Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

Modelling and Optimization of Polycaprolactone Ultrafine-Fibres Electrospinning Process Using Response Surface Methodology

PubMed Central

Ruys, Andrew J.

2018-01-01

Electrospun fibres have gained broad interest in biomedical applications, including tissue engineering scaffolds, due to their potential in mimicking extracellular matrix and producing structures favourable for cell and tissue growth. The development of scaffolds often involves multivariate production parameters and multiple output characteristics to define product quality. In this study on electrospinning of polycaprolactone (PCL), response surface methodology (RSM) was applied to investigate the determining parameters and find optimal settings to achieve the desired properties of fibrous scaffold for acetabular labrum implant. The results showed that solution concentration influenced fibre diameter, while elastic modulus was determined by solution concentration, flow rate, temperature, collector rotation speed, and interaction between concentration and temperature. Relationships between these variables and outputs were modelled, followed by an optimization procedure. Using the optimized setting (solution concentration of 10% w/v, flow rate of 4.5 mL/h, temperature of 45 °C, and collector rotation speed of 1500 RPM), a target elastic modulus of 25 MPa could be achieved at a minimum possible fibre diameter (1.39 ± 0.20 µm). This work demonstrated that multivariate factors of production parameters and multiple responses can be investigated, modelled, and optimized using RSM. PMID:29562614

Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD).

PubMed

Rhoades, Seth D; Weljie, Aalim M

2016-12-01

Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method.

Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD)

PubMed Central

Rhoades, Seth D.

2017-01-01

Introduction Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Objective Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). Methods We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. Results LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. Conclusions The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method. PMID:28348510

Optimization of Maghemite (γ-Fe2O3) Nano-Powder Mixed micro-EDM of CoCrMo with Multiple Responses Using Gray Relational Analysis (GRA)

NASA Astrophysics Data System (ADS)

Mejid Elsiti, Nagwa; Noordin, M. Y.; Idris, Ani; Saed Majeed, Faraj

2017-10-01

This paper presents an optimization of process parameters of Micro-Electrical Discharge Machining (EDM) process with (γ-Fe2O3) nano-powder mixed dielectric using multi-response optimization Grey Relational Analysis (GRA) method instead of single response optimization. These parameters were optimized based on 2-Level factorial design combined with Grey Relational Analysis. The machining parameters such as peak current, gap voltage, and pulse on time were chosen for experimentation. The performance characteristics chosen for this study are material removal rate (MRR), tool wear rate (TWR), Taper and Overcut. Experiments were conducted using electrolyte copper as the tool and CoCrMo as the workpiece. Experimental results have been improved through this approach.

SynGenics Optimization System (SynOptSys)

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Multiple optimization of chemical components and texture of purple maize expanded by IVDV treatment using the response surface methodology.

PubMed

Mrad, Rachelle; Debs, Espérance; Maroun, Richard G; Louka, Nicolas

2014-12-15

A new process, Intensification of Vaporization by Decompression to the Vacuum (IVDV), is proposed for texturizing purple maize. It consists in exposing humid kernels to high steam pressure followed by a decompression to the vacuum. Response surface methodology with three operating parameters (initial water content (W), steam pressure (P) and processing time (T)) was used to study the response parameters: Total Anthocyanins Content, Total Polyphenols Content, Free Radical Scavenging Activity, Expansion Ratio, Hardness and Work Done. P was the most important variable, followed by T. Pressure drop helped the release of bound phenolics arriving to their expulsion outside the cell. Combined with convenient T and W, it caused kernels expansion. Multiple optimization of expansion and chemical content showed that IVDV resulted in good texturization of maize while preserving the antioxidant compounds and activity. Optimal conditions were: W=29%, P=5 bar and T=37s. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimal function explains forest responses to global change

Treesearch

Roderick Dewar; Oskar Franklin; Annikki Makela; Ross E. McMurtrie; Harry T. Valentine

2009-01-01

Plant responses to global changes in carbon dioxide (CO2), nitrogen, and water availability are critical to future atmospheric CO2 concentrations, hydrology, and hence climate. Our understanding of those responses is incomplete, however. Multiple-resource manipulation experiments and empirical observations have revealed a...

Multiple sclerosis: individualized disease susceptibility and therapy response.

PubMed

Pravica, Vera; Markovic, Milos; Cupic, Maja; Savic, Emina; Popadic, Dusan; Drulovic, Jelena; Mostarica-Stojkovic, Marija

2013-02-01

Multiple sclerosis (MS) is a heterogeneous disease in which diverse genetic, pathological and clinical backgrounds lead to variable therapy response. Accordingly, MS care should be tailored to address disease traits unique to each person. At the core of personalized management is the emergence of new knowledge, enabling optimized treatment and disease-modifying therapies. This overview analyzes the promise of genetic and nongenetic biomarkers in advancing decision-making algorithms to assist diagnosis or in predicting the disease course and therapy response in any given MS patient.

