate in the abdomen, and modest in the calves and hands. Prospective CE-MRA studies using optimal CAIPIRINHA show reduced noise amplification with identical acquisition time in studies of the feet, with minor improvements in the hands and calves. A method for selection of the optimal CAIPIRINHA kernel for high (R ≥ 8) acceleration CE-MRA exams given a specific patient and receiver array was demonstrated. CAIPIRINHA optimization appears valuable in accelerated CE-MRA of the feet and to a lesser extent in the abdomen. © 2014 Wiley Periodicals, Inc.

[Optimization of end-tool parameters based on robot hand-eye calibration].

PubMed

Zhang, Lilong; Cao, Tong; Liu, Da

2017-04-01

A new one-time registration method was developed in this research for hand-eye calibration of a surgical robot to simplify the operation process and reduce the preparation time. And a new and practical method is introduced in this research to optimize the end-tool parameters of the surgical robot based on analysis of the error sources in this registration method. In the process with one-time registration method, firstly a marker on the end-tool of the robot was recognized by a fixed binocular camera, and then the orientation and position of the marker were calculated based on the joint parameters of the robot. Secondly the relationship between the camera coordinate system and the robot base coordinate system could be established to complete the hand-eye calibration. Because of manufacturing and assembly errors of robot end-tool, an error equation was established with the transformation matrix between the robot end coordinate system and the robot end-tool coordinate system as the variable. Numerical optimization was employed to optimize end-tool parameters of the robot. The experimental results showed that the one-time registration method could significantly improve the efficiency of the robot hand-eye calibration compared with the existing methods. The parameter optimization method could significantly improve the absolute positioning accuracy of the one-time registration method. The absolute positioning accuracy of the one-time registration method can meet the requirements of the clinical surgery.

[Academic burnout and selection-optimization-compensation strategy in medical students].

PubMed

Chun, Kyung Hee; Park, Young Soon; Lee, Young Hwan; Kim, Seong Yong

2014-12-01

This study was conducted to examine the relationship between academic demand, academic burnout, and the selection-optimization-compensation (SOC) strategy in medical students. A total of 317 students at Yeungnam University, comprising 90 premedical course students, 114 medical course students, and 113 graduate course students, completed a survey that addressed the factors of academic burnout and the selection-optimization-compensation strategy. We analyzed variances of burnout and SOC strategy use by group, and stepwise multiple regression analysis was conducted. There were significant differences in emotional exhaustion and cynicism between groups and year in school. In the SOC strategy, there were no significant differences between groups except for elective selection. The second-year medical and graduate students experienced significantly greater exhaustion (p<0.001), and first-year premedical students experienced significantly higher cynicism (p<0.001). By multiple regression analysis, subfactors of academic burnout and emotional exhaustion were significantly affected by academic demand (p<0.001), and 46% of the variance was explained. Cynicism was significantly affected by elective selection (p<0.05), and inefficacy was significantly influenced by optimization (p<0.001). To improve adaptation, prescriptive strategies and preventive support should be implemented with regard to academic burnout in medical school. Longitudinal and qualitative studies on burnout must be conducted.

Optimal Paths in Gliding Flight

NASA Astrophysics Data System (ADS)

Wolek, Artur

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

Improved pharmacokinetics and antihyperlipidemic efficacy of rosuvastatin-loaded nanostructured lipid carriers.

PubMed

Rizwanullah, Md; Amin, Saima; Ahmad, Javed

2017-01-01

In the present study, rosuvastatin calcium-loaded nanostructured lipid carriers were developed and optimized for improved efficacy. The ROS-Ca-loaded NLC was prepared using melt emulsification ultrasonication technique and optimized by Box-Behnken statistical design. The optimized NLC composed of glyceryl monostearate (solid lipid) and capmul MCM EP (liquid lipid) as lipid phase (3% w/v), poloxamer 188 (1%) and tween 80 (1%) as surfactant. The mean particle size, polydispersity index (PDI), zeta potential (ζ) and entrapment efficiency (%) of optimized NLC formulation was observed to be 150.3 ± 4.67 nm, 0.175 ± 0.022, -32.9 ± 1.36 mV and 84.95 ± 5.63%, respectively. NLC formulation showed better in vitro release in simulated intestinal fluid (pH 6.8) than API suspension. Confocal laser scanning showed deeper permeation of formulation across rat intestine compared to rhodamine B dye solution. Pharmacokinetic study on female albino Wistar rats showed 5.4-fold increase in relative bioavailability with NLC compared to API suspension. Optimized NLC formulation also showed significant (p < 0.01) lipid lowering effect in hyperlipidemic rats. Therefore, NLC represents a great potential for improved efficacy of ROS-Ca after oral administration.

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

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

Huang, Xiaobiao; Safranek, James

2014-09-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

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

PubMed

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

2018-05-01

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

Optimal debulking targets in women with advanced stage ovarian cancer: a retrospective study of immediate versus interval debulking surgery.

PubMed

Altman, Alon D; Nelson, Gregg; Chu, Pamela; Nation, Jill; Ghatage, Prafull

2012-06-01

The objective of this study was to examine both overall and disease-free survival of patients with advanced stage ovarian cancer after immediate or interval debulking surgery based on residual disease. We performed a retrospective chart review at the Tom Baker Cancer Centre in Calgary, Alberta of patients with pathologically confirmed stage III or IV ovarian cancer, fallopian tube cancer, or primary peritoneal cancer between 2003 and 2007. We collected data on the dates of diagnosis, recurrence, and death; cancer stage and grade, patients' age, surgery performed, and residual disease. One hundred ninety-two patients were included in the final analysis. The optimal debulking rate with immediate surgery was 64.8%, and with interval surgery it was 85.9%. There were improved overall and disease-free survival rates for optimally debulked disease (< 1 cm) with both immediate and interval surgery (P < 0.001) compared to suboptimally debulked disease. Overall survival rates for optimally debulked disease were not significantly different in patients having immediate and interval surgery (P = 0.25). In the immediate surgery group, patients with microscopic residual disease had better disease-free survival (P = 0.015) and overall survival (P = 0.005) than patients with < 1 cm residual disease. In patients who had interval surgery, those who had microscopic residual disease had more improved disease-free survival than those with < 1 cm disease (P = 0.05), but they did not have more improved overall survival (P = 0.42). Patients with microscopic residual disease who had immediate surgery had a significantly better overall survival rate than those who had interval surgery (P = 0.034). In women with advanced stage ovarian cancer, the goal of surgery should be resection of disease to microscopic residual at the initial procedure. This results in improved overall survival than lesser degrees of resection. Further studies are required to determine optimal surgical management.

Bandwidth reduction for video-on-demand broadcasting using secondary content insertion

NASA Astrophysics Data System (ADS)

Golynski, Alexander; Lopez-Ortiz, Alejandro; Poirier, Guillaume; Quimper, Claude-Guy

2005-01-01

An optimal broadcasting scheme under the presence of secondary content (i.e. advertisements) is proposed. The proposed scheme works both for movies encoded in a Constant Bit Rate (CBR) or a Variable Bit Rate (VBR) format. It is shown experimentally that secondary content in movies can make Video-on-Demand (VoD) broadcasting systems more efficient. An efficient algorithm is given to compute the optimal broadcasting schedule with secondary content, which in particular significantly improves over the best previously known algorithm for computing the optimal broadcasting schedule without secondary content.

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.

Supersonic transport grid generation, validation, and optimization

NASA Technical Reports Server (NTRS)

Aaronson, Philip G.

1995-01-01

The ever present demand for reduced flight times has renewed interest in High Speed Civil Transports (HSCT). The need for an HSCT becomes especially apparent when the long distance, over-sea, high growth Pacific rim routes are considered. Crucial to any successful HSCT design are minimal environmental impact and economic viability. Vital is the transport's aerodynamic efficiency, ultimately effecting both the environmental impact and the operating cost. Optimization, including numerical optimization, coupled with the use of computational fluid dynamics (CFD) technology, has and will offer a significant improvement beyond traditional methods.

The Improvement Cycle: Analyzing Our Experience

NASA Technical Reports Server (NTRS)

Pajerski, Rose; Waligora, Sharon

1996-01-01

NASA's Software Engineering Laboratory (SEL), one of the earliest pioneers in the areas of software process improvement and measurement, has had a significant impact on the software business at NASA Goddard. At the heart of the SEL's improvement program is a belief that software products can be improved by optimizing the software engineering process used to develop them and a long-term improvement strategy that facilitates small incremental improvements that accumulate into significant gains. As a result of its efforts, the SEL has incrementally reduced development costs by 60%, decreased error rates by 85%, and reduced cycle time by 25%. In this paper, we analyze the SEL's experiences on three major improvement initiatives to better understand the cyclic nature of the improvement process and to understand why some improvements take much longer than others.

Optimized multi-electrode stimulation increases focality and intensity at target

NASA Astrophysics Data System (ADS)

Dmochowski, Jacek P.; Datta, Abhishek; Bikson, Marom; Su, Yuzhuo; Parra, Lucas C.

2011-08-01

Transcranial direct current stimulation (tDCS) provides a non-invasive tool to elicit neuromodulation by delivering current through electrodes placed on the scalp. The present clinical paradigm uses two relatively large electrodes to inject current through the head resulting in electric fields that are broadly distributed over large regions of the brain. In this paper, we present a method that uses multiple small electrodes (i.e. 1.2 cm diameter) and systematically optimize the applied currents to achieve effective and targeted stimulation while ensuring safety of stimulation. We found a fundamental trade-off between achievable intensity (at the target) and focality, and algorithms to optimize both measures are presented. When compared with large pad-electrodes (approximated here by a set of small electrodes covering 25cm2), the proposed approach achieves electric fields which exhibit simultaneously greater focality (80% improvement) and higher target intensity (98% improvement) at cortical targets using the same total current applied. These improvements illustrate the previously unrecognized and non-trivial dependence of the optimal electrode configuration on the desired electric field orientation and the maximum total current (due to safety). Similarly, by exploiting idiosyncratic details of brain anatomy, the optimization approach significantly improves upon prior un-optimized approaches using small electrodes. The analysis also reveals the optimal use of conventional bipolar montages: maximally intense tangential fields are attained with the two electrodes placed at a considerable distance from the target along the direction of the desired field; when radial fields are desired, the maximum-intensity configuration consists of an electrode placed directly over the target with a distant return electrode. To summarize, if a target location and stimulation orientation can be defined by the clinician, then the proposed technique is superior in terms of both focality and intensity as compared to previous solutions and is thus expected to translate into improved patient safety and increased clinical efficacy.

Deep Learning Methods for Improved Decoding of Linear Codes

NASA Astrophysics Data System (ADS)

Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

2018-02-01

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.

Optimal periodic proof test based on cost-effective and reliability criteria

NASA Technical Reports Server (NTRS)

Yang, J.-N.

1976-01-01

An exploratory study for the optimization of periodic proof tests for fatigue-critical structures is presented. The optimal proof load level and the optimal number of periodic proof tests are determined by minimizing the total expected (statistical average) cost, while the constraint on the allowable level of structural reliability is satisfied. The total expected cost consists of the expected cost of proof tests, the expected cost of structures destroyed by proof tests, and the expected cost of structural failure in service. It is demonstrated by numerical examples that significant cost saving and reliability improvement for fatigue-critical structures can be achieved by the application of the optimal periodic proof test. The present study is relevant to the establishment of optimal maintenance procedures for fatigue-critical structures.

Slot Optimization Design of Induction Motor for Electric Vehicle

NASA Astrophysics Data System (ADS)

Shen, Yiming; Zhu, Changqing; Wang, Xiuhe

2018-01-01

Slot design of induction motor has a great influence on its performance. The RMxprt module based on magnetic circuit method can be used to analyze the influence of rotor slot type on motor characteristics and optimize slot parameters. In this paper, the authors take an induction motor of electric vehicle for a typical example. The first step of the design is to optimize the rotor slot by RMxprt, and then compare the main performance of the motor before and after the optimization through Ansoft Maxwell 2D. After that, the combination of optimum slot type and the optimum parameters are obtained. The results show that the power factor and the starting torque of the optimized motor have been improved significantly. Furthermore, the electric vehicle works at a better running status after the optimization.

New Hybrid Algorithms for Estimating Tree Stem Diameters at Breast Height Using a Two Dimensional Terrestrial Laser Scanner

PubMed Central

Kong, Jianlei; Ding, Xiaokang; Liu, Jinhao; Yan, Lei; Wang, Jianli

2015-01-01

In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS), which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents. PMID:26147726

[Research and design for optimal position of electrocardio-electrodes in monitoring clothing for men].

PubMed

Liang, Lijun; Hu, Yao; Liu, Hao; Li, Xiaojiu; Li, Jin; He, Yin

2017-04-01

In order to reduce the mortality rate of cardiovascular disease patients effectively, improve the electrocardiogram (ECG) accuracy of signal acquisition, and reduce the influence of motion artifacts caused by the electrodes in inappropriate location in the clothing for ECG measurement, we in this article present a research on the optimum place of ECG electrodes in male clothing using three-lead monitoring methods. In the 3-lead ECG monitoring clothing for men we selected test points. Comparing the ECG and power spectrum analysis of the acquired ECG signal quality of each group of points, we determined the best location of ECG electrodes in the male monitoring clothing. The electrode motion artifacts caused by improper location had been significantly improved when electrodes were put in the best position of the clothing for men. The position of electrodes is crucial for ECG monitoring clothing. The stability of the acquired ECG signal could be improved significantly when electrodes are put at optimal locations.

Methodologies in the modeling of combined chemo-radiation treatments

NASA Astrophysics Data System (ADS)

Grassberger, C.; Paganetti, H.

2016-11-01

The variety of treatment options for cancer patients has increased significantly in recent years. Not only do we combine radiation with surgery and chemotherapy, new therapeutic approaches such as immunotherapy and targeted therapies are starting to play a bigger role. Physics has made significant contributions to radiation therapy treatment planning and delivery. In particular, treatment plan optimization using inverse planning techniques has improved dose conformity considerably. Furthermore, medical physics is often the driving force behind tumor control and normal tissue complication modeling. While treatment optimization and outcome modeling does focus mainly on the effects of radiation, treatment modalities such as chemotherapy are treated independently or are even neglected entirely. This review summarizes the published efforts to model combined modality treatments combining radiation and chemotherapy. These models will play an increasing role in optimizing cancer therapy not only from a radiation and drug dosage standpoint, but also in terms of spatial and temporal optimization of treatment schedules.

Co-Optimization of Internal Combustion Engines and Biofuels

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

McCormick, Robert L.

2016-03-08

The development of advanced engines has significant potential advantages in reduced aftertreatment costs for air pollutant emission control, and just as importantly for efficiency improvements and associated greenhouse gas emission reductions. There are significant opportunities to leverage fuel properties to create more optimal engine designs for both advanced spark-ignition and compression-ignition combustion strategies. The fact that biofuel blendstocks offer a potentially low-carbon approach to fuel production, leads to the idea of optimizing the entire fuel production-utilization value chain as a system from the standpoint of life cycle greenhouse gas emissions. This is a difficult challenge that has yet to bemore » realized. This presentation will discuss the relationship between chemical structure and critical fuel properties for more efficient combustion, survey the properties of a range of biofuels that may be produced in the future, and describe the ongoing challenges of fuel-engine co-optimization.« less

Hybrid Power Management Program Continued

NASA Technical Reports Server (NTRS)

Eichenberg, Dennis J.

2002-01-01

Hybrid Power Management (HPM) is the innovative integration of diverse, state-of-the-art power devices in an optimal configuration for space and terrestrial applications. The appropriate application and control of the various power devices significantly improves overall system performance and efficiency. The advanced power devices include ultracapacitors and photovoltaics. HPM has extremely wide potential with applications including power-generation, transportation, biotechnology, and space power systems. It may significantly alleviate global energy concerns, improve the environment, and stimulate the economy.

Waste-Activated Sludge Fermentation for Polyacrylamide Biodegradation Improved by Anaerobic Hydrolysis and Key Microorganisms Involved in Biological Polyacrylamide Removal

PubMed Central

Dai, Xiaohu; Luo, Fan; Zhang, Dong; Dai, Lingling; Chen, Yinguang; Dong, Bin

2015-01-01

During the anaerobic digestion of dewatered sludge, polyacrylamide (PAM), a chemical conditioner, can usually be consumed as a carbon and nitrogen source along with other organic matter (e.g., proteins and carbohydrates in the sludge). However, a significant accumulation of acrylamide monomers (AMs) was observed during the PAM biodegradation process. To improve the anaerobic hydrolysis of PAM, especially the amide hydrolysis process, and to avoid the generation of the intermediate product AM, a new strategy is reported herein that uses an initial pH of 9, 200 mg COD/L of PAM and a fermentation time of 17 d. First, response surface methodology (RSM) was applied to optimize PAM removal in the anaerobic digestion of the sludge. The biological hydrolysis of PAM reached 86.64% under the optimal conditions obtained from the RSM. Then, the mechanisms for the optimized parameters that significantly improved the biological hydrolysis of PAM were investigated by the synergistic effect of the main organic compounds in the sludge, the floc size distribution, and the enzymatic activities. Finally, semi-continuous-flow experiments for a microbial community study were investigated based on the determination of key microorganisms involved in the biological hydrolysis of PAM. PMID:26144551

Optimization of Aqueous Ammonia Soaking of manure fibers by Response Surface Methodology for unlocking the methane potential of swine manure.

PubMed

Lymperatou, Anna; Gavala, Hariklia N; Skiadas, Ioannis V

2017-11-01

Swine manure mono-digestion often results to economically non-feasible processes, due to the high dilution and ammonia concentration together with the low degradation rates it presents. The effects of different parameters of Aqueous Ammonia Soaking (AAS) as a pretreatment for improving the digestion of manure fibers when coupled to an ammonia removal step were investigated in this study. Response Surface Methodology was followed and the influence and interactions of the following AAS parameters were studied: NH 3 concentration, duration and solid-to-liquid ratio. The mild conditions found to be optimal (7%w/w NH 3 , 96h, and 0.16kg/L) in combination to a significant increase of the short term CH 4 yield (244% in 17days), make this pretreatment a promising solution for improving swine manure mono-digestion. Furthermore, compositional analysis of the manure fibers revealed significant solubilization of hemicellulose, while no lignin removal or loss of cellulose occurred under optimal conditions. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Effective Padding of Multi-Dimensional Arrays to Avoid Cache Conflict Misses

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

Hong, Changwan; Bao, Wenlei; Cohen, Albert

Caches are used to significantly improve performance. Even with high degrees of set-associativity, the number of accessed data elements mapping to the same set in a cache can easily exceed the degree of associativity, causing conflict misses and lowered performance, even if the working set is much smaller than cache capacity. Array padding (increasing the size of array dimensions) is a well known optimization technique that can reduce conflict misses. In this paper, we develop the first algorithms for optimal padding of arrays for a set associative cache for arbitrary tile sizes, In addition, we develop the first solution tomore » padding for nested tiles and multi-level caches. The techniques are in implemented in PAdvisor tool. Experimental results with multiple benchmarks demonstrate significant performance improvement from use of PAdvisor for padding.« less

Genetic algorithm based task reordering to improve the performance of batch scheduled massively parallel scientific applications

DOE PAGES

Sankaran, Ramanan; Angel, Jordan; Brown, W. Michael

2015-04-08

The growth in size of networked high performance computers along with novel accelerator-based node architectures has further emphasized the importance of communication efficiency in high performance computing. The world's largest high performance computers are usually operated as shared user facilities due to the costs of acquisition and operation. Applications are scheduled for execution in a shared environment and are placed on nodes that are not necessarily contiguous on the interconnect. Furthermore, the placement of tasks on the nodes allocated by the scheduler is sub-optimal, leading to performance loss and variability. Here, we investigate the impact of task placement on themore » performance of two massively parallel application codes on the Titan supercomputer, a turbulent combustion flow solver (S3D) and a molecular dynamics code (LAMMPS). Benchmark studies show a significant deviation from ideal weak scaling and variability in performance. The inter-task communication distance was determined to be one of the significant contributors to the performance degradation and variability. A genetic algorithm-based parallel optimization technique was used to optimize the task ordering. This technique provides an improved placement of the tasks on the nodes, taking into account the application's communication topology and the system interconnect topology. As a result, application benchmarks after task reordering through genetic algorithm show a significant improvement in performance and reduction in variability, therefore enabling the applications to achieve better time to solution and scalability on Titan during production.« less

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

NASA Astrophysics Data System (ADS)

Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

2015-08-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

Research on logistics scheduling based on PSO

NASA Astrophysics Data System (ADS)

Bao, Huifang; Zhou, Linli; Liu, Lei

2017-08-01

With the rapid development of e-commerce based on the network, the logistics distribution support of e-commerce is becoming more and more obvious. The optimization of vehicle distribution routing can improve the economic benefit and realize the scientific of logistics [1]. Therefore, the study of logistics distribution vehicle routing optimization problem is not only of great theoretical significance, but also of considerable value of value. Particle swarm optimization algorithm is a kind of evolutionary algorithm, which is based on the random solution and the optimal solution by iteration, and the quality of the solution is evaluated through fitness. In order to obtain a more ideal logistics scheduling scheme, this paper proposes a logistics model based on particle swarm optimization algorithm.

An effective model for ergonomic optimization applied to a new automotive assembly line

NASA Astrophysics Data System (ADS)

Duraccio, Vincenzo; Elia, Valerio; Forcina, Antonio

2016-06-01

An efficient ergonomic optimization can lead to a significant improvement in production performance and a considerable reduction of costs. In the present paper new model for ergonomic optimization is proposed. The new approach is based on the criteria defined by National Institute of Occupational Safety and Health and, adapted to Italian legislation. The proposed model provides an ergonomic optimization, by analyzing ergonomic relations between manual work in correct conditions. The model includes a schematic and systematic analysis method of the operations, and identifies all possible ergonomic aspects to be evaluated. The proposed approach has been applied to an automotive assembly line, where the operation repeatability makes the optimization fundamental. The proposed application clearly demonstrates the effectiveness of the new approach.

Optimization of a low-cost hyperosmotic medium and establishing the fermentation kinetics of erythritol production by Yarrowia lipolytica from crude glycerol.

PubMed

Yang, Li-Bo; Zhan, Xiao-Bei; Zhu, Li; Gao, Min-Jie; Lin, Chi-Chung

2016-05-18

The production of erythritol by Yarrowia lipolytica from low-cost substitutable substrates for high yield was investigated. Crude glycerol, urea, and NaCl related to osmotic pressure were the most significant factors affecting erythritol production. An artificial neural network model and genetic algorithm were used to search the optimal composition of the significant factors and locate the resulting erythritol yield. Medium with 232.39 g/L crude glycerol, 1.57 g/L urea, and 31.03 g/L NaCl led to predictive maximum erythritol concentration of 110.7 g/L. The erythritol concentration improved from 50.4 g/L to 109.2 g/L with the optimized medium, which was reproducible. Erythritol fermentation kinetics were investigated in a batch system. Multistep fermentation kinetic models with hyperosmotic inhibitory effects were developed. The resulting mathematical equations provided a good description of temporal variations such as microbial growth (X), substrate consumption (S), and product formation (P) in erythritol fermentation. The accordingly derived model is the first reported model for fermentative erythritol production from glycerol, providing useful information to optimize the growth of Y. lipolytica and contributing visual description for the erythritol fermentation process under high osmotic pressure, as well as improvement of productivity and efficiency.

Optimization of lipid profile and hardness of low-fat mortadella following a sequential strategy of experimental design.

PubMed

Saldaña, Erick; Siche, Raúl; da Silva Pinto, Jair Sebastião; de Almeida, Marcio Aurélio; Selani, Miriam Mabel; Rios-Mera, Juan; Contreras-Castillo, Carmen J

2018-02-01

This study aims to optimize simultaneously the lipid profile and instrumental hardness of low-fat mortadella. For lipid mixture optimization, the overlapping of surface boundaries was used to select the quantities of canola, olive, and fish oils, in order to maximize PUFAs, specifically the long-chain n-3 fatty acids (eicosapentaenoic-EPA, docosahexaenoic acids-DHA) using the minimum content of fish oil. Increased quantities of canola oil were associated with higher PUFA/SFA ratios. The presence of fish oil, even in small amounts, was effective in improving the nutritional quality of the mixture, showing lower n-6/n-3 ratios and significant levels of EPA and DHA. Thus, the optimal lipid mixture comprised of 20, 30 and 50% fish, olive and canola oils, respectively, which present PUFA/SFA (2.28) and n-6/n-3 (2.30) ratios within the recommendations of a healthy diet. Once the lipid mixture was optimized, components of the pre-emulsion used as fat replacer in the mortadella, such as lipid mixture (LM), sodium alginate (SA), and milk protein concentrate (PC), were studied to optimize hardness and springiness to target ranges of 13-16 N and 0.86-0.87, respectively. Results showed that springiness was not significantly affected by these variables. However, as the concentration of the three components increased, hardness decreased. Through the desirability function, the optimal proportions were 30% LM, 0.5% SA, and 0.5% PC. This study showed that the pre-emulsion decreases hardness of mortadella. In addition, response surface methodology was efficient to model lipid mixture and hardness, resulting in a product with improved texture and lipid quality.

Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

PubMed Central

Lancaster, Jenessa; Lorenz, Romy; Leech, Rob; Cole, James H.

2018-01-01

Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years) we trained support vector machines to (i) distinguish between young (<22 years) and old (>50 years) brains (classification) and (ii) predict chronological age (regression). We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years). Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm). For predicting chronological age, a mean absolute error (MAE) of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm). This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian optimization framework to the new dataset, out-performing the parameters optimized for the initial training dataset. Our study outlines the proof-of-principle that neuroimaging models for brain-age prediction can use Bayesian optimization to derive case-specific pre-processing parameters. Our results suggest that different pre-processing parameters are selected when optimization is conducted in specific contexts. This potentially motivates use of optimization techniques at many different points during the experimental process, which may improve statistical sensitivity and reduce opportunities for experimenter-led bias. PMID:29483870

A new enhanced index tracking model in portfolio optimization with sum weighted approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

NASA Technical Reports Server (NTRS)

Englander, Jacob; Englander, Arnold

2014-01-01

Trajectory optimization methods using MBH have become well developed during the past decade. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing RVs from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by Englander significantly improves MBH performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness, where efficiency is finding better solutions in less time, and robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive RWs originally developed in the field of statistical physics.

Can we discover double Higgs production at the LHC?

NASA Astrophysics Data System (ADS)

Alves, Alexandre; Ghosh, Tathagata; Sinha, Kuver

2017-08-01

We explore double Higgs production via gluon fusion in the b b ¯γ γ channel at the high-luminosity LHC using machine learning tools. We first propose a Bayesian optimization approach to select cuts on kinematic variables, obtaining a 30%-50% increase in the significance compared to current results in the literature. We show that this improvement persists once systematic uncertainties are taken into account. We next use boosted decision trees (BDT) to further discriminate signal and background events. Our analysis shows that a joint optimization of kinematic cuts and BDT hyperparameters results in an appreciable improvement in the significance. Finally, we perform a multivariate analysis of the output scores of the BDT. We find that assuming a very low level of systematics, the techniques proposed here will be able to confirm the production of a pair of standard model Higgs bosons at 5 σ level with 3 ab-1 of data. Assuming a more realistic projection of the level of systematics, around 10%, the optimization of cuts to train BDTs combined with a multivariate analysis delivers a respectable significance of 4.6 σ . Even assuming large systematics of 20%, our analysis predicts a 3.6 σ significance, which represents at least strong evidence in favor of double Higgs production. We carefully incorporate background contributions coming from light flavor jets or c jets being misidentified as b jets and jets being misidentified as photons in our analysis.

Optimization of brain PET imaging for a multicentre trial: the French CATI experience.

PubMed

Habert, Marie-Odile; Marie, Sullivan; Bertin, Hugo; Reynal, Moana; Martini, Jean-Baptiste; Diallo, Mamadou; Kas, Aurélie; Trébossen, Régine

2016-12-01

CATI is a French initiative launched in 2010 to handle the neuroimaging of a large cohort of subjects recruited for an Alzheimer's research program called MEMENTO. This paper presents our test protocol and results obtained for the 22 PET centres (overall 13 different scanners) involved in the MEMENTO cohort. We determined acquisition parameters using phantom experiments prior to patient studies, with the aim of optimizing PET quantitative values to the highest possible per site, while reducing, if possible, variability across centres. Jaszczak's and 3D-Hoffman's phantom measurements were used to assess image spatial resolution (ISR), recovery coefficients (RC) in hot and cold spheres, and signal-to-noise ratio (SNR). For each centre, the optimal reconstruction parameters were chosen as those maximizing ISR and RC without a noticeable decrease in SNR. Point-spread-function (PSF) modelling reconstructions were discarded. The three figures of merit extracted from the images reconstructed with optimized parameters and routine schemes were compared, as were volumes of interest ratios extracted from Hoffman acquisitions. The net effect of the 3D-OSEM reconstruction parameter optimization was investigated on a subset of 18 scanners without PSF modelling reconstruction. Compared to the routine parameters of the 22 PET centres, average RC in the two smallest hot and cold spheres and average ISR remained stable or were improved with the optimized reconstruction, at the expense of slight SNR degradation, while the dispersion of values was reduced. For the subset of scanners without PSF modelling, the mean RC of the smallest hot sphere obtained with the optimized reconstruction was significantly higher than with routine reconstruction. The putamen and caudate-to-white matter ratios measured on 3D-Hoffman acquisitions of all centres were also significantly improved by the optimization, while the variance was reduced. This study provides guidelines for optimizing quantitative results for multicentric PET neuroimaging trials.

Optimizing Metabolite Production Using Periodic Oscillations

PubMed Central

Sowa, Steven W.; Baldea, Michael; Contreras, Lydia M.

2014-01-01

Methods for improving microbial strains for metabolite production remain the subject of constant research. Traditionally, metabolic tuning has been mostly limited to knockouts or overexpression of pathway genes and regulators. In this paper, we establish a new method to control metabolism by inducing optimally tuned time-oscillations in the levels of selected clusters of enzymes, as an alternative strategy to increase the production of a desired metabolite. Using an established kinetic model of the central carbon metabolism of Escherichia coli, we formulate this concept as a dynamic optimization problem over an extended, but finite time horizon. Total production of a metabolite of interest (in this case, phosphoenolpyruvate, PEP) is established as the objective function and time-varying concentrations of the cellular enzymes are used as decision variables. We observe that by varying, in an optimal fashion, levels of key enzymes in time, PEP production increases significantly compared to the unoptimized system. We demonstrate that oscillations can improve metabolic output in experimentally feasible synthetic circuits. PMID:24901332

Optimization of blade motion of vertical axis turbine

NASA Astrophysics Data System (ADS)

Ma, Yong; Zhang, Liang; Zhang, Zhi-yang; Han, Duan-feng

2016-04-01

In this paper, a method is proposed to improve the energy efficiency of the vertical axis turbine. First of all, a single disk multiple stream-tube model is used to calculate individual fitness. Genetic algorithm is adopted to optimize blade pitch motion of vertical axis turbine with the maximum energy efficiency being selected as the optimization objective. Then, a particular data processing method is proposed, fitting the result data into a cosine-like curve. After that, a general formula calculating the blade motion is developed. Finally, CFD simulation is used to validate the blade pitch motion formula. The results show that the turbine's energy efficiency becomes higher after the optimization of blade pitch motion; compared with the fixed pitch turbine, the efficiency of variable-pitch turbine is significantly improved by the active blade pitch control; the energy efficiency declines gradually with the growth of speed ratio; besides, compactness has lager effect on the blade motion while the number of blades has little effect on it.

Adaptive Grouping Cloud Model Shuffled Frog Leaping Algorithm for Solving Continuous Optimization Problems

PubMed Central

Liu, Haorui; Yi, Fengyan; Yang, Heli

2016-01-01

The shuffled frog leaping algorithm (SFLA) easily falls into local optimum when it solves multioptimum function optimization problem, which impacts the accuracy and convergence speed. Therefore this paper presents grouped SFLA for solving continuous optimization problems combined with the excellent characteristics of cloud model transformation between qualitative and quantitative research. The algorithm divides the definition domain into several groups and gives each group a set of frogs. Frogs of each region search in their memeplex, and in the search process the algorithm uses the “elite strategy” to update the location information of existing elite frogs through cloud model algorithm. This method narrows the searching space and it can effectively improve the situation of a local optimum; thus convergence speed and accuracy can be significantly improved. The results of computer simulation confirm this conclusion. PMID:26819584

On the effect of response transformations in sequential parameter optimization.

PubMed

Wagner, Tobias; Wessing, Simon

2012-01-01

Parameter tuning of evolutionary algorithms (EAs) is attracting more and more interest. In particular, the sequential parameter optimization (SPO) framework for the model-assisted tuning of stochastic optimizers has resulted in established parameter tuning algorithms. In this paper, we enhance the SPO framework by introducing transformation steps before the response aggregation and before the actual modeling. Based on design-of-experiments techniques, we empirically analyze the effect of integrating different transformations. We show that in particular, a rank transformation of the responses provides significant improvements. A deeper analysis of the resulting models and additional experiments with adaptive procedures indicates that the rank and the Box-Cox transformation are able to improve the properties of the resultant distributions with respect to symmetry and normality of the residuals. Moreover, model-based effect plots document a higher discriminatory power obtained by the rank transformation.

Discovery and Optimization of Imidazopyridine-Based Inhibitors of Diacylglycerol Acyltransferase 2 (DGAT2).

PubMed

Futatsugi, Kentaro; Kung, Daniel W; Orr, Suvi T M; Cabral, Shawn; Hepworth, David; Aspnes, Gary; Bader, Scott; Bian, Jianwei; Boehm, Markus; Carpino, Philip A; Coffey, Steven B; Dowling, Matthew S; Herr, Michael; Jiao, Wenhua; Lavergne, Sophie Y; Li, Qifang; Clark, Ronald W; Erion, Derek M; Kou, Kou; Lee, Kyuha; Pabst, Brandon A; Perez, Sylvie M; Purkal, Julie; Jorgensen, Csilla C; Goosen, Theunis C; Gosset, James R; Niosi, Mark; Pettersen, John C; Pfefferkorn, Jeffrey A; Ahn, Kay; Goodwin, Bryan

2015-09-24

The medicinal chemistry and preclinical biology of imidazopyridine-based inhibitors of diacylglycerol acyltransferase 2 (DGAT2) is described. A screening hit 1 with low lipophilic efficiency (LipE) was optimized through two key structural modifications: (1) identification of the pyrrolidine amide group for a significant LipE improvement, and (2) insertion of a sp(3)-hybridized carbon center in the core of the molecule for simultaneous improvement of N-glucuronidation metabolic liability and off-target pharmacology. The preclinical candidate 9 (PF-06424439) demonstrated excellent ADMET properties and decreased circulating and hepatic lipids when orally administered to dyslipidemic rodent models.

Increasing the statistical significance of entanglement detection in experiments.

PubMed

Jungnitsch, Bastian; Niekamp, Sönke; Kleinmann, Matthias; Gühne, Otfried; Lu, He; Gao, Wei-Bo; Chen, Yu-Ao; Chen, Zeng-Bing; Pan, Jian-Wei

2010-05-28

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. Experimentally, we observe this phenomenon in a four-photon experiment, testing the Mermin and Ardehali inequality for different levels of noise. Furthermore, we provide a way to develop entanglement tests with high statistical significance.

Wavefront-guided versus wavefront-optimized laser in situ keratomileusis: contralateral comparative study.

PubMed

Padmanabhan, Prema; Mrochen, Michael; Basuthkar, Subam; Viswanathan, Deepa; Joseph, Roy

2008-03-01

To compare the outcomes of wavefront-guided and wavefront-optimized treatment in fellow eyes of patients having laser in situ keratomileusis (LASIK) for myopia. Medical and Vision Research Foundation, Tamil Nadu, India. This prospective comparative study comprised 27 patients who had wavefront-guided LASIK in 1 eye and wavefront-optimized LASIK in the fellow eye. The Hansatome (Bausch & Lomb) was used to create a superior-hinged flap and the Allegretto laser (WaveLight Laser Technologie AG), for photoablation. The Allegretto wave analyzer was used to measure ocular wavefront aberrations and the Functional Acuity Contrast Test chart, to measure contrast sensitivity before and 1 month after LASIK. The refractive and visual outcomes and the changes in aberrations and contrast sensitivity were compared between the 2 treatment modalities. One month postoperatively, 92% of eyes in the wavefront-guided group and 85% in the wavefront-optimized group had uncorrected visual acuity of 20/20 or better; 93% and 89%, respectively, had a postoperative spherical equivalent refraction of +/-0.50 diopter. The differences between groups were not statistically significant. Wavefront-guided LASIK induced less change in 18 of 22 higher-order Zernike terms than wavefront-optimized LASIK, with the change in positive spherical aberration the only statistically significant one (P= .01). Contrast sensitivity improved at the low and middle spatial frequencies (not statistically significant) and worsened significantly at high spatial frequencies after wavefront-guided LASIK; there was a statistically significant worsening at all spatial frequencies after wavefront-optimized LASIK. Although both wavefront-guided and wavefront-optimized LASIK gave excellent refractive correction results, the former induced less higher-order aberrations and was associated with better contrast sensitivity.

Improving striping operations through system optimization.

DOT National Transportation Integrated Search

2015-09-01

Striping operations generate a significant workload for Missouri Department of Transportation (MoDOT) maintenance : operations. The requirement for each striping crew to replenish its stock of paint and other consumable items from a bulk storage : fa...

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

PubMed Central

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

2011-01-01

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

Identification of vehicle suspension parameters by design optimization

NASA Astrophysics Data System (ADS)

Tey, J. Y.; Ramli, R.; Kheng, C. W.; Chong, S. Y.; Abidin, M. A. Z.

2014-05-01

The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.

Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

2017-10-01

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

Sb2Te3 and Its Superlattices: Optimization by Statistical Design.

PubMed

Behera, Jitendra K; Zhou, Xilin; Ranjan, Alok; Simpson, Robert E

2018-05-02

The objective of this work is to demonstrate the usefulness of fractional factorial design for optimizing the crystal quality of chalcogenide van der Waals (vdW) crystals. We statistically analyze the growth parameters of highly c axis oriented Sb 2 Te 3 crystals and Sb 2 Te 3 -GeTe phase change vdW heterostructured superlattices. The statistical significance of the growth parameters of temperature, pressure, power, buffer materials, and buffer layer thickness was found by fractional factorial design and response surface analysis. Temperature, pressure, power, and their second-order interactions are the major factors that significantly influence the quality of the crystals. Additionally, using tungsten rather than molybdenum as a buffer layer significantly enhances the crystal quality. Fractional factorial design minimizes the number of experiments that are necessary to find the optimal growth conditions, resulting in an order of magnitude improvement in the crystal quality. We highlight that statistical design of experiment methods, which is more commonly used in product design, should be considered more broadly by those designing and optimizing materials.

Prescribing and up-titration in recently hospitalized heart failure patients attending a disease management program.

PubMed

Carroll, Robert; Mudge, Alison; Suna, Jessica; Denaro, Charles; Atherton, John

2016-08-01

Heart failure (HF) medications improve clinical outcomes, with optimal doses defined in clinical trials. Patient, provider and system barriers may limit achievement of optimal doses in real life settings, although disease management programs (HF-DMPs) can facilitate up-titration. Secondary analysis of a prospective cohort of 216 participants recently hospitalized with systolic HF, attending 5 HF-DMPs in Queensland, Australia. Medication history at baseline (6weeks after discharge) and 6months provided data to describe prescription rates, dosage and optimal titration of HF medications, and associations with patient and system factors were explored. At baseline, 94% were on an angiotensin converting enzyme inhibitor/angiotensin II receptor blocker (ACEI/ARB), 94% on a beta-blocker (BB) and 42% on a mineralocorticoid receptor antagonist (MRA). The proportion of participants on optimal doses of ACEI/ARB increased from 38% (baseline) to 52% (6months, p=0.001) and on optimal BB dose from 23% to 49% (p<0.001). Significant barriers to ACEI/ARB up-titration were body mass index (BMI)<25, female gender, polypharmacy, previously diagnosed HF, and tertiary hospital. Significant barriers for BB up-titration were BMI<25, previously diagnosed HF and non-cardiologist care. Effective up-titration in HF DMPs is influenced by patient, disease and service factors. Better understanding of barriers to effective up-titration in women, normal weight, and established HF patients may help provide targeted strategies for improving outcomes in these groups. Copyright © 2016 Elsevier Ltd. All rights reserved.

Parameter assessment for virtual Stackelberg game in aerodynamic shape optimization

NASA Astrophysics Data System (ADS)

Wang, Jing; Xie, Fangfang; Zheng, Yao; Zhang, Jifa

2018-05-01

In this paper, parametric studies of virtual Stackelberg game (VSG) are conducted to assess the impact of critical parameters on aerodynamic shape optimization, including design cycle, split of design variables and role assignment. Typical numerical cases, including the inverse design and drag reduction design of airfoil, have been carried out. The numerical results confirm the effectiveness and efficiency of VSG. Furthermore, the most significant parameters are identified, e.g. the increase of design cycle can improve the optimization results but it will also add computational burden. These studies will maximize the productivity of the effort in aerodynamic optimization for more complicated engineering problems, such as the multi-element airfoil and wing-body configurations.

Response Ant Colony Optimization of End Milling Surface Roughness

PubMed Central

Kadirgama, K.; Noor, M. M.; Abd Alla, Ahmed N.

2010-01-01

Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper presents optimum surface roughness by using milling mould aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO). The approach is based on Response Surface Method (RSM) and Ant Colony Optimization (ACO). The main objectives to find the optimized parameters and the most dominant variables (cutting speed, feedrate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factor affecting surface roughness. PMID:22294914

An optimal routing strategy on scale-free networks

NASA Astrophysics Data System (ADS)

Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin

Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

A micropower electrocardiogram amplifier.

PubMed

Fay, L; Misra, V; Sarpeshkar, R

2009-10-01

We introduce an electrocardiogram (EKG) preamplifier with a power consumption of 2.8 muW, 8.1 muVrms input-referred noise, and a common-mode rejection ratio of 90 dB. Compared to previously reported work, this amplifier represents a significant reduction in power with little compromise in signal quality. The improvement in performance may be attributed to many optimizations throughout the design including the use of subthreshold transistor operation to improve noise efficiency, gain-setting capacitors versus resistors, half-rail operation wherever possible, optimal power allocations among amplifier blocks, and the sizing of devices to improve matching and reduce noise. We envision that the micropower amplifier can be used as part of a wireless EKG monitoring system powered by rectified radio-frequency energy or other forms of energy harvesting like body vibration and body heat.

Quantum connectivity optimization algorithms for entanglement source deployment in a quantum multi-hop network

NASA Astrophysics Data System (ADS)

Zou, Zhen-Zhen; Yu, Xu-Tao; Zhang, Zai-Chen

2018-04-01

At first, the entanglement source deployment problem is studied in a quantum multi-hop network, which has a significant influence on quantum connectivity. Two optimization algorithms are introduced with limited entanglement sources in this paper. A deployment algorithm based on node position (DNP) improves connectivity by guaranteeing that all overlapping areas of the distribution ranges of the entanglement sources contain nodes. In addition, a deployment algorithm based on an improved genetic algorithm (DIGA) is implemented by dividing the region into grids. From the simulation results, DNP and DIGA improve quantum connectivity by 213.73% and 248.83% compared to random deployment, respectively, and the latter performs better in terms of connectivity. However, DNP is more flexible and adaptive to change, as it stops running when all nodes are covered.