Adaptive reference update (ARU) algorithm. A stochastic search algorithm for efficient optimization of multi-drug cocktails

PubMed Central

2012-01-01

Background Multi-target therapeutics has been shown to be effective for treating complex diseases, and currently, it is a common practice to combine multiple drugs to treat such diseases to optimize the therapeutic outcomes. However, considering the huge number of possible ways to mix multiple drugs at different concentrations, it is practically difficult to identify the optimal drug combination through exhaustive testing. Results In this paper, we propose a novel stochastic search algorithm, called the adaptive reference update (ARU) algorithm, that can provide an efficient and systematic way for optimizing multi-drug cocktails. The ARU algorithm iteratively updates the drug combination to improve its response, where the update is made by comparing the response of the current combination with that of a reference combination, based on which the beneficial update direction is predicted. The reference combination is continuously updated based on the drug response values observed in the past, thereby adapting to the underlying drug response function. To demonstrate the effectiveness of the proposed algorithm, we evaluated its performance based on various multi-dimensional drug functions and compared it with existing algorithms. Conclusions Simulation results show that the ARU algorithm significantly outperforms existing stochastic search algorithms, including the Gur Game algorithm. In fact, the ARU algorithm can more effectively identify potent drug combinations and it typically spends fewer iterations for finding effective combinations. Furthermore, the ARU algorithm is robust to random fluctuations and noise in the measured drug response, which makes the algorithm well-suited for practical drug optimization applications. PMID:23134742

Dispositional optimism and sleep quality: a test of mediating pathways

PubMed Central

Cribbet, Matthew; Kent de Grey, Robert G.; Cronan, Sierra; Trettevik, Ryan; Smith, Timothy W.

2016-01-01

Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways. PMID:27592128

Dispositional optimism and sleep quality: a test of mediating pathways.

PubMed

Uchino, Bert N; Cribbet, Matthew; de Grey, Robert G Kent; Cronan, Sierra; Trettevik, Ryan; Smith, Timothy W

2017-04-01

Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways.

Generalized Likelihood Uncertainty Estimation (GLUE) methodology for optimization of extraction in natural products.

PubMed

Maulidiani; Rudiyanto; Abas, Faridah; Ismail, Intan Safinar; Lajis, Nordin H

2018-06-01

Optimization process is an important aspect in the natural product extractions. Herein, an alternative approach is proposed for the optimization in extraction, namely, the Generalized Likelihood Uncertainty Estimation (GLUE). The approach combines the Latin hypercube sampling, the feasible range of independent variables, the Monte Carlo simulation, and the threshold criteria of response variables. The GLUE method is tested in three different techniques including the ultrasound, the microwave, and the supercritical CO 2 assisted extractions utilizing the data from previously published reports. The study found that this method can: provide more information on the combined effects of the independent variables on the response variables in the dotty plots; deal with unlimited number of independent and response variables; consider combined multiple threshold criteria, which is subjective depending on the target of the investigation for response variables; and provide a range of values with their distribution for the optimization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization of multi response in end milling process of ASSAB XW-42 tool steel with liquid nitrogen cooling using Taguchi-grey relational analysis

NASA Astrophysics Data System (ADS)

Norcahyo, Rachmadi; Soepangkat, Bobby O. P.

2017-06-01

A research was conducted for the optimization of the end milling process of ASSAB XW-42 tool steel with multiple performance characteristics based on the orthogonal array with Taguchi-grey relational analysis method. Liquid nitrogen was applied as a coolant. The experimental studies were conducted under varying the liquid nitrogen cooling flow rates (FL), and the end milling process variables, i.e., cutting speed (Vc), feeding speed (Vf), and axial depth of cut (Aa). The optimized multiple performance characteristics were surface roughness (SR), flank wear (VB), and material removal rate (MRR). An orthogonal array, signal-to-noise (S/N) ratio, grey relational analysis, grey relational grade, and analysis of variance were employed to study the multiple performance characteristics. Experimental results showed that flow rate gave the highest contribution for reducing the total variation of the multiple responses, followed by cutting speed, feeding speed, and axial depth of cut. The minimum surface roughness, flank wear, and maximum material removal rate could be obtained by using the values of flow rate, cutting speed, feeding speed, and axial depth of cut of 0.5 l/minute, 109.9 m/minute, 440 mm/minute, and 0.9 mm, respectively.

Analyzing multicomponent receptive fields from neural responses to natural stimuli

PubMed Central

Rowekamp, Ryan; Sharpee, Tatyana O

2011-01-01

The challenge of building increasingly better models of neural responses to natural stimuli is to accurately estimate the multiple stimulus features that may jointly affect the neural spike probability. The selectivity for combinations of features is thought to be crucial for achieving classical properties of neural responses such as contrast invariance. The joint search for these multiple stimulus features is difficult because estimating spike probability as a multidimensional function of stimulus projections onto candidate relevant dimensions is subject to the curse of dimensionality. An attractive alternative is to search for relevant dimensions sequentially, as in projection pursuit regression. Here we demonstrate using analytic arguments and simulations of model cells that different types of sequential search strategies exhibit systematic biases when used with natural stimuli. Simulations show that joint optimization is feasible for up to three dimensions with current algorithms. When applied to the responses of V1 neurons to natural scenes, models based on three jointly optimized dimensions had better predictive power in a majority of cases compared to dimensions optimized sequentially, with different sequential methods yielding comparable results. Thus, although the curse of dimensionality remains, at least several relevant dimensions can be estimated by joint information maximization. PMID:21780916

Digital robust active control law synthesis for large order flexible structure using parameter optimization

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.

1988-01-01

A generic procedure for the parameter optimization of a digital control law for a large-order flexible flight vehicle or large space structure modeled as a sampled data system is presented. A linear quadratic Guassian type cost function was minimized, while satisfying a set of constraints on the steady-state rms values of selected design responses, using a constrained optimization technique to meet multiple design requirements. Analytical expressions for the gradients of the cost function and the design constraints on mean square responses with respect to the control law design variables are presented.

Combined mixture-process variable approach: a suitable statistical tool for nanovesicular systems optimization.

PubMed

Habib, Basant A; AbouGhaly, Mohamed H H

2016-06-01

This study aims to illustrate the applicability of combined mixture-process variable (MPV) design and modeling for optimization of nanovesicular systems. The D-optimal experimental plan studied the influence of three mixture components (MCs) and two process variables (PVs) on lercanidipine transfersomes. The MCs were phosphatidylcholine (A), sodium glycocholate (B) and lercanidipine hydrochloride (C), while the PVs were glycerol amount in the hydration mixture (D) and sonication time (E). The studied responses were Y1: particle size, Y2: zeta potential and Y3: entrapment efficiency percent (EE%). Polynomial equations were used to study the influence of MCs and PVs on each response. Response surface methodology and multiple response optimization were applied to optimize the formulation with the goals of minimizing Y1 and maximizing Y2 and Y3. The obtained polynomial models had prediction R(2) values of 0.645, 0.947 and 0.795 for Y1, Y2 and Y3, respectively. Contour, Piepel's response trace, perturbation, and interaction plots were drawn for responses representation. The optimized formulation, A: 265 mg, B: 10 mg, C: 40 mg, D: zero g and E: 120 s, had desirability of 0.9526. The actual response values for the optimized formulation were within the two-sided 95% prediction intervals and were close to the predicted values with maximum percent deviation of 6.2%. This indicates the validity of combined MPV design and modeling for optimization of transfersomal formulations as an example of nanovesicular systems.

Optimization of constrained density functional theory

NASA Astrophysics Data System (ADS)

O'Regan, David D.; Teobaldi, Gilberto

2016-07-01

Constrained density functional theory (cDFT) is a versatile electronic structure method that enables ground-state calculations to be performed subject to physical constraints. It thereby broadens their applicability and utility. Automated Lagrange multiplier optimization is necessary for multiple constraints to be applied efficiently in cDFT, for it to be used in tandem with geometry optimization, or with molecular dynamics. In order to facilitate this, we comprehensively develop the connection between cDFT energy derivatives and response functions, providing a rigorous assessment of the uniqueness and character of cDFT stationary points while accounting for electronic interactions and screening. In particular, we provide a nonperturbative proof that stable stationary points of linear density constraints occur only at energy maxima with respect to their Lagrange multipliers. We show that multiple solutions, hysteresis, and energy discontinuities may occur in cDFT. Expressions are derived, in terms of convenient by-products of cDFT optimization, for quantities such as the dielectric function and a condition number quantifying ill definition in multiple constraint cDFT.

Optimization of performance and emission characteristics of PPCCI engine fuelled with ethanol and diesel blends using grey-Taguchi method

NASA Astrophysics Data System (ADS)

Natarajan, S.; Pitchandi, K.; Mahalakshmi, N. V.