Utilization of nanotechnology to enhance percutaneous absorption of acyclovir in the treatment of herpes simplex viral infections

PubMed Central

Al-Subaie, Mutlaq M; Hosny, Khaled M; El-Say, Khalid Mohamed; Ahmed, Tarek A; Aljaeid, Bader M

2015-01-01

This study aimed to formulate an optimized acyclovir (ACV) nanoemulsion hydrogel in order to provide a solution for the slow, variable, and incomplete oral drug absorption in patient suffering from herpes simplex viral infection. Solubility of ACV in different oils, surfactants, and cosurfactants was explored utilizing a cubic model mixture design to obtain a nanoemulsion with minimum globule size. Preparation of an optimized ACV nanoemulsion hydrogel using a three-factor, three-level Box–Behnken statistical design was conducted. The molecular weight of chitosan (X1), percentage of chitosan (X2), and percentage of Eugenol as a skin permeation enhancer (X3) were selected to study their effects on hydrogel spreadability (Y1) and percent ACV permeated through rat skin after 2.5 hours (Y2). A pharmacokinetic study of the optimized ACV nanoemulsion hydrogel was conducted in rats. Mixtures of clove oil and castor oil (3:1 ratio), Tween 80 and Span 80 (3:1 ratio), and propylene glycol and Myo-6V (3:1 ratio) were selected as the oil, surfactant, and cosurfactant phases, respectively. Statistical analysis indicated that the molecular weight of chitosan has a significant antagonistic effect on spreadability, but has no significant effect on the percent ACV permeated. The percentage of chitosan also has a significant antagonistic effect on the spreadability and percent ACV permeated. On the other hand, the percentage of Eugenol has a significant synergistic effect on percent ACV permeated, with no effect on spreadability. The ex vivo study demonstrated that the optimized ACV nanoemulsion hydrogel showed a twofold and 1.5-fold higher permeation percentage than the control gel and marketed cream, respectively. The relative bioavailability of the optimized ACV nanoemulsion hydrogel improved to 535.2% and 244.6% with respect to the raw ACV hydrogel and marketed cream, respectively, confirming improvement of the relative bioavailability of ACV in the formulated nanoemulsion hydrogel. PMID:26109856

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

Yu, V; Nguyen, D; Tran, A

Purpose: To develop and clinically implement 4π radiotherapy, an inverse optimization platform that maximally utilizes non-coplanar intensity modulated radiotherapy (IMRT) beams to significantly improve critical organ sparing. Methods: A 3D scanner was used to digitize the human and phantom subject surfaces, which were positioned in the computer assisted design (CAD) model of a TrueBeam machine to create a virtual geometrical model, based on which, the feasible beam space was calculated for different tumor locations. Beamlets were computed for all feasible beams using convolution/superposition. A column generation algorithm was employed to optimize patient specific beam orientations and fluence maps. Optimal routingmore » through all selected beams were calculated by a level set method. The resultant plans were converted to XML files and delivered to phantoms in the TrueBeam developer mode. Finally, 4π plans were recomputed in Eclipse and manually delivered to recurrent GBM patients. Results: Compared to IMRT utilizing manually selected beams and volumetric modulated arc therapy plans, markedly improved dosimetry was observed using 4π for the brain, head and neck, liver, lung, and prostate patients. The improvements were due to significantly improved conformality and reduced high dose spillage to organs mediolateral to the PTV. The virtual geometrical model was experimentally validated. Safety margins with 99.9% confidence in collision avoidance were included to the model based model accuracy estimates determined via 300 physical machine to phantom distance measurements. Automated delivery in the developer mode was completed in 10 minutes and collision free. Manual 4 π treatment on the GBM cases resulted in significant brainstem sparing and took 35–45 minutes including multiple images, which showed submillimeter cranial intrafractional motion. Conclusion: The mathematical modeling utilized in 4π is accurate to create and guide highly complex non-coplanar IMRT treatments that consistently and significantly outperform human-operator-created plans. Deliverability of such plans is clinically demonstrated. This work is funded by Varian Medical Systems and the NSF Graduate Research Fellowship DGE-1144087.« less

Optimization of global model composed of radial basis functions using the term-ranking approach

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

Cai, Peng; Tao, Chao, E-mail: taochao@nju.edu.cn; Liu, Xiao-Jun

2014-03-15

A term-ranking method is put forward to optimize the global model composed of radial basis functions to improve the predictability of the model. The effectiveness of the proposed method is examined by numerical simulation and experimental data. Numerical simulations indicate that this method can significantly lengthen the prediction time and decrease the Bayesian information criterion of the model. The application to real voice signal shows that the optimized global model can capture more predictable component in chaos-like voice data and simultaneously reduce the predictable component (periodic pitch) in the residual signal.

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.

Limiting the risk of cardiac toxicity with esophageal-sparing intensity modulated radiotherapy for locally advanced lung cancers.

PubMed

Woodford, Katrina; Panettieri, Vanessa; Ruben, Jeremy D; Senthi, Sashendra

2016-05-01

Intensity modulated radiotherapy (IMRT) is routinely utilized in the treatment of locally advanced non-small cell lung cancer (NSCLC). RTOG 0617 found that overall survival was impacted by increased low (5 Gy) and intermediate (30 Gy) cardiac doses. We evaluated the impact of esophageal-sparing IMRT on cardiac doses with and without the heart considered in the planning process and predicted toxicity compared to 3D-conventional radiotherapy (3DCRT). Ten consecutive patients with N2 Stage III NSCLC treated to 60 Gy in 30 fractions, between February 2012 and September 2014, were evaluated. For each patient, 3DCRT and esophageal-sparing IMRT plans were generated. IMRT plans were then created with and without the heart considered in the optimization process. To compare plans, the dose delivered to 95% and 99% of the target (D95% and D99%), and doses to the esophagus, lung and heart were compared by determining the volume receiving X dose (VXGy) and the normal tissue complication probability (NTCP) calculated. IMRT reduced maximum esophagus dose to below 60 Gy in all patients and produced significant reductions to V50Gy, V40Gy and esophageal NTCP. The cost of this reduction was a non-statistically, non-clinically significant increase in low dose (5 Gy) lung exposure that did not worsen lung NTCP. IMRT plans produced significant cardiac sparing, with the amount of improvement correlating to the amount of heart overlapping with the target. When included in plan optimization, for selected patients further sparing of the heart and improvement in heart NTCP was possible. Esophageal-sparing IMRT can significantly spare the heart even if it is not considered in the optimization process. Further sparing can be achieved if plan optimization constrains low and intermediate heart doses, without compromising lung doses.

Relationships among depressive symptoms, benefit-finding, optimism, and positive affect in multiple sclerosis patients after psychotherapy for depression.

PubMed

Hart, Stacey L; Vella, Lea; Mohr, David C

2008-03-01

While many patients with multiple sclerosis (MS) experience psychological problems, such as depression, benefit-finding is commonly reported. Using the Broaden-and-Build Model of positive emotions (Fredrickson, 2001) and the Expectancy-Value Model of optimism (Carver & Scheier, 1998) as two related, yet, distinct conceptual frameworks, this study examined positive affect and optimism as mediators of the relationship between improved depression and enhanced benefit-finding. MS patients (N=127), who participated in a larger, randomized clinical trial comparing two types of telephone psychotherapy for depression, were assessed at baseline, midtherapy (8 weeks), end of therapy (16 weeks), and 6- and 12-month posttherapy. Depression was measured with a telephone administered version of the Hamilton Rating Scale for Depression; Positive Affect was measured with the Positive Affect Subscale from the Positive and Negative Affect Scale; Optimism was measured with the Life Orientation Test-Revised; Benefit-Finding was measured with the revised version of the Stress-Related Growth Scale. Data were analyzed with multilevel random-effects models, controlling for time since MS diagnosis and type of treatment. Improved depression was associated with increased benefit-finding over time. The relationship between improved depression and benefit-finding was significantly mediated by both increased optimism and increased positive affect. Findings provide support to both theoretical models. Positivity appears to promote benefit-finding in MS. Copyright (c) 2008 APA, all rights reserved.

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.

Robotics in Orthopedics: A Brave New World.

PubMed

Parsley, Brian S

2018-02-16

Future health-care projection projects a significant growth in population by 2020. Health care has seen an exponential growth in technology to address the growing population with the decreasing number of physicians and health-care workers. Robotics in health care has been introduced to address this growing need. Early adoption of robotics was limited because of the limited application of the technology, the cumbersome nature of the equipment, and technical complications. A continued improvement in efficacy, adaptability, and cost reduction has stimulated increased interest in robotic-assisted surgery. The evolution in orthopedic surgery has allowed for advanced surgical planning, precision robotic machining of bone, improved implant-bone contact, optimization of implant placement, and optimization of the mechanical alignment. The potential benefits of robotic surgery include improved surgical work flow, improvements in efficacy and reduction in surgical time. Robotic-assisted surgery will continue to evolve in the orthopedic field. Copyright © 2018 Elsevier Inc. All rights reserved.

Development and optimization of a self-microemulsifying drug delivery system for atorvastatin calcium by using D-optimal mixture design.

PubMed

Yeom, Dong Woo; Song, Ye Seul; Kim, Sung Rae; Lee, Sang Gon; Kang, Min Hyung; Lee, Sangkil; Choi, Young Wook

2015-01-01

In this study, we developed and optimized a self-microemulsifying drug delivery system (SMEDDS) formulation for improving the dissolution and oral absorption of atorvastatin calcium (ATV), a poorly water-soluble drug. Solubility and emulsification tests were performed to select a suitable combination of oil, surfactant, and cosurfactant. A D-optimal mixture design was used to optimize the concentration of components used in the SMEDDS formulation for achieving excellent physicochemical characteristics, such as small droplet size and high dissolution. The optimized ATV-loaded SMEDDS formulation containing 7.16% Capmul MCM (oil), 48.25% Tween 20 (surfactant), and 44.59% Tetraglycol (cosurfactant) significantly enhanced the dissolution rate of ATV in different types of medium, including simulated intestinal fluid, simulated gastric fluid, and distilled water, compared with ATV suspension. Good agreement was observed between predicted and experimental values for mean droplet size and percentage of the drug released in 15 minutes. Further, pharmacokinetic studies in rats showed that the optimized SMEDDS formulation considerably enhanced the oral absorption of ATV, with 3.4-fold and 4.3-fold increases in the area under the concentration-time curve and time taken to reach peak plasma concentration, respectively, when compared with the ATV suspension. Thus, we successfully developed an optimized ATV-loaded SMEDDS formulation by using the D-optimal mixture design, that could potentially be used for improving the oral absorption of poorly water-soluble drugs.

Development and optimization of a self-microemulsifying drug delivery system for ator vastatin calcium by using d-optimal mixture design

PubMed Central

Yeom, Dong Woo; Song, Ye Seul; Kim, Sung Rae; Lee, Sang Gon; Kang, Min Hyung; Lee, Sangkil; Choi, Young Wook

2015-01-01

In this study, we developed and optimized a self-microemulsifying drug delivery system (SMEDDS) formulation for improving the dissolution and oral absorption of atorvastatin calcium (ATV), a poorly water-soluble drug. Solubility and emulsification tests were performed to select a suitable combination of oil, surfactant, and cosurfactant. A d-optimal mixture design was used to optimize the concentration of components used in the SMEDDS formulation for achieving excellent physicochemical characteristics, such as small droplet size and high dissolution. The optimized ATV-loaded SMEDDS formulation containing 7.16% Capmul MCM (oil), 48.25% Tween 20 (surfactant), and 44.59% Tetraglycol (cosurfactant) significantly enhanced the dissolution rate of ATV in different types of medium, including simulated intestinal fluid, simulated gastric fluid, and distilled water, compared with ATV suspension. Good agreement was observed between predicted and experimental values for mean droplet size and percentage of the drug released in 15 minutes. Further, pharmacokinetic studies in rats showed that the optimized SMEDDS formulation considerably enhanced the oral absorption of ATV, with 3.4-fold and 4.3-fold increases in the area under the concentration-time curve and time taken to reach peak plasma concentration, respectively, when compared with the ATV suspension. Thus, we successfully developed an optimized ATV-loaded SMEDDS formulation by using the d-optimal mixture design, that could potentially be used for improving the oral absorption of poorly water-soluble drugs. PMID:26089663

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

PubMed

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.

An effective model for ergonomic optimization applied to a new automotive assembly line

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

Duraccio, Vincenzo; Elia, Valerio; Forcina, Antonio

2016-06-08

An efficient ergonomic optimization can lead to a significant improvement in production performance and a considerable reduction of costs. In the present paper new model for ergonomic optimization is proposed. The new approach is based on the criteria defined by National Institute of Occupational Safety and Health and, adapted to Italian legislation. The proposed model provides an ergonomic optimization, by analyzing ergonomic relations between manual work in correct conditions. The model includes a schematic and systematic analysis method of the operations, and identifies all possible ergonomic aspects to be evaluated. The proposed approach has been applied to an automotive assemblymore » line, where the operation repeatability makes the optimization fundamental. The proposed application clearly demonstrates the effectiveness of the new approach.« less

REopt Improves the Operations of Alcatraz's Solar PV-Battery-Diesel Hybrid System

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

Olis, Daniel R; Walker, H. A; Van Geet, Otto D

This poster identifies operations improvement strategies for a photovoltaic (PV)-battery-diesel hybrid system at the National Park Service's Alcatraz Island using NREL's REopt analysis tool. The current 'cycle charging' strategy results in significant curtailing of energy production from the PV array, requiring excessive diesel use, while also incurring high wear on batteries without benefit of improved efficiency. A simple 'load following' strategy results in near optimal operating cost reduction.

Quality Improvement Initiatives to Optimize the Management of Chronic Obstructive Pulmonary Disease in Patients With Lung Cancer.

PubMed

Digby, Geneviève C; Robinson, Andrew

2017-11-01

Patients with lung cancer (LC) frequently have chronic obstructive pulmonary disease (COPD), the optimization of which improves outcomes. A 2014 Queen's University Hospitals audit demonstrated that COPD was underdiagnosed and undertreated in outpatients with LC. We sought to improve the diagnosis and management of COPD in this population. We implemented change using a Define/Measure/Analyze/Improve/Control (DMAIC) improvement cycle. Data were obtained by chart review from the Cancer Care Ontario database and e-Patient System for patients with newly diagnosed LC, including patient characteristics, pulmonary function test (PFT) data, and bronchodilator therapies. Improvement cycle 1 included engaging stakeholders and prioritizing COPD management by respirologists in the Lung Diagnostic Assessment Program. Improvement cycle 2 included physician restructuring and developing a standard work protocol. Data were analyzed monthly and presented on statistical process control P-charts, which assessed differences over time. The χ 2 and McNemar tests assessed for significance between independent and dependent groups, respectively. A total of 477 patients were studied (165 patients at baseline, 166 patients in cycle 1, and 127 patients in cycle 2). There was no change in PFT completion over time, although respirology-managed patients were significantly more likely to undergo a PFT than patients who were not managed by respirology (56.7% v 96.1%; P < .00001). The proportion of respirology-managed patients with LC with airflow obstruction receiving inhaled bronchodilator significantly increased (baseline, 46.3%; cycle 1, 51.0%; and cycle 2, 74.3%). By cycle 2, patients with airflow obstruction were more likely to receive a long-acting bronchodilator if managed by respirology (74.3% v 44.8%; P = .0009). COPD is underdiagnosed and undertreated in outpatients with LC. A DMAIC quality improvement strategy emphasizing COPD treatment during LC evaluation in the Lung Diagnostic Assessment Program significantly improved COPD management.

High-intensity Interval Training Dosage for Heart Failure and Coronary Artery Disease Cardiac Rehabilitation. A Systematic Review and Meta-analysis.

PubMed

Ballesta García, Ismael; Rubio Arias, Jacobo Ángel; Ramos Campo, Domingo Jesús; Martínez González-Moro, Ignacio; Carrasco Poyatos, María

2018-04-09

High-interval intensity training (HIT) has been suggested to improve peak VO 2 in cardiac rehabilitation programs. However, the optimal HIT protocol is unknown. The objective of this study was to identify the most effective doses of HIT to optimize peak VO 2 in coronary artery disease (CAD) and heart failure (HF) patients. A search was conducted in 6 databases (MEDLINE, Web of Science, LILACS, CINAHL, Academic Search Complete, and SportDiscus). Studies using a HIT protocol in CAD or HF patients and measuring peak VO 2 were included. The PEDro Scale and Cochrane Collaboration tools were used. Analyses reported significant improvements in peak VO 2 after HIT in both diseases (P = .000001), with a higher increase in HF patients (P = .03). Nevertheless, in HF patients, there were no improvements when the intensity recovery was ≤ 40% of peak VO 2 (P = .19) and the frequency of training was ≤ 2 d/wk (P = .07). There were significant differences regarding duration in CAD patients, with greater improvements in peak VO 2 when the duration was < 12 weeks (P = .05). In HF, programs lasting < 12 weeks did not significantly improve peak VO 2 (P = .1). The HIT is an effective method for improving peak VO 2 in HF and CAD, with a significantly greater increase in HF patients. The recovery intervals should be active and be between 40% and 60% of peak VO 2 in HF patients. Training frequency should be ≥ 2 d/wk for CAD patients and ≥ 3 d/wk for HF patients. Copyright © 2018 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Multi-Constraint Multi-Variable Optimization of Source-Driven Nuclear Systems

NASA Astrophysics Data System (ADS)

Watkins, Edward Francis

1995-01-01

A novel approach to the search for optimal designs of source-driven nuclear systems is investigated. Such systems include radiation shields, fusion reactor blankets and various neutron spectrum-shaping assemblies. The novel approach involves the replacement of the steepest-descents optimization algorithm incorporated in the code SWAN by a significantly more general and efficient sequential quadratic programming optimization algorithm provided by the code NPSOL. The resulting SWAN/NPSOL code system can be applied to more general, multi-variable, multi-constraint shield optimization problems. The constraints it accounts for may include simple bounds on variables, linear constraints, and smooth nonlinear constraints. It may also be applied to unconstrained, bound-constrained and linearly constrained optimization. The shield optimization capabilities of the SWAN/NPSOL code system is tested and verified in a variety of optimization problems: dose minimization at constant cost, cost minimization at constant dose, and multiple-nonlinear constraint optimization. The replacement of the optimization part of SWAN with NPSOL is found feasible and leads to a very substantial improvement in the complexity of optimization problems which can be efficiently handled.

Throughput of Coded Optical CDMA Systems with AND Detectors

NASA Astrophysics Data System (ADS)

Memon, Kehkashan A.; Umrani, Fahim A.; Umrani, A. W.; Umrani, Naveed A.

2012-09-01

Conventional detection techniques used in optical code-division multiple access (OCDMA) systems are not optimal and result in poor bit error rate performance. This paper analyzes the coded performance of optical CDMA systems with AND detectors for enhanced throughput efficiencies and improved error rate performance. The results show that the use of AND detectors significantly improve the performance of an optical channel.

(Too) optimistic about optimism: the belief that optimism improves performance.

PubMed

Tenney, Elizabeth R; Logg, Jennifer M; Moore, Don A

2015-03-01

A series of experiments investigated why people value optimism and whether they are right to do so. In Experiments 1A and 1B, participants prescribed more optimism for someone implementing decisions than for someone deliberating, indicating that people prescribe optimism selectively, when it can affect performance. Furthermore, participants believed optimism improved outcomes when a person's actions had considerable, rather than little, influence over the outcome (Experiment 2). Experiments 3 and 4 tested the accuracy of this belief; optimism improved persistence, but it did not improve performance as much as participants expected. Experiments 5A and 5B found that participants overestimated the relationship between optimism and performance even when their focus was not on optimism exclusively. In summary, people prescribe optimism when they believe it has the opportunity to improve the chance of success-unfortunately, people may be overly optimistic about just how much optimism can do. PsycINFO Database Record (c) 2015 APA, all rights reserved.

A study of viscous interaction effects on hypersonic waveriders. Ph.D. Thesis, Dec. 1991

NASA Technical Reports Server (NTRS)

Chang, Jinhwa

1992-01-01

The effects of viscous interaction in the analysis and design of improved classes of viscous optimized hypersonic waveriders is examined. The Corda computer program is used to generate viscous optimized hypersonic waveriders from conical flow fields without viscous interaction. Each waverider is optimized for maximum L/D, and comparison studies are made between cases with and without viscous interaction. The results show that aerodynamic performance of the viscous interaction waveriders are reduced due mainly to a large increase in skin-friction drag associated with the viscous interaction phenomena that grows with increasing Mach number and altitude, but some of this performance loss can be recouped by including viscous interactions within the optimization procedure. When the waverider is optimized for viscous interaction, the shape can change dramatically. A significant result of the present work delineates on a velocity-altitude map the region where viscous interaction effects are significant for modern hypersonic waveriders by performing parametric runs to produce L/D, C sub L, and C sub D contour plots for Mach numbers from 6 to 30 at altitudes from 30 to 80 km.

Molecular design for enhancement of ocular penetration.

PubMed

Shirasaki, Yoshihisa

2008-07-01

Over the past two decades, many oral drugs have been designed in consideration of physicochemical properties to attain optimal pharmacokinetic properties. This strategy significantly reduced attrition in drug development owing to inadequate pharmacokinetics during the last decade. On the other hand, most ophthalmic drugs are generated from reformulation of other therapeutic dosage forms. Therefore, the modification of formulations has been used mainly as the approach to improve ocular pharmacokinetics. However, to maximize ocular pharmacokinetic properties, a specific molecular design for ocular drug is preferable. Passive diffusion of drugs across the cornea membranes requires appropriate lipophilicity and aqueous solubility. Improvement of such physicochemical properties has been achieved by structure optimization or prodrug approaches. This review discusses the current knowledge about ophthalmic drugs adapted from systemic drugs and molecular design for ocular drugs. I propose the approaches for molecular design to obtain the optimal ocular penetration into anterior segment based on published studies to date.

Patient specific optimization-based treatment planning for catheter-based ultrasound hyperthermia and thermal ablation

NASA Astrophysics Data System (ADS)

Prakash, Punit; Chen, Xin; Wootton, Jeffery; Pouliot, Jean; Hsu, I.-Chow; Diederich, Chris J.

2009-02-01

A 3D optimization-based thermal treatment planning platform has been developed for the application of catheter-based ultrasound hyperthermia in conjunction with high dose rate (HDR) brachytherapy for treating advanced pelvic tumors. Optimal selection of applied power levels to each independently controlled transducer segment can be used to conform and maximize therapeutic heating and thermal dose coverage to the target region, providing significant advantages over current hyperthermia technology and improving treatment response. Critical anatomic structures, clinical target outlines, and implant/applicator geometries were acquired from sequential multi-slice 2D images obtained from HDR treatment planning and used to reconstruct patient specific 3D biothermal models. A constrained optimization algorithm was devised and integrated within a finite element thermal solver to determine a priori the optimal applied power levels and the resulting 3D temperature distributions such that therapeutic heating is maximized within the target, while placing constraints on maximum tissue temperature and thermal exposure of surrounding non-targeted tissue. This optimizationbased treatment planning and modeling system was applied on representative cases of clinical implants for HDR treatment of cervix and prostate to evaluate the utility of this planning approach. The planning provided significant improvement in achievable temperature distributions for all cases, with substantial increase in T90 and thermal dose (CEM43T90) coverage to the hyperthermia target volume while decreasing maximum treatment temperature and reducing thermal dose exposure to surrounding non-targeted tissues and thermally sensitive rectum and bladder. This optimization based treatment planning platform with catheter-based ultrasound applicators is a useful tool that has potential to significantly improve the delivery of hyperthermia in conjunction with HDR brachytherapy. The planning platform has been extended to model thermal ablation, including the addition of temperature dependent attenuation, perfusion, and tissue damage. Pilot point control at the target boundaries was implemented to control power delivery to each transducer section, simulating an approach feasible for MR guided procedures. The computer model of thermal ablation was evaluated on representative patient anatomies to demonstrate the feasibility of using catheter-based ultrasound thermal ablation for treatment of benign prostate hyperplasia (BPH) and prostate cancer, and to assist in designing applicators and treatment delivery strategies.

Knowledge Translation to Optimize Adult Inpatient Glycemic Management with Basal Bolus Insulin Therapy and Improve Patient Outcomes.

PubMed

Helmle, Karmon E; Chacko, Sunita; Chan, Trevor; Drake, Alison; Edwards, Alun L; Moore, Glenda E; Philp, Leta C; Popeski, Naomi; Roedler, Rhonda L; Rogers, Edwin J R; Zimmermann, Gabrielle L; McKeen, Julie

2017-12-27

To develop and evaluate a Basal Bolus Insulin Therapy (BBIT) Knowledge Translation toolkit to address barriers to adoption of established best practice with BBIT in the care of adult inpatients. This study was conducted in 2 phases and focused on the hospitalist provider group across 4 acute care facilities in Calgary. Phase 1 involved a qualitative evaluation of provider and site specific barriers and facilitators, which were mapped to validated interventions using behaviour change theory. This informed the co-development and optimization of the BBIT Knowledge Translation toolkit, with each tool targeting a specific barrier to improved diabetes care practice, including BBIT ordering. In Phase 2, the BBIT Knowledge Translation toolkit was implemented and evaluated, focusing on BBIT ordering frequency, as well as secondary outcomes of hyperglycemia (patient-days with BG >14.0 mmol/L), hypoglycemia (patient-days with BG <4.0 mmol/L), and acute length of stay. Implementation of the BBIT Knowledge Translation toolkit resulted in a significant 13% absolute increase in BBIT ordering. Hyperglycemic patient-days were significantly reduced, with no increase in hypoglycemia. There was a significant, absolute 14% reduction in length of stay. The implementation of an evidence-informed, multifaceted BBIT Knowledge Translation toolkit effectively reduced a deeply entrenched in-patient diabetes care gap. The resulting sustained practice change improved patient clinical and system resource utilization outcomes. This systemic approach to implementation will guide further scale and spread of glycemic optimization initiatives. Copyright © 2018 Diabetes Canada. Published by Elsevier Inc. All rights reserved.

Efficient Expression of Maltohexaose-Forming α-Amylase from Bacillus stearothermophilus in Brevibacillus choshinensis SP3 and Its Use in Maltose Production

PubMed Central

Duan, Xuguo

2017-01-01

The maltohexaose-forming, Ca2+-independent α-amylase gene from Bacillus stearothermophilus (AmyMH) was efficiently expressed in Brevibacillus choshinensis SP3. To improve the production of AmyMH in B. choshinensis SP3, the temperature and initial pH of culture medium were optimized. In addition, single-factor and response surface methodologies were pursued to optimize culture medium. Addition of proline to the culture medium significantly improved the production of recombinant α-amylase in B. choshinensis SP3. This improvement may result from improved cellular integrity of recombinant B. choshinensis SP3 in existence of proline. Culture medium optimization resulted in an 8-fold improvement in α-amylase yield, which reached 1.72 × 104 U·mL−1. The recombinant α-amylase was applied to the production of maltose on a laboratory scale. A maltose content of 90.72%, which could be classified as an extremely high maltose syrup, could be achieved using 15% (m/v) corn starch as the substrate. This study demonstrated that the B. choshinensis SP3 expression system was able to produce substantial quantities of recombinant α-amylase that has potential application in the starch industry. PMID:29250543

Optimization of cold-adapted lysozyme production from the psychrophilic yeast Debaryomyces hansenii using statistical experimental methods.

PubMed

Wang, Quanfu; Hou, Yanhua; Yan, Peisheng

2012-06-01

Statistical experimental designs were employed to optimize culture conditions for cold-adapted lysozyme production of a psychrophilic yeast Debaryomyces hansenii. In the first step of optimization using Plackett-Burman design (PBD), peptone, glucose, temperature, and NaCl were identified as significant variables that affected lysozyme production, the formula was further optimized using a four factor central composite design (CCD) to understand their interaction and to determine their optimal levels. A quadratic model was developed and validated. Compared to the initial level (18.8 U/mL), the maximum lysozyme production (65.8 U/mL) observed was approximately increased by 3.5-fold under the optimized conditions. Cold-adapted lysozymes production was first optimized using statistical experimental methods. A 3.5-fold enhancement of microbial lysozyme was gained after optimization. Such an improved production will facilitate the application of microbial lysozyme. Thus, D. hansenii lysozyme may be a good and new resource for the industrial production of cold-adapted lysozymes. © 2012 Institute of Food Technologists®

Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

PubMed Central

Li, Kaiming; Guo, Lei; Zhu, Dajiang; Hu, Xintao; Han, Junwei; Liu, Tianming

2013-01-01

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain. PMID:22281931

A method of network topology optimization design considering application process characteristic

NASA Astrophysics Data System (ADS)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

Design of experiments confirms optimization of lithium administration parameters for enhanced fracture healing.

PubMed

Vachhani, Kathak; Pagotto, Andrea; Wang, Yufa; Whyne, Cari; Nam, Diane

2018-01-03

Fracture healing is a lengthy process which fails in 5-10% of cases. Lithium, a low-cost therapeutic used in psychiatric medicine, up-regulates the canonical Wingless pathway crucial for osteoblastic mineralization in fracture healing. A design-of-experiments (DOE) methodology was used to optimize lithium administration parameters (dose, onset time and treatment duration) to enhance healing in a rat femoral fracture model. In the previously completed first stage (screening), onset time was found to significantly impact healing, with later (day 7 vs. day 3 post-fracture) treatment yielding improved maximum yield torque. The greatest strength was found in healing femurs treated at day 7 post fracture, with a low lithium dose (20 mg/kg) for 2 weeks duration. This paper describes the findings of the second (optimization) and third (verification) stages of the DOE investigation. Closed traumatic diaphyseal femur fractures were induced in 3-month old rats. Healing was evaluated on day 28 post fracture by CT-based morphometry and torsional loading. In optimization, later onset times of day 10 and 14 did not perform as well as day 7 onset. As such, efficacy of the best regimen (20 mg/kg dose given at day 7 onset for 2 weeks duration) was reassessed in a distinct cohort of animals to complete the DOE verification. A significant 44% higher maximum yield torque (primary outcome) was seen with optimized lithium treatment vs. controls, which paralleled the 46% improvement seen in the screening stage. Successful completion of this robustly designed preclinical DOE study delineates the optimal lithium regimen for enhancing preclinical long-bone fracture healing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of optimized root water uptake parameterization schemes on water and heat flux simulation in a maize agroecosystem

NASA Astrophysics Data System (ADS)

Cai, Fu; Ming, Huiqing; Mi, Na; Xie, Yanbing; Zhang, Yushu; Li, Rongping

2017-04-01

As root water uptake (RWU) is an important link in the water and heat exchange between plants and ambient air, improving its parameterization is key to enhancing the performance of land surface model simulations. Although different types of RWU functions have been adopted in land surface models, there is no evidence as to which scheme most applicable to maize farmland ecosystems. Based on the 2007-09 data collected at the farmland ecosystem field station in Jinzhou, the RWU function in the Common Land Model (CoLM) was optimized with scheme options in light of factors determining whether roots absorb water from a certain soil layer ( W x ) and whether the baseline cumulative root efficiency required for maximum plant transpiration ( W c ) is reached. The sensibility of the parameters of the optimization scheme was investigated, and then the effects of the optimized RWU function on water and heat flux simulation were evaluated. The results indicate that the model simulation was not sensitive to W x but was significantly impacted by W c . With the original model, soil humidity was somewhat underestimated for precipitation-free days; soil temperature was simulated with obvious interannual and seasonal differences and remarkable underestimations for the maize late-growth stage; and sensible and latent heat fluxes were overestimated and underestimated, respectively, for years with relatively less precipitation, and both were simulated with high accuracy for years with relatively more precipitation. The optimized RWU process resulted in a significant improvement of CoLM's performance in simulating soil humidity, temperature, sensible heat, and latent heat, for dry years. In conclusion, the optimized RWU scheme available for the CoLM model is applicable to the simulation of water and heat flux for maize farmland ecosystems in arid areas.

Improving multi-objective reservoir operation optimization with sensitivity-informed problem decomposition

NASA Astrophysics Data System (ADS)

Chu, J. G.; Zhang, C.; Fu, G. T.; Li, Y.; Zhou, H. C.

2015-04-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce the computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed problem decomposition dramatically reduces the computational demands required for attaining high quality approximations of optimal tradeoff relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed problem decomposition and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform problem decomposition when solving the complex multi-objective reservoir operation problems.

Oil-Free Rotor Support Technologies for an Optimized Helicopter Propulsion System

NASA Technical Reports Server (NTRS)

DellaCorte, Christopher; Bruckner, Robert J.

2007-01-01

An optimized rotorcraft propulsion system incorporating a foil air bearing supported Oil-Free engine coupled to a high power density gearbox using high viscosity gear oil is explored. Foil air bearings have adequate load capacity and temperature capability for the highspeed gas generator shaft of a rotorcraft engine. Managing the axial loads of the power turbine shaft (low speed spool) will likely require thrust load support from the gearbox through a suitable coupling or other design. Employing specially formulated, high viscosity gear oil for the transmission can yield significant improvements (approx. 2X) in allowable gear loading. Though a completely new propulsion system design is needed to implement such a system, improved performance is possible.

Optimization Under Uncertainty for Wake Steering Strategies

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

Quick, Julian; Annoni, Jennifer; King, Ryan N.

Here, wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in themore » presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.« less

Optimization Under Uncertainty for Wake Steering Strategies: Preprint

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

Quick, Julian; Annoni, Jennifer; King, Ryan N

Wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presencemore » of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.« less

The Effects of Creatine Supplementation on Explosive Performance and Optimal Individual Postactivation Potentiation Time.

PubMed

Wang, Chia-Chi; Yang, Ming-Ta; Lu, Kang-Hao; Chan, Kuei-Hui

2016-03-04

Creatine plays an important role in muscle energy metabolism. Postactivation potentiation (PAP) is a phenomenon that can acutely increase muscle power, but it is an individualized process that is influenced by muscle fatigue. This study examined the effects of creatine supplementation on explosive performance and the optimal individual PAP time during a set of complex training bouts. Thirty explosive athletes performed tests of back squat for one repetition maximum (1RM) strength and complex training bouts for determining the individual optimal timing of PAP, height and peak power of a counter movement jump before and after the supplementation. Subjects were assigned to a creatine or placebo group and then consumed 20 g of creatine or carboxymethyl cellulose per day for six days. After the supplementation, the 1RM strength in the creatine group significantly increased (p < 0.05). The optimal individual PAP time in the creatine group was also significant earlier than the pre-supplementation and post-supplementation of the placebo group (p < 0.05). There was no significant difference in jump performance between the groups. This study demonstrates that creatine supplementation improves maximal muscle strength and the optimal individual PAP time of complex training but has no effect on explosive performance.

The Effects of Creatine Supplementation on Explosive Performance and Optimal Individual Postactivation Potentiation Time

PubMed Central

Wang, Chia-Chi; Yang, Ming-Ta; Lu, Kang-Hao; Chan, Kuei-Hui

2016-01-01

Creatine plays an important role in muscle energy metabolism. Postactivation potentiation (PAP) is a phenomenon that can acutely increase muscle power, but it is an individualized process that is influenced by muscle fatigue. This study examined the effects of creatine supplementation on explosive performance and the optimal individual PAP time during a set of complex training bouts. Thirty explosive athletes performed tests of back squat for one repetition maximum (1RM) strength and complex training bouts for determining the individual optimal timing of PAP, height and peak power of a counter movement jump before and after the supplementation. Subjects were assigned to a creatine or placebo group and then consumed 20 g of creatine or carboxymethyl cellulose per day for six days. After the supplementation, the 1RM strength in the creatine group significantly increased (p < 0.05). The optimal individual PAP time in the creatine group was also significant earlier than the pre-supplementation and post-supplementation of the placebo group (p < 0.05). There was no significant difference in jump performance between the groups. This study demonstrates that creatine supplementation improves maximal muscle strength and the optimal individual PAP time of complex training but has no effect on explosive performance. PMID:26959056

Optimization Under Uncertainty for Wake Steering Strategies

NASA Astrophysics Data System (ADS)

Quick, Julian; Annoni, Jennifer; King, Ryan; Dykes, Katherine; Fleming, Paul; Ning, Andrew

2017-05-01

Wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as “wake steering,” in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.

Optimization Under Uncertainty for Wake Steering Strategies

DOE PAGES

Quick, Julian; Annoni, Jennifer; King, Ryan N.; ...

2017-06-13

Here, wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in themore » presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.« less

Improving cylinder-type LiFePO4 battery performance via control of internal resistance

NASA Astrophysics Data System (ADS)

Purwanto, Agus; Jumari, Arif; Nizam, Muhammad; Widiyandari, Hendri; Sudaryanto; Deswita; Azmin Mohamad, Ahmad

2018-04-01

Strategies for controlling the internal resistance to improve battery performance were systematically investigated. Electrode densification of LiFePO4 cathodes significantly reduced the internal resistance of the prepared batteries. Densification by reduction to 31.25% of initial thickness resulted in optimal electrochemical performance of the prepared LiFePO4 batteries. The addition of KS 6 graphite material improved the conductivity of the cathodes, which was indicated by a lowering of the internal resistance. The internal resistance was decreased from 73 to 54 when the KS6/AB ratio was varied from 3 to 1. Another factor in controlling the internal resistance was the location of a welded aluminum tab in the cathode. The welding of an aluminum tab in a small gap in the cathode significantly reduced the internal resistance. Thus, three main factors can be performed during fabrication to reduce the internal resistance of a LiFePO4 battery: cathode densification, KS-6 graphite addition, and the arrangement of an aluminum tab welded to the cathode. By optimizing these factors, high-performance LFP batteries were produced.

Reduction of wafer-edge overlay errors using advanced correction models, optimized for minimal metrology requirements

NASA Astrophysics Data System (ADS)

Kim, Min-Suk; Won, Hwa-Yeon; Jeong, Jong-Mun; Böcker, Paul; Vergaij-Huizer, Lydia; Kupers, Michiel; Jovanović, Milenko; Sochal, Inez; Ryan, Kevin; Sun, Kyu-Tae; Lim, Young-Wan; Byun, Jin-Moo; Kim, Gwang-Gon; Suh, Jung-Joon

2016-03-01

In order to optimize yield in DRAM semiconductor manufacturing for 2x nodes and beyond, the (processing induced) overlay fingerprint towards the edge of the wafer needs to be reduced. Traditionally, this is achieved by acquiring denser overlay metrology at the edge of the wafer, to feed field-by-field corrections. Although field-by-field corrections can be effective in reducing localized overlay errors, the requirement for dense metrology to determine the corrections can become a limiting factor due to a significant increase of metrology time and cost. In this study, a more cost-effective solution has been found in extending the regular correction model with an edge-specific component. This new overlay correction model can be driven by an optimized, sparser sampling especially at the wafer edge area, and also allows for a reduction of noise propagation. Lithography correction potential has been maximized, with significantly less metrology needs. Evaluations have been performed, demonstrating the benefit of edge models in terms of on-product overlay performance, as well as cell based overlay performance based on metrology-to-cell matching improvements. Performance can be increased compared to POR modeling and sampling, which can contribute to (overlay based) yield improvement. Based on advanced modeling including edge components, metrology requirements have been optimized, enabling integrated metrology which drives down overall metrology fab footprint and lithography cycle time.

A unified framework of unsupervised subjective optimized bit allocation for multiple video object coding

NASA Astrophysics Data System (ADS)

Chen, Zhenzhong; Han, Junwei; Ngan, King Ngi

2005-10-01

MPEG-4 treats a scene as a composition of several objects or so-called video object planes (VOPs) that are separately encoded and decoded. Such a flexible video coding framework makes it possible to code different video object with different distortion scale. It is necessary to analyze the priority of the video objects according to its semantic importance, intrinsic properties and psycho-visual characteristics such that the bit budget can be distributed properly to video objects to improve the perceptual quality of the compressed video. This paper aims to provide an automatic video object priority definition method based on object-level visual attention model and further propose an optimization framework for video object bit allocation. One significant contribution of this work is that the human visual system characteristics are incorporated into the video coding optimization process. Another advantage is that the priority of the video object can be obtained automatically instead of fixing weighting factors before encoding or relying on the user interactivity. To evaluate the performance of the proposed approach, we compare it with traditional verification model bit allocation and the optimal multiple video object bit allocation algorithms. Comparing with traditional bit allocation algorithms, the objective quality of the object with higher priority is significantly improved under this framework. These results demonstrate the usefulness of this unsupervised subjective quality lifting framework.

Warpage investigation on side arms using response surface methodology (RSM) and glow-worm swarm optimizations (GSO)

NASA Astrophysics Data System (ADS)

Sow, C. K.; Fathullah, M.; Nasir, S. M.; Shayfull, Z.; Shazzuan, S.

2017-09-01

This paper discusses on an analysis run via injection moulding process in determination of the optimum processing parameters used for manufacturing side arms of catheters in minimizing the warpage issues. The optimization method used was RSM. Moreover, in this research tries to find the most significant factor affecting the warpage. From the previous literature review,4 most significant parameters on warpage defect was selected. Those parameters were melt temperature, packing time, packing pressure, mould temperature and cooling time. At the beginning, side arm was drawn using software of CATIA V5. Then, software Mouldflow and Design Expert were employed to analyses on the popular warpage issues. After that, GSO artificial intelligence was apply using the mathematical model from Design Expert for more optimization on RSM result. Recommended parameter settings from the simulation work were then compared with the optimization work of RSM and GSO. The result show that the warpage on the side arm was improved by 3.27 %

Production optimization of invertase by Lactobacillus brevis Mm-6 and its immobilization on alginate beads.

PubMed

Awad, Ghada E A; Amer, Hassan; El-Gammal, Eman W; Helmy, Wafaa A; Esawy, Mona A; Elnashar, Magdy M M

2013-04-02

A sequential optimization strategy, based on statistical experimental designs, was employed to enhance the production of invertase by Lactobacillus brevis Mm-6 isolated from breast milk. First, a 2-level Plackett-Burman design was applied to screen the bioprocess parameters that significantly influence the invertase production. The second optimization step was performed using fractional factorial design in order to optimize the amounts of variables have the highest positive significant effect on the invertase production. A maximal enzyme activity of 1399U/ml was more than five folds the activity obtained using the basal medium. Invertase was immobilized onto grafted alginate beads to improve the enzyme's stability. Immobilization process increased the operational temperature from 30 to 60°C compared to the free enzyme. The reusability test proved the durability of the grafted alginate beads for 15 cycles with retention of 100% of the immobilized enzyme activity to be more convenient for industrial uses. Copyright © 2013 Elsevier Ltd. All rights reserved.

Data centers as dispatchable loads to harness stranded power

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

Kim, Kibaek; Yang, Fan; Zavala, Victor M.

Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast,more » optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.« less

Data centers as dispatchable loads to harness stranded power

DOE PAGES

Kim, Kibaek; Yang, Fan; Zavala, Victor M.; ...

2016-07-20

Here, we analyze how traditional data center placement and optimal placement of dispatchable data centers affect power grid efficiency. We use detailed network models, stochastic optimization formulations, and diverse renewable generation scenarios to perform our analysis. Our results reveal that significant spillage and stranded power will persist in power grids as wind power levels are increased. A counter-intuitive finding is that collocating data centers with inflexible loads next to wind farms has limited impacts on renewable portfolio standard (RPS) goals because it provides limited system-level flexibility. Such an approach can, in fact, increase stranded power and fossil-fueled generation. In contrast,more » optimally placing data centers that are dispatchable provides system-wide flexibility, reduces stranded power, and improves efficiency. In short, optimally placed dispatchable computing loads can enable better scaling to high RPS. In our case study, we find that these dispatchable computing loads are powered to 60-80% of their requested capacity, indicating that there are significant economic incentives provided by stranded power.« less

A Novel Optimization Technique to Improve Gas Recognition by Electronic Noses Based on the Enhanced Krill Herd Algorithm

PubMed Central

Wang, Li; Jia, Pengfei; Huang, Tailai; Duan, Shukai; Yan, Jia; Wang, Lidan

2016-01-01

An electronic nose (E-nose) is an intelligent system that we will use in this paper to distinguish three indoor pollutant gases (benzene (C6H6), toluene (C7H8), formaldehyde (CH2O)) and carbon monoxide (CO). The algorithm is a key part of an E-nose system mainly composed of data processing and pattern recognition. In this paper, we employ support vector machine (SVM) to distinguish indoor pollutant gases and two of its parameters need to be optimized, so in order to improve the performance of SVM, in other words, to get a higher gas recognition rate, an effective enhanced krill herd algorithm (EKH) based on a novel decision weighting factor computing method is proposed to optimize the two SVM parameters. Krill herd (KH) is an effective method in practice, however, on occasion, it cannot avoid the influence of some local best solutions so it cannot always find the global optimization value. In addition its search ability relies fully on randomness, so it cannot always converge rapidly. To address these issues we propose an enhanced KH (EKH) to improve the global searching and convergence speed performance of KH. To obtain a more accurate model of the krill behavior, an updated crossover operator is added to the approach. We can guarantee the krill group are diversiform at the early stage of iterations, and have a good performance in local searching ability at the later stage of iterations. The recognition results of EKH are compared with those of other optimization algorithms (including KH, chaotic KH (CKH), quantum-behaved particle swarm optimization (QPSO), particle swarm optimization (PSO) and genetic algorithm (GA)), and we can find that EKH is better than the other considered methods. The research results verify that EKH not only significantly improves the performance of our E-nose system, but also provides a good beginning and theoretical basis for further study about other improved krill algorithms’ applications in all E-nose application areas. PMID:27529247

Parametrization of turbulence models using 3DVAR data assimilation in laboratory conditions

NASA Astrophysics Data System (ADS)

Olbert, A. I.; Nash, S.; Ragnoli, E.; Hartnett, M.

2013-12-01

In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ɛ model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ɛ model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. Such analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows. This research further demonstrates how 3DVAR can be utilized to identify and quantify shortcomings of the numerical model and consequently to improve forecasting by correct parameterization of the turbulence models. Such improvements may greatly benefit physical oceanography in terms of understanding and monitoring of coastal systems and the engineering sector through applications in coastal structure design, marine renewable energy and pollutant transport.

Effect of Aptensio XR (Methylphenidate HCl Extended-Release) Capsules on Sleep in Children with Attention-Deficit/Hyperactivity Disorder.

PubMed

Owens, Judith; Weiss, Margaret; Nordbrock, Earl; Mattingly, Greg; Wigal, Sharon; Greenhill, Laurence L; Chang, Wei-Wei; Childress, Ann; Kupper, Robert J; Adjei, Akwete

2016-12-01

To evaluate measures of sleep (exploratory endpoints) in two pivotal studies of a multilayer bead extended-release methylphenidate (MPH-MLR) treatment of attention-deficit/hyperactivity disorder in children. Study 1 evaluated the time course of response to MPH-MLR (n = 26) patients in an analog classroom setting through four phases: screening (≤28 days), open label (OL) dose optimization (4 weeks), double-blind (DB) crossover (2 weeks; placebo vs. optimized dose), and follow-up call. Study 2 was a forced-dose parallel evaluation of MPH-MLR (n = 230) in four phases: screening (≤28 days), DB (1 week; placebo or MPH-MLR 10, 15, 20, or 40 mg/day), OL dose optimization (11 weeks), and follow-up call. Sleep was evaluated by parents using the Children's or Adolescent Sleep Habits Questionnaire (CSHQ or ASHQ) during the DB and OL phases. DB analysis: Study 1 (crossover), analysis of variance; Study 2, analysis of covariance. OL analysis: paired t-test. DB: treatments were significantly different in Study 1 only for CSHQ Sleep Onset Delay (MPH-MLR, 1.90 vs. placebo, 1.34; p = 0.0046, placebo was better), and Study 2 for CSHQ Parasomnias (treatment, p = 0.0295), but no MPH-MLR treatment was different from placebo (pairwise MPH-MLR treatment to placebo, all p ≥ 0.170). OL: CSHQ total and Bedtime Resistance, Sleep Duration, Sleep Anxiety, Night Wakings, Parasomnias, and Sleep-disordered Breathing subscales decreased (improved, Study 1) significant only for CSHQ Night Wakings (p < 0.05); in Study 2 CSHQ total and Bedtime Resistance, Sleep Duration, Night Wakings, Parasomnias, and Daytime Sleepiness, and ASHQ total, Bedtime, Sleep Behavior, and Morning Waking all significantly improved (p < 0.05). In both studies, there was minimal negative impact of MPH-MLR on sleep during the brief DB phase and none during the longer duration OL phase. Some measures of sleep improved with optimized MPH-MLR dose.

Spectral optimized asymmetric segmented phase-only correlation filter.

PubMed

Leonard, I; Alfalou, A; Brosseau, C

2012-05-10

We suggest a new type of optimized composite filter, i.e., the asymmetric segmented phase-only filter (ASPOF), for improving the effectiveness of a VanderLugt correlator (VLC) when used for face identification. Basically, it consists in merging several reference images after application of a specific spectral optimization method. After segmentation of the spectral filter plane to several areas, each area is assigned to a single winner reference according to a new optimized criterion. The point of the paper is to show that this method offers a significant performance improvement on standard composite filters for face identification. We first briefly revisit composite filters [adapted, phase-only, inverse, compromise optimal, segmented, minimum average correlation energy, optimal trade-off maximum average correlation, and amplitude-modulated phase-only (AMPOF)], which are tools of choice for face recognition based on correlation techniques, and compare their performances with those of the ASPOF. We illustrate some of the drawbacks of current filters for several binary and grayscale image identifications. Next, we describe the optimization steps and introduce the ASPOF that can overcome these technical issues to improve the quality and the reliability of the correlation-based decision. We derive performance measures, i.e., PCE values and receiver operating characteristic curves, to confirm consistency of the results. We numerically find that this filter increases the recognition rate and decreases the false alarm rate. The results show that the discrimination of the ASPOF is comparable to that of the AMPOF, but the ASPOF is more robust than the trade-off maximum average correlation height against rotation and various types of noise sources. Our method has several features that make it amenable to experimental implementation using a VLC.

A new sol-gel processing routine without chelating agents for preparing highly transparent solutions and nanothin films: engineering the role of chemistry to design the process

NASA Astrophysics Data System (ADS)

Ashiri, Rouholah

2015-01-01

The great sensitivity of titanium alkoxides to hydrolysis makes their sol-gel transformation very fast and thus difficult to control. A method was proposed to alleviate this drawback. Preparation of highly transparent solutions and nanothin films is another objective of the present research. Employing nanoemulsion method and optimizing the processing conditions, a clear solution of well-dispersed nanosized particles was obtained. With the proposed process BaTiO3 precursor sols and nanothin films with enhanced optical transparency towards the visible were prepared. The optimal formulation of the sol consists of acetic acid, barium acetate, 2-propanol, TTIP and deionized water with 6:1:1:1:150 M ratios, respectively. It was found that the reduction of the temperature in the initial stage of mixing of precursors controls the size of the forming species and accordingly improves the stability and transparency of the sol. The results also showed that the applied modifications and optimizations significantly downsize the particles within the sol to the nanometric scale and accordingly result in a significant improvement in the optical response of the products.

Optimal electrode selection for multi-channel electroencephalogram based detection of auditory steady-state responses.

PubMed

Van Dun, Bram; Wouters, Jan; Moonen, Marc

2009-07-01

Auditory steady-state responses (ASSRs) are used for hearing threshold estimation at audiometric frequencies. Hearing impaired newborns, in particular, benefit from this technique as it allows for a more precise diagnosis than traditional techniques, and a hearing aid can be better fitted at an early age. However, measurement duration of current single-channel techniques is still too long for clinical widespread use. This paper evaluates the practical performance of a multi-channel electroencephalogram (EEG) processing strategy based on a detection theory approach. A minimum electrode set is determined for ASSRs with frequencies between 80 and 110 Hz using eight-channel EEG measurements of ten normal-hearing adults. This set provides a near-optimal hearing threshold estimate for all subjects and improves response detection significantly for EEG data with numerous artifacts. Multi-channel processing does not significantly improve response detection for EEG data with few artifacts. In this case, best response detection is obtained when noise-weighted averaging is applied on single-channel data. The same test setup (eight channels, ten normal-hearing subjects) is also used to determine a minimum electrode setup for 10-Hz ASSRs. This configuration allows to record near-optimal signal-to-noise ratios for 80% of subjects.

Performance optimization of dye-sensitized solar cells by multilayer gradient scattering architecture of TiO2 microspheres.

PubMed

Li, Mingyue; Li, Meiya; Liu, Xiaolian; Bai, Lihua; Luoshan, Mengdai; Lei, Wen; Wang, Zhen; Zhu, Yongdan; Zhao, Xingzhong

2017-01-20

TiO 2 microspheres (TMSs) with unique hierarchical structure and unusual high specific surface area are synthesized and incorporated into a photoanode in various TMS multilayer gradient architectures to form novel photoanodes and dye-sensitized solar cells (DSSCs). Significant influences of these architectures on the photoelectric properties of DSSCs are obtained. The DSSC with the optimal TMS gradient-ascent architecture of M036 has the largest amounts of dye absorption, strongest light absorption, longest electron lifetime and lowest electron recombination, and thus exhibits the maximum short circuit current density (J sc ) of 16.49 mA cm -2 and photoelectric conversion efficiency (η) of 7.01%, notably higher than those of conventional DSSCs by 21% and 22%, respectively. These notable improvements in the properties of DSSCs can be attributed to the TMS gradient-ascent architecture of M036 which can most effectively increase dye absorption and localize incident light within the photoanode by the light scattering of TMSs, and thus utilize the incident light thoroughly. This study provides an optimized and universal configuration for the scattering microspheres incorporated in the hybrid photoanode, which can significantly improve the performance of DSSCs.

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Englander, Arnold C.

2014-01-01

Trajectory optimization methods using monotonic basin hopping (MBH) have become well developed during the past decade [1, 2, 3, 4, 5, 6]. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing random variable (RV)s from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by J. Englander [3, 6]) significantly improves monotonic basin hopping (MBH) performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness. Efficiency is finding better solutions in less time. Robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive random walks (RWs) originally developed in the field of statistical physics.

Optimized survey design for electrical resistivity tomography: combined optimization of measurement configuration and electrode placement

NASA Astrophysics Data System (ADS)

Uhlemann, Sebastian; Wilkinson, Paul B.; Maurer, Hansruedi; Wagner, Florian M.; Johnson, Timothy C.; Chambers, Jonathan E.

2018-07-01

Within geoelectrical imaging, the choice of measurement configurations and electrode locations is known to control the image resolution. Previous work has shown that optimized survey designs can provide a model resolution that is superior to standard survey designs. This paper demonstrates a methodology to optimize resolution within a target area, while limiting the number of required electrodes, thereby selecting optimal electrode locations. This is achieved by extending previous work on the `Compare-R' algorithm, which by calculating updates to the resolution matrix optimizes the model resolution in a target area. Here, an additional weighting factor is introduced that allows to preferentially adding measurement configurations that can be acquired on a given set of electrodes. The performance of the optimization is tested on two synthetic examples and verified with a laboratory study. The effect of the weighting factor is investigated using an acquisition layout comprising a single line of electrodes. The results show that an increasing weight decreases the area of improved resolution, but leads to a smaller number of electrode positions. Imaging results superior to a standard survey design were achieved using 56 per cent fewer electrodes. The performance was also tested on a 3-D acquisition grid, where superior resolution within a target at the base of an embankment was achieved using 22 per cent fewer electrodes than a comparable standard survey. The effect of the underlying resistivity distribution on the performance of the optimization was investigated and it was shown that even strong resistivity contrasts only have minor impact. The synthetic results were verified in a laboratory tank experiment, where notable image improvements were achieved. This work shows that optimized surveys can be designed that have a resolution superior to standard survey designs, while requiring significantly fewer electrodes. This methodology thereby provides a means for improving the efficiency of geoelectrical imaging.

Optimized survey design for Electrical Resistivity Tomography: combined optimization of measurement configuration and electrode placement

NASA Astrophysics Data System (ADS)

Uhlemann, Sebastian; Wilkinson, Paul B.; Maurer, Hansruedi; Wagner, Florian M.; Johnson, Timothy C.; Chambers, Jonathan E.

2018-03-01

Within geoelectrical imaging, the choice of measurement configurations and electrode locations is known to control the image resolution. Previous work has shown that optimized survey designs can provide a model resolution that is superior to standard survey designs. This paper demonstrates a methodology to optimize resolution within a target area, while limiting the number of required electrodes, thereby selecting optimal electrode locations. This is achieved by extending previous work on the `Compare-R' algorithm, which by calculating updates to the resolution matrix optimizes the model resolution in a target area. Here, an additional weighting factor is introduced that allows to preferentially adding measurement configurations that can be acquired on a given set of electrodes. The performance of the optimization is tested on two synthetic examples and verified with a laboratory study. The effect of the weighting factor is investigated using an acquisition layout comprising a single line of electrodes. The results show that an increasing weight decreases the area of improved resolution, but leads to a smaller number of electrode positions. Imaging results superior to a standard survey design were achieved using 56 per cent fewer electrodes. The performance was also tested on a 3D acquisition grid, where superior resolution within a target at the base of an embankment was achieved using 22 per cent fewer electrodes than a comparable standard survey. The effect of the underlying resistivity distribution on the performance of the optimization was investigated and it was shown that even strong resistivity contrasts only have minor impact. The synthetic results were verified in a laboratory tank experiment, where notable image improvements were achieved. This work shows that optimized surveys can be designed that have a resolution superior to standard survey designs, while requiring significantly fewer electrodes. This methodology thereby provides a means for improving the efficiency of geoelectrical imaging.

Optimized management of heart failure patients aged 80 years or more improves outcomes versus usual care: The HF80 randomized trial.

PubMed

Vorilhon, Charles; Jean, Frédéric; Mulliez, Aurélien; Clerfond, Guillaume; Pereira, Bruno; Sapin, Vincent; Souteyrand, Géraud; Citron, Bernard; Motreff, Pascal; Lusson, Jean-René; Eschalier, Romain

2016-12-01

The prevalence and incidence of heart failure (HF) in elderly patients are increasing worldwide. Management of HF with reduced ejection fraction (HF-REF) in patients aged 80 years or more follows international guidelines, despite the lack of a dedicated study in this frail population. To determine whether optimized management of HF-REF in patients aged 80 years or more can improve quality of life at 6 months. Patients aged 80 years or more hospitalized for acute HF-REF were randomized prospectively into an optimized group or a control group (usual care). All patients benefitted from the same in-hospital management. Optimized group patients were also managed at 3, 6 and 9 weeks, and 3, 6, 9 and 12 months after initial hospitalization, to optimize HF-REF treatment. The primary endpoint was quality of life at 6 months. The trial was stopped prematurely, according to prespecified rules and an independent data monitoring board, after 34 patients were included (n=17 in each group). There was no difference in quality of life at baseline and at 6 months between the two groups (P=0.14 and 0.64, respectively), although a significant improvement was observed between baseline and 6 months in the optimized group compared with the control group: -20.2±25.2 (P=0.01) versus -9.9±19.0 (P=0.19). Mortality at 12 months was lower in the optimized group (17.7% vs 47.1%; P=0.03). There was no increase in acute renal failure, hyperkalaemia or falls in the optimized group (P=0.49, 1 and 1, respectively). Optimizing the management of HF-REF in patients aged 80 years or more, according to the modalities of the HF80 study, seems to be both effective and safe. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Synthesis of Platinum-nickel Nanowires and Optimization for Oxygen Reduction Performance.

PubMed

Alia, Shaun M; Pivovar, Bryan S

2018-04-27

Platinum-nickel (Pt-Ni) nanowires were developed as fuel cell electrocatalysts, and were optimized for the performance and durability in the oxygen reduction reaction. Spontaneous galvanic displacement was used to deposit Pt layers onto Ni nanowire substrates. The synthesis approach produced catalysts with high specific activities and high Pt surface areas. Hydrogen annealing improved Pt and Ni mixing and specific activity. Acid leaching was used to preferentially remove Ni near the nanowire surface, and oxygen annealing was used to stabilize near-surface Ni, improving durability and minimizing Ni dissolution. These protocols detail the optimization of each post-synthesis processing step, including hydrogen annealing to 250 °C, exposure to 0.1 M nitric acid, and oxygen annealing to 175 °C. Through these steps, Pt-Ni nanowires produced increased activities more than an order of magnitude than Pt nanoparticles, while offering significant durability improvements. The presented protocols are based on Pt-Ni systems in the development of fuel cell catalysts. These techniques have also been used for a variety of metal combinations, and can be applied to develop catalysts for a number of electrochemical processes.

Optimizing a dynamical decoupling protocol for solid-state electronic spin ensembles in diamond

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

Farfurnik, D.; Jarmola, A.; Pham, L. M.

2015-08-24

In this study, we demonstrate significant improvements of the spin coherence time of a dense ensemble of nitrogen-vacancy (NV) centers in diamond through optimized dynamical decoupling (DD). Cooling the sample down to 77 K suppresses longitudinal spin relaxation T 1 effects and DD microwave pulses are used to increase the transverse coherence time T 2 from ~0.7ms up to ~30ms. Furthermore, we extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. Following a theoretical and experimental characterization of pulse and detuning errors, we compare the performance of various DD protocols. We also identify that themore » optimal control scheme for preserving an arbitrary spin state is a recursive protocol, the concatenated version of the XY8 pulse sequence. The improved spin coherence might have an immediate impact on improvements of the sensitivities of ac magnetometry. Moreover, the protocol can be used on denser diamond samples to increase coherence times up to NV-NV interaction time scales, a major step towards the creation of quantum collective NV spin states.« less

In-flight performance optimization for rotorcraft with redundant controls

NASA Astrophysics Data System (ADS)

Ozdemir, Gurbuz Taha

A conventional helicopter has limits on performance at high speeds because of the limitations of main rotor, such as compressibility issues on advancing side or stall issues on retreating side. Auxiliary lift and thrust components have been suggested to improve performance of the helicopter substantially by reducing the loading on the main rotor. Such a configuration is called the compound rotorcraft. Rotor speed can also be varied to improve helicopter performance. In addition to improved performance, compound rotorcraft and variable RPM can provide a much larger degree of control redundancy. This additional redundancy gives the opportunity to further enhance performance and handling qualities. A flight control system is designed to perform in-flight optimization of redundant control effectors on a compound rotorcraft in order to minimize power required and extend range. This "Fly to Optimal" (FTO) control law is tested in simulation using the GENHEL model. A model of the UH-60, a compound version of the UH-60A with lifting wing and vectored thrust ducted propeller (VTDP), and a generic compound version of the UH-60A with lifting wing and propeller were developed and tested in simulation. A model following dynamic inversion controller is implemented for inner loop control of roll, pitch, yaw, heave, and rotor RPM. An outer loop controller regulates airspeed and flight path during optimization. A Golden Section search method was used to find optimal rotor RPM on a conventional helicopter, where the single redundant control effector is rotor RPM. The FTO builds off of the Adaptive Performance Optimization (APO) method of Gilyard by performing low frequency sweeps on a redundant control for a fixed wing aircraft. A method based on the APO method was used to optimize trim on a compound rotorcraft with several redundant control effectors. The controller can be used to optimize rotor RPM and compound control effectors through flight test or simulations in order to establish a schedule. The method has been expanded to search a two-dimensional control space. Simulation results demonstrate the ability to maximize range by optimizing stabilator deflection and an airspeed set point. Another set of results minimize power required in high speed flight by optimizing collective pitch and stabilator deflection. Results show that the control laws effectively hold the flight condition while the FTO method is effective at improving performance. Optimizations show there can be issues when the control laws regulating altitude push the collective control towards it limits. So a modification was made to the control law to regulate airspeed and altitude using propeller pitch and angle of attack while the collective is held fixed or used as an optimization variable. A dynamic trim limit avoidance algorithm is applied to avoid control saturation in other axes during optimization maneuvers. Range and power optimization FTO simulations are compared with comprehensive sweeps of trim solutions and FTO optimization shown to be effective and reliable in reaching an optimal when optimizing up to two redundant controls. Use of redundant controls is shown to be beneficial for improving performance. The search method takes almost 25 minutes of simulated flight for optimization to be complete. The optimization maneuver itself can sometimes drive the power required to high values, so a power limit is imposed to restrict the search to avoid conditions where power is more than5% higher than that of the initial trim state. With this modification, the time the optimization maneuver takes to complete is reduced down to 21 minutes without any significant change in the optimal power value.

Optimized tomography of continuous variable systems using excitation counting

NASA Astrophysics Data System (ADS)

Shen, Chao; Heeres, Reinier W.; Reinhold, Philip; Jiang, Luyao; Liu, Yi-Kai; Schoelkopf, Robert J.; Jiang, Liang

2016-11-01

We propose a systematic procedure to optimize quantum state tomography protocols for continuous variable systems based on excitation counting preceded by a displacement operation. Compared with conventional tomography based on Husimi or Wigner function measurement, the excitation counting approach can significantly reduce the number of measurement settings. We investigate both informational completeness and robustness, and provide a bound of reconstruction error involving the condition number of the sensing map. We also identify the measurement settings that optimize this error bound, and demonstrate that the improved reconstruction robustness can lead to an order-of-magnitude reduction of estimation error with given resources. This optimization procedure is general and can incorporate prior information of the unknown state to further simplify the protocol.

Impact of Pharmacy Practice Model Expansion on Pharmacokinetic Services: Optimization of Vancomycin Dosing and Improved Patient Safety.

PubMed

Han, Zhe; Pettit, Natasha N; Landon, Emily M; Brielmaier, Benjamin D

2017-04-01

Background: The impact of pharmacy interventions on optimizing vancomycin therapy has been described, however interventions vary among studies and the most optimal pharmacy practice model (PPM) for pharmacokinetic (PK) services has not been established. Objective: The purpose of this study is to demonstrate the value of 24 hours a day, 7 days a week (24/7) PK services. Methods: New PK services were implemented in 2 phases with institutional PPM expansion. Phase 1 included universal monitoring by pharmacists with recommendations made to prescribers during business hours. Phase 2 expanded clinical pharmacists' coverage to 24/7 and provided an optional 24/7 pharmacist-managed PK consult service. We compared vancomycin therapeutic trough attainment, dosing, and clinical and safety outcomes between phases 1 and 2 in adult inpatients receiving therapeutic intravenous vancomycin. Results. One hundred and fifty patients were included in each phase. Phase 2 had a greater proportion of vancomycin courses with therapeutic initial trough concentrations (27.5% vs 46.1%; p = 0.002), higher initial trough concentrations (10.9 mcg/mL vs 16.4 mcg/mL; p < 0.001), and optimized initial vancomycin dosing (13.5 mg/kg vs 16.2 mg/kg; p < 0.001). Phase 2 also saw significant reduction in the incidence of vancomycin-associated nephrotoxicity (21.1% vs 11.7%; p = 0.038). Dose optimization and improvement in initial target trough attainment were most notable among intensive care unit (ICU) patients. Conclusions. Our study demonstrated that 24/7 PK services implemented with institutional PPM expansion optimized vancomycin target trough attainment and improved patient safety.

An improved marriage in honey bees optimization algorithm for single objective unconstrained optimization.

PubMed

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms.

Impact of database quality in knowledge-based treatment planning for prostate cancer.

PubMed

Wall, Phillip D H; Carver, Robert L; Fontenot, Jonas D

2018-03-13

This article investigates dose-volume prediction improvements in a common knowledge-based planning (KBP) method using a Pareto plan database compared with using a conventional, clinical plan database. Two plan databases were created using retrospective, anonymized data of 124 volumetric modulated arc therapy (VMAT) prostate cancer patients. The clinical plan database (CPD) contained planning data from each patient's clinically treated VMAT plan, which were manually optimized by various planners. The multicriteria optimization database (MCOD) contained Pareto-optimal plan data from VMAT plans created using a standardized multicriteria optimization protocol. Overlap volume histograms, incorporating fractional organ at risk volumes only within the treatment fields, were computed for each patient and used to match new patient anatomy to similar database patients. For each database patient, CPD and MCOD KBP predictions were generated for D 10 , D 30 , D 50 , D 65 , and D 80 of the bladder and rectum in a leave-one-out manner. Prediction achievability was evaluated through a replanning study on a subset of 31 randomly selected database patients using the best KBP predictions, regardless of plan database origin, as planning goals. MCOD predictions were significantly lower than CPD predictions for all 5 bladder dose-volumes and rectum D 50 (P = .004) and D 65 (P < .001), whereas CPD predictions for rectum D 10 (P = .005) and D 30 (P < .001) were significantly less than MCOD predictions. KBP predictions were statistically achievable in the replans for all predicted dose-volumes, excluding D 10 of bladder (P = .03) and rectum (P = .04). Compared with clinical plans, replans showed significant average reductions in D mean for bladder (7.8 Gy; P < .001) and rectum (9.4 Gy; P < .001), while maintaining statistically similar planning target volume, femoral head, and penile bulb dose. KBP dose-volume predictions derived from Pareto plans were more optimal overall than those resulting from manually optimized clinical plans, which significantly improved KBP-assisted plan quality. This work investigates how the plan quality of knowledge databases affects the performance and achievability of dose-volume predictions from a common knowledge-based planning approach for prostate cancer. Bladder and rectum dose-volume predictions derived from a database of standardized Pareto-optimal plans were compared with those derived from clinical plans manually designed by various planners. Dose-volume predictions from the Pareto plan database were significantly lower overall than those from the clinical plan database, without compromising achievability. Copyright © 2018 Elsevier Inc. All rights reserved.

Hybrid Power Management (HPM) Program Resulted in Several New Applications

NASA Technical Reports Server (NTRS)

Eichenberg, Dennis J.

2003-01-01

Hybrid Power Management (HPM) is the innovative integration of diverse, state-of-the-art power devices in an optimal configuration for space and terrestrial applications. The appropriate application and control of the various power devices significantly improves overall system performance and efficiency. The advanced power devices include ultracapacitors, fuel cells, and photovoltaics. HPM has extremely wide potential with applications from nanowatts to megawatts. Applications include power generation, transportation systems, biotechnology systems, and space power systems. HPM has the potential to significantly alleviate global energy concerns, improve the environment, and stimulate the economy.

Co-optimization of lithographic and patterning processes for improved EPE performance

NASA Astrophysics Data System (ADS)

Maslow, Mark J.; Timoshkov, Vadim; Kiers, Ton; Jee, Tae Kwon; de Loijer, Peter; Morikita, Shinya; Demand, Marc; Metz, Andrew W.; Okada, Soichiro; Kumar, Kaushik A.; Biesemans, Serge; Yaegashi, Hidetami; Di Lorenzo, Paolo; Bekaert, Joost P.; Mao, Ming; Beral, Christophe; Larivière, Stephane

2017-03-01

Complimentary lithography is already being used for advanced logic patterns. The tight pitches for 1D Metal layers are expected to be created using spacer based multiple patterning ArF-i exposures and the more complex cut/block patterns are made using EUV exposures. At the same time, control requirements of CDU, pattern shift and pitch-walk are approaching sub-nanometer levels to meet edge placement error (EPE) requirements. Local variability, such as Line Edge Roughness (LER), Local CDU, and Local Placement Error (LPE), are dominant factors in the total Edge Placement error budget. In the lithography process, improving the imaging contrast when printing the core pattern has been shown to improve the local variability. In the etch process, it has been shown that the fusion of atomic level etching and deposition can also improve these local variations. Co-optimization of lithography and etch processing is expected to further improve the performance over individual optimizations alone. To meet the scaling requirements and keep process complexity to a minimum, EUV is increasingly seen as the platform for delivering the exposures for both the grating and the cut/block patterns beyond N7. In this work, we evaluated the overlay and pattern fidelity of an EUV block printed in a negative tone resist on an ArF-i SAQP grating. High-order Overlay modeling and corrections during the exposure can reduce overlay error after development, a significant component of the total EPE. During etch, additional degrees of freedom are available to improve the pattern placement error in single layer processes. Process control of advanced pitch nanoscale-multi-patterning techniques as described above is exceedingly complicated in a high volume manufacturing environment. Incorporating potential patterning optimizations into both design and HVM controls for the lithography process is expected to bring a combined benefit over individual optimizations. In this work we will show the EPE performance improvement for a 32nm pitch SAQP + block patterned Metal 2 layer by cooptimizing the lithography and etch processes. Recommendations for further improvements and alternative processes will be given.

Effects of hard mask etch on final topography of advanced phase shift masks

NASA Astrophysics Data System (ADS)

Hortenbach, Olga; Rolff, Haiko; Lajn, Alexander; Baessler, Martin

2017-07-01

Continuous shrinking of the semiconductor device dimensions demands steady improvements of the lithographic resolution on wafer level. These requirements challenge the photomask industry to further improve the mask quality in all relevant printing characteristics. In this paper topography of the Phase Shift Masks (PSM) was investigated. Effects of hard mask etch on phase shift uniformity and mask absorber profile were studied. Design of experiments method (DoE) was used for the process optimization, whereas gas composition, bias power of the hard mask main etch and bias power of the over-etch were varied. In addition, influence of the over-etch time was examined at the end of the experiment. Absorber depth uniformity, sidewall angle (SWA), reactive ion etch lag (RIE lag) and through pitch (TP) dependence were analyzed. Measurements were performed by means of Atomic-force microscopy (AFM) using critical dimension (CD) mode with a boot-shaped tip. Scanning electron microscope (SEM) cross-section images were prepared to verify the profile quality. Finally CD analysis was performed to confirm the optimal etch conditions. Significant dependence of the absorber SWA on hard mask (HM) etch conditions was observed revealing an improvement potential for the mask absorber profile. It was found that hard mask etch can leave a depth footprint in the absorber layer. Thus, the etch depth uniformity of hard mask etch is crucial for achieving a uniform phase shift over the active mask area. The optimized hard mask etch process results in significantly improved mask topography without deterioration of tight CD specifications.

A Rapid Aerodynamic Design Procedure Based on Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

2001-01-01

An aerodynamic design procedure that uses neural networks to model the functional behavior of the objective function in design space has been developed. This method incorporates several improvements to an earlier method that employed a strategy called parameter-based partitioning of the design space in order to reduce the computational costs associated with design optimization. As with the earlier method, the current method uses a sequence of response surfaces to traverse the design space in search of the optimal solution. The new method yields significant reductions in computational costs by using composite response surfaces with better generalization capabilities and by exploiting synergies between the optimization method and the simulation codes used to generate the training data. These reductions in design optimization costs are demonstrated for a turbine airfoil design study where a generic shape is evolved into an optimal airfoil.

Language Recognition via Sparse Coding

DTIC Science & Technology

2016-09-08

a posteriori (MAP) adaptation scheme that further optimizes the discriminative quality of sparse-coded speech fea - tures. We empirically validate the...significantly improve the discriminative quality of sparse-coded speech fea - tures. In Section 4, we evaluate the proposed approaches against an i-vector

Improving striping operations through system optimization - phase 2 : final report.

DOT National Transportation Integrated Search

2016-07-01

Striping operations generate a significant workload for MoDOT maintenance operations. The requirement for each striping crew : to replenish its stock of paint and other consumable items from a bulk storage facility, along with the necessity to make s...

Impact of a phenytoin loading dose program in the emergency department.

PubMed

Brancaccio, Adam; Giuliano, Christopher; McNorton, Kelly; Delgado, George

2014-11-01

The use of a combined physician-and pharmacist-directed phenytoin loading dose program in an emergency department (ED) was evaluated. This single-center, observational, preimplementation-postimplementation study evaluated adult patients who received a phenytoin loading dose in the ED. The primary outcome compared the proportion of optimal phenytoin loading doses in the preimplementation and postimplementation groups. The postimplementation group was further stratified into pharmacist- and prescriber-dosing groups. Other outcomes evaluated included the numbers of appropriate serum phenytoin concentrations measured, adverse drug reactions (ADRs), and recurrence of seizures within 24 hours of loading dose administration in the preimplementation and postimplementation groups. There was no difference in the proportion of optimal phenytoin loading doses between the preimplementation and postimplementation groups (50% versus 62%, respectively; p=0.19). When stratified by individual groups, the rate of optimal phenytoin loading doses increased by 64% in the postimplementation pharmacist group (50% versus 82%, p=0.007), while the rate in the prescriber-dosing group remained relatively unchanged (50% versus 49%, p=0.91). The number of appropriate serum phenytoin concentrations significantly improved in the postimplementation versus preimplementation group (65% versus 40%, p=0.025). Rates of ADRs and recurrence of seizures did not differ across the study groups. No change in the percentage of optimal phenytoin loading doses in the ED was observed after implementation of a combined pharmacist- and physician- dosing program. When stratified into pharmacist or prescriber dosing, the pharmacist-led dosing program significantly improved the proportion of patients who received optimal phenytoin loading doses. Copyright © 2014 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Big Data-Based Approach to Detect, Locate, and Enhance the Stability of an Unplanned Microgrid Islanding

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

Jiang, Huaiguang; Li, Yan; Zhang, Yingchen

In this paper, a big data-based approach is proposed for the security improvement of an unplanned microgrid islanding (UMI). The proposed approach contains two major steps: the first step is big data analysis of wide-area monitoring to detect a UMI and locate it; the second step is particle swarm optimization (PSO)-based stability enhancement for the UMI. First, an optimal synchrophasor measurement device selection (OSMDS) and matching pursuit decomposition (MPD)-based spatial-temporal analysis approach is proposed to significantly reduce the volume of data while keeping appropriate information from the synchrophasor measurements. Second, a random forest-based ensemble learning approach is trained to detectmore » the UMI. When combined with grid topology, the UMI can be located. Then the stability problem of the UMI is formulated as an optimization problem and the PSO is used to find the optimal operational parameters of the UMI. An eigenvalue-based multiobjective function is proposed, which aims to improve the damping and dynamic characteristics of the UMI. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed approach.« less

Lipopolysaccharide based oral nanocarriers for the improvement of bioavailability and anticancer efficacy of curcumin.

PubMed

Chaurasia, Sundeep; Patel, Ravi R; Chaubey, Pramila; Kumar, Nagendra; Khan, Gayasuddin; Mishra, Brahmeshwar

2015-10-05

Soluthin MD(®), a unique phosphatidylcholine-maltodextrin based hydrophilic lipopolysaccharide, which exhibits superior biocompatibility and bioavailability enhancer properties for poorly water soluble drug(s). Curcumin (CUR) is a potential natural anticancer drug with low bioavailability due to poor aqueous solubility. The study aims at formulation and optimization of CUR loaded lipopolysaccharide nanocarriers (C-LPNCs) to enhance oral bioavailability and anticancer efficacy in colon-26 tumor-bearing mice in vitro and in vivo. The Optimized C-LPNCs demonstrated favorable mean particle size (108 ± 3.4 nm) and percent entrapment efficiency (65.29 ± 1.0%). Pharmacokinetic parameters revealed ∼130-fold increase in oral bioavailability and cytotoxicity studies demonstrated ∼23-fold reduction in 50% cell growth inhibition when treated with optimized C-LPNCs as compared to pure CUR. In vivo anticancer study performed with optimized C-LPNCs showed significant increase in efficacy compared with pure CUR. Thus, lipopolysaccharide nanocarriers show potential delivery strategy to improve oral bioavailability and anticancer efficacy of CUR in the treatment of colorectal cancer. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimizing Diagnostic Imaging in the Emergency Department

PubMed Central

Mills, Angela M.; Raja, Ali S.; Marin, Jennifer R.

2015-01-01

While emergency diagnostic imaging use has increased significantly, there is a lack of evidence for corresponding improvements in patient outcomes. Optimizing emergency department (ED) diagnostic imaging has the potential to improve the quality, safety, and outcomes of ED patients, but to date, there have not been any coordinated efforts to further our evidence-based knowledge in this area. The objective of this article is to discuss six aspects of diagnostic imaging in order to provide background information on the underlying framework for the 2015 Academic Emergency Medicine consensus conference, “Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization.” The consensus conference aims to generate a high priority research agenda for emergency diagnostic imaging that will inform the design of future investigations. The six components herein will serve as the group topics for the conference: 1) patient-centered outcomes research; 2) clinical decision rules; 3) training, education, and competency; 4) knowledge translation and barriers to image optimization; 5) use of administrative data; and 6) comparative effectiveness research: alternatives to traditional CT use. PMID:25731864

Optimizing diagnostic imaging in the emergency department.

PubMed

Mills, Angela M; Raja, Ali S; Marin, Jennifer R

2015-05-01

While emergency diagnostic imaging use has increased significantly, there is a lack of evidence for corresponding improvements in patient outcomes. Optimizing emergency department (ED) diagnostic imaging has the potential to improve the quality, safety, and outcomes of ED patients, but to date, there have not been any coordinated efforts to further our evidence-based knowledge in this area. The objective of this article is to discuss six aspects of diagnostic imaging to provide background information on the underlying framework for the 2015 Academic Emergency Medicine consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization." The consensus conference aims to generate a high priority research agenda for emergency diagnostic imaging that will inform the design of future investigations. The six components herein will serve as the group topics for the conference: 1) patient-centered outcomes research; 2) clinical decision rules; 3) training, education, and competency; 4) knowledge translation and barriers to image optimization; 5) use of administrative data; and 6) comparative effectiveness research: alternatives to traditional CT use. © 2015 by the Society for Academic Emergency Medicine.

Performance of arrays of direct-driven wave energy converters under optimal power take-off damping

NASA Astrophysics Data System (ADS)

Wang, Liguo; Engström, Jens; Leijon, Mats; Isberg, Jan

2016-08-01

It is well known that the total power converted by a wave energy farm is influenced by the hydrodynamic interactions between wave energy converters, especially when they are close to each other. Therefore, to improve the performance of a wave energy farm, the hydrodynamic interaction between converters must be considered, which can be influenced by the power take-off damping of individual converters. In this paper, the performance of arrays of wave energy converters under optimal hydrodynamic interaction and power take-off damping is investigated. This is achieved by coordinating the power take-off damping of individual converters, resulting in optimal hydrodynamic interaction as well as higher production of time-averaged power converted by the farm. Physical constraints on motion amplitudes are considered in the solution, which is required for the practical implementation of wave energy converters. Results indicate that the natural frequency of a wave energy converter under optimal damping will not vary with sea states, but the production performance of a wave energy farm can be improved significantly while satisfying the motion constraints.

Optimization of a Small Tropomyosin-related Kinase B (TrkB) Agonist 7,8-Dihydroxyflavone Active in Mouse Models of Depression

PubMed Central

Liu, Xia; Chan, Chi-Bun; Qi, Qi; Xiao, Ge; Luo, Hongbo R.; He, Xiaolin; Ye, Keqiang

2012-01-01

Structure-activity relationship study shows that the catechol group in 7,8-dihdyroxyflavone, a selective small TrkB receptor agonist, is critical for the agonistic activity. To improve the poor pharmacokinetic profiles intrinsic to catechol-containing molecules and elevate the agonistic effect of the lead compound, we initiated the lead optimization campaign by synthesizing various bioisosteric derivatives. Here we show that the optimized 2-methyl-8-(4′-(pyrrolidin-1-yl)phenyl)chromeno[7,8-d]imidazol-6(1H)-one derivative possesses the enhanced TrkB stimulatory activity. Chronic oral administration of this compound significantly reduces the immobility in forced swim test and tail suspension test, two classical antidepressant behavioral animal models, which is accompanied by robust TrkB activation in hippocampus of mouse brain. Further, in vitro ADMET studies demonstrate that this compound possesses the improved features compared to the previous lead compound. Hence, this optimized compound may act as a promising lead candidate for in-depth drug development for treating various neurological disorders including depression. PMID:22984948

Clinical evidence on the efficacy and safety of an antioxidant optimized 1.5% salicylic acid (SA) cream in the treatment of facial acne: an open, baseline-controlled clinical study.

PubMed

Zheng, Yue; Wan, Miaojian; Chen, Haiyan; Ye, Congxiu; Zhao, Yue; Yi, Jinling; Xia, Yue; Lai, Wei

2013-05-01

Acne pathogenesis is multifactorial and includes inflammation. Combining active ingredients targeting multiple components of acne pathogenesis may yield optimal outcomes. This study investigates the safety and efficacy of an antioxidant optimized topical salicylic acid (SA) 1.5% cream containing natural skin penetration enhancers in combination with antioxidant activity for treatment of facial acne. A total of 20 patients with facial acne, aged 19-32 years (2 males, 18 females; mean age 26.1 ± 3.2), were enrolled. Patients were treated with topical 1.5% SA cream and instructed to apply the cream as a thin film over the affected area twice daily (in the morning and evening) for 4 weeks. Inflammatory severity, numbers of papules and pustules were evaluated by investigators at day 0 and weekly, and patients ranked their improvement. In all, 95% of patients improved: 20% had complete clearing, 30% had significantly improved, 15% had moderate improvement, 30% had mild improved, and there was no response in 5% of the patients by 4 weeks of treatment. No side effects were observed. This study demonstrates the efficacy and safety of this optimized topical 1.5% SA cream containing natural skin penetration enhancers in combination with antioxidant activity when applied twice daily for the reduction of facial acne; in particular, it is most effective for mild-to-moderate acne. © 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

Multiple model analysis with discriminatory data collection (MMA-DDC): A new method for improving measurement selection

NASA Astrophysics Data System (ADS)

Kikuchi, C.; Ferre, P. A.; Vrugt, J. A.

2011-12-01

Hydrologic models are developed, tested, and refined based on the ability of those models to explain available hydrologic data. The optimization of model performance based upon mismatch between model outputs and real world observations has been extensively studied. However, identification of plausible models is sensitive not only to the models themselves - including model structure and model parameters - but also to the location, timing, type, and number of observations used in model calibration. Therefore, careful selection of hydrologic observations has the potential to significantly improve the performance of hydrologic models. In this research, we seek to reduce prediction uncertainty through optimization of the data collection process. A new tool - multiple model analysis with discriminatory data collection (MMA-DDC) - was developed to address this challenge. In this approach, multiple hydrologic models are developed and treated as competing hypotheses. Potential new data are then evaluated on their ability to discriminate between competing hypotheses. MMA-DDC is well-suited for use in recursive mode, in which new observations are continuously used in the optimization of subsequent observations. This new approach was applied to a synthetic solute transport experiment, in which ranges of parameter values constitute the multiple hydrologic models, and model predictions are calculated using likelihood-weighted model averaging. MMA-DDC was used to determine the optimal location, timing, number, and type of new observations. From comparison with an exhaustive search of all possible observation sequences, we find that MMA-DDC consistently selects observations which lead to the highest reduction in model prediction uncertainty. We conclude that using MMA-DDC to evaluate potential observations may significantly improve the performance of hydrologic models while reducing the cost associated with collecting new data.

Optimizing bowel preparation for colonoscopy: a guide to enhance quality of visualization

PubMed Central

Bechtold, Matthew L.; Mir, Fazia; Puli, Srinivas R.; Nguyen, Douglas L.

2016-01-01

Colonoscopy is an important screening and therapeutic modality for colorectal cancer. Unlike other screening tests, colonoscopy is dependent on pre-procedure bowel preparation. If the bowel preparation is poor, significant pathology may be missed. Many factors are known to improve bowel preparation. This review will highlight those factors that may optimize the bowel preparation, including choice of bowel preparation, grading or scoring of the bowel preparation, special factors that influence preparation, and diet prior to colonoscopy that affects bowel preparation. The aim of the review is to offer suggestions and guide endoscopists on how to optimize the bowel preparation for the patients undergoing colonoscopy. PMID:27065725

Warpage minimization on wheel caster by optimizing process parameters using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Safuan, N. S.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

In injection moulding process, it is important to keep the productivity increase constantly with least of waste produced such as warpage defect. Thus, this study is concerning on minimizing warpage defect on wheel caster part. Apart from eliminating product wastes, this project also giving out best optimization techniques using response surface methodology. This research studied on five parameters A-packing pressure, B-packing time, C-mold temperature, D-melting temperature and E-cooling time. The optimization showed that packing pressure is the most significant parameter. Warpage have been improved 42.64% from 0.6524 mm to 0.3742mm.

Driving external chemistry optimization via operations management principles.