2018-02-01

The performance and emission characteristics of a PPCCI engine fuelled with ethanol and diesel blends were carried out on a single cylinder air cooled CI engine. In order to achieve the optimal process response with a limited number of experimental cycles, multi objective grey relational analysis had been applied for solving a multiple response optimization problem. Using grey relational grade and signal-to-noise ratio as a performance index, a combination of input parameters was prefigured so as to achieve optimum response characteristics. It was observed that 20% premixed ratio of blend was most suitable for use in a PPCCI engine without significantly affecting the engine performance and emissions characteristics.

Optimizing Basic French Skills Utilizing Multiple Teaching Techniques.

ERIC Educational Resources Information Center

Skala, Carol

This action research project examined the impact of foreign language teaching techniques on the language acquisition and retention of 19 secondary level French I students, focusing on student perceptions of the effectiveness and ease of four teaching techniques: total physical response, total physical response storytelling, literature approach,…

Enhanced nonlinearity interval mapping scheme for high-performance simulation-optimization of watershed-scale BMP placement

NASA Astrophysics Data System (ADS)

Zou, Rui; Riverson, John; Liu, Yong; Murphy, Ryan; Sim, Youn

2015-03-01

Integrated continuous simulation-optimization models can be effective predictors of a process-based responses for cost-benefit optimization of best management practices (BMPs) selection and placement. However, practical application of simulation-optimization model is computationally prohibitive for large-scale systems. This study proposes an enhanced Nonlinearity Interval Mapping Scheme (NIMS) to solve large-scale watershed simulation-optimization problems several orders of magnitude faster than other commonly used algorithms. An efficient interval response coefficient (IRC) derivation method was incorporated into the NIMS framework to overcome a computational bottleneck. The proposed algorithm was evaluated using a case study watershed in the Los Angeles County Flood Control District. Using a continuous simulation watershed/stream-transport model, Loading Simulation Program in C++ (LSPC), three nested in-stream compliance points (CP)—each with multiple Total Maximum Daily Loads (TMDL) targets—were selected to derive optimal treatment levels for each of the 28 subwatersheds, so that the TMDL targets at all the CP were met with the lowest possible BMP implementation cost. Genetic Algorithm (GA) and NIMS were both applied and compared. The results showed that the NIMS took 11 iterations (about 11 min) to complete with the resulting optimal solution having a total cost of 67.2 million, while each of the multiple GA executions took 21-38 days to reach near optimal solutions. The best solution obtained among all the GA executions compared had a minimized cost of 67.7 million—marginally higher, but approximately equal to that of the NIMS solution. The results highlight the utility for decision making in large-scale watershed simulation-optimization formulations.

Integrated aerodynamic/dynamic optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Chattopadhyay, Aditi; Walsh, Joanne L.; Riley, Michael F.

1989-01-01

An integrated aerodynamic/dynamic optimization procedure is used to minimize blade weight and 4 per rev vertical hub shear for a rotor blade in forward flight. The coupling of aerodynamics and dynamics is accomplished through the inclusion of airloads which vary with the design variables during the optimization process. Both single and multiple objective functions are used in the optimization formulation. The Global Criteria Approach is used to formulate the multiple objective optimization and results are compared with those obtained by using single objective function formulations. Constraints are imposed on natural frequencies, autorotational inertia, and centrifugal stress. The program CAMRAD is used for the blade aerodynamic and dynamic analyses, and the program CONMIN is used for the optimization. Since the spanwise and the azimuthal variations of loading are responsible for most rotor vibration and noise, the vertical airload distributions on the blade, before and after optimization, are compared. The total power required by the rotor to produce the same amount of thrust for a given area is also calculated before and after optimization. Results indicate that integrated optimization can significantly reduce the blade weight, the hub shear and the amplitude of the vertical airload distributions on the blade and the total power required by the rotor.

Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

Real time PI-backstepping induction machine drive with efficiency optimization.

PubMed

Farhani, Fethi; Ben Regaya, Chiheb; Zaafouri, Abderrahmen; Chaari, Abdelkader

2017-09-01

This paper describes a robust and efficient speed control of a three phase induction machine (IM) subjected to load disturbances. First, a Multiple-Input Multiple-Output (MIMO) PI-Backstepping controller is proposed for a robust and highly accurate tracking of the mechanical speed and rotor flux. Asymptotic stability of the control scheme is proven by Lyapunov Stability Theory. Second, an active online optimization algorithm is used to optimize the efficiency of the drive system. The efficiency improvement approach consists of adjusting the rotor flux with respect to the load torque in order to minimize total losses in the IM. A dSPACE DS1104 R&D board is used to implement the proposed solution. The experimental results released on 3kW squirrel cage IM, show that the reference speed as well as the rotor flux are rapidly achieved with a fast transient response and without overshoot. A good load disturbances rejection response and IM parameters variation are fairly handled. The improvement of drive system efficiency reaches up to 180% at light load. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-Satellite Observation Scheduling for Large Area Disaster Emergency Response

NASA Astrophysics Data System (ADS)

Niu, X. N.; Tang, H.; Wu, L. X.