PubMed

Bi, F Christopher; Frost, Heather N; Ling, Xiaolan; Perry, David A; Sakata, Sylvie K; Bailey, Simon; Fobian, Yvette M; Sloan, Leslie; Wood, Anthony

2014-03-01

Confronted with the need to significantly raise the productivity of remotely located chemistry CROs Pfizer embraced a commitment to continuous improvement which leveraged the tools from both Lean Six Sigma and queue management theory to deliver positive measurable outcomes. During 2012 cycle times were reduced by 48% by optimization of the work in progress and conducting a detailed workflow analysis to identify and address pinch points. Compound flow was increased by 29% by optimizing the request process and de-risking the chemistry. Underpinning both achievements was the development of close working relationships and productive communications between Pfizer and CRO chemists. Copyright © 2013 Elsevier Ltd. All rights reserved.

Application of advanced multidisciplinary analysis and optimization methods to vehicle design synthesis

NASA Technical Reports Server (NTRS)

Consoli, Robert David; Sobieszczanski-Sobieski, Jaroslaw

1990-01-01

Advanced multidisciplinary analysis and optimization methods, namely system sensitivity analysis and non-hierarchical system decomposition, are applied to reduce the cost and improve the visibility of an automated vehicle design synthesis process. This process is inherently complex due to the large number of functional disciplines and associated interdisciplinary couplings. Recent developments in system sensitivity analysis as applied to complex non-hierarchic multidisciplinary design optimization problems enable the decomposition of these complex interactions into sub-processes that can be evaluated in parallel. The application of these techniques results in significant cost, accuracy, and visibility benefits for the entire design synthesis process.

Robust optimization of the laser induced damage threshold of dielectric mirrors for high power lasers.

PubMed

Chorel, Marine; Lanternier, Thomas; Lavastre, Éric; Bonod, Nicolas; Bousquet, Bruno; Néauport, Jérôme

2018-04-30

We report on a numerical optimization of the laser induced damage threshold of multi-dielectric high reflection mirrors in the sub-picosecond regime. We highlight the interplay between the electric field distribution, refractive index and intrinsic laser induced damage threshold of the materials on the overall laser induced damage threshold (LIDT) of the multilayer. We describe an optimization method of the multilayer that minimizes the field enhancement in high refractive index materials while preserving a near perfect reflectivity. This method yields a significant improvement of the damage resistance since a maximum increase of 40% can be achieved on the overall LIDT of the multilayer.

Radio frequency discharge with control of plasma potential distribution.

PubMed

Dudnikov, Vadim; Dudnikov, A

2012-02-01

A RF discharge plasma generator with additional electrodes for independent control of plasma potential distribution is proposed. With positive biasing of this ring electrode relative end flanges and longitudinal magnetic field a confinement of fast electrons in the discharge will be improved for reliable triggering of pulsed RF discharge at low gas density and rate of ion generation will be enhanced. In the proposed discharge combination, the electron energy is enhanced by RF field and the fast electron confinement is improved by enhanced positive plasma potential which improves the efficiency of plasma generation significantly. This combination creates a synergetic effect with a significantly improving the plasma generation performance at low gas density. The discharge parameters can be optimized for enhance plasma generation with acceptable electrode sputtering.

Status of integrated multidisciplinary rotorcraft optimization research at the Langley Research Center

NASA Technical Reports Server (NTRS)

Mantay, Wayne R.; Adelman, Howard M.

1990-01-01

This paper describes a joint NASA/Army research activity at the Langley Research Center to develop optimization procedures aimed at improving the rotor blade design process by integrating appropriate disciplines and accounting for important interactions among the disciplines. The activity is being guided by a Steering Committee made up of key NASA and Army researchers and managers. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. The analysis aspects are discussed, and the interdisciplinary interactions are defined in terms of the information that must be transferred among disciplinary analyses as well as the trade-offs between disciplines in determining the details of the design. At this writing, some significant progress has been made. Results given in the paper represent accomplishments in rotor aerodynamic performance optimization for minimum horsepower, rotor dynamic optimization for vibration reduction, approximate analysis of frequencies and mode shapes, rotor structural optimization for minimum weight, and integrated aerodynamic load/dynamics optimization for minimum vibration and weight.

Exceptional oxygen reduction reaction activity and durability of platinum–nickel nanowires through synthesis and post-treatment optimization

DOE PAGES

Alia, Shaun M.; Ngo, Chilan; Shulda, Sarah; ...

2017-04-11

For the first time, extended nanostructured catalysts are demonstrated with both high specific activity (>6000 μA cm Pt –2 at 0.9 V) and high surface areas (>90 m 2 g Pt –1). Platinum–nickel (Pt—Ni) nanowires, synthesized by galvanic displacement, have previously produced surface areas in excess of 90 m 2 g Pt –1, a significant breakthrough in and of itself for extended surface catalysts. Unfortunately, these materials were limited in terms of their specific activity and durability upon exposure to relevant electrochemical test conditions. Through a series of optimized postsynthesis steps, significant improvements were made to the activity (3-fold increasemore » in specific activity), durability (21% mass activity loss reduced to 3%), and Ni leaching (reduced from 7 to 0.3%) of the Pt—Ni nanowires. Finally, these materials show more than a 10-fold improvement in mass activity compared to that of traditional carbon-supported Pt nanoparticle catalysts and offer significant promise as a new class of electrocatalysts in fuel cell applications.« less

Exceptional oxygen reduction reaction activity and durability of platinum–nickel nanowires through synthesis and post-treatment optimization

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

Alia, Shaun M.; Ngo, Chilan; Shulda, Sarah

For the first time, extended nanostructured catalysts are demonstrated with both high specific activity (>6000 μA cm Pt –2 at 0.9 V) and high surface areas (>90 m 2 g Pt –1). Platinum–nickel (Pt—Ni) nanowires, synthesized by galvanic displacement, have previously produced surface areas in excess of 90 m 2 g Pt –1, a significant breakthrough in and of itself for extended surface catalysts. Unfortunately, these materials were limited in terms of their specific activity and durability upon exposure to relevant electrochemical test conditions. Through a series of optimized postsynthesis steps, significant improvements were made to the activity (3-fold increasemore » in specific activity), durability (21% mass activity loss reduced to 3%), and Ni leaching (reduced from 7 to 0.3%) of the Pt—Ni nanowires. Finally, these materials show more than a 10-fold improvement in mass activity compared to that of traditional carbon-supported Pt nanoparticle catalysts and offer significant promise as a new class of electrocatalysts in fuel cell applications.« less

Blinded evaluation of the effects of hyaluronic acid filler injections on first impressions.

PubMed

Dayan, Steven H; Arkins, John P; Gal, Thomas J

2010-11-01

Facial appearance has profound influence on the first impression that is projected to others. To determine the effects that complete correction of the nasolabial folds (NLFs) with hyaluronic acid (HA) filler has on the first impression one makes. Twenty-two subjects received injections of HA filler into the NLFs. Photographs of the face in a relaxed pose were taken at baseline, optimal correction visit, and 4 weeks after optimal correction. Three hundred four blinded evaluators completed a survey rating first impression on various measures of success for each photo. In total, 5,776 first impressions were recorded, totaling 46,208 individual assessments of first impression. Our findings indicate a significant improvement in mean first impression in the categories of dating success, attractiveness, financial success, relationship success, athletic success, and overall first impression at the optimal correction visit. At 4 weeks after the optimal correction visit, significance was observed in all categories measured: social skills, academic performance, dating success, occupational success, attractiveness, financial success, relationship success, athletic success, and overall first impression. Full correction of the NLFs with HA filler significantly and positively influences the first impression an individual projects. © 2010 by the American Society for Dermatologic Surgery, Inc.

Formulation and Statistical Optimization of Culture Medium for Improved Production of Antimicrobial Compound by Streptomyces sp. JAJ06

PubMed Central

Arul Jose, Polpass; Sivakala, Kunjukrishnan Kamalakshi; Jebakumar, Solomon Robinson David

2013-01-01

Streptomyces sp. JAJ06 is a seawater-dependent antibiotic producer, previously isolated and characterised from an Indian coastal solar saltern. This paper reports replacement of seawater with a defined salt formulation in production medium and subsequent statistical media optimization to ensure consistent as well as improved antibiotic production by Streptomyces sp. JAJ06. This strain was observed to be proficient to produce antibiotic compound with incorporation of chemically defined sodium-chloride-based salt formulation instead of seawater into the production medium. Plackett-Burman design experiment was applied, and three media constituents, starch, KBr, and CaCO3, were recognised to have significant effect on the antibiotic production of Streptomyces JAJ06 at their individual levels. Subsequently, Response surface methodology with Box-Behnken design was employed to optimize these influencing medium constituents for the improved antibiotic production of Streptomyces sp. JAJ06. A total of 17 experiments were conducted towards the construction of a quadratic model and a second-order polynomial equation. Optimum levels of medium constituents were obtained by analysis of the model and numerical optimization method. When the strain JAJ06 was cultivated in the optimized medium, the antibiotic activity was increased to 173.3 U/mL, 26.8% increase as compared to the original (136.7 U/mL). This study found a useful way to cultivate Streptomyces sp. JAJ06 for enhanced production of antibiotic compound. PMID:24454383

An optimized proportional-derivative controller for the human upper extremity with gravity.

PubMed

Jagodnik, Kathleen M; Blana, Dimitra; van den Bogert, Antonie J; Kirsch, Robert F

2015-10-15

When Functional Electrical Stimulation (FES) is used to restore movement in subjects with spinal cord injury (SCI), muscle stimulation patterns should be selected to generate accurate and efficient movements. Ideally, the controller for such a neuroprosthesis will have the simplest architecture possible, to facilitate translation into a clinical setting. In this study, we used the simulated annealing algorithm to optimize two proportional-derivative (PD) feedback controller gain sets for a 3-dimensional arm model that includes musculoskeletal dynamics and has 5 degrees of freedom and 22 muscles, performing goal-oriented reaching movements. Controller gains were optimized by minimizing a weighted sum of position errors, orientation errors, and muscle activations. After optimization, gain performance was evaluated on the basis of accuracy and efficiency of reaching movements, along with three other benchmark gain sets not optimized for our system, on a large set of dynamic reaching movements for which the controllers had not been optimized, to test ability to generalize. Robustness in the presence of weakened muscles was also tested. The two optimized gain sets were found to have very similar performance to each other on all metrics, and to exhibit significantly better accuracy, compared with the three standard gain sets. All gain sets investigated used physiologically acceptable amounts of muscular activation. It was concluded that optimization can yield significant improvements in controller performance while still maintaining muscular efficiency, and that optimization should be considered as a strategy for future neuroprosthesis controller design. Published by Elsevier Ltd.

Comparison of the progressive resolution optimizer and photon optimizer in VMAT optimization for stereotactic treatments.

PubMed

Liu, Han; Sintay, Benjamin; Pearman, Keith; Shang, Qingyang; Hayes, Lane; Maurer, Jacqueline; Vanderstraeten, Caroline; Wiant, David

2018-05-20

The photon optimization (PO) algorithm was recently released by Varian Medical Systems to improve volumetric modulated arc therapy (VMAT) optimization within Eclipse (Version 13.5). The purpose of this study is to compare the PO algorithm with its predecessor, progressive resolution optimizer (PRO) for lung SBRT and brain SRS treatments. A total of 30 patients were selected retrospectively. Previously, all the plans were generated with the PRO algorithm within Eclipse Version 13.6. In the new version of PO algorithm (Version 15), dynamic conformal arcs (DCA) were first conformed to the target, then VMAT inverse planning was performed to achieve the desired dose distributions. PTV coverages were forced to be identical for the same patient for a fair comparison. SBRT plan quality was assessed based on selected dose-volume parameters, including the conformity index, V 20 for lung, V 30 Gy for chest wall, and D 0.035 cc for other critical organs. SRS plan quality was evaluated based on the conformity index and normal tissue volumes encompassed by the 12 and 6 Gy isodose lines (V 12 and V 6 ). The modulation complexity score (MCS) was used to compare plan complexity of two algorithms. No statistically significant differences between the PRO and PO algorithms were found for any of the dosimetric parameters studied, which indicates both algorithms produce comparable plan quality. Significant improvements in the gamma passing rate (increased from 97.0% to 99.2% for SBRT and 96.1% to 98.4% for SRS), MCS (average increase of 0.15 for SBRT and 0.10 for SRS), and delivery efficiency (MU reduction of 29.8% for SBRT and 28.3% for SRS) were found for the PO algorithm. MCS showed a strong correlation with the gamma passing rate, and an inverse correlation with total MUs used. The PO algorithm offers comparable plan quality to the PRO, while minimizing MLC complexity, thereby improving the delivery efficiency and accuracy. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Zhang, Jian; Gan, Yang

2018-04-01

The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

A novel channel selection method for optimal classification in different motor imagery BCI paradigms.

PubMed

Shan, Haijun; Xu, Haojie; Zhu, Shanan; He, Bin

2015-10-21

For sensorimotor rhythms based brain-computer interface (BCI) systems, classification of different motor imageries (MIs) remains a crucial problem. An important aspect is how many scalp electrodes (channels) should be used in order to reach optimal performance classifying motor imaginations. While the previous researches on channel selection mainly focus on MI tasks paradigms without feedback, the present work aims to investigate the optimal channel selection in MI tasks paradigms with real-time feedback (two-class control and four-class control paradigms). In the present study, three datasets respectively recorded from MI tasks experiment, two-class control and four-class control experiments were analyzed offline. Multiple frequency-spatial synthesized features were comprehensively extracted from every channel, and a new enhanced method IterRelCen was proposed to perform channel selection. IterRelCen was constructed based on Relief algorithm, but was enhanced from two aspects: change of target sample selection strategy and adoption of the idea of iterative computation, and thus performed more robust in feature selection. Finally, a multiclass support vector machine was applied as the classifier. The least number of channels that yield the best classification accuracy were considered as the optimal channels. One-way ANOVA was employed to test the significance of performance improvement among using optimal channels, all the channels and three typical MI channels (C3, C4, Cz). The results show that the proposed method outperformed other channel selection methods by achieving average classification accuracies of 85.2, 94.1, and 83.2 % for the three datasets, respectively. Moreover, the channel selection results reveal that the average numbers of optimal channels were significantly different among the three MI paradigms. It is demonstrated that IterRelCen has a strong ability for feature selection. In addition, the results have shown that the numbers of optimal channels in the three different motor imagery BCI paradigms are distinct. From a MI task paradigm, to a two-class control paradigm, and to a four-class control paradigm, the number of required channels for optimizing the classification accuracy increased. These findings may provide useful information to optimize EEG based BCI systems, and further improve the performance of noninvasive BCI.

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce

PubMed Central

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network’s initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data. PMID:27304987

An approach for aerodynamic optimization of transonic fan blades

NASA Astrophysics Data System (ADS)

Khelghatibana, Maryam

Aerodynamic design optimization of transonic fan blades is a highly challenging problem due to the complexity of flow field inside the fan, the conflicting design requirements and the high-dimensional design space. In order to address all these challenges, an aerodynamic design optimization method is developed in this study. This method automates the design process by integrating a geometrical parameterization method, a CFD solver and numerical optimization methods that can be applied to both single and multi-point optimization design problems. A multi-level blade parameterization is employed to modify the blade geometry. Numerical analyses are performed by solving 3D RANS equations combined with SST turbulence model. Genetic algorithms and hybrid optimization methods are applied to solve the optimization problem. In order to verify the effectiveness and feasibility of the optimization method, a singlepoint optimization problem aiming to maximize design efficiency is formulated and applied to redesign a test case. However, transonic fan blade design is inherently a multi-faceted problem that deals with several objectives such as efficiency, stall margin, and choke margin. The proposed multi-point optimization method in the current study is formulated as a bi-objective problem to maximize design and near-stall efficiencies while maintaining the required design pressure ratio. Enhancing these objectives significantly deteriorate the choke margin, specifically at high rotational speeds. Therefore, another constraint is embedded in the optimization problem in order to prevent the reduction of choke margin at high speeds. Since capturing stall inception is numerically very expensive, stall margin has not been considered as an objective in the problem statement. However, improving near-stall efficiency results in a better performance at stall condition, which could enhance the stall margin. An investigation is therefore performed on the Pareto-optimal solutions to demonstrate the relation between near-stall efficiency and stall margin. The proposed method is applied to redesign NASA rotor 67 for single and multiple operating conditions. The single-point design optimization showed +0.28 points improvement of isentropic efficiency at design point, while the design pressure ratio and mass flow are, respectively, within 0.12% and 0.11% of the reference blade. Two cases of multi-point optimization are performed: First, the proposed multi-point optimization problem is relaxed by removing the choke margin constraint in order to demonstrate the relation between near-stall efficiency and stall margin. An investigation on the Pareto-optimal solutions of this optimization shows that the stall margin has been increased with improving near-stall efficiency. The second multi-point optimization case is performed with considering all the objectives and constraints. One selected optimized design on the Pareto front presents +0.41, +0.56 and +0.9 points improvement in near-peak efficiency, near-stall efficiency and stall margin, respectively. The design pressure ratio and mass flow are, respectively, within 0.3% and 0.26% of the reference blade. Moreover the optimized design maintains the required choking margin. Detailed aerodynamic analyses are performed to investigate the effect of shape optimization on shock occurrence, secondary flows, tip leakage and shock/tip-leakage interactions in both single and multi-point optimizations.

A new predictive model for continuous positive airway pressure in the treatment of obstructive sleep apnea.

PubMed

Ebben, Matthew R; Narizhnaya, Mariya; Krieger, Ana C

2017-05-01

Numerous mathematical formulas have been developed to determine continuous positive airway pressure (CPAP) without an in-laboratory titration study. Recent studies have shown that style of CPAP mask can affect the optimal pressure requirement. However, none of the current models take mask style into account. Therefore, the goal of this study was to develop new predictive models of CPAP that take into account the style of mask interface. Data from 200 subjects with attended CPAP titrations during overnight polysomnograms using nasal masks and 132 subjects using oronasal masks were randomized and split into either a model development or validation group. Predictive models were then created in each model development group and the accuracy of the models was then tested in the model validation groups. The correlation between our new oronasal model and laboratory determined optimal CPAP was significant, r = 0.61, p < 0.001. Our nasal formula was also significantly related to laboratory determined optimal CPAP, r = 0.35, p < 0.001. The oronasal model created in our study significantly outperformed the original CPAP predictive model developed by Miljeteig and Hoffstein, z = 1.99, p < 0.05. The predictive performance of our new nasal model did not differ significantly from Miljeteig and Hoffstein's original model, z = -0.16, p < 0.90. The best predictors for the nasal mask group were AHI, lowest SaO2, and neck size, whereas the top predictors in the oronasal group were AHI and lowest SaO2. Our data show that predictive models of CPAP that take into account mask style can significantly improve the formula's accuracy. Most of the past models likely focused on model development with nasal masks (mask style used for model development was not typically reported in previous investigations) and are not well suited for patients using an oronasal interface. Our new oronasal CPAP prediction equation produced significantly improved performance compared to the well-known Miljeteig and Hoffstein formula in patients titrated on CPAP with an oronasal mask and was also significantly related to laboratory determined optimal CPAP.

Optimal reproducibility of gated sestamibi and thallium myocardial perfusion study left ventricular ejection fractions obtained on a solid-state CZT cardiac camera requires operator input.

PubMed

Cherk, Martin H; Ky, Jason; Yap, Kenneth S K; Campbell, Patrina; McGrath, Catherine; Bailey, Michael; Kalff, Victor

2012-08-01

To evaluate the reproducibility of serial re-acquisitions of gated Tl-201 and Tc-99m sestamibi left ventricular ejection fraction (LVEF) measurements obtained on a new generation solid-state cardiac camera system during myocardial perfusion imaging and the importance of manual operator optimization of left ventricular wall tracking. Resting blinded automated (auto) and manual operator optimized (opt) LVEF measurements were measured using ECT toolbox (ECT) and Cedars-Sinai QGS software in two separate cohorts of 55 Tc-99m sestamibi (MIBI) and 50 thallium (Tl-201) myocardial perfusion studies (MPS) acquired in both supine and prone positions on a cadmium zinc telluride (CZT) solid-state camera system. Resting supine and prone automated LVEF measurements were similarly obtained in a further separate cohort of 52 gated cardiac blood pool scans (GCBPS) for validation of methodology and comparison. Appropriate use of Bland-Altman, chi-squared and Levene's equality of variance tests was used to analyse the resultant data comparisons. For all radiotracer and software combinations, manual checking and optimization of valve planes (+/- centre radius with ECT software) resulted in significant improvement in MPS LVEF reproducibility that approached that of planar GCBPS. No difference was demonstrated between optimized MIBI/Tl-201 QGS and planar GCBPS LVEF reproducibility (P = .17 and P = .48, respectively). ECT required significantly more manual optimization compared to QGS software in both supine and prone positions independent of radiotracer used (P < .02). Reproducibility of gated sestamibi and Tl-201 LVEF measurements obtained during myocardial perfusion imaging with ECT toolbox or QGS software packages using a new generation solid-state cardiac camera with improved image quality approaches that of planar GCBPS however requires visual quality control and operator optimization of left ventricular wall tracking for best results. Using this superior cardiac technology, Tl-201 reproducibility also appears at least equivalent to sestamibi for measuring LVEF.

An Improved Marriage in Honey Bees Optimization Algorithm for Single Objective Unconstrained Optimization

PubMed Central

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms. PMID:23935416

Discriminative motif optimization based on perceptron training

PubMed Central

Patel, Ronak Y.; Stormo, Gary D.

2014-01-01

Motivation: Generating accurate transcription factor (TF) binding site motifs from data generated using the next-generation sequencing, especially ChIP-seq, is challenging. The challenge arises because a typical experiment reports a large number of sequences bound by a TF, and the length of each sequence is relatively long. Most traditional motif finders are slow in handling such enormous amount of data. To overcome this limitation, tools have been developed that compromise accuracy with speed by using heuristic discrete search strategies or limited optimization of identified seed motifs. However, such strategies may not fully use the information in input sequences to generate motifs. Such motifs often form good seeds and can be further improved with appropriate scoring functions and rapid optimization. Results: We report a tool named discriminative motif optimizer (DiMO). DiMO takes a seed motif along with a positive and a negative database and improves the motif based on a discriminative strategy. We use area under receiver-operating characteristic curve (AUC) as a measure of discriminating power of motifs and a strategy based on perceptron training that maximizes AUC rapidly in a discriminative manner. Using DiMO, on a large test set of 87 TFs from human, drosophila and yeast, we show that it is possible to significantly improve motifs identified by nine motif finders. The motifs are generated/optimized using training sets and evaluated on test sets. The AUC is improved for almost 90% of the TFs on test sets and the magnitude of increase is up to 39%. Availability and implementation: DiMO is available at http://stormo.wustl.edu/DiMO Contact: rpatel@genetics.wustl.edu, ronakypatel@gmail.com PMID:24369152

Hospital discharge summary scorecard: a quality improvement tool used in a tertiary hospital general medicine service.

PubMed

Singh, G; Harvey, R; Dyne, A; Said, A; Scott, I

2015-12-01

We assessed the impact of completion and feedback of discharge summary scorecards on the quality of discharge summaries written by interns in a general medicine service of a tertiary hospital. The scorecards significantly improved summary quality in the first three rotations of the intern year and could be readily adopted by other units as a quality improvement intervention for optimizing clinical handover to primary care providers. © 2015 Royal Australasian College of Physicians.

Optimal implementation of best management practices to improve agricultural hydrology and water quality

NASA Astrophysics Data System (ADS)

Liu, Y.; Engel, B.; Collingsworth, P.; Pijanowski, B. C.

2017-12-01

Nutrient loading from the Maumee River watershed is a significant reason for the harmful algal blooms (HABs) problem in Lake Erie. Strategies to reduce nutrient loading from agricultural areas in the Maumee River watershed need to be explored. Best management practices (BMPs) are popular approaches for improving hydrology and water quality. Various scenarios of BMP implementation were simulated in the AXL watershed (an agricultural watershed in Maumee River watershed) using Soil and Water Assessment Tool (SWAT) and a new BMP cost tool to explore the cost-effectiveness of the practices. BMPs of interest included vegetative filter strips, grassed waterways, blind inlets, grade stabilization structures, wetlands, no-till, nutrient management, residue management, and cover crops. The following environmental concerns were considered: streamflow, Total Phosphorous (TP), Dissolved Reactive Phosphorus (DRP), Total Kjeldahl Nitrogen (TKN), and Nitrate+Nitrite (NOx). To obtain maximum hydrological and water quality benefits with minimum cost, an optimization tool was developed to optimally select and place BMPs by connecting SWAT, the BMP cost tool, and optimization algorithms. The optimization tool was then applied in AXL watershed to explore optimization focusing on critical areas (top 25% of areas with highest runoff volume/pollutant loads per area) vs. all areas of the watershed, optimization using weather data for spring (March to July, due to the goal of reducing spring phosphorus in watershed management plan) vs. full year, and optimization results of implementing BMPs to achieve the watershed management plan goal (reducing 2008 TP levels by 40%). The optimization tool and BMP optimization results can be used by watershed groups and communities to solve hydrology and water quality problems.

Number of Blades-up Runs Using JetStream XC Atherectomy for Optimal Tissue Debulking in Patients with Femoropopliteal Artery In-Stent Restenosis.

PubMed

Shammas, Nicolas W; Shammas, Gail A; Aasen, Nicole; Jarvis, Gary

2015-12-01

Rotational atherectomy with the use of the JetStream XC device is indicated for treatment of infrainguinal arterial obstructive disease. The number of blades-up (BU) runs needed for optimal tissue debulking in femoropopliteal in-stent restenosis (ISR) is unknown. In the present series, 6 patients (15 lesions) were treated for femoropopliteal ISR with the JetStream XC device. Minimal luminal diameter or percent stenosis improved significantly from baseline after 2 BU runs, but no further gain was seen between 2 and 4 BU runs (P > .05). However, adjunctive balloon angioplasty reduced percent stenosis significantly following BU runs. In conclusion, the JetStream XC device achieved optimal acute angiographic results in treating femoropopliteal ISR following 2 BU runs and adjunctive balloon angioplasty. Copyright © 2015 SIR. Published by Elsevier Inc. All rights reserved.

First Steps in the Smart Grid Framework: An Optimal and Feasible Pathway Toward Power System Reform in Mexico

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

Bracho, Riccardo; Linvill, Carl; Sedano, Richard

With the vision to transform the power sector, Mexico included in the new laws and regulations deployment of smart grid technologies and provided various attributes to the Ministry of Energy and the Energy Regulatory Commission to enact public policies and regulation. The use of smart grid technologies can have a significant impact on the integration of variable renewable energy resources while maintaining reliability and stability of the system, significantly reducing technical and non-technical electricity losses in the grid, improving cyber security, and allowing consumers to make distributed generation and demand response decisions. This report describes for Mexico's Ministry of Energymore » (SENER) an overall approach (Optimal Feasible Pathway) for moving forward with smart grid policy development in Mexico to enable increasing electric generation from renewable energy in a way that optimizes system stability and reliability in an efficient and cost-effective manner.« less

Enhancement of L-asparaginase production by isolated Bacillus circulans (MTCC 8574) using response surface methodology.

PubMed

Hymavathi, M; Sathish, T; Subba Rao, Ch; Prakasham, R S

2009-10-01

L-asparaginase production was optimized using isolated Bacillus circulans (MTCC 8574) under solid-state fermentation (SSF) using locally available agricultural waste materials. Among different agricultural materials (red gram husk, bengal gram husk, coconut, and groundnut cake), red gram husk gave the maximum enzyme production. A wide range of SSF parameters were optimized for maximize the production of L-asparaginase. Preliminary studies revealed that incubation temperature, moisture content, inoculum level, glucose, and L-asparagine play a vital role in enzyme yield. The interactive behavior of each of these parameters along with their significance on enzyme yield was analyzed using fractional factorial central composite design (FFCCD). The observed correlation coefficient (R(2)) was 0.9714. Only L-asparagine and incubation temperature, were significant in linear and quadratic terms. L-asparaginase yield improved from 780 to 2,322 U/gds which is more than 300% using FFCCD as a means of optimizing conditions.

Maximization of fructose esters synthesis by response surface methodology.

PubMed

Neta, Nair Sampaio; Peres, António M; Teixeira, José A; Rodrigues, Ligia R

2011-07-01

Enzymatic synthesis of fructose fatty acid ester was performed in organic solvent media, using a purified lipase from Candida antartica B immobilized in acrylic resin. Response surface methodology with a central composite rotatable design based on five levels was implemented to optimize three experimental operating conditions (temperature, agitation and reaction time). A statistical significant cubic model was established. Temperature and reaction time were found to be the most significant parameters. The optimum operational conditions for maximizing the synthesis of fructose esters were 57.1°C, 100 rpm and 37.8 h. The model was validated in the identified optimal conditions to check its adequacy and accuracy, and an experimental esterification percentage of 88.4% (±0.3%) was obtained. These results showed that an improvement of the enzymatic synthesis of fructose esters was obtained under the optimized conditions. Copyright © 2011 Elsevier B.V. All rights reserved.

Research on bulbous bow optimization based on the improved PSO algorithm

NASA Astrophysics Data System (ADS)

Zhang, Sheng-long; Zhang, Bao-ji; Tezdogan, Tahsin; Xu, Le-ping; Lai, Yu-yang

2017-08-01

In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation (ASD) technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.

Optimal time for initiating extracorporeal membrane oxygenation.

PubMed

Haile, Dawit T; Schears, Gregory J

2009-09-01

The technical evolution of extracorporeal membrane oxygenation (ECMO) coincides with the vast improvement in intensive care medicine of the past 4 decades. Extracorporeal circulatory technology substitutes for acutely failed cardiac or pulmonary function until these organs regain sustainable function through goal-oriented intensive care practice. The technology has been validated to improve survival in select patients who would otherwise have 100% mortality. This is by far the most complex life-sustaining technology employed and thus can contribute significant risks such that the decision to institute ECMO requires prompt risk and benefit analysis. Delaying the institution of ECMO may cause irreversible pulmonary and cardiac injuries in addition to other organs. Therefore, the optimal time of initiating ECMO support is crucial to the survival of a critically ill patient.

Matching pursuit parallel decomposition of seismic data

NASA Astrophysics Data System (ADS)

Li, Chuanhui; Zhang, Fanchang

2017-07-01

In order to improve the computation speed of matching pursuit decomposition of seismic data, a matching pursuit parallel algorithm is designed in this paper. We pick a fixed number of envelope peaks from the current signal in every iteration according to the number of compute nodes and assign them to the compute nodes on average to search the optimal Morlet wavelets in parallel. With the help of parallel computer systems and Message Passing Interface, the parallel algorithm gives full play to the advantages of parallel computing to significantly improve the computation speed of the matching pursuit decomposition and also has good expandability. Besides, searching only one optimal Morlet wavelet by every compute node in every iteration is the most efficient implementation.

Did recent world record marathon runners employ optimal pacing strategies?

PubMed

Angus, Simon D

2014-01-01

We apply statistical analysis of high frequency (1 km) split data for the most recent two world-record marathon runs: Run 1 (2:03:59, 28 September 2008) and Run 2 (2:03:38, 25 September 2011). Based on studies in the endurance cycling literature, we develop two principles to approximate 'optimal' pacing in the field marathon. By utilising GPS and weather data, we test, and then de-trend, for each athlete's field response to gradient and headwind on course, recovering standardised proxies for power-based pacing traces. The resultant traces were analysed to ascertain if either runner followed optimal pacing principles; and characterise any deviations from optimality. Whereas gradient was insignificant, headwind was a significant factor in running speed variability for both runners, with Runner 2 targeting the (optimal) parallel variation principle, whilst Runner 1 did not. After adjusting for these responses, neither runner followed the (optimal) 'even' power pacing principle, with Runner 2's macro-pacing strategy fitting a sinusoidal oscillator with exponentially expanding envelope whilst Runner 1 followed a U-shaped, quadratic form. The study suggests that: (a) better pacing strategy could provide elite marathon runners with an economical pathway to significant performance improvements at world-record level; and (b) the data and analysis herein is consistent with a complex-adaptive model of power regulation.

Determine Optimal Stimulus Amplitude for Using Vestibular Stochastic Stimulation to Improve Balance Function

NASA Technical Reports Server (NTRS)

Goel, R.; Kofman, I.; DeDios, Y. E.; Jeevarajan, J.; Stepanyan, V.; Nair, M.; Congdon, S.; Fregia, M.; Cohen, H.; Bloomberg, J.J.;

Model-based sensor-less wavefront aberration correction in optical coherence tomography.

PubMed

Verstraete, Hans R G W; Wahls, Sander; Kalkman, Jeroen; Verhaegen, Michel

2015-12-15

Several sensor-less wavefront aberration correction methods that correct nonlinear wavefront aberrations by maximizing the optical coherence tomography (OCT) signal are tested on an OCT setup. A conventional coordinate search method is compared to two model-based optimization methods. The first model-based method takes advantage of the well-known optimization algorithm (NEWUOA) and utilizes a quadratic model. The second model-based method (DONE) is new and utilizes a random multidimensional Fourier-basis expansion. The model-based algorithms achieve lower wavefront errors with up to ten times fewer measurements. Furthermore, the newly proposed DONE method outperforms the NEWUOA method significantly. The DONE algorithm is tested on OCT images and shows a significantly improved image quality.

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

Yazawa, Kazuaki; Shakouri, Ali

The energy conversion efficiency of today’s thermoelectric generators is significantly lower than that of conventional mechanical engines. Almost all of the existing research is focused on materials to improve the conversion efficiency. Here we propose a general framework to study the cost-efficiency trade-off for thermoelectric power generation. A key factor is the optimization of thermoelectric modules together with their heat source and heat sinks. Full electrical and thermal co-optimization yield a simple analytical expression for optimum design. Based on this model, power output per unit mass can be maximized. We show that the fractional area coverage of thermoelectric elements inmore » a module could play a significant role in reducing the cost of power generation systems.« less

Optimization of the Performance of Segmented Scintillators for Radiotherapy Imaging through Novel Binning Techniques

PubMed Central

El-Mohri, Youcef; Antonuk, Larry E.; Choroszucha, Richard B.; Zhao, Qihua; Jiang, Hao; Liu, Langechuan

2014-01-01

Thick, segmented crystalline scintillators have shown increasing promise as replacement x-ray converters for the phosphor screens currently used in active matrix flat-panel imagers (AMFPIs) in radiotherapy, by virtue of providing over an order of magnitude improvement in the DQE. However, element-to-element misalignment in current segmented scintillator prototypes creates a challenge for optimal registration with underlying AMFPI arrays, resulting in degradation of spatial resolution. To overcome this challenge, a methodology involving the use of a relatively high resolution AMFPI array in combination with novel binning techniques is presented. The array, which has a pixel pitch of 0.127 mm, was coupled to prototype segmented scintillators based on BGO, LYSO and CsI:Tl materials, each having a nominal element-to-element pitch of 1.016 mm and thickness of ~1 cm. The AMFPI systems incorporating these prototypes were characterized at a radiotherapy energy of 6 MV in terms of MTF, NPS, DQE, and reconstructed images of a resolution phantom acquired using a cone-beam CT geometry. For each prototype, the application of 8×8 pixel binning to achieve a sampling pitch of 1.016 mm was optimized through use of an alignment metric which minimized misregistration and thereby improved spatial resolution. In addition, the application of alternative binning techniques that exclude the collection of signal near septal walls resulted in further significant improvement in spatial resolution for the BGO and LYSO prototypes, though not for the CsI:Tl prototype due to the large amount of optical cross-talk resulting from significant light spread between scintillator elements in that device. The efficacy of these techniques for improving spatial resolution appears to be enhanced for scintillator materials that exhibit mechanical hardness, high density and high refractive index, such as BGO. Moreover, materials that exhibit these properties as well as offer significantly higher light output than BGO, such as CdWO4, should provide the additional benefit of preserving DQE performance. PMID:24487347

Optimization in Radiation Therapy: Applications in Brachytherapy and Intensity Modulated Radiation Therapy

NASA Astrophysics Data System (ADS)

McGeachy, Philip David

Over 50% of cancer patients require radiation therapy (RT). RT is an optimization problem requiring maximization of the radiation damage to the tumor while minimizing the harm to the healthy tissues. This dissertation focuses on two main RT optimization problems: 1) brachytherapy and 2) intensity modulated radiation therapy (IMRT). The brachytherapy research involved solving a non-convex optimization problem by creating an open-source genetic algorithm optimizer to determine the optimal radioactive seed distribution for a given set of patient volumes and constraints, both dosimetric- and implant-based. The optimizer was tested for a set of 45 prostate brachytherapy patients. While all solutions met the clinical standards, they also benchmarked favorably with those generated by a standard commercial solver. Compared to its compatriot, the salient features of the generated solutions were: slightly reduced prostate coverage, lower dose to the urethra and rectum, and a smaller number of needles required for an implant. Historically, IMRT requires modulation of fluence while keeping the photon beam energy fixed. The IMRT-related investigation in this thesis aimed at broadening the solution space by varying photon energy. The problem therefore involved simultaneous optimization of photon beamlet energy and fluence, denoted by XMRT. Formulating the problem as convex, linear programming was applied to obtain solutions for optimal energy-dependent fluences, while achieving all clinical objectives and constraints imposed. Dosimetric advantages of XMRT over single-energy IMRT in the improved sparing of organs at risk (OARs) was demonstrated in simplified phantom studies. The XMRT algorithm was improved to include clinical dose-volume constraints and clinical studies for prostate and head and neck cancer patients were investigated. Compared to IMRT, XMRT provided improved dosimetric benefit in the prostate case, particularly within intermediate- to low-dose regions (≤ 40 Gy) for OARs. For head and neck cases, XMRT solutions showed no significant disadvantage or advantage over IMRT. The deliverability concerns for the fluence maps generated from XMRT were addressed by incorporating smoothing constraints during the optimization and through successful generation of treatment machine files. Further research is needed to explore the full potential of the XMRT approach to RT.

A Simplified GCS-DCSK Modulation and Its Performance Optimization

NASA Astrophysics Data System (ADS)

Xu, Weikai; Wang, Lin; Chi, Chong-Yung

2016-12-01

In this paper, a simplified Generalized Code-Shifted Differential Chaos Shift Keying (GCS-DCSK) whose transmitter never needs any delay circuits, is proposed. However, its performance is deteriorated because the orthogonality between substreams cannot be guaranteed. In order to optimize its performance, the system model of the proposed GCS-DCSK with power allocations on substreams is presented. An approximate bit error rate (BER) expression of the proposed model, which is a function of substreams’ power, is derived using Gaussian Approximation. Based on the BER expression, an optimal power allocation strategy between information substreams and reference substream is obtained. Simulation results show that the BER performance of the proposed GCS-DCSK with the optimal power allocation can be significantly improved when the number of substreams M is large.

Multifidelity Analysis and Optimization for Supersonic Design

NASA Technical Reports Server (NTRS)

Kroo, Ilan; Willcox, Karen; March, Andrew; Haas, Alex; Rajnarayan, Dev; Kays, Cory

2010-01-01

Supersonic aircraft design is a computationally expensive optimization problem and multifidelity approaches over a significant opportunity to reduce design time and computational cost. This report presents tools developed to improve supersonic aircraft design capabilities including: aerodynamic tools for supersonic aircraft configurations; a systematic way to manage model uncertainty; and multifidelity model management concepts that incorporate uncertainty. The aerodynamic analysis tools developed are appropriate for use in a multifidelity optimization framework, and include four analysis routines to estimate the lift and drag of a supersonic airfoil, a multifidelity supersonic drag code that estimates the drag of aircraft configurations with three different methods: an area rule method, a panel method, and an Euler solver. In addition, five multifidelity optimization methods are developed, which include local and global methods as well as gradient-based and gradient-free techniques.

Optimizing Crawler4j using MapReduce Programming Model

NASA Astrophysics Data System (ADS)

Siddesh, G. M.; Suresh, Kavya; Madhuri, K. Y.; Nijagal, Madhushree; Rakshitha, B. R.; Srinivasa, K. G.

2017-06-01

World wide web is a decentralized system that consists of a repository of information on the basis of web pages. These web pages act as a source of information or data in the present analytics world. Web crawlers are used for extracting useful information from web pages for different purposes. Firstly, it is used in web search engines where the web pages are indexed to form a corpus of information and allows the users to query on the web pages. Secondly, it is used for web archiving where the web pages are stored for later analysis phases. Thirdly, it can be used for web mining where the web pages are monitored for copyright purposes. The amount of information processed by the web crawler needs to be improved by using the capabilities of modern parallel processing technologies. In order to solve the problem of parallelism and the throughput of crawling this work proposes to optimize the Crawler4j using the Hadoop MapReduce programming model by parallelizing the processing of large input data. Crawler4j is a web crawler that retrieves useful information about the pages that it visits. The crawler Crawler4j coupled with data and computational parallelism of Hadoop MapReduce programming model improves the throughput and accuracy of web crawling. The experimental results demonstrate that the proposed solution achieves significant improvements with respect to performance and throughput. Hence the proposed approach intends to carve out a new methodology towards optimizing web crawling by achieving significant performance gain.

A hybrid design to optimize preparation of lopinavir loaded solid lipid nanoparticles and comparative pharmacokinetic evaluation with marketed lopinavir/ritonavir coformulation.

PubMed

Ravi, Punna Rao; Vats, Rahul; Dalal, Vikas; Murthy, Aditya Narasimha

2014-07-01

To prepare stearic acid-based lopinavir (LPV) loaded solid lipid nanoparticles (SLNs) using a hybrid design and compare in-vivo performance of optimized formulation with marketed LPV/ritonavir (RTV) coformulation. LPV SLNs were prepared by hot melt emulsion technique and optimized using Plackett-Burman design and Box-Behnken design. Physical characterization studies were conducted for the optimized SLNs. Comparative oral pharmacokinetic studies and tissue distribution studies of optimized SLNs and LPV/RTV coformulation were done in Wistar rats. In-vitro metabolic stability and intestinal permeability studies for LPV SLNs were undertaken to elucidate the mechanism involved in the pharmacokinetic improvement of LPV. Optimized SLNs exhibited nanometeric size (223 nm) with high entrapment efficiency (83%). In-vitro drug release study of SLNs showed biphasic sustained release behaviour. Significant increase in oral bioavailability of LPV from LPV SLNs (5 folds) and LPV/RTV coformulation (3.7 folds) was observed as compared with free LPV. LPV SLNs showed better tissue distribution of LPV in HIV reservoirs than LPV/RTV coformulation. In-vitro studies demonstrated that SLNs provided metabolic protection of LPV and were endocytosized during absorption. SLNs enhanced oral bioavailability and improved distribution profile of LPV to HIV reservoirs and hence could be better alternative to LPV/RTV coformulation. © 2014 Royal Pharmaceutical Society.

Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy

NASA Astrophysics Data System (ADS)

Zhu, Changsheng; Liu, Jieqiong; Zhu, Mingfang; Feng, Li

2018-03-01

In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Hybrid PV/diesel solar power system design using multi-level factor analysis optimization

NASA Astrophysics Data System (ADS)

Drake, Joshua P.

Solar power systems represent a large area of interest across a spectrum of organizations at a global level. It was determined that a clear understanding of current state of the art software and design methods, as well as optimization methods, could be used to improve the design methodology. Solar power design literature was researched for an in depth understanding of solar power system design methods and algorithms. Multiple software packages for the design and optimization of solar power systems were analyzed for a critical understanding of their design workflow. In addition, several methods of optimization were studied, including brute force, Pareto analysis, Monte Carlo, linear and nonlinear programming, and multi-way factor analysis. Factor analysis was selected as the most efficient optimization method for engineering design as it applied to solar power system design. The solar power design algorithms, software work flow analysis, and factor analysis optimization were combined to develop a solar power system design optimization software package called FireDrake. This software was used for the design of multiple solar power systems in conjunction with an energy audit case study performed in seven Tibetan refugee camps located in Mainpat, India. A report of solar system designs for the camps, as well as a proposed schedule for future installations was generated. It was determined that there were several improvements that could be made to the state of the art in modern solar power system design, though the complexity of current applications is significant.

Improved conventional and microwave-assisted silylation protocols for simultaneous gas chromatographic determination of tocopherols and sterols: Method development and multi-response optimization.

PubMed

Poojary, Mahesha M; Passamonti, Paolo

2016-12-09

This paper reports on improved conventional thermal silylation (CTS) and microwave-assisted silylation (MAS) methods for simultaneous determination of tocopherols and sterols by gas chromatography. Reaction parameters in each of the methods developed were systematically optimized using a full factorial design followed by a central composite design. Initially, experimental conditions for CTS were optimized using a block heater. Further, a rapid MAS was developed and optimized. To understand microwave heating mechanisms, MAS was optimized by two distinct modes of microwave heating: temperature-controlled MAS and power-controlled MAS, using dedicated instruments where reaction temperature and microwave power level were controlled and monitored online. Developed methods: were compared with routine overnight derivatization. On a comprehensive level, while both CTS and MAS were found to be efficient derivatization techniques, MAS significantly reduced the reaction time. The optimal derivatization temperature and time for CTS found to be 55°C and 54min, while it was 87°C and 1.2min for temperature-controlled MAS. Further, a microwave power of 300W and a derivatization time 0.5min found to be optimal for power-controlled MAS. The use of an appropriate derivatization solvent, such as pyridine, was found to be critical for the successful determination. Catalysts, like potassium acetate and 4-dimethylaminopyridine, enhanced the efficiency slightly. The developed methods showed excellent analytical performance in terms of linearity, accuracy and precision. Copyright © 2016 Elsevier B.V. All rights reserved.

Polymer optical fiber compound parabolic concentrator tip for enhanced coupling efficiency for fluorescence based glucose sensors

PubMed Central

Hassan, Hafeez Ul; Nielsen, Kristian; Aasmul, Soren; Bang, Ole

2015-01-01

We demonstrate that the light excitation and capturing efficiency of fluorescence based fiber-optical sensors can be significantly increased by using a CPC (Compound Parabolic Concentrator) tip instead of the standard plane-cut tip. We use Zemax modelling to find the optimum CPC tip profile and fiber length of a polymer optical fiber diabetes sensor for continuous monitoring of glucose levels. We experimentally verify the improved performance of the CPC tipped sensor and the predicted production tolerances. Due to physical size requirements when the sensor has to be inserted into the body a non-optimal fiber length of 35 mm is chosen. For this length an average improvement in efficiency of a factor of 1.7 is experimentally demonstrated and critically compared to the predicted ideal factor of 3 in terms of parameters that should be improved through production optimization. PMID:26713213

Visual Perceptual Learning and Models.

PubMed

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

APC implementation in Chandra Asri - ethylene plant

NASA Astrophysics Data System (ADS)

Sidiq, Mochamad; Mustofa, Ali

2017-05-01

Nowadays, the modern process plants are continuously improved for maximizing production, Optimization of the energy and raw material and reducing the risk. Due to many disturbances appearance between the process units, hence, the failure of one unit might have a bad effect on the overall productivity. Ethylene Plant have significant opportunities for using Advanced Process Control (APC) technologies to improve operation stability, push closer to quality or equipment limit, and improve the capability of process units to handle disturbances. APC implementation had considered a best answer for solving multivariable control problem. PT. Chandra Asri Petrochemical, Tbk (CAP) operates a large naphtha cracker complex at Cilegon, Indonesia. To optimize the plant operation and to enhance the benefit, Chandra Asri has been decided to implement Advance Process Control (APC) for ethylene plant. The APC implementation technology scopes at CAP are as follows: 1. Hot Section : Furnaces, Quench Tower 2. Cold Section : Demethanizer, Deethanizer, Acetylene Converter, Ethylene Fractionator, Depropanizer, Propylene Fractionator, Debutanizer

Polymer optical fiber compound parabolic concentrator tip for enhanced coupling efficiency for fluorescence based glucose sensors.

PubMed

Hassan, Hafeez Ul; Nielsen, Kristian; Aasmul, Soren; Bang, Ole

2015-12-01

We demonstrate that the light excitation and capturing efficiency of fluorescence based fiber-optical sensors can be significantly increased by using a CPC (Compound Parabolic Concentrator) tip instead of the standard plane-cut tip. We use Zemax modelling to find the optimum CPC tip profile and fiber length of a polymer optical fiber diabetes sensor for continuous monitoring of glucose levels. We experimentally verify the improved performance of the CPC tipped sensor and the predicted production tolerances. Due to physical size requirements when the sensor has to be inserted into the body a non-optimal fiber length of 35 mm is chosen. For this length an average improvement in efficiency of a factor of 1.7 is experimentally demonstrated and critically compared to the predicted ideal factor of 3 in terms of parameters that should be improved through production optimization.

Cache Locality Optimization for Recursive Programs

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

Lifflander, Jonathan; Krishnamoorthy, Sriram

We present an approach to optimize the cache locality for recursive programs by dynamically splicing--recursively interleaving--the execution of distinct function invocations. By utilizing data effect annotations, we identify concurrency and data reuse opportunities across function invocations and interleave them to reduce reuse distance. We present algorithms that efficiently track effects in recursive programs, detect interference and dependencies, and interleave execution of function invocations using user-level (non-kernel) lightweight threads. To enable multi-core execution, a program is parallelized using a nested fork/join programming model. Our cache optimization strategy is designed to work in the context of a random work stealing scheduler. Wemore » present an implementation using the MIT Cilk framework that demonstrates significant improvements in sequential and parallel performance, competitive with a state-of-the-art compile-time optimizer for loop programs and a domain- specific optimizer for stencil programs.« less

Optimal policy for value-based decision-making.

PubMed

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-08-18

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

Optimal policy for value-based decision-making

PubMed Central

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-01-01

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down. PMID:27535638

Customer demand prediction of service-oriented manufacturing using the least square support vector machine optimized by particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Cao, Jin; Jiang, Zhibin; Wang, Kangzhou

2017-07-01

Many nonlinear customer satisfaction-related factors significantly influence the future customer demand for service-oriented manufacturing (SOM). To address this issue and enhance the prediction accuracy, this article develops a novel customer demand prediction approach for SOM. The approach combines the phase space reconstruction (PSR) technique with the optimized least square support vector machine (LSSVM). First, the prediction sample space is reconstructed by the PSR to enrich the time-series dynamics of the limited data sample. Then, the generalization and learning ability of the LSSVM are improved by the hybrid polynomial and radial basis function kernel. Finally, the key parameters of the LSSVM are optimized by the particle swarm optimization algorithm. In a real case study, the customer demand prediction of an air conditioner compressor is implemented. Furthermore, the effectiveness and validity of the proposed approach are demonstrated by comparison with other classical predication approaches.

Particle swarm optimization based space debris surveillance network scheduling

NASA Astrophysics Data System (ADS)

Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao

2017-02-01

The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.

Optimization of vibratory energy harvesters with stochastic parametric uncertainty: a new perspective

NASA Astrophysics Data System (ADS)

Haji Hosseinloo, Ashkan; Turitsyn, Konstantin

2016-04-01

Vibration energy harvesting has been shown as a promising power source for many small-scale applications mainly because of the considerable reduction in the energy consumption of the electronics and scalability issues of the conventional batteries. However, energy harvesters may not be as robust as the conventional batteries and their performance could drastically deteriorate in the presence of uncertainty in their parameters. Hence, study of uncertainty propagation and optimization under uncertainty is essential for proper and robust performance of harvesters in practice. While all studies have focused on expectation optimization, we propose a new and more practical optimization perspective; optimization for the worst-case (minimum) power. We formulate the problem in a generic fashion and as a simple example apply it to a linear piezoelectric energy harvester. We study the effect of parametric uncertainty in its natural frequency, load resistance, and electromechanical coupling coefficient on its worst-case power and then optimize for it under different confidence levels. The results show that there is a significant improvement in the worst-case power of thus designed harvester compared to that of a naively-optimized (deterministically-optimized) harvester.

An initiative in multidisciplinary optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Mantay, Wayne R.

1989-01-01

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

An initiative in multidisciplinary optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Mantay, Wayne R.

1988-01-01

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

Innovative Technologies and a Technology Selection Roadmap for Optimization of Pipeline Inspection and Assessment

EPA Science Inventory

In the past five years, a multitude of new inspection technologies have emerged as viable sources of pipeline condition data. Furthermore, many of these new technologies provide quantitative (versus qualitative) data that can significantly improve diagnostic and predictive capab...

Optimized ultra-high-pressure-assisted extraction of procyanidins from lychee pericarp improves the antioxidant activity of extracts.

PubMed

Zhang, Ruifen; Su, Dongxiao; Hou, Fangli; Liu, Lei; Huang, Fei; Dong, Lihong; Deng, Yuanyuan; Zhang, Yan; Wei, Zhencheng; Zhang, Mingwei

2017-08-01

To establish optimal ultra-high-pressure (UHP)-assisted extraction conditions for procyanidins from lychee pericarp, a response surface analysis method with four factors and three levels was adopted. The optimum conditions were as follows: 295 MPa pressure, 13 min pressure holding time, 16.0 mL/g liquid-to-solid ratio, and 70% ethanol concentration. Compared with conventional ethanol extraction and ultrasonic-assisted extraction methods, the yields of the total procyanidins, flavonoids, and phenolics extracted using the UHP process were significantly increased; consequently, the oxygen radical absorbance capacity and cellular antioxidant activity of UHP-assisted lychee pericarp extracts were substantially enhanced. LC-MS/MS and high-performance liquid chromatography quantification results for individual phenolic compounds revealed that the yield of procyanidin compounds, including epicatechin, procyanidin A2, and procyanidin B2, from lychee pericarp could be significantly improved by the UHP-assisted extraction process. This UHP-assisted extraction process is thus a practical method for the extraction of procyanidins from lychee pericarp.

Elimination sequence optimization for SPAR

NASA Technical Reports Server (NTRS)

Hogan, Harry A.

1986-01-01

SPAR is a large-scale computer program for finite element structural analysis. The program allows user specification of the order in which the joints of a structure are to be eliminated since this order can have significant influence over solution performance, in terms of both storage requirements and computer time. An efficient elimination sequence can improve performance by over 50% for some problems. Obtaining such sequences, however, requires the expertise of an experienced user and can take hours of tedious effort to affect. Thus, an automatic elimination sequence optimizer would enhance productivity by reducing the analysts' problem definition time and by lowering computer costs. Two possible methods for automating the elimination sequence specifications were examined. Several algorithms based on the graph theory representations of sparse matrices were studied with mixed results. Significant improvement in the program performance was achieved, but sequencing by an experienced user still yields substantially better results. The initial results provide encouraging evidence that the potential benefits of such an automatic sequencer would be well worth the effort.

Optimal river monitoring network using optimal partition analysis: a case study of Hun River, Northeast China.

PubMed

Wang, Hui; Liu, Chunyue; Rong, Luge; Wang, Xiaoxu; Sun, Lina; Luo, Qing; Wu, Hao

2018-01-09

River monitoring networks play an important role in water environmental management and assessment, and it is critical to develop an appropriate method to optimize the monitoring network. In this study, an effective method was proposed based on the attainment rate of National Grade III water quality, optimal partition analysis and Euclidean distance, and Hun River was taken as a method validation case. There were 7 sampling sites in the monitoring network of the Hun River, and 17 monitoring items were analyzed once a month during January 2009 to December 2010. The results showed that the main monitoring items in the surface water of Hun River were ammonia nitrogen (NH 4 + -N), chemical oxygen demand, and biochemical oxygen demand. After optimization, the required number of monitoring sites was reduced from seven to three, and 57% of the cost was saved. In addition, there were no significant differences between non-optimized and optimized monitoring networks, and the optimized monitoring networks could correctly represent the original monitoring network. The duplicate setting degree of monitoring sites decreased after optimization, and the rationality of the monitoring network was improved. Therefore, the optimal method was identified as feasible, efficient, and economic.

A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems.

PubMed

Su, Weixing; Chen, Hanning; Liu, Fang; Lin, Na; Jing, Shikai; Liang, Xiaodan; Liu, Wei

2017-03-01

There are many dynamic optimization problems in the real world, whose convergence and searching ability is cautiously desired, obviously different from static optimization cases. This requires an optimization algorithm adaptively seek the changing optima over dynamic environments, instead of only finding the global optimal solution in the static environment. This paper proposes a novel comprehensive learning artificial bee colony optimizer (CLABC) for optimization in dynamic environments problems, which employs a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff. The main motive of CLABC is to enrich artificial bee foraging behaviors in the ABC model by combining Powell's pattern search method, life-cycle, and crossover-based social learning strategy. The proposed CLABC is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. The experiments for evaluating CLABC are conducted on the dynamic moving peak benchmarks. Furthermore, the proposed algorithm is applied to a real-world application of dynamic RFID network optimization. Statistical analysis of all these cases highlights the significant performance improvement due to the beneficial combination and demonstrates the performance superiority of the proposed algorithm.

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

Point-based warping with optimized weighting factors of displacement vectors

NASA Astrophysics Data System (ADS)

Pielot, Ranier; Scholz, Michael; Obermayer, Klaus; Gundelfinger, Eckart D.; Hess, Andreas

2000-06-01

The accurate comparison of inter-individual 3D image brain datasets requires non-affine transformation techniques (warping) to reduce geometric variations. Constrained by the biological prerequisites we use in this study a landmark-based warping method with weighted sums of displacement vectors, which is enhanced by an optimization process. Furthermore, we investigate fast automatic procedures for determining landmarks to improve the practicability of 3D warping. This combined approach was tested on 3D autoradiographs of Gerbil brains. The autoradiographs were obtained after injecting a non-metabolized radioactive glucose derivative into the Gerbil thereby visualizing neuronal activity in the brain. Afterwards the brain was processed with standard autoradiographical methods. The landmark-generator computes corresponding reference points simultaneously within a given number of datasets by Monte-Carlo-techniques. The warping function is a distance weighted exponential function with a landmark- specific weighting factor. These weighting factors are optimized by a computational evolution strategy. The warping quality is quantified by several coefficients (correlation coefficient, overlap-index, and registration error). The described approach combines a highly suitable procedure to automatically detect landmarks in autoradiographical brain images and an enhanced point-based warping technique, optimizing the local weighting factors. This optimization process significantly improves the similarity between the warped and the target dataset.

Development and clinical introduction of automated radiotherapy treatment planning for prostate cancer

NASA Astrophysics Data System (ADS)

Winkel, D.; Bol, G. H.; van Asselen, B.; Hes, J.; Scholten, V.; Kerkmeijer, L. G. W.; Raaymakers, B. W.

2016-12-01

To develop an automated radiotherapy treatment planning and optimization workflow to efficiently create patient specifically optimized clinical grade treatment plans for prostate cancer and to implement it in clinical practice. A two-phased planning and optimization workflow was developed to automatically generate 77Gy 5-field simultaneously integrated boost intensity modulated radiation therapy (SIB-IMRT) plans for prostate cancer treatment. A retrospective planning study (n  =  100) was performed in which automatically and manually generated treatment plans were compared. A clinical pilot (n  =  21) was performed to investigate the usability of our method. Operator time for the planning process was reduced to  <5 min. The retrospective planning study showed that 98 plans met all clinical constraints. Significant improvements were made in the volume receiving 72Gy (V72Gy) for the bladder and rectum and the mean dose of the bladder and the body. A reduced plan variance was observed. During the clinical pilot 20 automatically generated plans met all constraints and 17 plans were selected for treatment. The automated radiotherapy treatment planning and optimization workflow is capable of efficiently generating patient specifically optimized and improved clinical grade plans. It has now been adopted as the current standard workflow in our clinic to generate treatment plans for prostate cancer.

Speech coding at low to medium bit rates

NASA Astrophysics Data System (ADS)

Leblanc, Wilfred Paul

1992-09-01

Improved search techniques coupled with improved codebook design methodologies are proposed to improve the performance of conventional code-excited linear predictive coders for speech. Improved methods for quantizing the short term filter are developed by employing a tree search algorithm and joint codebook design to multistage vector quantization. Joint codebook design procedures are developed to design locally optimal multistage codebooks. Weighting during centroid computation is introduced to improve the outlier performance of the multistage vector quantizer. Multistage vector quantization is shown to be both robust against input characteristics and in the presence of channel errors. Spectral distortions of about 1 dB are obtained at rates of 22-28 bits/frame. Structured codebook design procedures for excitation in code-excited linear predictive coders are compared to general codebook design procedures. Little is lost using significant structure in the excitation codebooks while greatly reducing the search complexity. Sparse multistage configurations are proposed for reducing computational complexity and memory size. Improved search procedures are applied to code-excited linear prediction which attempt joint optimization of the short term filter, the adaptive codebook, and the excitation. Improvements in signal to noise ratio of 1-2 dB are realized in practice.

Mechanical behavior and shape optimization of lining structure for subsea tunnel excavated in weathered slot

NASA Astrophysics Data System (ADS)

Li, Peng-fei; Zhou, Xiao-jun

2015-12-01

Subsea tunnel lining structures should be designed to sustain the loads transmitted from surrounding ground and groundwater during excavation. Extremely high pore-water pressure reduces the effective strength of the country rock that surrounds a tunnel, thereby lowering the arching effect and stratum stability of the structure. In this paper, the mechanical behavior and shape optimization of the lining structure for the Xiang'an tunnel excavated in weathered slots are examined. Eight cross sections with different geometric parameters are adopted to study the mechanical behavior and shape optimization of the lining structure. The hyperstatic reaction method is used through finite element analysis software ANSYS. The mechanical behavior of the lining structure is evidently affected by the geometric parameters of crosssectional shape. The minimum safety factor of the lining structure elements is set to be the objective function. The efficient tunnel shape to maximize the minimum safety factor is identified. The minimum safety factor increases significantly after optimization. The optimized cross section significantly improves the mechanical characteristics of the lining structure and effectively reduces its deformation. Force analyses of optimization process and program are conducted parametrically so that the method can be applied to the optimization design of other similar structures. The results obtained from this study enhance our understanding of the mechanical behavior of the lining structure for subsea tunnels. These results are also beneficial to the optimal design of lining structures in general.

Novel Goal-Directed Hemodynamic Optimization Therapy Based on Major Vasopressor during Corrective Cardiac Surgery in Patients with Severe Pulmonary Arterial Hypertension: A Pilot Study.

PubMed

Li, Shuwen; Ma, Qing; Yang, Yanwei; Lu, Jiakai; Zhang, Zhiquan; Jin, Mu; Cheng, Weiping

2016-12-22

Pulmonary arterial hypertension (PAH) is a common and fatal complication of congenital heart disease (CHD). PAH-CHD increases the risk for postoperative complications. Recent evidence suggests that perioperative goal-directed hemodynamic optimization therapy (GDHOT) significantly improves outcomes in surgery patients. Standard GDHOT is based on major solution volume, vasodilators and inotropic therapy, while novel GDHOT is based on major vasopressor and inotropic therapy. Therefore, we tested whether standard or novel GDHOT improves surgical outcomes in PAH-CHD patients. Forty PAH-CHD patients with a ventricular septal defect (VSD) and mean pulmonary arterial pressure (mPAP) >50 mmHg, who were scheduled for corrective surgery, were randomly assigned to 2 groups: SG (study group, n = 20) and CG (control group, n = 20). SG patients received perioperative hemodynamic therapy guided by novel GDHOT, while CG patients received standard GDHOT. Outcome data were recorded up to 28 days postoperatively. Ventilator time, length of ICU stay, and mortality were the primary endpoints. There were no significant differences in preoperative data, surgical procedure, and hospital mortality rates between the 2 groups. Time of mechanical ventilation and length of ICU stay were significantly shorter in SG patients compared to CG patients (P < .05, n = 20). Patients in SG showed a significantly increased systemic vascular resistance index and decreased cardiac index, but no change in pulmonary vascular resistance index at 12 and 24 hours after surgery compared to the controls (P < .05). Patients in SG had significantly decreased PAP, pulmonary arterial pressure/systemic arterial pressure (Pp/Ps), and RVSWI (right ventricular stroke work index) at 12 and 24 hours after surgery (P < .05, respectively). Patients in SG also showed significantly decreased central venous pressure at 4, 12, and 24 hours after surgery compared to those treated with standard protocol (P < .05). Our study provides clinical evidence that perioperative goal-directed hemodynamic optimization therapy based on major vasopressor is associated with reduced duration of postoperative respiratory support, and length of ICU stay in PAH-CHD patients undergoing elective surgery. These outcomes, then, may be linked to improved hemodynamics and preservation of right ventricular dynamic function.

The Effectiveness and Tolerability of Central Nervous System Stimulants in School-Age Children with Attention-Deficit/Hyperactivity Disorder and Disruptive Mood Dysregulation Disorder Across Home and School.

PubMed

Baweja, Raman; Belin, Peter J; Humphrey, Hugh H; Babocsai, Lysett; Pariseau, Meaghan E; Waschbusch, Daniel A; Hoffman, Martin T; Akinnusi, Opeolowa O; Haak, Jenifer L; Pelham, William E; Waxmonsky, James G

2016-03-01

This study examines the effectiveness and tolerability of stimulants in children with attention-deficit/hyperactivity disorder (ADHD) and disruptive mood dysregulation disorder (DMDD). To be eligible, participants had to meet Diagnostic and Statistical Manual of Mental Disorders, 4th ed., Text Revision (DSM-IV) criteria for the combined subtype of ADHD and National Institute of Mental Health (NIMH) severe mood dysregulation criteria. The Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-V) DMDD criteria were retrospectively assessed after the study was completed. An open-label medication trial lasting up to 6 weeks was completed to optimize the central nervous system (CNS) stimulant dose. Measures of affective symptoms, ADHD symptoms and other disruptive behaviors, impairment, and structured side effect ratings were collected before and after the medication trial. Optimization of stimulant medication was associated with a significant decline in depressive symptoms on the Childhood Depression Rating Score-Revised Scale (p<0.05, Cohen's d=0.61) and Mood Severity Index score (p<0.05, Cohen's d=0.55), but not in manic-like symptoms on the Young Mania Rating Scale. There was a significant reduction in ADHD (p<0.05, Cohen's d=0.95), oppositional defiant disorder (ODD) (p<0.05, Cohen's d=0.5), and conduct disorder (CD) symptoms (p<0.05, Cohen's d=0.65) as rated by parents. There was also a significant reduction in teacher-rated ADHD (p<0.05, Cohen's d=0.33) but not in ODD symptoms. Medications were well tolerated and there was no increase in side effect ratings seen with dose optimization. Significant improvement in functioning was reported by clinicians and parents (all p's<0.05), but youth still manifested appreciable impairment at end-point. CNS simulants were well tolerated by children with ADHD comorbid with a diagnosis of DMDD. CNS stimulants were associated with clinically significant reductions in externalizing symptoms, along with smaller improvements in mood. However, most participants still exhibited significant impairment, suggesting that additional treatments may be needed to optimize functioning.

The Effectiveness and Tolerability of Central Nervous System Stimulants in School-Age Children with Attention-Deficit/Hyperactivity Disorder and Disruptive Mood Dysregulation Disorder Across Home and School

PubMed Central

Belin, Peter J.; Humphrey, Hugh H.; Babocsai, Lysett; Pariseau, Meaghan E.; Waschbusch, Daniel A.; Hoffman, Martin T.; Akinnusi, Opeolowa O.; Haak, Jenifer L.; Pelham, William E.; Waxmonsky, James G.

2016-01-01

Abstract Objective: This study examines the effectiveness and tolerability of stimulants in children with attention-deficit/hyperactivity disorder (ADHD) and disruptive mood dysregulation disorder (DMDD). Methods: To be eligible, participants had to meet Diagnostic and Statistical Manual of Mental Disorders, 4th ed., Text Revision (DSM-IV) criteria for the combined subtype of ADHD and National Institute of Mental Health (NIMH) severe mood dysregulation criteria. The Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-V) DMDD criteria were retrospectively assessed after the study was completed. An open-label medication trial lasting up to 6 weeks was completed to optimize the central nervous system (CNS) stimulant dose. Measures of affective symptoms, ADHD symptoms and other disruptive behaviors, impairment, and structured side effect ratings were collected before and after the medication trial. Results: Optimization of stimulant medication was associated with a significant decline in depressive symptoms on the Childhood Depression Rating Score–Revised Scale (p<0.05, Cohen's d=0.61) and Mood Severity Index score (p<0.05, Cohen's d=0.55), but not in manic-like symptoms on the Young Mania Rating Scale. There was a significant reduction in ADHD (p<0.05, Cohen's d=0.95), oppositional defiant disorder (ODD) (p<0.05, Cohen's d=0.5), and conduct disorder (CD) symptoms (p<0.05, Cohen's d=0.65) as rated by parents. There was also a significant reduction in teacher-rated ADHD (p<0.05, Cohen's d=0.33) but not in ODD symptoms. Medications were well tolerated and there was no increase in side effect ratings seen with dose optimization. Significant improvement in functioning was reported by clinicians and parents (all p's<0.05), but youth still manifested appreciable impairment at end-point. Conclusions: CNS simulants were well tolerated by children with ADHD comorbid with a diagnosis of DMDD. CNS stimulants were associated with clinically significant reductions in externalizing symptoms, along with smaller improvements in mood. However, most participants still exhibited significant impairment, suggesting that additional treatments may be needed to optimize functioning. PMID:26771437

Null steering of adaptive beamforming using linear constraint minimum variance assisted by particle swarm optimization, dynamic mutated artificial immune system, and gravitational search algorithm.

PubMed

Darzi, Soodabeh; Kiong, Tiong Sieh; Islam, Mohammad Tariqul; Ismail, Mahamod; Kibria, Salehin; Salem, Balasem

2014-01-01

Linear constraint minimum variance (LCMV) is one of the adaptive beamforming techniques that is commonly applied to cancel interfering signals and steer or produce a strong beam to the desired signal through its computed weight vectors. However, weights computed by LCMV usually are not able to form the radiation beam towards the target user precisely and not good enough to reduce the interference by placing null at the interference sources. It is difficult to improve and optimize the LCMV beamforming technique through conventional empirical approach. To provide a solution to this problem, artificial intelligence (AI) technique is explored in order to enhance the LCMV beamforming ability. In this paper, particle swarm optimization (PSO), dynamic mutated artificial immune system (DM-AIS), and gravitational search algorithm (GSA) are incorporated into the existing LCMV technique in order to improve the weights of LCMV. The simulation result demonstrates that received signal to interference and noise ratio (SINR) of target user can be significantly improved by the integration of PSO, DM-AIS, and GSA in LCMV through the suppression of interference in undesired direction. Furthermore, the proposed GSA can be applied as a more effective technique in LCMV beamforming optimization as compared to the PSO technique. The algorithms were implemented using Matlab program.

Null Steering of Adaptive Beamforming Using Linear Constraint Minimum Variance Assisted by Particle Swarm Optimization, Dynamic Mutated Artificial Immune System, and Gravitational Search Algorithm

PubMed Central

Sieh Kiong, Tiong; Tariqul Islam, Mohammad; Ismail, Mahamod; Salem, Balasem

2014-01-01

Linear constraint minimum variance (LCMV) is one of the adaptive beamforming techniques that is commonly applied to cancel interfering signals and steer or produce a strong beam to the desired signal through its computed weight vectors. However, weights computed by LCMV usually are not able to form the radiation beam towards the target user precisely and not good enough to reduce the interference by placing null at the interference sources. It is difficult to improve and optimize the LCMV beamforming technique through conventional empirical approach. To provide a solution to this problem, artificial intelligence (AI) technique is explored in order to enhance the LCMV beamforming ability. In this paper, particle swarm optimization (PSO), dynamic mutated artificial immune system (DM-AIS), and gravitational search algorithm (GSA) are incorporated into the existing LCMV technique in order to improve the weights of LCMV. The simulation result demonstrates that received signal to interference and noise ratio (SINR) of target user can be significantly improved by the integration of PSO, DM-AIS, and GSA in LCMV through the suppression of interference in undesired direction. Furthermore, the proposed GSA can be applied as a more effective technique in LCMV beamforming optimization as compared to the PSO technique. The algorithms were implemented using Matlab program. PMID:25147859

A dose optimization method for electron radiotherapy using randomized aperture beams

NASA Astrophysics Data System (ADS)

Engel, Konrad; Gauer, Tobias

2009-09-01

The present paper describes the entire optimization process of creating a radiotherapy treatment plan for advanced electron irradiation. Special emphasis is devoted to the selection of beam incidence angles and beam energies as well as to the choice of appropriate subfields generated by a refined version of intensity segmentation and a novel random aperture approach. The algorithms have been implemented in a stand-alone programme using dose calculations from a commercial treatment planning system. For this study, the treatment planning system Pinnacle from Philips has been used and connected to the optimization programme using an ASCII interface. Dose calculations in Pinnacle were performed by Monte Carlo simulations for a remote-controlled electron multileaf collimator (MLC) from Euromechanics. As a result, treatment plans for breast cancer patients could be significantly improved when using randomly generated aperture beams. The combination of beams generated through segmentation and randomization achieved the best results in terms of target coverage and sparing of critical organs. The treatment plans could be further improved by use of a field reduction algorithm. Without a relevant loss in dose distribution, the total number of MLC fields and monitor units could be reduced by up to 20%. In conclusion, using randomized aperture beams is a promising new approach in radiotherapy and exhibits potential for further improvements in dose optimization through a combination of randomized electron and photon aperture beams.

Optimizing Insulin Glargine Plus One Injection of Insulin Glulisine in Type 2 Diabetes in the ELEONOR Study

PubMed Central

Nicolucci, Antonio; Del Prato, Stefano; Vespasiani, Giacomo

2011-01-01

OBJECTIVE To determine the functional health status and treatment satisfaction in patients with type 2 diabetes from the Evaluation of Lantus Effect ON Optimization of use of single dose Rapid insulin (ELEONOR) study that investigated whether a telecare program helps optimization of basal insulin glargine with one bolus injection of insulin glulisine. RESEARCH DESIGN AND METHODS Functional health status and treatment satisfaction were investigated using the 36-Item Short-Form (SF-36) Health Survey, the World Health Organization Well-Being Questionnaire (WBQ), and the Diabetes Treatment Satisfaction Questionnaire. RESULTS Of 291 randomized patients, 238 completed the study (telecare: 114; self-monitoring blood glucose: 124). Significant improvements were detected in most SF-36 domains, in WBQ depression and anxiety scores, and in treatment satisfaction, without differences between study groups. CONCLUSIONS An insulin regimen that substantially improves metabolic control, while minimizing the risk of hypoglycemia, can positively affect physical and psychologic well-being and treatment satisfaction irrespective of the educational support system used. PMID:21953799

Rationally optimized cryopreservation of multiple mouse embryonic stem cell lines: I--Comparative fundamental cryobiology of multiple mouse embryonic stem cell lines and the implications for embryonic stem cell cryopreservation protocols.

PubMed

Kashuba, Corinna M; Benson, James D; Critser, John K

2014-04-01

The post-thaw recovery of mouse embryonic stem cells (mESCs) is often assumed to be adequate with current methods. However as this publication will show, this recovery of viable cells actually varies significantly by genetic background. Therefore there is a need to improve the efficiency and reduce the variability of current mESC cryopreservation methods. To address this need, we employed the principles of fundamental cryobiology to improve the cryopreservation protocol of four mESC lines from different genetic backgrounds (BALB/c, CBA, FVB, and 129R1 mESCs) through a comparative study characterizing the membrane permeability characteristics and membrane integrity osmotic tolerance limits of each cell line. In the companion paper, these values were used to predict optimal cryoprotectants, cooling rates, warming rates, and plunge temperatures, and then these predicted optimal protocols were validated against standard freezing protocols. Copyright © 2014 Elsevier Inc. All rights reserved.

Coupled Solid Rocket Motor Ballistics and Trajectory Modeling for Higher Fidelity Launch Vehicle Design

NASA Technical Reports Server (NTRS)

Ables, Brett

2014-01-01

Multi-stage launch vehicles with solid rocket motors (SRMs) face design optimization challenges, especially when the mission scope changes frequently. Significant performance benefits can be realized if the solid rocket motors are optimized to the changing requirements. While SRMs represent a fixed performance at launch, rapid design iterations enable flexibility at design time, yielding significant performance gains. The streamlining and integration of SRM design and analysis can be achieved with improved analysis tools. While powerful and versatile, the Solid Performance Program (SPP) is not conducive to rapid design iteration. Performing a design iteration with SPP and a trajectory solver is a labor intensive process. To enable a better workflow, SPP, the Program to Optimize Simulated Trajectories (POST), and the interfaces between them have been improved and automated, and a graphical user interface (GUI) has been developed. The GUI enables real-time visual feedback of grain and nozzle design inputs, enforces parameter dependencies, removes redundancies, and simplifies manipulation of SPP and POST's numerous options. Automating the analysis also simplifies batch analyses and trade studies. Finally, the GUI provides post-processing, visualization, and comparison of results. Wrapping legacy high-fidelity analysis codes with modern software provides the improved interface necessary to enable rapid coupled SRM ballistics and vehicle trajectory analysis. Low cost trade studies demonstrate the sensitivities of flight performance metrics to propulsion characteristics. Incorporating high fidelity analysis from SPP into vehicle design reduces performance margins and improves reliability. By flying an SRM designed with the same assumptions as the rest of the vehicle, accurate comparisons can be made between competing architectures. In summary, this flexible workflow is a critical component to designing a versatile launch vehicle model that can accommodate a volatile mission scope.

A systematic study of posterior cervical lymph node irradiation with electrons: Conventional versus customized planning.

PubMed

Jankowska, Petra J; Kong, Christine; Burke, Kevin; Harrington, Kevin J; Nutting, Christopher

2007-10-01

High dose irradiation of the posterior cervical lymph nodes usually employs applied electron fields to treat the target volume and maintain the spinal cord dose within tolerance. In the light of recent advances in elective lymph node localisation we investigated optimization of field shape and electron energy to treat this target volume. In this study, three sequential hypotheses were tested. Firstly, that customization of the electron fields based on the nodal PTV outlined gives better PTV coverage than conventional field delineation. Using the consensus guidelines, customization of the electron field shape was compared to conventional fields based on bony landmarks. Secondly, that selection of electron energy using DVHs for spinal cord and PTV improves the minimum dose to PTV. Electron dose-volume histograms (DVHs) for the PTV, spinal cord and para-vertebral muscles, were generated using the Monte Carlo electron algorithm. These DVHs were used to compare standard vs optimized electron energy calculations. Finally, that combination of field customization and electron energy optimization improves both the minimum and mean doses to PTV compared with current standard practice. Customized electron beam shaping based on the consensus guidelines led to fewer geographical misses than standard field shaping. Customized electron energy calculation led to higher minimum doses to the PTV. Overall, the customization of field shape and energy resulted in an improved mean dose to the PTV (92% vs 83% p=0.02) and a 27% improvement in the minimum dose delivered to the PTV (45% vs 18% p=0.0009). Optimization of electron field shape and beam energy based on current consensus guidelines led to significant improvement in PTV coverage and may reduce recurrence rates.

Research on charging and discharging control strategy for electric vehicles as distributed energy storage devices

NASA Astrophysics Data System (ADS)

Zhang, Min; Yang, Feng; Zhang, Dongqing; Tang, Pengcheng

2018-02-01

A large number of electric vehicles are connected to the family micro grid will affect the operation safety of the power grid and the quality of power. Considering the factors of family micro grid price and electric vehicle as a distributed energy storage device, a two stage optimization model is established, and the improved discrete binary particle swarm optimization algorithm is used to optimize the parameters in the model. The proposed control strategy of electric vehicle charging and discharging is of practical significance for the rational control of electric vehicle as a distributed energy storage device and electric vehicle participating in the peak load regulation of power consumption.

Monte Carlo design of optimal wire mesh collimator for breast tumor imaging process

NASA Astrophysics Data System (ADS)

Saad, W. H. M.; Roslan, R. E.; Mahdi, M. A.; Choong, W.-S.; Saion, E.; Saripan, M. I.

2011-08-01

This paper presents the modeling of breast tumor imaging process using wire mesh collimator gamma camera. Previous studies showed that the wire mesh collimator has a potential to improve the sensitivity of the tumor detection. In this paper, we extend our research significantly, to find an optimal configuration of the wire mesh collimator specifically for semi-compressed breast tumor detection, by looking into four major factors: weight, sensitivity, spatial resolution and tumor contrast. The numbers of layers in the wire mesh collimator is varied to optimize the collimator design. The statistical variations of the results are studied by simulating multiple realizations for each experiment using different starting random numbers. All the simulation environments are modeled using Monte Carlo N-Particle Code (MCNP). The quality of the detection is measured directly by comparing the sensitivity, spatial resolution and tumor contrast of the images produced by the wire mesh collimator and benchmarked that with a standard multihole collimator. The proposed optimal configuration of the wire mesh collimator is optimized by selecting the number of layers in wire mesh collimator, where the tumor contrast shows a relatively comparable value to the multihole collimator, when it is tested with uniformly semi-compressed breast phantom. The wire mesh collimator showed higher number of sensitivity because of its loose arrangement while the spatial resolution of wire mesh collimator does not shows much different compared to the multihole collimator. With a relatively good tumor contrast and spatial resolution, and increased in sensitivity, a new proposed wire mesh collimator gives a significant improvement in the wire mesh collimator design for breast cancer imaging process. The proposed collimator configuration is reduced to 44.09% from the total multihole collimator weight.

A novel task-oriented optimal design for P300-based brain-computer interfaces.

PubMed

Zhou, Zongtan; Yin, Erwei; Liu, Yang; Jiang, Jun; Hu, Dewen

2014-10-01

Objective. The number of items of a P300-based brain-computer interface (BCI) should be adjustable in accordance with the requirements of the specific tasks. To address this issue, we propose a novel task-oriented optimal approach aimed at increasing the performance of general P300 BCIs with different numbers of items. Approach. First, we proposed a stimulus presentation with variable dimensions (VD) paradigm as a generalization of the conventional single-character (SC) and row-column (RC) stimulus paradigms. Furthermore, an embedding design approach was employed for any given number of items. Finally, based on the score-P model of each subject, the VD flash pattern was selected by a linear interpolation approach for a certain task. Main results. The results indicate that the optimal BCI design consistently outperforms the conventional approaches, i.e., the SC and RC paradigms. Specifically, there is significant improvement in the practical information transfer rate for a large number of items. Significance. The results suggest that the proposed optimal approach would provide useful guidance in the practical design of general P300-based BCIs.

A novel task-oriented optimal design for P300-based brain-computer interfaces

NASA Astrophysics Data System (ADS)

Zhou, Zongtan; Yin, Erwei; Liu, Yang; Jiang, Jun; Hu, Dewen

2014-10-01

Objective. The number of items of a P300-based brain-computer interface (BCI) should be adjustable in accordance with the requirements of the specific tasks. To address this issue, we propose a novel task-oriented optimal approach aimed at increasing the performance of general P300 BCIs with different numbers of items. Approach. First, we proposed a stimulus presentation with variable dimensions (VD) paradigm as a generalization of the conventional single-character (SC) and row-column (RC) stimulus paradigms. Furthermore, an embedding design approach was employed for any given number of items. Finally, based on the score-P model of each subject, the VD flash pattern was selected by a linear interpolation approach for a certain task. Main results. The results indicate that the optimal BCI design consistently outperforms the conventional approaches, i.e., the SC and RC paradigms. Specifically, there is significant improvement in the practical information transfer rate for a large number of items. Significance. The results suggest that the proposed optimal approach would provide useful guidance in the practical design of general P300-based BCIs.

An approach to unbiased subsample interpolation for motion tracking.

PubMed

McCormick, Matthew M; Varghese, Tomy

2013-04-01

Accurate subsample displacement estimation is necessary for ultrasound elastography because of the small deformations that occur and the subsequent application of a derivative operation on local displacements. Many of the commonly used subsample estimation techniques introduce significant bias errors. This article addresses a reduced bias approach to subsample displacement estimations that consists of a two-dimensional windowed-sinc interpolation with numerical optimization. It is shown that a Welch or Lanczos window with a Nelder-Mead simplex or regular-step gradient-descent optimization is well suited for this purpose. Little improvement results from a sinc window radius greater than four data samples. The strain signal-to-noise ratio (SNR) obtained in a uniformly elastic phantom is compared with other parabolic and cosine interpolation methods; it is found that the strain SNR ratio is improved over parabolic interpolation from 11.0 to 13.6 in the axial direction and 0.7 to 1.1 in the lateral direction for an applied 1% axial deformation. The improvement was most significant for small strains and displacement tracking in the lateral direction. This approach does not rely on special properties of the image or similarity function, which is demonstrated by its effectiveness with the application of a previously described regularization technique.

Unexpected and rapid recovery of left ventricular function in patients with peripartum cardiomyopathy: impact of cardiac resynchronization therapy.

PubMed

Mouquet, Frederic; Mostefa Kara, Meriem; Lamblin, Nicolas; Coulon, Capucine; Langlois, Stephane; Marquie, Christelle; de Groote, Pascal

2012-05-01

Aim Peripartum cardiomyopathy (PPCM) is a rare cause of dilated cardiomyopathy responsible for heart failure toward the end of pregnancy, which can lead to chronic heart failure in 50% of cases. In this short report, we assessed the benefit of cardiac resynchronization in patients with PPCM and chronic systolic dysfunction despite optimal medical treatment. For the last 10 years, we managed eight patients diagnosed with PPCM. Two of them presented severe systolic dysfunction, and medical treatment resulted in limited improvement from 10% to 25% and from 25% to 28% despite optimal treatment for 9 and 6 years, respectively. These two patients were porposed to receive an implantatable cardioverter defibrillator (ICD) and cardiac resynchronization therapy (CRT). Six months after ICD-CRT treatment, we observed a significant improvement in systolic function from 25% to 45% and 28% to 50%, respectively, and positive remodelling with reduction of left ventricular end-diastolic volume from 216 to 144 mL and from 354 to 105 mL, which represent a 34% and a 70% reduction, respectively. Physicians in charge of patients with PPCM should offer the opportunity of CRT for patients whose cardiac function has not significantly improved under standard medical treatment.

Fabrication of hydrophobic fluorinated silica-polyamide thin film nanocomposite reverse osmosis membranes with dramatically improved salt rejection.

PubMed

Pang, Ruizhi; Zhang, Kaisong

2018-01-15

Thin film nanocomposite reverse osmosis (TFN RO) membranes incorporated with hydrophilic nanoparticles show a potential problem that the salt rejection can not be improved significantly. In this study, novel TFN RO membranes incorporated with hydrophobic fluorinated silica nanoparticles were fabricated to improve the salt rejection. Fluorinated silica nanoparticles were well dispersed in organic phase during the interfacial polymerization (IP) process. The TFN RO membranes were characterized with attenuated total reflectance infra-red, field emission scanning electron microscopy, atomic force microscopy and water contact angle measurements. The preparation conditions of TFN RO membranes, including IP reaction time, organic solvent removal time, and fluorinated silica loading, were optimized by characterizing desalination performance using 2000ppm NaCl aqueous solution at 1.55MPa and 25°C. The salt rejection increased significantly from 96.0% without fluorinated silica nanoparticles to 98.6% with the optimal 0.12% (w/v) fluorinated silica nanoparticles, while the water flux decreased slightly from 0.99m 3 /m 2 /day to 0.93m 3 /m 2 /day. This study demonstrated the potential use of hydrophobic nanoparticles in high-performance TFN RO membranes. Copyright © 2017 Elsevier Inc. All rights reserved.

Physical Therapy for an Adult with Chronic Stroke after Botulinum Toxin Injection for Spasticity: A Case Report

PubMed Central

Phadke, Chetan P.; Ismail, Farooq; Boulias, Chris

2015-01-01

ABSTRACT Purpose: In this case report, we describe the type and duration of a physical therapy and botulinum toxin type A (BoNTA) intervention directed at lower limb spasticity and the gait and balance improvement in a patient post-stroke. Treatment of focal spasticity with BoNTA intramuscular injections combined with physical therapy is recommended by rehabilitation experts. However, the optimal type and duration of physical therapy intervention to optimize any functional gains that follow chemodenervation induced by BoNTA has not been established. Method: One individual with chronic stroke who received BoNTA injections for upper and lower extremity spasticity was included. Physical therapy intervention consisted of 45- to 60-min sessions twice weekly for 12 weeks, based on the Bobath–neurodevelopmental therapy approach, and an activity-based home program. Results: After BoNTA injections and physical therapy, the patient made clinically significant improvements in balance and gait speed and became more independent with his ambulation. Conclusions: This case report demonstrates that physical therapy after BoNTA injections can result in significant functional improvements for individuals with spasticity after chronic stroke that may not be possible with BoNTA injections alone. PMID:25931655

Post-Optimality Analysis In Aerospace Vehicle Design

NASA Technical Reports Server (NTRS)

Braun, Robert D.; Kroo, Ilan M.; Gage, Peter J.