2018-04-01

an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

Gear optimization

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Treatment optimization in MS: Canadian MS Working Group updated recommendations.

PubMed

Freedman, Mark S; Selchen, Daniel; Arnold, Douglas L; Prat, Alexandre; Banwell, Brenda; Yeung, Michael; Morgenthau, David; Lapierre, Yves

2013-05-01

The Canadian Multiple Sclerosis Working Group (CMSWG) developed practical recommendations in 2004 to assist clinicians in optimizing the use of disease-modifying therapies (DMT) in patients with relapsing multiple sclerosis. The CMSWG convened to review how disease activity is assessed, propose a more current approach for assessing suboptimal response, and to suggest a scheme for switching or escalating treatment. Practical criteria for relapses, Expanded Disability Status Scale (EDSS) progression and MRI were developed to classify the clinical level of concern as Low, Medium and High. The group concluded that a change in treatment may be considered in any RRMS patient if there is a high level of concern in any one domain (relapses, progression or MRI), a medium level of concern in any two domains, or a low level of concern in all three domains. These recommendations for assessing treatment response should assist clinicians in making more rational choices in their management of relapsing MS patients.

Three-dimensional polarization marked multiple-QR code encryption by optimizing a single vectorial beam

NASA Astrophysics Data System (ADS)

Lin, Chao; Shen, Xueju; Hua, Binbin; Wang, Zhisong

2015-10-01

We demonstrate the feasibility of three dimensional (3D) polarization multiplexing by optimizing a single vectorial beam using a multiple-signal window multiple-plane (MSW-MP) phase retrieval algorithm. Original messages represented with multiple quick response (QR) codes are first partitioned into a series of subblocks. Then, each subblock is marked with a specific polarization state and randomly distributed in 3D space with both longitudinal and transversal adjustable freedoms. A generalized 3D polarization mapping protocol is established to generate a 3D polarization key. Finally, multiple-QR code is encrypted into one phase only mask and one polarization only mask based on the modified Gerchberg-Saxton (GS) algorithm. We take the polarization mask as the cyphertext and the phase only mask as additional dimension of key. Only when both the phase key and 3D polarization key are correct, original messages can be recovered. We verify our proposal with both simulation and experiment evidences.

Effects of homogenization process parameters on physicochemical properties of astaxanthin nanodispersions prepared using a solvent-diffusion technique

PubMed Central

Anarjan, Navideh; Jafarizadeh-Malmiri, Hoda; Nehdi, Imededdine Arbi; Sbihi, Hassen Mohamed; Al-Resayes, Saud Ibrahim; Tan, Chin Ping

2015-01-01

Nanodispersion systems allow incorporation of lipophilic bioactives, such as astaxanthin (a fat soluble carotenoid) into aqueous systems, which can improve their solubility, bioavailability, and stability, and widen their uses in water-based pharmaceutical and food products. In this study, response surface methodology was used to investigate the influences of homogenization time (0.5–20 minutes) and speed (1,000–9,000 rpm) in the formation of astaxanthin nanodispersions via the solvent-diffusion process. The product was characterized for particle size and astaxanthin concentration using laser diffraction particle size analysis and high performance liquid chromatography, respectively. Relatively high determination coefficients (ranging from 0.896 to 0.969) were obtained for all suggested polynomial regression models. The overall optimal homogenization conditions were determined by multiple response optimization analysis to be 6,000 rpm for 7 minutes. In vitro cellular uptake of astaxanthin from the suggested individual and multiple optimized astaxanthin nanodispersions was also evaluated. The cellular uptake of astaxanthin was found to be considerably increased (by more than five times) as it became incorporated into optimum nanodispersion systems. The lack of a significant difference between predicted and experimental values confirms the suitability of the regression equations connecting the response variables studied to the independent parameters. PMID:25709435

Screening and Monitoring Response to Treatment Using Subsecond Molecular Imaging and Hyperpolarized Contrast Agents

DTIC Science & Technology

2013-05-01

Magnetization transfer MRI in multiple sclerosis . J Neuroimaging. 2007;17 Suppl 1:S22–S26. 82. Filippi M, Rocca MA. Magnetization transfer magnetic resonance... multiple sclerosis . Neuroimaging Clin N Am. 2009;19(1):27–36. 84. Lundbom N. Determination of magnetization transfer contrast in tissue: an MR... multiple RF coils intended for optimal direct and indirect detection of hyperpolarized contrast agents in vivo. 4.b. Y1Q3-Y1Q4. Low field MRI: pre

Shape Optimization of Cylindrical Shell for Interior Noise

NASA Technical Reports Server (NTRS)

Robinson, Jay H.

1999-01-01

In this paper an analytic method is used to solve for the cross spectral density of the interior acoustic response of a cylinder with nonuniform thickness subjected to turbulent boundary layer excitation. The cylinder is of honeycomb core construction with the thickness of the core material expressed as a cosine series in the circumferential direction. The coefficients of this series are used as the design variable in the optimization study. The objective function is the space and frequency averaged acoustic response. Results confirm the presence of multiple local minima as previously reported and demonstrate the potential for modest noise reduction.

Mineralization of pyrrole, a recalcitrant heterocyclic compound, by electrochemical method: Multi-response optimization and degradation mechanism.

PubMed

Hiwarkar, Ajay Devidas; Singh, Seema; Srivastava, Vimal Chandra; Mall, Indra Deo

2017-08-01

In this study, the electrochemical (EC) oxidation of a recalcitrant heterocyclic compound namely pyrrole has been reported using platinum coated titanium (Pt/Ti) electrodes. Response surface methodology (RSM) comprising of full factorial central composite design (CCD) with four factors and five levels has been used to examine the effects of different operating parameters such as current density (j), aqueous solution pH, conductivity (k) and treatment time (t) in an EC batch reactor. Pyrrole mineralization in aqueous solution was examined with multiple responses such as chemical oxygen demand (COD) (response, Y 1 ) and specific energy consumption (SEC) in kWh/kg of COD removed (response, Y 2 ). During multiple response optimization, the desirability function approach was employed to concurrently maximize Y 1 and minimize Y 2 . At the optimum condition, 82.9% COD removal and 7.7 kWh/kg of COD removed were observed. Degradation mechanism of pyrrole in wastewater was elucidated at the optimum condition of treatment by using UV-visible spectroscopy, Fourier transformed infra-red spectroscopy (FTIR), cyclic voltammetry (CV), ion chromatography (IC), higher performance liquid chromatography (HPLC) and gas chromatography-mass spectroscopy (GC-MS). The degradation pathway of pyrrole was proposed on the basis of the various analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simultaneous Optimization of Multiple Response Variables for the Gelatin-chitosan Microcapsules Containing Angelica Essential Oil.

PubMed

Li, Qiang; Sun, Li-Jian; Gong, Xian-Feng; Wang, Yang; Zhao, Xue-Ling

2017-01-01

Angelica essential oil (AO), a major pharmacologically active component of Angelica sinensis (Oliv.) Diels, possesses hemogenesis, analgesic activities, and sedative effect. The application of AO in pharmaceutical systems had been limited because of its low oxidative stability. The AO-loaded gelatin-chitosan microcapsules with prevention from oxidation were developed and optimized using response surface methodology. The effects of formulation variables (pH at complex coacervation, gelatin concentration, and core/wall ratio) on multiple response variables (yield, encapsulation efficiency, antioxidation rate, percent of drug released in 1 h, and time to 85% drug release) were systemically investigated. A desirability function that combined these five response variables was constructed. All response variables investigated were found to be highly dependent on the formulation variables, with strong interactions observed between the formulation variables. It was found that optimum overall desirability of AO microcapsules could be obtained at pH 6.20, gelatin concentration 25.00%, and core/wall ratio 40.40%. The experimental values of the response variables highly agreed with the predicted values. The antioxidation rate of optimum formulation was approximately 8 times higher than that of AO. The in-vitro drug release from microcapsules was followed Higuchi model with super case-II transport mechanism.

A Multivariate Quality Loss Function Approach for Optimization of Spinning Processes

NASA Astrophysics Data System (ADS)

Chakraborty, Shankar; Mitra, Ankan

2018-05-01

Recent advancements in textile industry have given rise to several spinning techniques, such as ring spinning, rotor spinning etc., which can be used to produce a wide variety of textile apparels so as to fulfil the end requirements of the customers. To achieve the best out of these processes, they should be utilized at their optimal parametric settings. However, in presence of multiple yarn characteristics which are often conflicting in nature, it becomes a challenging task for the spinning industry personnel to identify the best parametric mix which would simultaneously optimize all the responses. Hence, in this paper, the applicability of a new systematic approach in the form of multivariate quality loss function technique is explored for optimizing multiple quality characteristics of yarns while identifying the ideal settings of two spinning processes. It is observed that this approach performs well against the other multi-objective optimization techniques, such as desirability function, distance function and mean squared error methods. With slight modifications in the upper and lower specification limits of the considered quality characteristics, and constraints of the non-linear optimization problem, it can be successfully applied to other processes in textile industry to determine their optimal parametric settings.