1993-01-01

This analysis pertains to the applicability of optimal sensitivity information to aerospace vehicle design. An optimal sensitivity (or post-optimality) analysis refers to computations performed once the initial optimization problem is solved. These computations may be used to characterize the design space about the present solution and infer changes in this solution as a result of constraint or parameter variations, without reoptimizing the entire system. The present analysis demonstrates that post-optimality information generated through first-order computations can be used to accurately predict the effect of constraint and parameter perturbations on the optimal solution. This assessment is based on the solution of an aircraft design problem in which the post-optimality estimates are shown to be within a few percent of the true solution over the practical range of constraint and parameter variations. Through solution of a reusable, single-stage-to-orbit, launch vehicle design problem, this optimal sensitivity information is also shown to improve the efficiency of the design process, For a hierarchically decomposed problem, this computational efficiency is realized by estimating the main-problem objective gradient through optimal sep&ivity calculations, By reducing the need for finite differentiation of a re-optimized subproblem, a significant decrease in the number of objective function evaluations required to reach the optimal solution is obtained.

Synthesis of Platinum-nickel Nanowires and Optimization for Oxygen Reduction Performance

DOE PAGES

Alia, Shaun M.; Pivovar, Bryan S.

2018-01-01

Platinum-nickel (Pt-Ni) nanowires were developed as fuel cell electrocatalysts, and were optimized for the performance and durability in the oxygen reduction reaction. Spontaneous galvanic displacement was used to deposit Pt layers onto Ni nanowire substrates. The synthesis approach produced catalysts with high specific activities and high Pt surface areas. Hydrogen annealing improved Pt and Ni mixing and specific activity. Acid leaching was used to preferentially remove Ni near the nanowire surface, and oxygen annealing was used to stabilize near-surface Ni, improving durability and minimizing Ni dissolution. These protocols detail the optimization of each post-synthesis processing step, including hydrogen annealing tomore » 250 degrees C, exposure to 0.1 M nitric acid, and oxygen annealing to 175 degrees C. Through these steps, Pt-Ni nanowires produced increased activities more than an order of magnitude than Pt nanoparticles, while offering significant durability improvements. The presented protocols are based on Pt-Ni systems in the development of fuel cell catalysts. Furthermore, these techniques have also been used for a variety of metal combinations, and can be applied to develop catalysts for a number of electrochemical processes.« less

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

NASA Astrophysics Data System (ADS)

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system.

PubMed

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Design principles and operating principles: the yin and yang of optimal functioning.

PubMed

Voit, Eberhard O

2003-03-01

Metabolic engineering has as a goal the improvement of yield of desired products from microorganisms and cell lines. This goal has traditionally been approached with experimental biotechnological methods, but it is becoming increasingly popular to precede the experimental phase by a mathematical modeling step that allows objective pre-screening of possible improvement strategies. The models are either linear and represent the stoichiometry and flux distribution in pathways or they are non-linear and account for the full kinetic behavior of the pathway, which is often significantly effected by regulatory signals. Linear flux analysis is simpler and requires less input information than a full kinetic analysis, and the question arises whether the consideration of non-linearities is really necessary for devising optimal strategies for yield improvements. The article analyzes this question with a generic, representative pathway. It shows that flux split ratios, which are the key criterion for linear flux analysis, are essentially sufficient for unregulated, but not for regulated branch points. The interrelationships between regulatory design on one hand and optimal patterns of operation on the other suggest the investigation of operating principles that complement design principles, like a user's manual complements the hardwiring of electronic equipment.

Synthesis of Platinum-nickel Nanowires and Optimization for Oxygen Reduction Performance

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

Alia, Shaun M.; Pivovar, Bryan S.

Platinum-nickel (Pt-Ni) nanowires were developed as fuel cell electrocatalysts, and were optimized for the performance and durability in the oxygen reduction reaction. Spontaneous galvanic displacement was used to deposit Pt layers onto Ni nanowire substrates. The synthesis approach produced catalysts with high specific activities and high Pt surface areas. Hydrogen annealing improved Pt and Ni mixing and specific activity. Acid leaching was used to preferentially remove Ni near the nanowire surface, and oxygen annealing was used to stabilize near-surface Ni, improving durability and minimizing Ni dissolution. These protocols detail the optimization of each post-synthesis processing step, including hydrogen annealing tomore » 250 degrees C, exposure to 0.1 M nitric acid, and oxygen annealing to 175 degrees C. Through these steps, Pt-Ni nanowires produced increased activities more than an order of magnitude than Pt nanoparticles, while offering significant durability improvements. The presented protocols are based on Pt-Ni systems in the development of fuel cell catalysts. Furthermore, these techniques have also been used for a variety of metal combinations, and can be applied to develop catalysts for a number of electrochemical processes.« less

Effectiveness of cognitive behavioral therapy on health-related quality of life: An evaluation of therapies provided by trainee therapists.

PubMed

Henriksson, Sophie; Anclair, Malin; Hiltunen, Arto J

2016-06-01

The present study was carried out to examine the treatment effect of cognitive behavioral therapy provided by trainee therapists at a university clinic, focusing on health-related quality of life (HRQOL) optimism and symptoms. The study was conducted through a repeated measures design and included a treatment group (n = 21), which received cognitive behavioral therapy for an average of 10.7 therapy sessions and a control group (n = 14), that was put on a wait list for 8.6 weeks on average. After treatment, the treatment group improved significantly concerning general health (p = 0.028) and optimism (p = 0.027). In addition, clients improved in several areas within mental health and displayed some reduction in anxiety symptoms. Concurrently, the results also indicated some improvement within the control group, which may have been caused by the initial therapeutic contact, expectancy effects or spontaneous remission. The study concluded that cognitive behavioral therapy provided by trainee therapists may have a positive effect on areas within HRQOL and optimism. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

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.

Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL).

PubMed

Koestler, Devin C; Jones, Meaghan J; Usset, Joseph; Christensen, Brock C; Butler, Rondi A; Kobor, Michael S; Wiencke, John K; Kelsey, Karl T

2016-03-08

Confounding due to cellular heterogeneity represents one of the foremost challenges currently facing Epigenome-Wide Association Studies (EWAS). Statistical methods leveraging the tissue-specificity of DNA methylation for deconvoluting the cellular mixture of heterogenous biospecimens offer a promising solution, however the performance of such methods depends entirely on the library of methylation markers being used for deconvolution. Here, we introduce a novel algorithm for Identifying Optimal Libraries (IDOL) that dynamically scans a candidate set of cell-specific methylation markers to find libraries that optimize the accuracy of cell fraction estimates obtained from cell mixture deconvolution. Application of IDOL to training set consisting of samples with both whole-blood DNA methylation data (Illumina HumanMethylation450 BeadArray (HM450)) and flow cytometry measurements of cell composition revealed an optimized library comprised of 300 CpG sites. When compared existing libraries, the library identified by IDOL demonstrated significantly better overall discrimination of the entire immune cell landscape (p = 0.038), and resulted in improved discrimination of 14 out of the 15 pairs of leukocyte subtypes. Estimates of cell composition across the samples in the training set using the IDOL library were highly correlated with their respective flow cytometry measurements, with all cell-specific R (2)>0.99 and root mean square errors (RMSEs) ranging from [0.97 % to 1.33 %] across leukocyte subtypes. Independent validation of the optimized IDOL library using two additional HM450 data sets showed similarly strong prediction performance, with all cell-specific R (2)>0.90 and R M S E<4.00 %. In simulation studies, adjustments for cell composition using the IDOL library resulted in uniformly lower false positive rates compared to competing libraries, while also demonstrating an improved capacity to explain epigenome-wide variation in DNA methylation within two large publicly available HM450 data sets. Despite consisting of half as many CpGs compared to existing libraries for whole blood mixture deconvolution, the optimized IDOL library identified herein resulted in outstanding prediction performance across all considered data sets and demonstrated potential to improve the operating characteristics of EWAS involving adjustments for cell distribution. In addition to providing the EWAS community with an optimized library for whole blood mixture deconvolution, our work establishes a systematic and generalizable framework for the assembly of libraries that improve the accuracy of cell mixture deconvolution.

Decision-Making Strategies for College Students

ERIC Educational Resources Information Center

Morey, Janis T.; Dansereau, Donald F.

2010-01-01

College students' decision making is often less than optimal and sometimes leads to negative consequences. The effectiveness of two strategies for improving student decision making--node-link mapping and social perspective taking (SPT)--are examined. Participants using SPT were significantly better able to evaluate decision options and develop…

Methods for improving enzymatic trans-glycosylation for synthesis of human milk oligosaccharide biomimetics.

PubMed

Zeuner, Birgitte; Jers, Carsten; Mikkelsen, Jørn Dalgaard; Meyer, Anne S

2014-10-08

Recently, significant progress has been made within enzymatic synthesis of biomimetic, functional glycans, including, for example, human milk oligosaccharides. These compounds are mainly composed of N-acetylglucosamine, fucose, sialic acid, galactose, and glucose, and their controlled enzymatic synthesis is a novel field of research in advanced food ingredient chemistry, involving the use of rare enzymes, which have until now mainly been studied for their biochemical significance, not for targeted biosynthesis applications. For the enzymatic synthesis of biofunctional glycans reaction parameter optimization to promote "reverse" catalysis with glycosidases is currently preferred over the use of glycosyl transferases. Numerous methods exist for minimizing the undesirable glycosidase-catalyzed hydrolysis and for improving the trans-glycosylation yields. This review provides an overview of the approaches and data available concerning optimization of enzymatic trans-glycosylation for novel synthesis of complex bioactive carbohydrates using sialidases, α-l-fucosidases, and β-galactosidases as examples. The use of an adequately high acceptor/donor ratio, reaction time control, continuous product removal, enzyme recycling, and/or the use of cosolvents may significantly improve trans-glycosylation and biocatalytic productivity of the enzymatic reactions. Protein engineering is also a promising technique for obtaining high trans-glycosylation yields, and proof-of-concept for reversing sialidase activity to trans-sialidase action has been established. However, the protein engineering route currently requires significant research efforts in each case because the structure-function relationship of the enzymes is presently poorly understood.

Evaluation of the 'Fitting to Outcomes eXpert' (FOX®) with established cochlear implant users.

PubMed

Buechner, Andreas; Vaerenberg, Bart; Gazibegovic, Dzemal; Brendel, Martina; De Ceulaer, Geert; Govaerts, Paul; Lenarz, Thomas

2015-01-01

To evaluate the possible impact of 'Fitting to Outcomes eXpert (FOX(®))' on cochlear implant (CI) fitting in a clinic with extensive experience of fitting a range of CI systems, as a way to assess whether a software tool such as FOX is able to complement standard clinical procedures. Ten adult post-lingually deafened and unilateral long-term users of the Advanced Bionics(TM) CI system (Clarion CII or HiRes 90K(TM)) underwent speech perception assessment with their current clinical program. One cycle 'iteration' of FOX optimization was performed and the program adjusted accordingly. After a month of using both clinical and FOX programs, a second iteration of FOX optimization was performed. Following this, the assessments were repeated without further acclimatization. FOX prescribed programming modifications in all subjects. Soundfield-aided thresholds were significantly lower for FOX than the clinical program. Group speech scores in noise were not significantly different between the two programs but three individual subjects had improved speech scores with the FOX MAP, two had worse speech scores, and five were the same. FOX provided a standardized approach to fitting based on outcome measures rather than comfort alone. The results indicated that for this group of well-fitted patients, FOX improved outcomes in some individuals. There were significant changes, both better and worse, in individual speech perception scores but median scores remained unchanged. Soundfield-aided thresholds were significantly improved for the FOX group.

Joint contact forces can be reduced by improving joint moment symmetry in below-knee amputee gait simulations.

PubMed

Koelewijn, Anne D; van den Bogert, Antonie J

2016-09-01

Despite having a fully functional knee and hip in both legs, asymmetries in joint moments of the knee and hip are often seen in gait of persons with a unilateral transtibial amputation (TTA), possibly resulting in excessive joint loading. We hypothesize that persons with a TTA can walk with more symmetric joint moments at the cost of increased effort or abnormal kinematics. The hypothesis was tested using predictive simulations of gait. Open loop controls of one gait cycle were found by solving an optimization problem that minimizes a combination of walking effort and tracking error in joint angles, ground reaction force and gait cycle duration. A second objective was added to penalize joint moment asymmetry, creating a multi-objective optimization problem. A Pareto front was constructed by changing the weights of the objectives and three solutions were analyzed to study the effect of increasing joint moment symmetry. When the optimization placed more weight on moment symmetry, walking effort increased and kinematics became less normal, confirming the hypothesis. TTA gait improved with a moderate increase in joint moment symmetry. At a small cost of effort and abnormal kinematics, the peak hip extension moment in the intact leg was decreased significantly, and so was the joint contact force in the knee and hip. Additional symmetry required a significant increase in walking effort and the joint contact forces in both hips became significantly higher than in able-bodied gait. Copyright © 2016 Elsevier B.V. All rights reserved.

Development and optimization of press coated tablets of release engineered valsartan for pulsatile delivery.

PubMed

Shah, Sunny; Patel, Romik; Soniwala, Moinuddin; Chavda, Jayant

2015-01-01

The present work is aimed to develop and optimize pulsatile delivery during dissolution of an improved formulation of valsartan to coordinate the drug release with circadian rhythm. Preliminary studies suggested that β cyclodextrin could improve the solubility of valsartan and showed AL type solubility curve. A 1:1 stoichiometric ratio of valsartan to β cyclodextrin was revealed from phase solubility studies and Job's plot. The prepared complex showed significantly better dissolution efficiency (p < 0.05) compared to pure drug, which could be due to the formation of inclusion complex as revealed from FTIR and DSC studies. Continuous dissolution-absorption studies revealed that absorption of drug from valsartan β cyclodextrin complex was significantly higher (p < 0.05) compared to pure drug, in second part press-coated tablets of valsartan β cyclodextrin complex were subsequently prepared and application of the Plackett-Burman screening design revealed that HPMC K4M and EC showed significant effect on lag time. A 3(2) full factorial design was used to measure the response of HPMC K4M and EC on lag time and time taken for 90% drug release (T90). The optimized batch prepared according to the levels obtained from the desirability function had a lag time of 6 h and consisted of HPMC K4M:ethylcellulose in a 1:1.5 ratio with 180 mg of coating and revealed a close agreement between observed and predicted value (R(2 )= 0.9694).

Improved plan quality with automated radiotherapy planning for whole brain with hippocampus sparing: a comparison to the RTOG 0933 trial.

PubMed

Krayenbuehl, J; Di Martino, M; Guckenberger, M; Andratschke, N

2017-10-02

Whole-brain radiation therapy (WBRT) with hippocampus sparing (HS) has been investigated by the radiation oncology working group (RTOG) 0933 trial for patients with multiple brain metastases. They showed a decrease of adverse neurocognitive effects with HS WBRT compared to WBRT alone. With the development of automated treatment planning system (aTPS) in the last years, a standardization of the plan quality at a high level was achieved. The goal of this study was to evaluate the feasibility of using an aTPS for the treatment of HS WBRT and see if the RTOG 0933 dose constraints could be achieved and improved. Ten consecutive patients treated with HS WBRT were enrolled in this study. 10 × 3 Gy was prescribed according to the RTOG 0933 protocol to 92% of the target volume (whole-brain excluding the hippocampus expanded by 5 mm in 3-dimensions). In contrast to RTOG 0933, the maximum allowed point dose to normal brain was significantly lowered and restricted to 36.5 Gy. All patients were planned with volumetric modulated arc therapy (VMAT) technique using four arcs. Plans were optimized using Auto-Planning (AP) (Philips Radiation Oncology Systems) with one single AP template and optimization. All the constraints from the RTOG 0933 trial were achieved. A significant improvement for the maximal dose to 2% of the brain with a reduction of 4 Gy was achieved (33.5 Gy vs. RTOG 37.5 Gy) and the minimum hippocampus dose was reduced by 10% (8.1 Gy vs. RTOG 9 Gy). A steep dose gradient around the hippocampus was achieved with a mean dose of 27.3 Gy at a distance between 0.5 cm and 1 cm from the hippocampus. The effective working time to optimize a plan was kept below 6'. Automated treatment planning for HS WBRT was able to fulfil all the recommendations from the RTOG 0933 study while significantly improving dose homogeneity and decreasing unnecessary hot spot in the normal brain. With this approach, a standardization of plan quality was achieved and the effective time required for plan optimization was minimized.

Direct position determination for digital modulation signals based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yu, Wan-Ting; Yu, Hong-yi; Du, Jian-Ping; Wang, Ding

2018-04-01

The Direct Position Determination (DPD) algorithm has been demonstrated to achieve a better accuracy with known signal waveforms. However, the signal waveform is difficult to be completely known in the actual positioning process. To solve the problem, we proposed a DPD method for digital modulation signals based on improved particle swarm optimization algorithm. First, a DPD model is established for known modulation signals and a cost function is obtained on symbol estimation. Second, as the optimization of the cost function is a nonlinear integer optimization problem, an improved Particle Swarm Optimization (PSO) algorithm is considered for the optimal symbol search. Simulations are carried out to show the higher position accuracy of the proposed DPD method and the convergence of the fitness function under different inertia weight and population size. On the one hand, the proposed algorithm can take full advantage of the signal feature to improve the positioning accuracy. On the other hand, the improved PSO algorithm can improve the efficiency of symbol search by nearly one hundred times to achieve a global optimal solution.

Comparative study of surrogate models for groundwater contamination source identification at DNAPL-contaminated sites

NASA Astrophysics Data System (ADS)

Hou, Zeyu; Lu, Wenxi

2018-05-01

Knowledge of groundwater contamination sources is critical for effectively protecting groundwater resources, estimating risks, mitigating disaster, and designing remediation strategies. Many methods for groundwater contamination source identification (GCSI) have been developed in recent years, including the simulation-optimization technique. This study proposes utilizing a support vector regression (SVR) model and a kernel extreme learning machine (KELM) model to enrich the content of the surrogate model. The surrogate model was itself key in replacing the simulation model, reducing the huge computational burden of iterations in the simulation-optimization technique to solve GCSI problems, especially in GCSI problems of aquifers contaminated by dense nonaqueous phase liquids (DNAPLs). A comparative study between the Kriging, SVR, and KELM models is reported. Additionally, there is analysis of the influence of parameter optimization and the structure of the training sample dataset on the approximation accuracy of the surrogate model. It was found that the KELM model was the most accurate surrogate model, and its performance was significantly improved after parameter optimization. The approximation accuracy of the surrogate model to the simulation model did not always improve with increasing numbers of training samples. Using the appropriate number of training samples was critical for improving the performance of the surrogate model and avoiding unnecessary computational workload. It was concluded that the KELM model developed in this work could reasonably predict system responses in given operation conditions. Replacing the simulation model with a KELM model considerably reduced the computational burden of the simulation-optimization process and also maintained high computation accuracy.

Development and Testing of an Algorithm for Efficient Resource Positioning in Pre-hospital Emergency Care

PubMed Central

Saini, Devashish; Mazza, Giovanni; Shah, Najaf; Mirza, Muzna; Gori, Mandar M; Nandigam, Hari Krishna; Orthner, Helmuth F

2006-01-01

Response times for pre-hospital emergency care may be improved with the use of algorithms that analyzes historical patterns in incident location and suggests optimal places for prepositioning of emergency response units. We will develop such an algorithm based on cluster analysis and test whether it leads to significant improvement in mileage when compared to actual historical data of dispatching based on fixed stations. PMID:17238702

Development and testing of an algorithm for efficient resource positioning in pre-hospital emergency care.

PubMed

Saini, Devashish; Mazza, Giovanni; Shah, Najaf; Mirza, Muzna; Gori, Mandar M; Nandigam, Hari Krishna; Orthner, Helmuth F

2006-01-01

Response times for pre-hospital emergency care may be improved with the use of algorithms that analyzes historical patterns in incident location and suggests optimal places for pre-positioning of emergency response units. We will develop such an algorithm based on cluster analysis and test whether it leads to significant improvement in mileage when compared to actual historical data of dispatching based on fixed stations.

An Exploratory Study of Responses to Low-Dose Lithium in African Americans and Hispanics

PubMed Central

Arnold, Jodi Gonzalez; Salcedo, Stephanie; Ketter, Terrence A.; Calabrese, Joseph R.; Rabideau, Dustin J.; Nierenberg, Andrew A.; Bazan, Melissa; Leon, Andrew C.; Friedman, Edward S.; Iosifescu, Dan; Sylvia, Louisa G.; Ostacher, Michael; Thase, Michael; Reilly-Harrington, Noreen A.; Bowden, Charles L.

2015-01-01

Objectives Few prospective studies examine the impact of ethnicity or race on outcomes with lithium for bipolar disorder. This exploratory study examines differences in lithium response and treatment outcomes in Hispanics, African Americans, and non-Hispanic Whites with bipolar disorder in the Lithium Treatment Moderate Dose Use Study (LiTMUS). Methods LiTMUS was a six-site randomized controlled trial of low-dose lithium added to optimized treatment (OPT; personalized, evidence-based pharmacotherapy) versus OPT alone in outpatients with bipolar disorder. Of 283 participants, 47 African Americans, 39 Hispanics, and 175 non-Hispanic whites were examined. We predicted minority groups would have more negative medication attitudes and higher attrition rates, but better clinical outcomes. Results African Americans in the lithium group improved more on depression and life functioning compared to whites over the 6 month study. African Americans in the OPT only group had marginal improvement on depression symptoms. For Hispanics, satisfaction with life did not significantly improve in the OPT only group, in contrast to whites and African Americans who improved over time on all measures. Attitudes toward medications did not differ across ethnic/racial groups. Conclusions African Americans show some greater improvements with lithium than non-Hispanic whites, and Hispanics showed more consistent improvements in the lithium group. The impact of low-dose lithium should be studied in a larger sample as there may be particular benefit for African Americans and Hispanics. Given that the control group (regardless of ethnicity/race) had significant improvements, optimized treatment may be beneficial for any ethnic group. PMID:25827507

SoMIR framework for designing high-NDBP photonic crystal waveguides.

PubMed

Mirjalili, Seyed Mohammad

2014-06-20

This work proposes a modularized framework for designing the structure of photonic crystal waveguides (PCWs) and reducing human involvement during the design process. The proposed framework consists of three main modules: parameters module, constraints module, and optimizer module. The first module is responsible for defining the structural parameters of a given PCW. The second module defines various limitations in order to achieve desirable optimum designs. The third module is the optimizer, in which a numerical optimization method is employed to perform optimization. As case studies, two new structures called Ellipse PCW (EPCW) and Hypoellipse PCW (HPCW) with different shape of holes in each row are proposed and optimized by the framework. The calculation results show that the proposed framework is able to successfully optimize the structures of the new EPCW and HPCW. In addition, the results demonstrate the applicability of the proposed framework for optimizing different PCWs. The results of the comparative study show that the optimized EPCW and HPCW provide 18% and 9% significant improvements in normalized delay-bandwidth product (NDBP), respectively, compared to the ring-shape-hole PCW, which has the highest NDBP in the literature. Finally, the simulations of pulse propagation confirm the manufacturing feasibility of both optimized structures.

Optimization of Saanen sperm genes amplification: evaluation of standardized protocols in genetically uncharacterized rural goats reared under a subtropical environment.

PubMed

Barbour, Elie K; Saade, Maya F; Sleiman, Fawwak T; Hamadeh, Shady K; Mouneimne, Youssef; Kassaifi, Zeina; Kayali, Ghazi; Harakeh, Steve; Jaber, Lina S; Shaib, Houssam A

2012-10-01

The purpose of this research is to optimize quantitatively the amplification of specific sperm genes in reference genomically characterized Saanen goat and to evaluate the standardized protocols applicability on sperms of uncharacterized genome of rural goats reared under subtropical environment for inclusion in future selection programs. The optimization of the protocols in Saanen sperms included three production genes (growth hormone (GH) exons 2, 3, and 4, αS1-casein (CSN1S1), and α-lactalbumin) and two health genes (MHC class II DRB and prion (PrP)). The optimization was based on varying the primers concentrations and the inclusion of a PCR cosolvent (Triton X). The impact of the studied variables on statistically significant increase in the yield of amplicons was noticed in four out of five (80%) optimized protocols, namely in those related to GH, CSN1S1, α-lactalbumin, and PrP genes (P < 0.05). There was no significant difference in the yield of amplicons related to MHC class II DRB gene, regardless of the variables used (P > 0.05). The applicability of the optimized protocols of Saanen sperm genes on amplification of uncharacterized rural goat sperms revealed a 100% success in tested individuals for amplification of GH, CSN1S1, α-lactalbumin, and MHC class II DRB genes and a 75% success for the PrP gene. The significant success in applicability of the Saanen quantitatively optimized protocols to other uncharacterized genome of rural goats allows for their inclusion in future selection, targeting the sustainability of this farming system in a subtropical environment and the improvement of the farmers livelihood.

Using simulation modeling to improve patient flow at an outpatient orthopedic clinic.

PubMed

Rohleder, Thomas R; Lewkonia, Peter; Bischak, Diane P; Duffy, Paul; Hendijani, Rosa

2011-06-01

We report on the use of discrete event simulation modeling to support process improvements at an orthopedic outpatient clinic. The clinic was effective in treating patients, but waiting time and congestion in the clinic created patient dissatisfaction and staff morale issues. The modeling helped to identify improvement alternatives including optimized staffing levels, better patient scheduling, and an emphasis on staff arriving promptly. Quantitative results from the modeling provided motivation to implement the improvements. Statistical analysis of data taken before and after the implementation indicate that waiting time measures were significantly improved and overall patient time in the clinic was reduced.

Continuous Adaptive Population Reduction (CAPR) for Differential Evolution Optimization.

PubMed

Wong, Ieong; Liu, Wenjia; Ho, Chih-Ming; Ding, Xianting

2017-06-01

Differential evolution (DE) has been applied extensively in drug combination optimization studies in the past decade. It allows for identification of desired drug combinations with minimal experimental effort. This article proposes an adaptive population-sizing method for the DE algorithm. Our new method presents improvements in terms of efficiency and convergence over the original DE algorithm and constant stepwise population reduction-based DE algorithm, which would lead to a reduced number of cells and animals required to identify an optimal drug combination. The method continuously adjusts the reduction of the population size in accordance with the stage of the optimization process. Our adaptive scheme limits the population reduction to occur only at the exploitation stage. We believe that continuously adjusting for a more effective population size during the evolutionary process is the major reason for the significant improvement in the convergence speed of the DE algorithm. The performance of the method is evaluated through a set of unimodal and multimodal benchmark functions. In combining with self-adaptive schemes for mutation and crossover constants, this adaptive population reduction method can help shed light on the future direction of a completely parameter tune-free self-adaptive DE algorithm.

Optimal Wonderful Life Utility Functions in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan; Swanson, Keith (Technical Monitor)

2000-01-01

The mathematics of Collective Intelligence (COINs) is concerned with the design of multi-agent systems so as to optimize an overall global utility function when those systems lack centralized communication and control. Typically in COINs each agent runs a distinct Reinforcement Learning (RL) algorithm, so that much of the design problem reduces to how best to initialize/update each agent's private utility function, as far as the ensuing value of the global utility is concerned. Traditional team game solutions to this problem assign to each agent the global utility as its private utility function. In previous work we used the COIN framework to derive the alternative Wonderful Life Utility (WLU), and experimentally established that having the agents use it induces global utility performance up to orders of magnitude superior to that induced by use of the team game utility. The WLU has a free parameter (the clamping parameter) which we simply set to zero in that previous work. Here we derive the optimal value of the clamping parameter, and demonstrate experimentally that using that optimal value can result in significantly improved performance over that of clamping to zero, over and above the improvement beyond traditional approaches.

A system methodology for optimization design of the structural crashworthiness of a vehicle subjected to a high-speed frontal crash

NASA Astrophysics Data System (ADS)

Xia, Liang; Liu, Weiguo; Lv, Xiaojiang; Gu, Xianguang

2018-04-01

The structural crashworthiness design of vehicles has become an important research direction to ensure the safety of the occupants. To effectively improve the structural safety of a vehicle in a frontal crash, a system methodology is presented in this study. The surrogate model of Online support vector regression (Online-SVR) is adopted to approximate crashworthiness criteria and different kernel functions are selected to enhance the accuracy of the model. The Online-SVR model is demonstrated to have the advantages of solving highly nonlinear problems and saving training costs, and can effectively be applied for vehicle structural crashworthiness design. By combining the non-dominated sorting genetic algorithm II and Monte Carlo simulation, both deterministic optimization and reliability-based design optimization (RBDO) are conducted. The optimization solutions are further validated by finite element analysis, which shows the effectiveness of the RBDO solution in the structural crashworthiness design process. The results demonstrate the advantages of using RBDO, resulting in not only increased energy absorption and decreased structural weight from a baseline design, but also a significant improvement in the reliability of the design.

Optimization of controllability and robustness of complex networks by edge directionality

NASA Astrophysics Data System (ADS)

Liang, Man; Jin, Suoqin; Wang, Dingjie; Zou, Xiufen

2016-09-01

Recently, controllability of complex networks has attracted enormous attention in various fields of science and engineering. How to optimize structural controllability has also become a significant issue. Previous studies have shown that an appropriate directional assignment can improve structural controllability; however, the evolution of the structural controllability of complex networks under attacks and cascading has always been ignored. To address this problem, this study proposes a new edge orientation method (NEOM) based on residual degree that changes the link direction while conserving topology and directionality. By comparing the results with those of previous methods in two random graph models and several realistic networks, our proposed approach is demonstrated to be an effective and competitive method for improving the structural controllability of complex networks. Moreover, numerical simulations show that our method is near-optimal in optimizing structural controllability. Strikingly, compared to the original network, our method maintains the structural controllability of the network under attacks and cascading, indicating that the NEOM can also enhance the robustness of controllability of networks. These results alter the view of the nature of controllability in complex networks, change the understanding of structural controllability and affect the design of network models to control such networks.

Imidazopyridine CB2 agonists: optimization of CB2/CB1 selectivity and implications for in vivo analgesic efficacy.

PubMed

Trotter, B Wesley; Nanda, Kausik K; Burgey, Christopher S; Potteiger, Craig M; Deng, James Z; Green, Ahren I; Hartnett, John C; Kett, Nathan R; Wu, Zhicai; Henze, Darrell A; Della Penna, Kimberly; Desai, Reshma; Leitl, Michael D; Lemaire, Wei; White, Rebecca B; Yeh, Suzie; Urban, Mark O; Kane, Stefanie A; Hartman, George D; Bilodeau, Mark T

2011-04-15

A new series of imidazopyridine CB2 agonists is described. Structural optimization improved CB2/CB1 selectivity in this series and conferred physical properties that facilitated high in vivo exposure, both centrally and peripherally. Administration of a highly selective CB2 agonist in a rat model of analgesia was ineffective despite substantial CNS exposure, while administration of a moderately selective CB2/CB1 agonist exhibited significant analgesic effects. Copyright © 2011 Elsevier Ltd. All rights reserved.

MDTM: Optimizing Data Transfer using Multicore-Aware I/O Scheduling

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

Zhang, Liang; Demar, Phil; Wu, Wenji

2017-05-09

Bulk data transfer is facing significant challenges in the coming era of big data. There are multiple performance bottlenecks along the end-to-end path from the source to destination storage system. The limitations of current generation data transfer tools themselves can have a significant impact on end-to-end data transfer rates. In this paper, we identify the issues that lead to underperformance of these tools, and present a new data transfer tool with an innovative I/O scheduler called MDTM. The MDTM scheduler exploits underlying multicore layouts to optimize throughput by reducing delay and contention for I/O reading and writing operations. With ourmore » evaluations, we show how MDTM successfully avoids NUMA-based congestion and significantly improves end-to-end data transfer rates across high-speed wide area networks.« less

MDTM: Optimizing Data Transfer using Multicore-Aware I/O Scheduling

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

Zhang, Liang; Demar, Phil; Wu, Wenji

2017-01-01

Bulk data transfer is facing significant challenges in the coming era of big data. There are multiple performance bottlenecks along the end-to-end path from the source to destination storage system. The limitations of current generation data transfer tools themselves can have a significant impact on end-to-end data transfer rates. In this paper, we identify the issues that lead to underperformance of these tools, and present a new data transfer tool with an innovative I/O scheduler called MDTM. The MDTM scheduler exploits underlying multicore layouts to optimize throughput by reducing delay and contention for I/O reading and writing operations. With ourmore » evaluations, we show how MDTM successfully avoids NUMA-based congestion and significantly improves end-to-end data transfer rates across high-speed wide area networks.« less

Optimizing and Diversifying Electric Vehicle Driving Range for U.S. Drivers

DOE PAGES

Lin, Zhenhong

2014-08-11

Properly determining the driving range is critical for accurately predicting the sales and social benefits of battery electric vehicles (BEVs). This study proposes a framework for optimizing the driving range by minimizing the sum of battery price, electricity cost, and range limitation cost referred to as the "range-related cost" as a measurement of range anxiety. The objective function is linked to policy-relevant parameters, including battery cost and price markup, battery utilization, charging infrastructure availability, vehicle efficiency, electricity and gasoline prices, household vehicle ownership, daily driving patterns, discount rate, and perceived vehicle lifetime. Qualitative discussion of the framework and its empiricalmore » application to a sample (N=36664) representing new car drivers in the United States is included. The quantitative results strongly suggest that ranges of less than 100 miles are likely to be more popular in the BEV market for a long period of time. The average optimal range among U.S. drivers is found to be largely inelastic. Still, battery cost reduction significantly drives BEV demand toward longer ranges, whereas improvement in the charging infrastructure is found to significantly drive BEV demand toward shorter ranges. In conclusion, the bias of a single-range assumption and the effects of range optimization and diversification in reducing such biases are both found to be significant.« less

Optimizing and Diversifying Electric Vehicle Driving Range for U.S. Drivers

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

Lin, Zhenhong

Properly determining the driving range is critical for accurately predicting the sales and social benefits of battery electric vehicles (BEVs). This study proposes a framework for optimizing the driving range by minimizing the sum of battery price, electricity cost, and range limitation cost referred to as the "range-related cost" as a measurement of range anxiety. The objective function is linked to policy-relevant parameters, including battery cost and price markup, battery utilization, charging infrastructure availability, vehicle efficiency, electricity and gasoline prices, household vehicle ownership, daily driving patterns, discount rate, and perceived vehicle lifetime. Qualitative discussion of the framework and its empiricalmore » application to a sample (N=36664) representing new car drivers in the United States is included. The quantitative results strongly suggest that ranges of less than 100 miles are likely to be more popular in the BEV market for a long period of time. The average optimal range among U.S. drivers is found to be largely inelastic. Still, battery cost reduction significantly drives BEV demand toward longer ranges, whereas improvement in the charging infrastructure is found to significantly drive BEV demand toward shorter ranges. In conclusion, the bias of a single-range assumption and the effects of range optimization and diversification in reducing such biases are both found to be significant.« less

Development of multidisciplinary design optimization procedures for smart composite wings and turbomachinery blades

NASA Astrophysics Data System (ADS)

Jha, Ratneshwar

Multidisciplinary design optimization (MDO) procedures have been developed for smart composite wings and turbomachinery blades. The analysis and optimization methods used are computationally efficient and sufficiently rigorous. Therefore, the developed MDO procedures are well suited for actual design applications. The optimization procedure for the conceptual design of composite aircraft wings with surface bonded piezoelectric actuators involves the coupling of structural mechanics, aeroelasticity, aerodynamics and controls. The load carrying member of the wing is represented as a single-celled composite box beam. Each wall of the box beam is analyzed as a composite laminate using a refined higher-order displacement field to account for the variations in transverse shear stresses through the thickness. Therefore, the model is applicable for the analysis of composite wings of arbitrary thickness. Detailed structural modeling issues associated with piezoelectric actuation of composite structures are considered. The governing equations of motion are solved using the finite element method to analyze practical wing geometries. Three-dimensional aerodynamic computations are performed using a panel code based on the constant-pressure lifting surface method to obtain steady and unsteady forces. The Laplace domain method of aeroelastic analysis produces root-loci of the system which gives an insight into the physical phenomena leading to flutter/divergence and can be efficiently integrated within an optimization procedure. The significance of the refined higher-order displacement field on the aeroelastic stability of composite wings has been established. The effect of composite ply orientations on flutter and divergence speeds has been studied. The Kreisselmeier-Steinhauser (K-S) function approach is used to efficiently integrate the objective functions and constraints into a single envelope function. The resulting unconstrained optimization problem is solved using the Broyden-Fletcher-Goldberg-Shanno algorithm. The optimization problem is formulated with the objective of simultaneously minimizing wing weight and maximizing its aerodynamic efficiency. Design variables include composite ply orientations, ply thicknesses, wing sweep, piezoelectric actuator thickness and actuator voltage. Constraints are placed on the flutter/divergence dynamic pressure, wing root stresses and the maximum electric field applied to the actuators. Numerical results are presented showing significant improvements, after optimization, compared to reference designs. The multidisciplinary optimization procedure for the design of turbomachinery blades integrates aerodynamic and heat transfer design objective criteria along with various mechanical and geometric constraints on the blade geometry. The airfoil shape is represented by Bezier-Bernstein polynomials, which results in a relatively small number of design variables for the optimization. Thin shear layer approximation of the Navier-Stokes equation is used for the viscous flow calculations. Grid generation is accomplished by solving Poisson equations. The maximum and average blade temperatures are obtained through a finite element analysis. Total pressure and exit kinetic energy losses are minimized, with constraints on blade temperatures and geometry. The constrained multiobjective optimization problem is solved using the K-S function approach. The results for the numerical example show significant improvements after optimization.

iATTRACT: simultaneous global and local interface optimization for protein-protein docking refinement.

PubMed

Schindler, Christina E M; de Vries, Sjoerd J; Zacharias, Martin

2015-02-01

Protein-protein interactions are abundant in the cell but to date structural data for a large number of complexes is lacking. Computational docking methods can complement experiments by providing structural models of complexes based on structures of the individual partners. A major caveat for docking success is accounting for protein flexibility. Especially, interface residues undergo significant conformational changes upon binding. This limits the performance of docking methods that keep partner structures rigid or allow limited flexibility. A new docking refinement approach, iATTRACT, has been developed which combines simultaneous full interface flexibility and rigid body optimizations during docking energy minimization. It employs an atomistic molecular mechanics force field for intermolecular interface interactions and a structure-based force field for intramolecular contributions. The approach was systematically evaluated on a large protein-protein docking benchmark, starting from an enriched decoy set of rigidly docked protein-protein complexes deviating by up to 15 Å from the native structure at the interface. Large improvements in sampling and slight but significant improvements in scoring/discrimination of near native docking solutions were observed. Complexes with initial deviations at the interface of up to 5.5 Å were refined to significantly better agreement with the native structure. Improvements in the fraction of native contacts were especially favorable, yielding increases of up to 70%. © 2014 Wiley Periodicals, Inc.

An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae

PubMed Central

Lee, Insuk; Li, Zhihua; Marcotte, Edward M.

2007-01-01

Background Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations. Methodology/Principal Findings We report a significantly improved version (v. 2) of a probabilistic functional gene network [1] of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis. Conclusions/Significance YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome). YeastNet is available from http://www.yeastnet.org. PMID:17912365

Strategies for the Optimization of Natural Leads to Anticancer Drugs or Drug Candidates

PubMed Central

Xiao, Zhiyan; Morris-Natschke, Susan L.; Lee, Kuo-Hsiung

2015-01-01

Natural products have made significant contribution to cancer chemotherapy over the past decades and remain an indispensable source of molecular and mechanistic diversity for anticancer drug discovery. More often than not, natural products may serve as leads for further drug development rather than as effective anticancer drugs by themselves. Generally, optimization of natural leads into anticancer drugs or drug candidates should not only address drug efficacy, but also improve ADMET profiles and chemical accessibility associated with the natural leads. Optimization strategies involve direct chemical manipulation of functional groups, structure-activity relationship-directed optimization and pharmacophore-oriented molecular design based on the natural templates. Both fundamental medicinal chemistry principles (e.g., bio-isosterism) and state-of-the-art computer-aided drug design techniques (e.g., structure-based design) can be applied to facilitate optimization efforts. In this review, the strategies to optimize natural leads to anticancer drugs or drug candidates are illustrated with examples and described according to their purposes. Furthermore, successful case studies on lead optimization of bioactive compounds performed in the Natural Products Research Laboratories at UNC are highlighted. PMID:26359649

Biokinetic model-based multi-objective optimization of Dunaliella tertiolecta cultivation using elitist non-dominated sorting genetic algorithm with inheritance.

PubMed

Sinha, Snehal K; Kumar, Mithilesh; Guria, Chandan; Kumar, Anup; Banerjee, Chiranjib

2017-10-01

Algal model based multi-objective optimization using elitist non-dominated sorting genetic algorithm with inheritance was carried out for batch cultivation of Dunaliella tertiolecta using NPK-fertilizer. Optimization problems involving two- and three-objective functions were solved simultaneously. The objective functions are: maximization of algae-biomass and lipid productivity with minimization of cultivation time and cost. Time variant light intensity and temperature including NPK-fertilizer, NaCl and NaHCO 3 loadings are the important decision variables. Algal model involving Monod/Andrews adsorption kinetics and Droop model with internal nutrient cell quota was used for optimization studies. Sets of non-dominated (equally good) Pareto optimal solutions were obtained for the problems studied. It was observed that time variant optimal light intensity and temperature trajectories, including optimum NPK fertilizer, NaCl and NaHCO 3 concentration has significant influence to improve biomass and lipid productivity under minimum cultivation time and cost. Proposed optimization studies may be helpful to implement the control strategy in scale-up operation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Surrogate Based Uni/Multi-Objective Optimization and Distribution Estimation Methods

NASA Astrophysics Data System (ADS)

Gong, W.; Duan, Q.; Huo, X.

2017-12-01

Parameter calibration has been demonstrated as an effective way to improve the performance of dynamic models, such as hydrological models, land surface models, weather and climate models etc. Traditional optimization algorithms usually cost a huge number of model evaluations, making dynamic model calibration very difficult, or even computationally prohibitive. With the help of a serious of recently developed adaptive surrogate-modelling based optimization methods: uni-objective optimization method ASMO, multi-objective optimization method MO-ASMO, and probability distribution estimation method ASMO-PODE, the number of model evaluations can be significantly reduced to several hundreds, making it possible to calibrate very expensive dynamic models, such as regional high resolution land surface models, weather forecast models such as WRF, and intermediate complexity earth system models such as LOVECLIM. This presentation provides a brief introduction to the common framework of adaptive surrogate-based optimization algorithms of ASMO, MO-ASMO and ASMO-PODE, a case study of Common Land Model (CoLM) calibration in Heihe river basin in Northwest China, and an outlook of the potential applications of the surrogate-based optimization methods.

DOMe: A deduplication optimization method for the NewSQL database backups

PubMed Central

Wang, Longxiang; Zhu, Zhengdong; Zhang, Xingjun; Wang, Yinfeng

2017-01-01

Reducing duplicated data of database backups is an important application scenario for data deduplication technology. NewSQL is an emerging database system and is now being used more and more widely. NewSQL systems need to improve data reliability by periodically backing up in-memory data, resulting in a lot of duplicated data. The traditional deduplication method is not optimized for the NewSQL server system and cannot take full advantage of hardware resources to optimize deduplication performance. A recent research pointed out that the future NewSQL server will have thousands of CPU cores, large DRAM and huge NVRAM. Therefore, how to utilize these hardware resources to optimize the performance of data deduplication is an important issue. To solve this problem, we propose a deduplication optimization method (DOMe) for NewSQL system backup. To take advantage of the large number of CPU cores in the NewSQL server to optimize deduplication performance, DOMe parallelizes the deduplication method based on the fork-join framework. The fingerprint index, which is the key data structure in the deduplication process, is implemented as pure in-memory hash table, which makes full use of the large DRAM in NewSQL system, eliminating the performance bottleneck problem of fingerprint index existing in traditional deduplication method. The H-store is used as a typical NewSQL database system to implement DOMe method. DOMe is experimentally analyzed by two representative backup data. The experimental results show that: 1) DOMe can reduce the duplicated NewSQL backup data. 2) DOMe significantly improves deduplication performance by parallelizing CDC algorithms. In the case of the theoretical speedup ratio of the server is 20.8, the speedup ratio of DOMe can achieve up to 18; 3) DOMe improved the deduplication throughput by 1.5 times through the pure in-memory index optimization method. PMID:29049307

Network anomaly detection system with optimized DS evidence theory.

PubMed

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

Impact of structural optimization with aeroelastic/multidisciplinary constraints on helicopter rotor design

NASA Technical Reports Server (NTRS)

Friedmann, Peretz P.

1992-01-01

This paper presents a review of the state-of-the-art in the field of structural optimization when applied to vibration reduction of helicopters in forward flight with aeroelastic and multidisciplinary constraints. It emphasizes the application of the modern approach where the optimization is formulated as a mathematical programming problem and the objective function consists of the vibration levels at the hub and behavior constraints are imposed on the blade frequencies, aeroelastic stability margins as well as on a number of additional ingredients which can have a significant effect on the overall performance and flight mechanics of the helicopter. It is shown that the integrated multidisciplinary optimization of rotorcraft offers the potential for substantial improvements which can be achieved by careful preliminary design and analysis without requiring additional hardware such as rotor vibration absorbers or isolation systems.

Helicopter vibration reduction using structural optimization with aeroelastic/multidisciplinary constraints - A survey

NASA Technical Reports Server (NTRS)

Friedmann, Peretz P.

1991-01-01

This paper presents a survey of the state-of-the-art in the field of structural optimization when applied to vibration reduction of helicopters in forward flight with aeroelastic and multidisciplinary constraints. It emphasizes the application of the modern approach where the optimization is formulated as a mathematical programming problem, the objective function consists of the vibration levels at the hub, and behavior constraints are imposed on the blade frequencies and aeroelastic stability margins, as well as on a number of additional ingredients that can have a significant effect on the overall performance and flight mechanics of the helicopter. It is shown that the integrated multidisciplinary optimization of rotorcraft offers the potential for substantial improvements, which can be achieved by careful preliminary design and analysis without requiring additional hardware such as rotor vibration absorbers of isolation systems.

Network Anomaly Detection System with Optimized DS Evidence Theory

PubMed Central

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258

Optimization of a Biometric System Based on Acoustic Images

PubMed Central

Izquierdo Fuente, Alberto; Del Val Puente, Lara; Villacorta Calvo, Juan J.; Raboso Mateos, Mariano

2014-01-01

On the basis of an acoustic biometric system that captures 16 acoustic images of a person for 4 frequencies and 4 positions, a study was carried out to improve the performance of the system. On a first stage, an analysis to determine which images provide more information to the system was carried out showing that a set of 12 images allows the system to obtain results that are equivalent to using all of the 16 images. Finally, optimization techniques were used to obtain the set of weights associated with each acoustic image that maximizes the performance of the biometric system. These results improve significantly the performance of the preliminary system, while reducing the time of acquisition and computational burden, since the number of acoustic images was reduced. PMID:24616643

Optimal Stimulus Amplitude for Vestibular Stochastic Stimulation to Improve Sensorimotor Function

NASA Technical Reports Server (NTRS)

Goel, R.; Kofman, I.; DeDios, Y. E.; Jeevarajan, J.; Stepanyan, V.; Nair, M.; Congdon, S.; Fregia, M.; Cohen, H.; Bloomberg, J. J.;

Cost analysis of the stroke volume variation guided perioperative hemodynamic optimization - an economic evaluation of the SVVOPT trial results.

PubMed

Benes, Jan; Zatloukal, Jan; Simanova, Alena; Chytra, Ivan; Kasal, Eduard

2014-01-01

Perioperative goal directed therapy (GDT) can substantially improve the outcomes of high risk surgical patients as shown by many clinical studies. However, the approach needs initial investment and can increase the already very high staff workload. These economic imperatives may be at least partly responsible for weak adherence to the GDT concept. A few models are available for the evaluation of GDT cost-effectiveness, but studies of real economic data based on a recent clinical trial are lacking. In order to address this we have performed a retrospective analysis of the data from the "Intraoperative fluid optimization using stroke volume variation in high risk surgical patients" trial (ISRCTN95085011). The health-care payers perspective was used in order to evaluate the perioperative hemodynamic optimization costs. Hospital invoices from all patients included in the trial were extracted. A direct comparison between the study (GDT, N = 60) and control (N = 60) groups was performed. A cost tree was constructed and major cost drivers evaluated. The trial showed a significant improvement in clinical outcomes for GDT treated patients. The mean cost per patient were lower in the GDT group 2877 ± 2336€ vs. 3371 ± 3238€ in controls, but without reaching a statistical significance (p = 0.596). The mean cost of all items except for intraoperative monitoring and infusions were lower for GDT than control but due to the high variability they all failed to reach statistical significance. Those costs associated with clinical care (68 ± 177€ vs. 212 ± 593€; p = 0.023) and ward stay costs (213 ± 108€ vs. 349 ± 467€; p = 0.082) were the most important differences in favour of the GDT group. Intraoperative fluid optimization with the use of stroke volume variation and Vigileo/FloTrac system showed not only a substantial improvement of morbidity, but was associated with an economic benefit. The cost-savings observed in the overall costs of postoperative care trend to offset the investment needed to run the GDT strategy and intraoperative monitoring. ISRCTN95085011.

Coupling System Design Optimization : A Survey and Assessment of Automatic Coupling Concepts for Rail Freight Cars : Volume 2. Text and Appendices.

DOT National Transportation Integrated Search

1978-05-01

The purpose of this study is to provide an independent identification, classification, and analysis of significant freight car coupling system concepts offering potential for improved safety and operating costs over the present system. The basic meth...

Integrating Reservations and Queuing in Remote Laboratory Scheduling

ERIC Educational Resources Information Center

Lowe, D.

2013-01-01

Remote laboratories (RLs) have become increasingly seen as a useful tool in supporting flexible shared access to scarce laboratory resources. An important element in supporting shared access is coordinating the scheduling of the laboratory usage. Optimized scheduling can significantly decrease access waiting times and improve the utilization level…

Coupling System Design Optimization : A Survey and Assessment of Automatic Coupling Concepts for Rail Freight Cars : Volume 1. Executive Summary.

DOT National Transportation Integrated Search

1978-05-01

The purpose of this study is to provide an independent identification, classification, and analysis of significant freight car coupling systems concepts offering potential for improved safety and operating costs over the present system. The basic met...

Query-Time Optimization Techniques for Structured Queries in Information Retrieval

ERIC Educational Resources Information Center

Cartright, Marc-Allen

2013-01-01

The use of information retrieval (IR) systems is evolving towards larger, more complicated queries. Both the IR industrial and research communities have generated significant evidence indicating that in order to continue improving retrieval effectiveness, increases in retrieval model complexity may be unavoidable. From an operational perspective,…

Fabrication and Characterization of Three Dimensional Photonic Crystals Generated by Multibeam Interference Lithography

ERIC Educational Resources Information Center

Chen, Ying-Chieh

2009-01-01

Multibeam interference lithography is investigated as a manufacturing technique for three-dimensional photonic crystal templates. In this research, optimization of the optical setup and the photoresist initiation system leads to a significant improvement of the optical quality of the crystal, as characterized by normal incidence optical…

Rapid in vitro shoot multiplication of the recalcitrant species Juglans nigra L.

Treesearch

Micah E. Stevens; Paula M. Pijut

2018-01-01

Black walnut (Juglans nigra L.) has long been prized for its timber, leading to commercial cultivation and significant breeding efforts for improving marketable traits. Vegetative and in vitro black walnut propagation techniques, however, are variable and highly genotype dependent. Optimizing plant growth regulator type and...

Novel Amalgams for In-Space Parts Fabrication

NASA Technical Reports Server (NTRS)

Cochran, Calvin; VanHoose, James R.; Grugel, Richard N.

2012-01-01

Sound amalgams can be fabricated by substituting Ga-In liquid for mercury; Cu-coated steel fibers bond well with the amalgam components. Inclusion of steel fibers significantly improved mechanical properties. An application scenario utilizing amalgams for in-space parts fabrication and repair was suggested. Procedure and materials need to be optimized

Optimizing Health Care for Adults with Spina Bifida

ERIC Educational Resources Information Center

Webb, Thomas S.

2010-01-01

Survival into adulthood for individuals with spina bifida has significantly improved over the last 40 years with the majority of patients now living as adults. Despite this growing population of adult patients who have increased medical needs compared to the general population, including spina bifida (SB)-specific care, age-related secondary…

Cost-efficiency trade-off and the design of thermoelectric power generators.

PubMed

Yazawa, Kazuaki; Shakouri, Ali

2011-09-01

The energy conversion efficiency of today's thermoelectric generators is significantly lower than that of conventional mechanical engines. Almost all of the existing research is focused on materials to improve the conversion efficiency. Here we propose a general framework to study the cost-efficiency trade-off for thermoelectric power generation. A key factor is the optimization of thermoelectric modules together with their heat source and heat sinks. Full electrical and thermal co-optimization yield a simple analytical expression for optimum design. Based on this model, power output per unit mass can be maximized. We show that the fractional area coverage of thermoelectric elements in a module could play a significant role in reducing the cost of power generation systems.

Improved Ant Algorithms for Software Testing Cases Generation

PubMed Central

Yang, Shunkun; Xu, Jiaqi

2014-01-01

Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to porduce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations. PMID:24883391

Hand placement near the visual stimulus improves orientation selectivity in V2 neurons

PubMed Central

Sergio, Lauren E.; Crawford, J. Douglas; Fallah, Mazyar

2015-01-01

Often, the brain receives more sensory input than it can process simultaneously. Spatial attention helps overcome this limitation by preferentially processing input from a behaviorally-relevant location. Recent neuropsychological and psychophysical studies suggest that attention is deployed to near-hand space much like how the oculomotor system can deploy attention to an upcoming gaze position. Here we provide the first neuronal evidence that the presence of a nearby hand enhances orientation selectivity in early visual processing area V2. When the hand was placed outside the receptive field, responses to the preferred orientation were significantly enhanced without a corresponding significant increase at the orthogonal orientation. Consequently, there was also a significant sharpening of orientation tuning. In addition, the presence of the hand reduced neuronal response variability. These results indicate that attention is automatically deployed to the space around a hand, improving orientation selectivity. Importantly, this appears to be optimal for motor control of the hand, as opposed to oculomotor mechanisms which enhance responses without sharpening orientation selectivity. Effector-based mechanisms for visual enhancement thus support not only the spatiotemporal dissociation of gaze and reach, but also the optimization of vision for their separate requirements for guiding movements. PMID:25717165

Research on connection structure of aluminumbody bus using multi-objective topology optimization

NASA Astrophysics Data System (ADS)

Peng, Q.; Ni, X.; Han, F.; Rhaman, K.; Ulianov, C.; Fang, X.

2018-01-01

For connecting Aluminum Alloy bus body aluminum components often occur the problem of failure, a new aluminum alloy connection structure is designed based on multi-objective topology optimization method. Determining the shape of the outer contour of the connection structure with topography optimization, establishing a topology optimization model of connections based on SIMP density interpolation method, going on multi-objective topology optimization, and improving the design of the connecting piece according to the optimization results. The results show that the quality of the aluminum alloy connector after topology optimization is reduced by 18%, and the first six natural frequencies are improved and the strength performance and stiffness performance are obviously improved.

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

PubMed

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

2013-10-01

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

Long-term lifestyle intervention with optimized high-intensity interval training improves body composition, cardiometabolic risk, and exercise parameters in patients with abdominal obesity.

PubMed

Gremeaux, Vincent; Drigny, Joffrey; Nigam, Anil; Juneau, Martin; Guilbeault, Valérie; Latour, Elise; Gayda, Mathieu

2012-11-01

The aim of this study was to study the impact of a combined long-term lifestyle and high-intensity interval training intervention on body composition, cardiometabolic risk, and exercise tolerance in overweight and obese subjects. Sixty-two overweight and obese subjects (53.3 ± 9.7 yrs; mean body mass index, 35.8 ± 5 kg/m(2)) were retrospectively identified at their entry into a 9-mo program consisting of individualized nutritional counselling, optimized high-intensity interval exercise, and resistance training two to three times a week. Anthropometric measurements, cardiometabolic risk factors, and exercise tolerance were measured at baseline and program completion. Adherence rate was 97%, and no adverse events occurred with high-intensity interval exercise training. Exercise training was associated with a weekly energy expenditure of 1582 ± 284 kcal. Clinically and statistically significant improvements were observed for body mass (-5.3 ± 5.2 kg), body mass index (-1.9 ± 1.9 kg/m(2)), waist circumference (-5.8 ± 5.4 cm), and maximal exercise capacity (+1.26 ± 0.84 metabolic equivalents) (P < 0.0001 for all parameters). Total fat mass and trunk fat mass, lipid profile, and triglyceride/high-density lipoprotein ratio were also significantly improved (P < 0.0001). At program completion, the prevalence of metabolic syndrome was reduced by 32.5% (P < 0.05). Independent predictors of being a responder to body mass and waist circumference loss were baseline body mass index and resting metabolic rate; those for body mass index decrease were baseline waist circumference and triglyceride/high-density lipoprotein cholesterol ratio. A long-term lifestyle intervention with optimized high-intensity interval exercise improves body composition, cardiometabolic risk, and exercise tolerance in obese subjects. This intervention seems safe, efficient, and well tolerated and could improve adherence to exercise training in this population.

A gEUD-based inverse planning technique for HDR prostate brachytherapy: Feasibility study

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

Giantsoudi, D.; Department of Radiation Oncology, Francis H. Burr Proton Therapy Center, Boston, Massachusetts 02114; Baltas, D.

2013-04-15

Purpose: The purpose of this work was to study the feasibility of a new inverse planning technique based on the generalized equivalent uniform dose for image-guided high dose rate (HDR) prostate cancer brachytherapy in comparison to conventional dose-volume based optimization. Methods: The quality of 12 clinical HDR brachytherapy implants for prostate utilizing HIPO (Hybrid Inverse Planning Optimization) is compared with alternative plans, which were produced through inverse planning using the generalized equivalent uniform dose (gEUD). All the common dose-volume indices for the prostate and the organs at risk were considered together with radiobiological measures. The clinical effectiveness of the differentmore » dose distributions was investigated by comparing dose volume histogram and gEUD evaluators. Results: Our results demonstrate the feasibility of gEUD-based inverse planning in HDR brachytherapy implants for prostate. A statistically significant decrease in D{sub 10} or/and final gEUD values for the organs at risk (urethra, bladder, and rectum) was found while improving dose homogeneity or dose conformity of the target volume. Conclusions: Following the promising results of gEUD-based optimization in intensity modulated radiation therapy treatment optimization, as reported in the literature, the implementation of a similar model in HDR brachytherapy treatment plan optimization is suggested by this study. The potential of improved sparing of organs at risk was shown for various gEUD-based optimization parameter protocols, which indicates the ability of this method to adapt to the user's preferences.« less

An efficient hybrid approach for multiobjective optimization of water distribution systems

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.

2014-05-01

An efficient hybrid approach for the design of water distribution systems (WDSs) with multiple objectives is described in this paper. The objectives are the minimization of the network cost and maximization of the network resilience. A self-adaptive multiobjective differential evolution (SAMODE) algorithm has been developed, in which control parameters are automatically adapted by means of evolution instead of the presetting of fine-tuned parameter values. In the proposed method, a graph algorithm is first used to decompose a looped WDS into a shortest-distance tree (T) or forest, and chords (Ω). The original two-objective optimization problem is then approximated by a series of single-objective optimization problems of the T to be solved by nonlinear programming (NLP), thereby providing an approximate Pareto optimal front for the original whole network. Finally, the solutions at the approximate front are used to seed the SAMODE algorithm to find an improved front for the original entire network. The proposed approach is compared with two other conventional full-search optimization methods (the SAMODE algorithm and the NSGA-II) that seed the initial population with purely random solutions based on three case studies: a benchmark network and two real-world networks with multiple demand loading cases. Results show that (i) the proposed NLP-SAMODE method consistently generates better-quality Pareto fronts than the full-search methods with significantly improved efficiency; and (ii) the proposed SAMODE algorithm (no parameter tuning) exhibits better performance than the NSGA-II with calibrated parameter values in efficiently offering optimal fronts.

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.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE PAGES

Xi, Maolong; Lu, Dan; Gui, Dongwei; ...

2016-11-27

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Effects of Self-esteem, Optimism, and Perceived Control on Depressive Symptoms in Stroke Survivor-Spouse Dyads.

PubMed

Chung, Misook L; Bakas, Tamilyn; Plue, Laura D; Williams, Linda S

2016-01-01

Depressive symptoms are common in stroke survivors and their family caregivers. Given the interdependent relationship between the members of dyads in poststroke management, improving depressive symptoms in dyads may depend on their partner's characteristics. Self-esteem, optimism, and perceived control, all known to be associated with depressive symptoms in an individual, may also contribute to their partner's depressive symptoms. The purpose of this study is to examine actor and partner effects of self-esteem, optimism, and perceived control on depression in stroke survivors and their spousal caregivers. A total of 112 ischemic stroke survivors (78% white, 34% women; mean age, 62.5 ± 12.3 years) and their spouses (mean age, 60.6 ± 12.9 years) completed surveys in which depressive symptoms, self-esteem, optimism, and perceived control were assessed using the Patient Health Questionnaire, the Rosenberg Self-esteem Scale, the Revised Life Orientation Test, and the Sense of Control Scale. Multilevel modeling, actor-partner interdependence model regression was used to determine influences on depressive symptoms within the dyad. Individuals with lower self-esteem, optimism, and perceived control had higher levels of depressive symptoms. Stroke survivors whose spouses had lower levels of self-esteem (B = -0.338, P < .001) and optimism (B = -0.361, P < .027) tended to have higher levels of depressive symptoms. Spouses whose stroke survivors had lower levels of self-esteem (B = -0.047, P = .036) also had higher levels of depressive symptoms. We found significant partner effects of self-esteem on depression for both members and partner effect of optimism on patient's depressive symptoms. These findings suggest that further research is needed to determine if dyadic interventions may help to improve self-esteem, optimism, and depressive symptoms in both patients and their caregivers.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

NASA Astrophysics Data System (ADS)

Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan

2017-01-01

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

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

Xi, Maolong; Lu, Dan; Gui, Dongwei

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Using Intel Xeon Phi to accelerate the WRF TEMF planetary boundary layer scheme

NASA Astrophysics Data System (ADS)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen

2014-05-01

The Weather Research and Forecasting (WRF) model is designed for numerical weather prediction and atmospheric research. The WRF software infrastructure consists of several components such as dynamic solvers and physics schemes. Numerical models are used to resolve the large-scale flow. However, subgrid-scale parameterizations are for an estimation of small-scale properties (e.g., boundary layer turbulence and convection, clouds, radiation). Those have a significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. For the cloudy planetary boundary layer (PBL), it is fundamental to parameterize vertical turbulent fluxes and subgrid-scale condensation in a realistic manner. A parameterization based on the Total Energy - Mass Flux (TEMF) that unifies turbulence and moist convection components produces a better result that the other PBL schemes. For that reason, the TEMF scheme is chosen as the PBL scheme we optimized for Intel Many Integrated Core (MIC), which ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code at trillions of calculations per second using the familiar programming model. In this paper, we present our optimization results for TEMF planetary boundary layer scheme. The optimizations that were performed were quite generic in nature. Those optimizations included vectorization of the code to utilize vector units inside each CPU. Furthermore, memory access was improved by scalarizing some of the intermediate arrays. The results show that the optimization improved MIC performance by 14.8x. Furthermore, the optimizations increased CPU performance by 2.6x compared to the original multi-threaded code on quad core Intel Xeon E5-2603 running at 1.8 GHz. Compared to the optimized code running on a single CPU socket the optimized MIC code is 6.2x faster.

Effects of Self-Esteem, Optimism, and Perceived Control on Depressive Symptoms in Stroke Survivor-Spouse Dyads

PubMed Central

Chung, Misook L.; Bakas, Tamilyn; Plue, Laura D.; Williams, Linda S.

2014-01-01

Background Depressive symptoms are common in stroke survivors and their family caregivers. Given the interdependent relationship between the members of dyads in post-stroke management, improving depressive symptoms in dyads may depend on their partner's characteristics. Self-esteem, optimism, and perceived control, all known to be associated with depressive symptoms in an individual, may also contribute to their partner's depressive symptoms. Purpose The purpose of this study was to examine actor and partner effects of self-esteem, optimism, and perceived control on depression in the stroke survivors and their spousal caregivers. Methods A total of 112 ischemic stroke survivors (78% white, 34% female, mean age 62.5 ± 12.3) and their spouses (mean age 60.6 ±12.9) completed surveys in which depressive symptoms, self-esteem, optimism, and perceived control were assessed using the Patient Health Questionnaire, the Rosenberg Self-esteem Scale, the Revised Life Orientation Test, and the Sense of Control Scale. Multilevel modeling, actor-partner interdependence model regression was used to determine influences on depressive symptoms within the dyad. Results Individuals with lower self-esteem, optimism, and perceived control had higher levels of depressive symptoms. Stroke survivors whose spouses had lower levels of self-esteem (B= −.338, P<.001) and optimism (B= −.361, P<.027) tended to have higher levels of depressive symptoms. Spouses whose stroke survivors had lower levels of self-esteem (B= −.047, P=.036) also had higher levels of depressive symptoms. Conclusion We found significant partner effects of self-esteem on depression for both members and partner effect of optimism on patient's depressive symptoms. These findings suggest that further research is needed to determine if dyadic interventions may help to improve self-esteem, optimism, and depressive symptoms in both patients and their caregivers. PMID:25658182

Benzocaine loaded solid lipid nanoparticles: Formulation design, in vitro and in vivo evaluation of local anesthetic effect.

PubMed

Basha, Mona; Abd El-Alim, Sameh Hosam; Kassem, Ahmed Alaa; El Awdan, Sally; Awad, Gamal

2015-01-01

The aim of the present work is the development and evaluation of solid lipid nanoparticles (SLNs) as carrier system for topical delivery of benzocaine (BZC) improving its local anesthesia aiming to produce a fast acting and long lasting topical formulation. BZC loaded SLNs were prepared using a full factorial design to study the influence of the type of polyoxyethylene sorbitan ester surfactants as well as their concentration as independent variables on the particle size, entrapment efficacy and zeta potential selected as dependent variables. Design of experiment (DOE) and the analysis of variance (ANOVA) were conducted to assess the optimization of the developed formulations. The results indicated that the fatty acid chain length of tested surfactants and their concentration had a significant effect on the studied responses. The optimized formulations were spherical in shape of mean particle diameters<350 nm with negatively charged surface <-20mV. Particles were characterized using differential scanning calorimetry and X-ray powder diffraction confirming the amorphous nature and the uniformity of drug inclusion in the lipid matrix. Optimized BZC-SLNs were incorporated into hydrogels characterized by a pseudoplastic non-Newtonian behavior. In vitro release study revealed an apparently biphasic release process with sustained release profile following Higuchi kinetics. BZC loaded SLNs hydrogels showed more potent anesthetic effect compared to BZC hydrogel evaluated using tail-flick analgesimeter, confirming significant improvement in both the intensity and duration of anesthetic effect. The above results proved that SLNs represent good candidates to encapsulate BZC improving its therapeutic efficacy for the topical treatment of pain.

An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities.

PubMed

Amer, Hayder; Salman, Naveed; Hawes, Matthew; Chaqfeh, Moumena; Mihaylova, Lyudmila; Mayfield, Martin

2016-06-30

Vehicular traffic congestion is a significant problem that arises in many cities. This is due to the increasing number of vehicles that are driving on city roads of limited capacity. The vehicular congestion significantly impacts travel distance, travel time, fuel consumption and air pollution. Avoidance of traffic congestion and providing drivers with optimal paths are not trivial tasks. The key contribution of this work consists of the developed approach for dynamic calculation of optimal traffic routes. Two attributes (the average travel speed of the traffic and the roads' length) are utilized by the proposed method to find the optimal paths. The average travel speed values can be obtained from the sensors deployed in smart cities and communicated to vehicles via the Internet of Vehicles and roadside communication units. The performance of the proposed algorithm is compared to three other algorithms: the simulated annealing weighted sum, the simulated annealing technique for order preference by similarity to the ideal solution and the Dijkstra algorithm. The weighted sum and technique for order preference by similarity to the ideal solution methods are used to formulate different attributes in the simulated annealing cost function. According to the Sheffield scenario, simulation results show that the improved simulated annealing technique for order preference by similarity to the ideal solution method improves the traffic performance in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO₂ emissions as compared to other algorithms; also, similar performance patterns were achieved for the Birmingham test scenario.

Thermal Stability of Al2O3/Silicone Composites as High-Temperature Encapsulants

NASA Astrophysics Data System (ADS)

Yao, Yiying

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities

PubMed Central

Amer, Hayder; Salman, Naveed; Hawes, Matthew; Chaqfeh, Moumena; Mihaylova, Lyudmila; Mayfield, Martin

2016-01-01

Vehicular traffic congestion is a significant problem that arises in many cities. This is due to the increasing number of vehicles that are driving on city roads of limited capacity. The vehicular congestion significantly impacts travel distance, travel time, fuel consumption and air pollution. Avoidance of traffic congestion and providing drivers with optimal paths are not trivial tasks. The key contribution of this work consists of the developed approach for dynamic calculation of optimal traffic routes. Two attributes (the average travel speed of the traffic and the roads’ length) are utilized by the proposed method to find the optimal paths. The average travel speed values can be obtained from the sensors deployed in smart cities and communicated to vehicles via the Internet of Vehicles and roadside communication units. The performance of the proposed algorithm is compared to three other algorithms: the simulated annealing weighted sum, the simulated annealing technique for order preference by similarity to the ideal solution and the Dijkstra algorithm. The weighted sum and technique for order preference by similarity to the ideal solution methods are used to formulate different attributes in the simulated annealing cost function. According to the Sheffield scenario, simulation results show that the improved simulated annealing technique for order preference by similarity to the ideal solution method improves the traffic performance in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO2 emissions as compared to other algorithms; also, similar performance patterns were achieved for the Birmingham test scenario. PMID:27376289

Optimizing Irregular Applications for Energy and Performance on the Tilera Many-core Architecture

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

Chavarría-Miranda, Daniel; Panyala, Ajay R.; Halappanavar, Mahantesh

Optimizing applications simultaneously for energy and performance is a complex problem. High performance, parallel, irregular applications are notoriously hard to optimize due to their data-dependent memory accesses, lack of structured locality and complex data structures and code patterns. Irregular kernels are growing in importance in applications such as machine learning, graph analytics and combinatorial scientific computing. Performance- and energy-efficient implementation of these kernels on modern, energy efficient, multicore and many-core platforms is therefore an important and challenging problem. We present results from optimizing two irregular applications { the Louvain method for community detection (Grappolo), and high-performance conjugate gradient (HPCCG) {more » on the Tilera many-core system. We have significantly extended MIT's OpenTuner auto-tuning framework to conduct a detailed study of platform-independent and platform-specific optimizations to improve performance as well as reduce total energy consumption. We explore the optimization design space along three dimensions: memory layout schemes, compiler-based code transformations, and optimization of parallel loop schedules. Using auto-tuning, we demonstrate whole node energy savings of up to 41% relative to a baseline instantiation, and up to 31% relative to manually optimized variants.« less

Efficient Geometry Minimization and Transition Structure Optimization Using Interpolated Potential Energy Surfaces and Iteratively Updated Hessians.

PubMed

Zheng, Jingjing; Frisch, Michael J

2017-12-12

An efficient geometry optimization algorithm based on interpolated potential energy surfaces with iteratively updated Hessians is presented in this work. At each step of geometry optimization (including both minimization and transition structure search), an interpolated potential energy surface is properly constructed by using the previously calculated information (energies, gradients, and Hessians/updated Hessians), and Hessians of the two latest geometries are updated in an iterative manner. The optimized minimum or transition structure on the interpolated surface is used for the starting geometry of the next geometry optimization step. The cost of searching the minimum or transition structure on the interpolated surface and iteratively updating Hessians is usually negligible compared with most electronic structure single gradient calculations. These interpolated potential energy surfaces are often better representations of the true potential energy surface in a broader range than a local quadratic approximation that is usually used in most geometry optimization algorithms. Tests on a series of large and floppy molecules and transition structures both in gas phase and in solutions show that the new algorithm can significantly improve the optimization efficiency by using the iteratively updated Hessians and optimizations on interpolated surfaces.

A new chaotic multi-verse optimization algorithm for solving engineering optimization problems

NASA Astrophysics Data System (ADS)

Sayed, Gehad Ismail; Darwish, Ashraf; Hassanien, Aboul Ella

2018-03-01

Multi-verse optimization algorithm (MVO) is one of the recent meta-heuristic optimization algorithms. The main inspiration of this algorithm came from multi-verse theory in physics. However, MVO like most optimization algorithms suffers from low convergence rate and entrapment in local optima. In this paper, a new chaotic multi-verse optimization algorithm (CMVO) is proposed to overcome these problems. The proposed CMVO is applied on 13 benchmark functions and 7 well-known design problems in the engineering and mechanical field; namely, three-bar trust, speed reduce design, pressure vessel problem, spring design, welded beam, rolling element-bearing and multiple disc clutch brake. In the current study, a modified feasible-based mechanism is employed to handle constraints. In this mechanism, four rules were used to handle the specific constraint problem through maintaining a balance between feasible and infeasible solutions. Moreover, 10 well-known chaotic maps are used to improve the performance of MVO. The experimental results showed that CMVO outperforms other meta-heuristic optimization algorithms on most of the optimization problems. Also, the results reveal that sine chaotic map is the most appropriate map to significantly boost MVO's performance.

Parallel AFSA algorithm accelerating based on MIC architecture

NASA Astrophysics Data System (ADS)

Zhou, Junhao; Xiao, Hong; Huang, Yifan; Li, Yongzhao; Xu, Yuanrui

2017-05-01

Analysis AFSA past for solving the traveling salesman problem, the algorithm efficiency is often a big problem, and the algorithm processing method, it does not fully responsive to the characteristics of the traveling salesman problem to deal with, and therefore proposes a parallel join improved AFSA process. The simulation with the current TSP known optimal solutions were analyzed, the results showed that the AFSA iterations improved less, on the MIC cards doubled operating efficiency, efficiency significantly.

Study and Optimization of Helicopter Subfloor Energy Absorption Structure with Foldcore Sandwich Structures

NASA Astrophysics Data System (ADS)

HuaZhi, Zhou; ZhiJin, Wang

2017-11-01

The intersection element is an important part of the helicopter subfloor structure. In order to improve the crashworthiness properties, the floor and the skin of the intersection element are replaced with foldcore sandwich structures. Foldcore is a kind of high-energy absorption structure. Compared with original structure, the new intersection element shows better buffering capacity and energy-absorption capacity. To reduce structure’s mass while maintaining the crashworthiness requirements satisfied, optimization of the intersection element geometric parameters is conducted. An optimization method using NSGA-II and Anisotropic Kriging is used. A significant CPU time saving can be obtained by replacing numerical model with Anisotropic Kriging surrogate model. The operation allows 17.15% reduce of the intersection element mass.

Optimal approach to quantum communication using dynamic programming.

PubMed

Jiang, Liang; Taylor, Jacob M; Khaneja, Navin; Lukin, Mikhail D

2007-10-30

Reliable preparation of entanglement between distant systems is an outstanding problem in quantum information science and quantum communication. In practice, this has to be accomplished by noisy channels (such as optical fibers) that generally result in exponential attenuation of quantum signals at large distances. A special class of quantum error correction protocols, quantum repeater protocols, can be used to overcome such losses. In this work, we introduce a method for systematically optimizing existing protocols and developing more efficient protocols. Our approach makes use of a dynamic programming-based searching algorithm, the complexity of which scales only polynomially with the communication distance, letting us efficiently determine near-optimal solutions. We find significant improvements in both the speed and the final-state fidelity for preparing long-distance entangled states.

A Monte Carlo simulation and setup optimization of output efficiency to PGNAA thermal neutron using 252Cf neutrons

NASA Astrophysics Data System (ADS)

Zhang, Jin-Zhao; Tuo, Xian-Guo

2014-07-01

We present the design and optimization of a prompt γ-ray neutron activation analysis (PGNAA) thermal neutron output setup based on Monte Carlo simulations using MCNP5 computer code. In these simulations, the moderator materials, reflective materials, and structure of the PGNAA 252Cf neutrons of thermal neutron output setup are optimized. The simulation results reveal that the thin layer paraffin and the thick layer of heavy water moderating effect work best for the 252Cf neutron spectrum. Our new design shows a significantly improved performance of the thermal neutron flux and flux rate, that are increased by 3.02 times and 3.27 times, respectively, compared with the conventional neutron source design.

Early Detection of Ureteropelvic Junction Obstruction Using Signal Analysis and Machine Learning: A Dynamic Solution to a Dynamic Problem.

PubMed

Blum, Emily S; Porras, Antonio R; Biggs, Elijah; Tabrizi, Pooneh R; Sussman, Rachael D; Sprague, Bruce M; Shalaby-Rana, Eglal; Majd, Massoud; Pohl, Hans G; Linguraru, Marius George

2017-10-21

We sought to define features that describe the dynamic information in diuresis renograms for the early detection of clinically significant hydronephrosis caused by ureteropelvic junction obstruction. We studied the diuresis renogram of 55 patients with a mean ± SD age of 75 ± 66 days who had congenital hydronephrosis at initial presentation. Five patients had bilaterally affected kidneys for a total of 60 diuresis renograms. Surgery was performed on 35 kidneys. We extracted 45 features based on curve shape and wavelet analysis from the drainage curves recorded after furosemide administration. The optimal features were selected as the combination that maximized the ROC AUC obtained from a linear support vector machine classifier trained to classify patients as with or without obstruction. Using these optimal features we performed leave 1 out cross validation to estimate the accuracy, sensitivity and specificity of our framework. Results were compared to those obtained using post-diuresis drainage half-time and the percent of clearance after 30 minutes. Our framework had 93% accuracy, including 91% sensitivity and 96% specificity, to predict surgical cases. This was a significant improvement over the same accuracy of 82%, including 71% sensitivity and 96% specificity obtained from half-time and 30-minute clearance using the optimal thresholds of 24.57 minutes and 55.77%, respectively. Our machine learning framework significantly improved the diagnostic accuracy of clinically significant hydronephrosis compared to half-time and 30-minute clearance. This aids in the clinical decision making process by offering a tool for earlier detection of severe cases and it has the potential to reduce the number of diuresis renograms required for diagnosis. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

Optimal digital filtering for tremor suppression.

PubMed

Gonzalez, J G; Heredia, E A; Rahman, T; Barner, K E; Arce, G R

2000-05-01

Remote manually operated tasks such as those found in teleoperation, virtual reality, or joystick-based computer access, require the generation of an intermediate electrical signal which is transmitted to the controlled subsystem (robot arm, virtual environment, or a cursor in a computer screen). When human movements are distorted, for instance, by tremor, performance can be improved by digitally filtering the intermediate signal before it reaches the controlled device. This paper introduces a novel tremor filtering framework in which digital equalizers are optimally designed through pursuit tracking task experiments. Due to inherent properties of the man-machine system, the design of tremor suppression equalizers presents two serious problems: 1) performance criteria leading to optimizations that minimize mean-squared error are not efficient for tremor elimination and 2) movement signals show ill-conditioned autocorrelation matrices, which often result in useless or unstable solutions. To address these problems, a new performance indicator in the context of tremor is introduced, and the optimal equalizer according to this new criterion is developed. Ill-conditioning of the autocorrelation matrix is overcome using a novel method which we call pulled-optimization. Experiments performed with artificially induced vibrations and a subject with Parkinson's disease show significant improvement in performance. Additional results, along with MATLAB source code of the algorithms, and a customizable demo for PC joysticks, are available on the Internet at http:¿tremor-suppression.com.

Conflict Resolution for Wind-Optimal Aircraft Trajectories in North Atlantic Oceanic Airspace with Wind Uncertainties

NASA Technical Reports Server (NTRS)

Rodionova, Olga; Sridhar, Banavar; Ng, Hok K.

2016-01-01

Air traffic in the North Atlantic oceanic airspace (NAT) experiences very strong winds caused by jet streams. Flying wind-optimal trajectories increases individual flight efficiency, which is advantageous when operating in the NAT. However, as the NAT is highly congested during peak hours, a large number of potential conflicts between flights are detected for the sets of wind-optimal trajectories. Conflict resolution performed at the strategic level of flight planning can significantly reduce the airspace congestion. However, being completed far in advance, strategic planning can only use predicted environmental conditions that may significantly differ from the real conditions experienced further by aircraft. The forecast uncertainties result in uncertainties in conflict prediction, and thus, conflict resolution becomes less efficient. This work considers wind uncertainties in order to improve the robustness of conflict resolution in the NAT. First, the influence of wind uncertainties on conflict prediction is investigated. Then, conflict resolution methods accounting for wind uncertainties are proposed.

Targeted Structural Optimization with Additive Manufacturing of Metals

NASA Technical Reports Server (NTRS)

Burt, Adam; Hull, Patrick

2015-01-01

The recent advances in additive manufacturing (AM) of metals have now improved the state-of-the-art such that traditionally non-producible parts can be readily produced in a cost-effective way. Because of these advances in manufacturing technology, structural optimization techniques are well positioned to supplement and advance this new technology. The goal of this project is to develop a structural design, analysis, and optimization framework combined with AM to significantly light-weight the interior of metallic structures while maintaining the selected structural properties of the original solid. This is a new state-of-the-art capability to significantly reduce mass, while maintaining the structural integrity of the original design, something that can only be done with AM. In addition, this framework will couple the design, analysis, and fabrication process, meaning that what has been designed directly represents the produced part, thus closing the loop on the design cycle and removing human iteration between design and fabrication. This fundamental concept has applications from light-weighting launch vehicle components to in situ resource fabrication.

CONDUIT: A New Multidisciplinary Integration Environment for Flight Control Development

NASA Technical Reports Server (NTRS)

Tischler, Mark B.; Colbourne, Jason D.; Morel, Mark R.; Biezad, Daniel J.; Levine, William S.; Moldoveanu, Veronica

1997-01-01

A state-of-the-art computational facility for aircraft flight control design, evaluation, and integration called CONDUIT (Control Designer's Unified Interface) has been developed. This paper describes the CONDUIT tool and case study applications to complex rotary- and fixed-wing fly-by-wire flight control problems. Control system analysis and design optimization methods are presented, including definition of design specifications and system models within CONDUIT, and the multi-objective function optimization (CONSOL-OPTCAD) used to tune the selected design parameters. Design examples are based on flight test programs for which extensive data are available for validation. CONDUIT is used to analyze baseline control laws against pertinent military handling qualities and control system specifications. In both case studies, CONDUIT successfully exploits trade-offs between forward loop and feedback dynamics to significantly improve the expected handling, qualities and minimize the required actuator authority. The CONDUIT system provides a new environment for integrated control system analysis and design, and has potential for significantly reducing the time and cost of control system flight test optimization.

Optimizing Robinson Operator with Ant Colony Optimization As a Digital Image Edge Detection Method

NASA Astrophysics Data System (ADS)

Yanti Nasution, Tarida; Zarlis, Muhammad; K. M Nasution, Mahyuddin

2017-12-01

Edge detection serves to identify the boundaries of an object against a background of mutual overlap. One of the classic method for edge detection is operator Robinson. Operator Robinson produces a thin, not assertive and grey line edge. To overcome these deficiencies, the proposed improvements to edge detection method with the approach graph with Ant Colony Optimization algorithm. The repairs may be performed are thicken the edge and connect the edges cut off. Edge detection research aims to do optimization of operator Robinson with Ant Colony Optimization then compare the output and generated the inferred extent of Ant Colony Optimization can improve result of edge detection that has not been optimized and improve the accuracy of the results of Robinson edge detection. The parameters used in performance measurement of edge detection are morphology of the resulting edge line, MSE and PSNR. The result showed that Robinson and Ant Colony Optimization method produces images with a more assertive and thick edge. Ant Colony Optimization method is able to be used as a method for optimizing operator Robinson by improving the image result of Robinson detection average 16.77 % than classic Robinson result.

Feasibility study of modern airships, phase 1. Volume 2: Parametric analysis (task 3). [lift, weight (mass)

NASA Technical Reports Server (NTRS)

Lancaster, J. W.

1975-01-01

Various types of lighter-than-air vehicles from fully buoyant to semibuoyant hybrids were examined. Geometries were optimized for gross lifting capabilities for ellipsoidal airships, modified delta planform lifting bodies, and a short-haul, heavy-lift vehicle concept. It is indicated that: (1) neutrally buoyant airships employing a conservative update of materials and propulsion technology provide significant improvements in productivity; (2) propulsive lift for VTOL and aerodynamic lift for cruise significantly improve the productivity of low to medium gross weight ellipsoidal airships; and (3) the short-haul, heavy-lift vehicle, consisting of a simple combination of an ellipsoidal airship hull and existing helicopter componentry, provides significant potential for low-cost, near-term applications for ultra-heavy lift missions.

The Effects of Optimism and Gratitude on Physical Activity, Biomarkers, and Readmissions Following an Acute Coronary Syndrome: The Gratitude Research in Acute Coronary Events (GRACE) Study

PubMed Central

Huffman, Jeff C.; Beale, Eleanor E.; Celano, Christopher M.; Beach, Scott R.; Belcher, Arianna M.; Moore, Shannon V.; Suarez, Laura; Motiwala, Shweta R.; Gandhi, Parul U.; Gaggin, Hanna; Januzzi, James L.

2015-01-01

Background Positive psychological constructs, such as optimism, are associated with beneficial health outcomes. However, no study has separately examined the effects of multiple positive psychological constructs on behavioral, biological, and clinical outcomes after an acute coronary syndrome (ACS). Accordingly, we aimed to investigate associations of baseline optimism and gratitude with subsequent physical activity, prognostic biomarkers, and cardiac rehospitalizations in post-ACS patients. Methods and Results Participants were enrolled during admission for ACS and underwent assessments at baseline (2 weeks post-ACS) and follow-up (6 months later). Associations between baseline positive psychological constructs and subsequent physical activity/biomarkers were analyzed using multivariable linear regression. Associations between baseline positive constructs and 6-month rehospitalizations were assessed via multivariable Cox regression. Overall, 164 participants enrolled and completed the baseline 2-week assessments. Baseline optimism was significantly associated with greater physical activity at 6 months (n=153; β=102.5; 95% confidence interval [13.6-191.5]; p=.024), controlling for baseline activity and sociodemographic, medical, and negative psychological covariates. Baseline optimism was also associated with lower rates of cardiac readmissions at 6 months (N=164), controlling for age, gender, and medical comorbidity (hazard ratio=.92; 95% confidence interval [.86-.98]; p=.006). There were no significant relationships between optimism and biomarkers. Gratitude was minimally associated with post-ACS outcomes. Conclusions Post-ACS optimism, but not gratitude, was prospectively and independently associated with superior physical activity and fewer cardiac readmissions. Whether interventions that target optimism can successfully increase optimism or improve cardiovascular outcomes in post-ACS patients is not yet known, but can be tested in future studies. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT01709669. PMID:26646818

Effects of Optimism and Gratitude on Physical Activity, Biomarkers, and Readmissions After an Acute Coronary Syndrome: The Gratitude Research in Acute Coronary Events Study.