[Optimization of one-step pelletization technology of Biqiu granules by Plackett-Burman design and Box-Behnken response surface methodology].

PubMed

Zhang, Yan-jun; Liu, Li-li; Hu, Jun-hua; Wu, Yun; Chao, En-xiang; Xiao, Wei

2015-11-01

First with the qualified rate of granules as the evaluation index, significant influencing factors were firstly screened by Plackett-Burman design. Then, with the qualified rate and moisture content as the evaluation indexes, significant factors that affect one-step pelletization technology were further optimized by Box-Behnken design; experimental data were imitated by multiple regression and second-order polynomial equation; and response surface method was used for predictive analysis of optimal technology. The best conditions were as follows: inlet air temperature of 85 degrees C, sample introduction speed of 33 r x min(-1), density of concrete 1. 10. One-step pelletization technology of Biqiu granules by Plackett-Burman design and Box-Behnken response surface methodology was stable and feasible with good predictability, which provided reliable basis for the industrialized production of Biqiu granules.

Optimal design of clinical trials with biologics using dose-time-response models.

PubMed

Lange, Markus R; Schmidli, Heinz

2014-12-30

Biologics, in particular monoclonal antibodies, are important therapies in serious diseases such as cancer, psoriasis, multiple sclerosis, or rheumatoid arthritis. While most conventional drugs are given daily, the effect of monoclonal antibodies often lasts for months, and hence, these biologics require less frequent dosing. A good understanding of the time-changing effect of the biologic for different doses is needed to determine both an adequate dose and an appropriate time-interval between doses. Clinical trials provide data to estimate the dose-time-response relationship with semi-mechanistic nonlinear regression models. We investigate how to best choose the doses and corresponding sample size allocations in such clinical trials, so that the nonlinear dose-time-response model can be precisely estimated. We consider both local and conservative Bayesian D-optimality criteria for the design of clinical trials with biologics. For determining the optimal designs, computer-intensive numerical methods are needed, and we focus here on the particle swarm optimization algorithm. This metaheuristic optimizer has been successfully used in various areas but has only recently been applied in the optimal design context. The equivalence theorem is used to verify the optimality of the designs. The methodology is illustrated based on results from a clinical study in patients with gout, treated by a monoclonal antibody. Copyright © 2014 John Wiley & Sons, Ltd.

Do the right thing: the assumption of optimality in lay decision theory and causal judgment.

PubMed

Johnson, Samuel G B; Rips, Lance J

2015-03-01

Human decision-making is often characterized as irrational and suboptimal. Here we ask whether people nonetheless assume optimal choices from other decision-makers: Are people intuitive classical economists? In seven experiments, we show that an agent's perceived optimality in choice affects attributions of responsibility and causation for the outcomes of their actions. We use this paradigm to examine several issues in lay decision theory, including how responsibility judgments depend on the efficacy of the agent's actual and counterfactual choices (Experiments 1-3), individual differences in responsibility assignment strategies (Experiment 4), and how people conceptualize decisions involving trade-offs among multiple goals (Experiments 5-6). We also find similar results using everyday decision problems (Experiment 7). Taken together, these experiments show that attributions of responsibility depend not only on what decision-makers do, but also on the quality of the options they choose not to take. Copyright © 2015 Elsevier Inc. All rights reserved.

Inducible defense against pathogens and parasites: optimal choice among multiple options.

PubMed

Shudo, E; Iwasa, Y

2001-03-21

Defense against pathogen, parasites and herbivores is often enhanced after their invasion into the host's body. Sometimes different options are adopted depending on the identity and the quantity of the pathogen, exemplified by the switch between Th1 and Th2 systems in mammalian immunity. In this paper, we study the optimal defense of the host when two alternative responses are available, which differ in the effectiveness of suppressing the growth of pathogen (parasite, or herbivore), the damage to the host caused by the defense response, and the magnitude of time delay before the defense response becomes fully effective. The optimal defense is the one that minimizes the sum of the damages caused by the pathogen and the cost due to defense activities. The damage by pathogens increases in proportion to the time integral of the pathogen abundance, and the cost is proportional to the defense activity. We can prove that a single globally optimal combination of defense options always exists and there is no other local optimum. Depending on the parameters, the optimal is to adopt only the early response, only the late response, or both responses. The defense response with a shorter time delay is more heavily used when the pathogen grows fast, the initial pathogen abundance is large, and the difference in time delay is long. We also study the host's optimal choice between constitutive and inducible defenses. In the constitutive defense, the response to pathogen attack works without delay, but it causes the cost even when the pathogen attack does not occur. We discuss mammalian immunity and the plant chemical defense from the model's viewpoint. Copyright 2001 Academic Press.