PubMed

Huffman, Jeff C; Beale, Eleanor E; Celano, Christopher M; Beach, Scott R; Belcher, Arianna M; Moore, Shannon V; Suarez, Laura; Motiwala, Shweta R; Gandhi, Parul U; Gaggin, Hanna K; Januzzi, James L

2016-01-01

Positive psychological constructs, such as optimism, are associated with beneficial health outcomes. However, no study has separately examined the effects of multiple positive psychological constructs on behavioral, biological, and clinical outcomes after an acute coronary syndrome (ACS). Accordingly, we aimed to investigate associations of baseline optimism and gratitude with subsequent physical activity, prognostic biomarkers, and cardiac rehospitalizations in post-ACS patients. Participants were enrolled during admission for ACS and underwent assessments at baseline (2 weeks post-ACS) and follow-up (6 months later). Associations between baseline positive psychological constructs and subsequent physical activity/biomarkers were analyzed using multivariable linear regression. Associations between baseline positive constructs and 6-month rehospitalizations were assessed via multivariable Cox regression. Overall, 164 participants enrolled and completed the baseline 2-week assessments. Baseline optimism was significantly associated with greater physical activity at 6 months (n=153; β=102.5; 95% confidence interval, 13.6-191.5; P=0.024), controlling for baseline activity and sociodemographic, medical, and negative psychological covariates. Baseline optimism was also associated with lower rates of cardiac readmissions at 6 months (n=164), controlling for age, sex, and medical comorbidity (hazard ratio, 0.92; 95% confidence interval, [0.86-0.98]; P=0.006). There were no significant relationships between optimism and biomarkers. Gratitude was minimally associated with post-ACS outcomes. Post-ACS optimism, but not gratitude, was prospectively and independently associated with superior physical activity and fewer cardiac readmissions. Whether interventions that target optimism can successfully increase optimism or improve cardiovascular outcomes in post-ACS patients is not yet known, but can be tested in future studies. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01709669. © 2015 American Heart Association, Inc.

Beam orientation optimization for intensity-modulated radiation therapy using mixed integer programming

NASA Astrophysics Data System (ADS)

Yang, Ruijie; Dai, Jianrong; Yang, Yong; Hu, Yimin

2006-08-01

The purpose of this study is to extend an algorithm proposed for beam orientation optimization in classical conformal radiotherapy to intensity-modulated radiation therapy (IMRT) and to evaluate the algorithm's performance in IMRT scenarios. In addition, the effect of the candidate pool of beam orientations, in terms of beam orientation resolution and starting orientation, on the optimized beam configuration, plan quality and optimization time is also explored. The algorithm is based on the technique of mixed integer linear programming in which binary and positive float variables are employed to represent candidates for beam orientation and beamlet weights in beam intensity maps. Both beam orientations and beam intensity maps are simultaneously optimized in the algorithm with a deterministic method. Several different clinical cases were used to test the algorithm and the results show that both target coverage and critical structures sparing were significantly improved for the plans with optimized beam orientations compared to those with equi-spaced beam orientations. The calculation time was less than an hour for the cases with 36 binary variables on a PC with a Pentium IV 2.66 GHz processor. It is also found that decreasing beam orientation resolution to 10° greatly reduced the size of the candidate pool of beam orientations without significant influence on the optimized beam configuration and plan quality, while selecting different starting orientations had large influence. Our study demonstrates that the algorithm can be applied to IMRT scenarios, and better beam orientation configurations can be obtained using this algorithm. Furthermore, the optimization efficiency can be greatly increased through proper selection of beam orientation resolution and starting beam orientation while guaranteeing the optimized beam configurations and plan quality.

A Pharmacist-Physician Collaboration to Optimize Benzodiazepine Use for Anxiety and Sleep Symptom Control in Primary Care.

PubMed

Furbish, Shannon M L; Kroehl, Miranda E; Loeb, Danielle F; Lam, Huong Mindy; Lewis, Carmen L; Nelson, Jennifer; Chow, Zeta; Trinkley, Katy E

2017-08-01

Benzodiazepines are prescribed inappropriately in up to 40% of outpatients. The purpose of this study is to describe a collaborative team-based care model in which clinical pharmacists work with primary care providers (PCPs) to improve the safe use of benzodiazepines for anxiety and sleep disorders and to assess the preliminary results of the impact of the clinical service on patient outcomes. Adult patients were eligible if they received care from the academic primary care clinic, were prescribed a benzodiazepine chronically, and were not pregnant or managed by psychiatry. Outcomes included baseline PCP confidence and knowledge of appropriate benzodiazepine use, patient symptom severity, and medication changes. Twenty-five of 57 PCPs responded to the survey. PCPs reported greater confidence in diagnosing and treating generalized anxiety and panic disorders than sleep disorder and had variable knowledge of appropriate benzodiazepine prescribing. Twenty-nine patients had at least 1 visit. Over 44 total patient visits, 59% resulted in the addition or optimization of a nonbenzodiazepine medication and 46% resulted in the discontinuation or optimization of a benzodiazepine. Generalized anxiety symptom severity scores significantly improved (-2.0; 95% confidence interval (CI): -3.57 to -0.43). Collaborative team-based models that include clinical pharmacists in primary care can assist in optimizing high-risk benzodiazepine use. Although these findings suggest improvements in safe medication use and symptoms, additional studies are needed to confirm these preliminary results.

The Improvement of Particle Swarm Optimization: a Case Study of Optimal Operation in Goupitan Reservoir

NASA Astrophysics Data System (ADS)

Li, Haichen; Qin, Tao; Wang, Weiping; Lei, Xiaohui; Wu, Wenhui

2018-02-01

Due to the weakness in holding diversity and reaching global optimum, the standard particle swarm optimization has not performed well in reservoir optimal operation. To solve this problem, this paper introduces downhill simplex method to work together with the standard particle swarm optimization. The application of this approach in Goupitan reservoir optimal operation proves that the improved method had better accuracy and higher reliability with small investment.

Overview of CMOS process and design options for image sensor dedicated to space applications

NASA Astrophysics Data System (ADS)

Martin-Gonthier, P.; Magnan, P.; Corbiere, F.

2005-10-01

With the growth of huge volume markets (mobile phones, digital cameras...) CMOS technologies for image sensor improve significantly. New process flows appear in order to optimize some parameters such as quantum efficiency, dark current, and conversion gain. Space applications can of course benefit from these improvements. To illustrate this evolution, this paper reports results from three technologies that have been evaluated with test vehicles composed of several sub arrays designed with some space applications as target. These three technologies are CMOS standard, improved and sensor optimized process in 0.35μm generation. Measurements are focussed on quantum efficiency, dark current, conversion gain and noise. Other measurements such as Modulation Transfer Function (MTF) and crosstalk are depicted in [1]. A comparison between results has been done and three categories of CMOS process for image sensors have been listed. Radiation tolerance has been also studied for the CMOS improved process in the way of hardening the imager by design. Results at 4, 15, 25 and 50 krad prove a good ionizing dose radiation tolerance applying specific techniques.

Optimization of factors to obtain cassava starch films with improved mechanical properties

NASA Astrophysics Data System (ADS)

Monteiro, Mayra; Oliveira, Victor; Santos, Francisco; Barros Neto, Eduardo; Silva, Karyn; Silva, Rayane; Henrique, João; Chibério, Abimaelle

2017-08-01

In this study, was investigated the optimization of the factors that significantly influenced the mechanical property improvement of cassava starch films through complete factorial design 23. The factors to be analyzed were cassava starch, glycerol and modified clay contents. A regression model was proposed by the factorial analysis, aiming to estimate the condition of the individual factors investigated in the optimum state of the mechanical properties of the biofilm, using the following statistical tool: desirability function and response surface. The response variable that delimits the improvement of the mechanical property of the biofilm is the tensile strength, such improvement is obtained by maximizing the response variable. The factorial analysis showed that the best combination of factor configurations to reach the best response was found to be: with 5g of cassava starch, 10% of glycerol and 5% of modified clay, both percentages in relation to the dry mass of starch used. In addition, the starch biofilm showing the lowest response contained 2g of cassava starch, 0% of modified clay and 30% of glycerol, and was consequently considered the worst biofilm.

SU-F-P-61: Does It Matter Not to Use Optimization Points at the Apex for Vaginal Cylinder HDR Brachytherapy Planning?

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

Kim, Y

2016-06-15

Purpose: To test the impact of the use of apex optimization points for new vaginal cylinder (VC) applicators. Methods: New “ClickFit” single channel VC applicators (Varian) that have a different top thicknesses but the same diameters as the old VC applicators (2.3 cm diameter, 2.6 cm, 3.0 cm, and 3.5 cm) were compared using phantom studies. Old VC applicator plans without apex optimization points were also compared to the plans with the optimization points. The apex doses were monitored at 5 mm depth doses (8 points) where a prescription dose (Rx) of 6Gy was prescribed. VC surface doses (8 points)more » were also analyzed. Results: The new VC applicator plans without apex optimization points presented significantly lower 5mm depth doses than Rx (on average −31 ± 7%, p <0.00001) due to their thicker VC tops (3.4 ± 1.1 mm thicker with the range of 1.2 to 4.4 mm) than the old VC applicators. Old VC applicator plans also showed a statistically significant reduction (p <0.00001) due to Ir-192 source anisotropic effect at the apex region but the % reduction over Rx was only −7 ± 9%. However, by adding apex optimization points to the new VC applicator plans, the plans improved 5 mm depth doses (−7 ± 9% over Rx) that were not statistically different from old VC plans (p = 0.923), along with apex VC surface doses (−22 ± 10% over old VC versus −46 ± 7% without using apex optimization points). Conclusion: The use of apex optimization points are important in order to avoid significant additional cold doses (−24 ± 2%) at the prescription depth (5 mm) of apex, especially for the new VC applicators that have thicker tops.« less

Optimal design and uncertainty quantification in blood flow simulations for congenital heart disease

NASA Astrophysics Data System (ADS)

Marsden, Alison

2009-11-01

Recent work has demonstrated substantial progress in capabilities for patient-specific cardiovascular flow simulations. Recent advances include increasingly complex geometries, physiological flow conditions, and fluid structure interaction. However inputs to these simulations, including medical image data, catheter-derived pressures and material properties, can have significant uncertainties associated with them. For simulations to predict clinically useful and reliable output information, it is necessary to quantify the effects of input uncertainties on outputs of interest. In addition, blood flow simulation tools can now be efficiently coupled to shape optimization algorithms for surgery design applications, and these tools should incorporate uncertainty information. We present a unified framework to systematically and efficient account for uncertainties in simulations using adaptive stochastic collocation. In addition, we present a framework for derivative-free optimization of cardiovascular geometries, and layer these tools to perform optimization under uncertainty. These methods are demonstrated using simulations and surgery optimization to improve hemodynamics in pediatric cardiology applications.

Cascade Optimization Strategy with Neural Network and Regression Approximations Demonstrated on a Preliminary Aircraft Engine Design

NASA Technical Reports Server (NTRS)

Hopkins, Dale A.; Patnaik, Surya N.

2000-01-01

A preliminary aircraft engine design methodology is being developed that utilizes a cascade optimization strategy together with neural network and regression approximation methods. The cascade strategy employs different optimization algorithms in a specified sequence. The neural network and regression methods are used to approximate solutions obtained from the NASA Engine Performance Program (NEPP), which implements engine thermodynamic cycle and performance analysis models. The new methodology is proving to be more robust and computationally efficient than the conventional optimization approach of using a single optimization algorithm with direct reanalysis. The methodology has been demonstrated on a preliminary design problem for a novel subsonic turbofan engine concept that incorporates a wave rotor as a cycle-topping device. Computations of maximum thrust were obtained for a specific design point in the engine mission profile. The results (depicted in the figure) show a significant improvement in the maximum thrust obtained using the new methodology in comparison to benchmark solutions obtained using NEPP in a manual design mode.

Optimization of startup and shutdown operation of simulated moving bed chromatographic processes.

PubMed

Li, Suzhou; Kawajiri, Yoshiaki; Raisch, Jörg; Seidel-Morgenstern, Andreas

2011-06-24

This paper presents new multistage optimal startup and shutdown strategies for simulated moving bed (SMB) chromatographic processes. The proposed concept allows to adjust transient operating conditions stage-wise, and provides capability to improve transient performance and to fulfill product quality specifications simultaneously. A specially tailored decomposition algorithm is developed to ensure computational tractability of the resulting dynamic optimization problems. By examining the transient operation of a literature separation example characterized by nonlinear competitive isotherm, the feasibility of the solution approach is demonstrated, and the performance of the conventional and multistage optimal transient regimes is evaluated systematically. The quantitative results clearly show that the optimal operating policies not only allow to significantly reduce both duration of the transient phase and desorbent consumption, but also enable on-spec production even during startup and shutdown periods. With the aid of the developed transient procedures, short-term separation campaigns with small batch sizes can be performed more flexibly and efficiently by SMB chromatography. Copyright © 2011 Elsevier B.V. All rights reserved.

Use and optimization of a dual-flowrate loading strategy to maximize throughput in protein-a affinity chromatography.

PubMed

Ghose, Sanchayita; Nagrath, Deepak; Hubbard, Brian; Brooks, Clayton; Cramer, Steven M

2004-01-01

The effect of an alternate strategy employing two different flowrates during loading was explored as a means of increasing system productivity in Protein-A chromatography. The effect of such a loading strategy was evaluated using a chromatographic model that was able to accurately predict experimental breakthrough curves for this Protein-A system. A gradient-based optimization routine is carried out to establish the optimal loading conditions (initial and final flowrates and switching time). The two-step loading strategy (using a higher flowrate during the initial stages followed by a lower flowrate) was evaluated for an Fc-fusion protein and was found to result in significant improvements in process throughput. In an extension of this optimization routine, dynamic loading capacity and productivity were simultaneously optimized using a weighted objective function, and this result was compared to that obtained with the single flowrate. Again, the dual-flowrate strategy was found to be superior.

Model-data fusion across ecosystems: from multisite optimizations to global simulations

NASA Astrophysics Data System (ADS)

Kuppel, S.; Peylin, P.; Maignan, F.; Chevallier, F.; Kiely, G.; Montagnani, L.; Cescatti, A.

2014-11-01

This study uses a variational data assimilation framework to simultaneously constrain a global ecosystem model with eddy covariance measurements of daily net ecosystem exchange (NEE) and latent heat (LE) fluxes from a large number of sites grouped in seven plant functional types (PFTs). It is an attempt to bridge the gap between the numerous site-specific parameter optimization works found in the literature and the generic parameterization used by most land surface models within each PFT. The present multisite approach allows deriving PFT-generic sets of optimized parameters enhancing the agreement between measured and simulated fluxes at most of the sites considered, with performances often comparable to those of the corresponding site-specific optimizations. Besides reducing the PFT-averaged model-data root-mean-square difference (RMSD) and the associated daily output uncertainty, the optimization improves the simulated CO2 balance at tropical and temperate forests sites. The major site-level NEE adjustments at the seasonal scale are reduced amplitude in C3 grasslands and boreal forests, increased seasonality in temperate evergreen forests, and better model-data phasing in temperate deciduous broadleaf forests. Conversely, the poorer performances in tropical evergreen broadleaf forests points to deficiencies regarding the modelling of phenology and soil water stress for this PFT. An evaluation with data-oriented estimates of photosynthesis (GPP - gross primary productivity) and ecosystem respiration (Reco) rates indicates distinctively improved simulations of both gross fluxes. The multisite parameter sets are then tested against CO2 concentrations measured at 53 locations around the globe, showing significant adjustments of the modelled seasonality of atmospheric CO2 concentration, whose relevance seems PFT-dependent, along with an improved interannual variability. Lastly, a global-scale evaluation with remote sensing NDVI (normalized difference vegetation index) measurements indicates an improvement of the simulated seasonal variations of the foliar cover for all considered PFTs.

Lessons Learned from AIRS: Improved Determination of Surface and Atmospheric Temperatures Using Only Shortwave AIRS Channels

NASA Technical Reports Server (NTRS)

Susskind, Joel

2011-01-01

This slide presentation reviews the use of shortwave channels available to the Atmospheric Infrared Sounder (AIRS) to improve the determination of surface and atmospheric temperatures. The AIRS instrument is compared with the Infrared Atmospheric Sounding Interferometer (IASI) on-board the MetOp-A satellite. The objectives of the AIRS/AMSU were to (1) provide real time observations to improve numerical weather prediction via data assimilation, (2) Provide observations to measure and explain interannual variability and trends and (3) Use of AIRS product error estimates allows for QC optimized for each application. Successive versions in the AIRS retrieval methodology have shown significant improvement.

Queue and stack sorting algorithm optimization and performance analysis

NASA Astrophysics Data System (ADS)

Qian, Mingzhu; Wang, Xiaobao

2018-04-01

Sorting algorithm is one of the basic operation of a variety of software development, in data structures course specializes in all kinds of sort algorithm. The performance of the sorting algorithm is directly related to the efficiency of the software. A lot of excellent scientific research queue is constantly optimizing algorithm, algorithm efficiency better as far as possible, the author here further research queue combined with stacks of sorting algorithms, the algorithm is mainly used for alternating operation queue and stack storage properties, Thus avoiding the need for a large number of exchange or mobile operations in the traditional sort. Before the existing basis to continue research, improvement and optimization, the focus on the optimization of the time complexity of the proposed optimization and improvement, The experimental results show that the improved effectively, at the same time and the time complexity and space complexity of the algorithm, the stability study corresponding research. The improvement and optimization algorithm, improves the practicability.

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

Optimization of the Alkaline Pretreatment of Rice Straw for Enhanced Methane Yield

PubMed Central

Song, Zilin; Yang, Gaihe; Han, Xinhui; Feng, Yongzhong; Ren, Guangxin

2013-01-01

The lime pretreatment process for rice straw was optimized to enhance the biodegradation performance and increase biogas yield. The optimization was implemented using response surface methodology (RSM) and Box-Behnken experimental design. The effects of biodegradation, as well as the interactive effects of Ca(OH)2 concentration, pretreatment time, and inoculum amount on biogas improvement, were investigated. Rice straw compounds, such as lignin, cellulose, and hemicellulose, were significantly degraded with increasing Ca(OH)2 concentration. The optimal conditions for the use of pretreated rice straw in anaerobic digestion were 9.81% Ca(OH)2 (w/w TS), 5.89 d treatment time, and 45.12% inoculum content, which resulted in a methane yield of 225.3 mL/g VS. A determination coefficient (R 2) of 96% was obtained, indicating that the model used to predict the anabolic digestion process shows a favorable fit with the experimental parameters. PMID:23509824

Heterogeneous quantum computing for satellite constellation optimization: solving the weighted k-clique problem

NASA Astrophysics Data System (ADS)

Bass, Gideon; Tomlin, Casey; Kumar, Vaibhaw; Rihaczek, Pete; Dulny, Joseph, III

2018-04-01

NP-hard optimization problems scale very rapidly with problem size, becoming unsolvable with brute force methods, even with supercomputing resources. Typically, such problems have been approximated with heuristics. However, these methods still take a long time and are not guaranteed to find an optimal solution. Quantum computing offers the possibility of producing significant speed-up and improved solution quality. Current quantum annealing (QA) devices are designed to solve difficult optimization problems, but they are limited by hardware size and qubit connectivity restrictions. We present a novel heterogeneous computing stack that combines QA and classical machine learning, allowing the use of QA on problems larger than the hardware limits of the quantum device. These results represent experiments on a real-world problem represented by the weighted k-clique problem. Through this experiment, we provide insight into the state of quantum machine learning.

General purpose graphic processing unit implementation of adaptive pulse compression algorithms

NASA Astrophysics Data System (ADS)

Cai, Jingxiao; Zhang, Yan

2017-07-01

This study introduces a practical approach to implement real-time signal processing algorithms for general surveillance radar based on NVIDIA graphical processing units (GPUs). The pulse compression algorithms are implemented using compute unified device architecture (CUDA) libraries such as CUDA basic linear algebra subroutines and CUDA fast Fourier transform library, which are adopted from open source libraries and optimized for the NVIDIA GPUs. For more advanced, adaptive processing algorithms such as adaptive pulse compression, customized kernel optimization is needed and investigated. A statistical optimization approach is developed for this purpose without needing much knowledge of the physical configurations of the kernels. It was found that the kernel optimization approach can significantly improve the performance. Benchmark performance is compared with the CPU performance in terms of processing accelerations. The proposed implementation framework can be used in various radar systems including ground-based phased array radar, airborne sense and avoid radar, and aerospace surveillance radar.

Design of investment management optimization system for power grid companies under new electricity reform

NASA Astrophysics Data System (ADS)

Yang, Chunhui; Su, Zhixiong; Wang, Xin; Liu, Yang; Qi, Yongwei

2017-03-01

The new normalization of the economic situation and the implementation of a new round of electric power system reform put forward higher requirements to the daily operation of power grid companies. As an important day-to-day operation of power grid companies, investment management is directly related to the promotion of the company's operating efficiency and management level. In this context, the establishment of power grid company investment management optimization system will help to improve the level of investment management and control the company, which is of great significance for power gird companies to adapt to market environment changing as soon as possible and meet the policy environment requirements. Therefore, the purpose of this paper is to construct the investment management optimization system of power grid companies, which includes investment management system, investment process control system, investment structure optimization system, and investment project evaluation system and investment management information platform support system.

Prediction and optimization of the laccase-mediated synthesis of the antimicrobial compound iodine (I2).

PubMed

Schubert, M; Fey, A; Ihssen, J; Civardi, C; Schwarze, F W M R; Mourad, S

2015-01-10

An artificial neural network (ANN) and genetic algorithm (GA) were applied to improve the laccase-mediated oxidation of iodide (I(-)) to elemental iodine (I2). Biosynthesis of iodine (I2) was studied with a 5-level-4-factor central composite design (CCD). The generated ANN network was mathematically evaluated by several statistical indices and revealed better results than a classical quadratic response surface (RS) model. Determination of the relative significance of model input parameters, ranking the process parameters in order of importance (pH>laccase>mediator>iodide), was performed by sensitivity analysis. ANN-GA methodology was used to optimize the input space of the neural network model to find optimal settings for the laccase-mediated synthesis of iodine. ANN-GA optimized parameters resulted in a 9.9% increase in the conversion rate. Copyright © 2014 Elsevier B.V. All rights reserved.

Self-Configuration and Self-Optimization Process in Heterogeneous Wireless Networks

PubMed Central

Guardalben, Lucas; Villalba, Luis Javier García; Buiati, Fábio; Sobral, João Bosco Mangueira; Camponogara, Eduardo

2011-01-01

Self-organization in Wireless Mesh Networks (WMN) is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR) and the ad hoc on demand distance vector (AODV) routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network’s scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed. PMID:22346584

Self-configuration and self-optimization process in heterogeneous wireless networks.

PubMed

Guardalben, Lucas; Villalba, Luis Javier García; Buiati, Fábio; Sobral, João Bosco Mangueira; Camponogara, Eduardo

2011-01-01

Self-organization in Wireless Mesh Networks (WMN) is an emergent research area, which is becoming important due to the increasing number of nodes in a network. Consequently, the manual configuration of nodes is either impossible or highly costly. So it is desirable for the nodes to be able to configure themselves. In this paper, we propose an alternative architecture for self-organization of WMN based on Optimized Link State Routing Protocol (OLSR) and the ad hoc on demand distance vector (AODV) routing protocols as well as using the technology of software agents. We argue that the proposed self-optimization and self-configuration modules increase the throughput of network, reduces delay transmission and network load, decreases the traffic of HELLO messages according to network's scalability. By simulation analysis, we conclude that the self-optimization and self-configuration mechanisms can significantly improve the performance of OLSR and AODV protocols in comparison to the baseline protocols analyzed.

Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity modulated proton therapy treatment planning

PubMed Central

Cao, Wenhua; Lim, Gino; Li, Xiaoqiang; Li, Yupeng; Zhu, X. Ronald; Zhang, Xiaodong

2014-01-01

The purpose of this study is to investigate the feasibility and impact of incorporating deliverable monitor unit (MU) constraints into spot intensity optimization in intensity modulated proton therapy (IMPT) treatment planning. The current treatment planning system (TPS) for IMPT disregards deliverable MU constraints in the spot intensity optimization (SIO) routine. It performs a post-processing procedure on an optimized plan to enforce deliverable MU values that are required by the spot scanning proton delivery system. This procedure can create a significant dose distribution deviation between the optimized and post-processed deliverable plans, especially when small spot spacings are used. In this study, we introduce a two-stage linear programming (LP) approach to optimize spot intensities and constrain deliverable MU values simultaneously, i.e., a deliverable spot intensity optimization (DSIO) model. Thus, the post-processing procedure is eliminated and the associated optimized plan deterioration can be avoided. Four prostate cancer cases at our institution were selected for study and two parallel opposed beam angles were planned for all cases. A quadratic programming (QP) based model without MU constraints, i.e., a conventional spot intensity optimization (CSIO) model, was also implemented to emulate the commercial TPS. Plans optimized by both the DSIO and CSIO models were evaluated for five different settings of spot spacing from 3 mm to 7 mm. For all spot spacings, the DSIO-optimized plans yielded better uniformity for the target dose coverage and critical structure sparing than did the CSIO-optimized plans. With reduced spot spacings, more significant improvements in target dose uniformity and critical structure sparing were observed in the DSIO- than in the CSIO-optimized plans. Additionally, better sparing of the rectum and bladder was achieved when reduced spacings were used for the DSIO-optimized plans. The proposed DSIO approach ensures the deliverability of optimized IMPT plans that take into account MU constraints. This eliminates the post-processing procedure required by the TPS as well as the resultant deteriorating effect on ultimate dose distributions. This approach therefore allows IMPT plans to adopt all possible spot spacings optimally. Moreover, dosimetric benefits can be achieved using smaller spot spacings. PMID:23835656

Parameter Optimization and Electrode Improvement of Rotary Stepper Micromotor

NASA Astrophysics Data System (ADS)

Sone, Junji; Mizuma, Toshinari; Mochizuki, Shunsuke; Sarajlic, Edin; Yamahata, Christophe; Fujita, Hiroyuki

We developed a three-phase electrostatic stepper micromotor and performed a numerical simulation to improve its performance for practical use and to optimize its design. We conducted its circuit simulation by simplifying its structure, and the effect of springback force generated by supported mechanism using flexures was considered. And we considered new improvement method for electrodes. This improvement and other parameter optimizations achieved the low voltage drive of micromotor.

Improving Vector Evaluated Particle Swarm Optimisation Using Multiple Nondominated Leaders

PubMed Central

Lim, Kian Sheng; Buyamin, Salinda; Ahmad, Anita; Shapiai, Mohd Ibrahim; Naim, Faradila; Mubin, Marizan; Kim, Dong Hwa

2014-01-01

The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept of multiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume. The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms. PMID:24883386

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

PubMed

Guthier, Christian V; Damato, Antonio L; Hesser, Juergen W; Viswanathan, Akila N; Cormack, Robert A

2017-12-01

Interstitial high-dose rate (HDR) brachytherapy is an important therapeutic strategy for the treatment of locally advanced gynecologic (GYN) cancers. The outcome of this therapy is determined by the quality of dose distribution achieved. This paper focuses on a novel yet simple heuristic for catheter selection for GYN HDR brachytherapy and their comparison against state of the art optimization strategies. The proposed technique is intended to act as a decision-supporting tool to select a favorable needle configuration. The presented heuristic for catheter optimization is based on a shrinkage-type algorithm (SACO). It is compared against state of the art planning in a retrospective study of 20 patients who previously received image-guided interstitial HDR brachytherapy using a Syed Neblett template. From those plans, template orientation and position are estimated via a rigid registration of the template with the actual catheter trajectories. All potential straight trajectories intersecting the contoured clinical target volume (CTV) are considered for catheter optimization. Retrospectively generated plans and clinical plans are compared with respect to dosimetric performance and optimization time. All plans were generated with one single run of the optimizer lasting 0.6-97.4 s. Compared to manual optimization, SACO yields a statistically significant (P ≤ 0.05) improved target coverage while at the same time fulfilling all dosimetric constraints for organs at risk (OARs). Comparing inverse planning strategies, dosimetric evaluation for SACO and "hybrid inverse planning and optimization" (HIPO), as gold standard, shows no statistically significant difference (P > 0.05). However, SACO provides the potential to reduce the number of used catheters without compromising plan quality. The proposed heuristic for needle selection provides fast catheter selection with optimization times suited for intraoperative treatment planning. Compared to manual optimization, the proposed methodology results in fewer catheters without a clinically significant loss in plan quality. The proposed approach can be used as a decision support tool that guides the user to find the ideal number and configuration of catheters. © 2017 American Association of Physicists in Medicine.

Workflow Optimization in Vertebrobasilar Occlusion

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

Kamper, Lars, E-mail: lars.kamper@helios-kliniken.de; Meyn, Hannes; Rybacki, Konrad

2012-06-15

Objective: In vertebrobasilar occlusion, rapid recanalization is the only substantial means to improve the prognosis. We introduced a standard operating procedure (SOP) for interventional therapy to analyze the effects on interdisciplinary time management. Methods: Intrahospital time periods between hospital admission and neuroradiological intervention were retrospectively analyzed, together with the patients' outcome, before (n = 18) and after (n = 20) implementation of the SOP. Results: After implementation of the SOP, we observed statistically significant improvement of postinterventional patient neurological status (p = 0.017). In addition, we found a decrease of 5:33 h for the mean time period from hospital admissionmore » until neuroradiological intervention. The recanalization rate increased from 72.2% to 80% after implementation of the SOP. Conclusion: Our results underscore the relevance of SOP implementation and analysis of time management for clinical workflow optimization. Both may trigger awareness for the need of efficient interdisciplinary time management. This could be an explanation for the decreased time periods and improved postinterventional patient status after SOP implementation.« less

Using the principles of circadian physiology enhances shift schedule design

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

Connolly, J.J.; Moore-Ede, M.C.

1987-01-01

Nuclear power plants must operate 24 h, 7 days a week. For the most part, shift schedules currently in use at nuclear power plants have been designed to meet operational needs without considering the biological clocks of the human operators. The development of schedules that also take circadian principles into account is a positive step that can be taken to improve plant safety by optimizing operator alertness. These schedules reduce the probability of human errors especially during backshifts. In addition, training programs that teach round-the-clock workers how to deal with the problems of shiftwork can help to optimize performance andmore » alertness. These programs teach shiftworkers the underlying causes of the sleep problems associated with shiftwork and also provide coping strategies for improving sleep and dealing with the transition between shifts. When these training programs are coupled with an improved schedule, the problems associated with working round-the-clock can be significantly reduced.« less

Resolution improvement in positron emission tomography using anatomical Magnetic Resonance Imaging.

PubMed

Chu, Yong; Su, Min-Ying; Mandelkern, Mark; Nalcioglu, Orhan

2006-08-01

An ideal imaging system should provide information with high-sensitivity, high spatial, and temporal resolution. Unfortunately, it is not possible to satisfy all of these desired features in a single modality. In this paper, we discuss methods to improve the spatial resolution in positron emission imaging (PET) using a priori information from Magnetic Resonance Imaging (MRI). Our approach uses an image restoration algorithm based on the maximization of mutual information (MMI), which has found significant success for optimizing multimodal image registration. The MMI criterion is used to estimate the parameters in the Sharpness-Constrained Wiener filter. The generated filter is then applied to restore PET images of a realistic digital brain phantom. The resulting restored images show improved resolution and better signal-to-noise ratio compared to the interpolated PET images. We conclude that a Sharpness-Constrained Wiener filter having parameters optimized from a MMI criterion may be useful for restoring spatial resolution in PET based on a priori information from correlated MRI.

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.

Formulation optimization, characterization, and evaluation of in vitro cytotoxic potential of curcumin loaded solid lipid nanoparticles for improved anticancer activity.

PubMed

Rompicharla, Sri Vishnu Kiran; Bhatt, Himanshu; Shah, Aashma; Komanduri, Neeraja; Vijayasarathy, Dhanya; Ghosh, Balaram; Biswas, Swati

2017-11-01

The aim of the present research was to develop a novel, biocompatible, amenable to industrial scale up and affordable solid lipid nanoparticles (SLN) preparation of curcumin and evaluate the therapeutic efficacy in vitro using cancer cells. We have incorporated cholesterol as the lipid to prepare SLN along with the Poloxamer-188 as stabilizer. High shear homogenization was used to prepare the SLN and formulation was optimized using Quality by Design The optimized Chol CUR SLN exhibited a narrow size distribution with a particle size of 166.4±3.5nm. Percentage encapsulation (%EE) was found to be 76.9±1.9%. The SLN were further characterized by DSC, FTIR, XRD and drug release. In vitro cell studies in MDA-MB-231 (Human Breast cancer) cell line revealed that the Chol CUR SLN showed superior cytotoxicity and uptake in comparison to the free curcumin. Furthermore, Chol CUR SLN induced a significantly higher apoptosis compared to free CUR treatment. These results indicated that the curcumin encapsulated in Chol SLN was able to significantly improve the cytotoxic potential and induction of apoptosis in MDA-MB-231 cells. The promising result from our study could lead a further exploration of this nanoparticle formulation to be utilized clinically for cancer treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

PubMed

Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

2016-07-01

The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Optimization of prosthetic foot stiffness to reduce metabolic cost and intact knee loading during below-knee amputee walking: a theoretical study.

PubMed

Fey, Nicholas P; Klute, Glenn K; Neptune, Richard R

2012-11-01

Unilateral below-knee amputees develop abnormal gait characteristics that include bilateral asymmetries and an elevated metabolic cost relative to non-amputees. In addition, long-term prosthesis use has been linked to an increased prevalence of joint pain and osteoarthritis in the intact leg knee. To improve amputee mobility, prosthetic feet that utilize elastic energy storage and return (ESAR) have been designed, which perform important biomechanical functions such as providing body support and forward propulsion. However, the prescription of appropriate design characteristics (e.g., stiffness) is not well-defined since its influence on foot function and important in vivo biomechanical quantities such as metabolic cost and joint loading remain unclear. The design of feet that improve these quantities could provide considerable advancements in amputee care. Therefore, the purpose of this study was to couple design optimization with dynamic simulations of amputee walking to identify the optimal foot stiffness that minimizes metabolic cost and intact knee joint loading. A musculoskeletal model and distributed stiffness ESAR prosthetic foot model were developed to generate muscle-actuated forward dynamics simulations of amputee walking. Dynamic optimization was used to solve for the optimal muscle excitation patterns and foot stiffness profile that produced simulations that tracked experimental amputee walking data while minimizing metabolic cost and intact leg internal knee contact forces. Muscle and foot function were evaluated by calculating their contributions to the important walking subtasks of body support, forward propulsion and leg swing. The analyses showed that altering a nominal prosthetic foot stiffness distribution by stiffening the toe and mid-foot while making the ankle and heel less stiff improved ESAR foot performance by offloading the intact knee during early to mid-stance of the intact leg and reducing metabolic cost. The optimal design also provided moderate braking and body support during the first half of residual leg stance, while increasing the prosthesis contributions to forward propulsion and body support during the second half of residual leg stance. Future work will be directed at experimentally validating these results, which have important implications for future designs of prosthetic feet that could significantly improve amputee care.

Estimating irrigation water demand using an improved method and optimizing reservoir operation for water supply and hydropower generation: a case study of the Xinfengjiang reservoir in southern China

USGS Publications Warehouse

Wu, Yiping; Chen, Ji

2013-01-01

The ever-increasing demand for water due to growth of population and socioeconomic development in the past several decades has posed a worldwide threat to water supply security and to the environmental health of rivers. This study aims to derive reservoir operating rules through establishing a multi-objective optimization model for the Xinfengjiang (XFJ) reservoir in the East River Basin in southern China to minimize water supply deficit and maximize hydropower generation. Additionally, to enhance the estimation of irrigation water demand from the downstream agricultural area of the XFJ reservoir, a conventional method for calculating crop water demand is improved using hydrological model simulation results. Although the optimal reservoir operating rules are derived for the XFJ reservoir with three priority scenarios (water supply only, hydropower generation only, and equal priority), the river environmental health is set as the basic demand no matter which scenario is adopted. The results show that the new rules derived under the three scenarios can improve the reservoir operation for both water supply and hydropower generation when comparing to the historical performance. Moreover, these alternative reservoir operating policies provide the flexibility for the reservoir authority to choose the most appropriate one. Although changing the current operating rules may influence its hydropower-oriented functions, the new rules can be significant to cope with the increasingly prominent water shortage and degradation in the aquatic environment. Overall, our results and methods (improved estimation of irrigation water demand and formulation of the reservoir optimization model) can be useful for local watershed managers and valuable for other researchers worldwide.

Improving Rural Cancer Patients' Outcomes: A Group-Randomized Trial

ERIC Educational Resources Information Center

Elliott, Thomas E.; Elliott, Barbara A.; Regal, Ronald R.; Renier, Colleen M.; Haller, Irina V.; Crouse, Byron J.; Witrak, Martha T.; Jensen, Patricia B.

2004-01-01

Significant barriers exist in the delivery of state-of-the-art cancer care to rural populations. Rural providers' knowledge and practices, their rural health care delivery systems, and linkages to cancer specialists are not optimal; therefore, rural cancer patient outcomes are less than achievable. Purpose: To test the effects of a strategy…

Finite Element Analysis of Morphing Piezoelectric Structures Studied

NASA Technical Reports Server (NTRS)

Lee, Ho-Jun

2002-01-01

The development of morphing aerospace structures that optimize their shape offers the potential to significantly improve the performance of existing airplanes. These morphing vehicles will operate with new capabilities to reduce noise, damp vibrations, manipulate flow, and monitor damage. Piezoelectric materials represent one of the popular materials currently being investigated for applications in morphing structures.

ecoSmart landscapes: a versatile SaaS platform for green infrastructure applications in urban environments

Treesearch

Greg McPherson; Qingfu Xiao; Joe Purohit; Mark Dietenberger; Charles (C.R.) Boardman; Jim Simpson; Paula Peper

2014-01-01

The urban environment offers significant opportunities to improve sustainability and optimize water resources. Historically, research and software applications have been focused on the built environment (buildings). Cost-effective, practical tools that can assess the impact of different landscape configurations and their interactions with buildings have not been widely...

Optimizing shoot culture media for Rubus germplasm: the effects of NH4+, NO3-, and total nitrogen

USDA-ARS?s Scientific Manuscript database

The nitrogen components of Murashige and Skoog (MS) medium were significant factors for improved growth in our earlier study that modeled the effects of mineral nutrition on growth and development of micropropagated red raspberry(Rubus idaeus L.). In this study, a mixture component design was applie...

Improved method for reliable HMW-GS identification by RP-HPLC and SDS-PAGE in common wheat cultivars

USDA-ARS?s Scientific Manuscript database

The accurate identification of alleles for high-molecular weight glutenins (HMW-GS) is critical for wheat breeding programs targeting end-use quality. RP-HPLC methods were optimized for separation of HMW-GS, resulting in enhanced resolution of 1By and 1Dx subunits. Statistically significant differe...

Optimization of freeform surfaces using intelligent deformation techniques for LED applications

NASA Astrophysics Data System (ADS)

Isaac, Annie Shalom; Neumann, Cornelius

2018-04-01

For many years, optical designers have great interests in designing efficient optimization algorithms to bring significant improvement to their initial design. However, the optimization is limited due to a large number of parameters present in the Non-uniform Rationaly b-Spline Surfaces. This limitation was overcome by an indirect technique known as optimization using freeform deformation (FFD). In this approach, the optical surface is placed inside a cubical grid. The vertices of this grid are modified, which deforms the underlying optical surface during the optimization. One of the challenges in this technique is the selection of appropriate vertices of the cubical grid. This is because these vertices share no relationship with the optical performance. When irrelevant vertices are selected, the computational complexity increases. Moreover, the surfaces created by them are not always feasible to manufacture, which is the same problem faced in any optimization technique while creating freeform surfaces. Therefore, this research addresses these two important issues and provides feasible design techniques to solve them. Finally, the proposed techniques are validated using two different illumination examples: street lighting lens and stop lamp for automobiles.

Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.

PubMed

Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad

2016-12-01

Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.

Optimization of an idealized Y-Shaped Extracardiac Fontan Baffle

NASA Astrophysics Data System (ADS)

Yang, Weiguang; Feinstein, Jeffrey; Mohan Reddy, V.; Marsden, Alison

2008-11-01

Research has showed that vascular geometries can significantly impact hemodynamic performance, particularly in pediatric cardiology, where anatomy varies from one patient to another. In this study we optimize a newly proposed design for the Fontan procedure, a surgery used to treat single ventricle heart patients. The current Fontan procedure connects the inferior vena cava (IVC) to the pulmonary arteries (PA's) via a straight Gore-Tex tube, forming a T-shaped junction. In the Y-graft design, the IVC is connected to the left and right PAs by two branches. Initial studies on the Y-graft design showed an increase in efficiency and improvement in flow distribution compared to traditional designs in a single patient-specific model. We now optimize an idealized Y-graft model to refine the design prior to patient testing. A derivate-free optimization algorithm using Kriging surrogate functions and mesh adaptive direct search is coupled to a 3-D finite element Navier-Stokes solver. We will present optimization results for rest and exercise conditions and examine the influence of energy efficiency, wall shear stress, pulsatile flow, and flow distribution on the optimal design.

Using Low Levels of Stochastic Vestibular Stimulation to Improve Balance Function

PubMed Central

Goel, Rahul; Kofman, Igor; Jeevarajan, Jerome; De Dios, Yiri; Cohen, Helen S.; Bloomberg, Jacob J.; Mulavara, Ajitkumar P.

2015-01-01

Low-level stochastic vestibular stimulation (SVS) has been associated with improved postural responses in the medio-lateral (ML) direction, but its effect in improving balance function in both the ML and anterior-posterior (AP) directions has not been studied. In this series of studies, the efficacy of applying low amplitude SVS in 0–30 Hz range between the mastoids in the ML direction on improving cross-planar balance function was investigated. Forty-five (45) subjects stood on a compliant surface with their eyes closed and were instructed to maintain a stable upright stance. Measures of stability of the head, trunk, and whole body were quantified in ML, AP and combined APML directions. Results show that binaural bipolar SVS given in the ML direction significantly improved balance performance with the peak of optimal stimulus amplitude predominantly in the range of 100–500 μA for all the three directions, exhibiting stochastic resonance (SR) phenomenon. Objective perceptual and body motion thresholds as estimates of internal noise while subjects sat on a chair with their eyes closed and were given 1 Hz bipolar binaural sinusoidal electrical stimuli were also measured. In general, there was no significant difference between estimates of perceptual and body motion thresholds. The average optimal SVS amplitude that improved balance performance (peak SVS amplitude normalized to perceptual threshold) was estimated to be 46% in ML, 53% in AP, and 50% in APML directions. A miniature patch-type SVS device may be useful to improve balance function in people with disabilities due to aging, Parkinson’s disease or in astronauts returning from long-duration space flight. PMID:26295807

Material identification based on electrostatic sensing technology

NASA Astrophysics Data System (ADS)

Liu, Kai; Chen, Xi; Li, Jingnan

2018-04-01

When the robot travels on the surface of different media, the uncertainty of the medium will seriously affect the autonomous action of the robot. In this paper, the distribution characteristics of multiple electrostatic charges on the surface of materials are detected, so as to improve the accuracy of the existing electrostatic signal material identification methods, which is of great significance to help the robot optimize the control algorithm. In this paper, based on the electrostatic signal material identification method proposed by predecessors, the multi-channel detection circuit is used to obtain the electrostatic charge distribution at different positions of the material surface, the weights are introduced into the eigenvalue matrix, and the weight distribution is optimized by the evolutionary algorithm, which makes the eigenvalue matrix more accurately reflect the surface charge distribution characteristics of the material. The matrix is used as the input of the k-Nearest Neighbor (kNN)classification algorithm to classify the dielectric materials. The experimental results show that the proposed method can significantly improve the recognition rate of the existing electrostatic signal material recognition methods.