Magnetically multiplexed heating of single domain nanoparticles

NASA Astrophysics Data System (ADS)

Christiansen, M. G.; Senko, A. W.; Chen, R.; Romero, G.; Anikeeva, P.

2014-05-01

Selective hysteretic heating of multiple collocated types of single domain magnetic nanoparticles (SDMNPs) by alternating magnetic fields (AMFs) may offer a useful tool for biomedical applications. The possibility of "magnetothermal multiplexing" has not yet been realized, in part due to prevalent use of linear response theory to model SDMNP heating in AMFs. Dynamic hysteresis modeling suggests that specific driving conditions play an underappreciated role in determining optimal material selection strategies for high heat dissipation. Motivated by this observation, magnetothermal multiplexing is theoretically predicted and empirically demonstrated by selecting SDMNPs with properties that suggest optimal hysteretic heat dissipation at dissimilar AMF driving conditions. This form of multiplexing could effectively offer multiple channels for minimally invasive biological signaling applications.

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

PubMed

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

2015-01-01

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

Performance Dependences of Multiplication Layer Thickness for InP/InGaAs Avalanche Photodiodes Based on Time Domain Modeling

NASA Technical Reports Server (NTRS)

Xiao, Yegao; Bhat, Ishwara; Abedin, M. Nurul

2005-01-01

InP/InGaAs avalanche photodiodes (APDs) are being widely utilized in optical receivers for modern long haul and high bit-rate optical fiber communication systems. The separate absorption, grading, charge, and multiplication (SAGCM) structure is an important design consideration for APDs with high performance characteristics. Time domain modeling techniques have been previously developed to provide better understanding and optimize design issues by saving time and cost for the APD research and development. In this work, performance dependences on multiplication layer thickness have been investigated by time domain modeling. These performance characteristics include breakdown field and breakdown voltage, multiplication gain, excess noise factor, frequency response and bandwidth etc. The simulations are performed versus various multiplication layer thicknesses with certain fixed values for the areal charge sheet density whereas the values for the other structure and material parameters are kept unchanged. The frequency response is obtained from the impulse response by fast Fourier transformation. The modeling results are presented and discussed, and design considerations, especially for high speed operation at 10 Gbit/s, are further analyzed.

Robust design of multiple trailing edge flaps for helicopter vibration reduction: A multi-objective bat algorithm approach

NASA Astrophysics Data System (ADS)

Mallick, Rajnish; Ganguli, Ranjan; Seetharama Bhat, M.

2015-09-01

The objective of this study is to determine an optimal trailing edge flap configuration and flap location to achieve minimum hub vibration levels and flap actuation power simultaneously. An aeroelastic analysis of a soft in-plane four-bladed rotor is performed in conjunction with optimal control. A second-order polynomial response surface based on an orthogonal array (OA) with 3-level design describes both the objectives adequately. Two new orthogonal arrays called MGB2P-OA and MGB4P-OA are proposed to generate nonlinear response surfaces with all interaction terms for two and four parameters, respectively. A multi-objective bat algorithm (MOBA) approach is used to obtain the optimal design point for the mutually conflicting objectives. MOBA is a recently developed nature-inspired metaheuristic optimization algorithm that is based on the echolocation behaviour of bats. It is found that MOBA inspired Pareto optimal trailing edge flap design reduces vibration levels by 73% and flap actuation power by 27% in comparison with the baseline design.

Cortical membrane potential signature of optimal states for sensory signal detection

PubMed Central

McGinley, Matthew J.; David, Stephen V.; McCormick, David A.

2015-01-01

The neural correlates of optimal states for signal detection task performance are largely unknown. One hypothesis holds that optimal states exhibit tonically depolarized cortical neurons with enhanced spiking activity, such as occur during movement. We recorded membrane potentials of auditory cortical neurons in mice trained on a challenging tone-in-noise detection task while assessing arousal with simultaneous pupillometry and hippocampal recordings. Arousal measures accurately predicted multiple modes of membrane potential activity, including: rhythmic slow oscillations at low arousal, stable hyperpolarization at intermediate arousal, and depolarization during phasic or tonic periods of hyper-arousal. Walking always occurred during hyper-arousal. Optimal signal detection behavior and sound-evoked responses, at both sub-threshold and spiking levels, occurred at intermediate arousal when pre-decision membrane potentials were stably hyperpolarized. These results reveal a cortical physiological signature of the classically-observed inverted-U relationship between task performance and arousal, and that optimal detection exhibits enhanced sensory-evoked responses and reduced background synaptic activity. PMID:26074005

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

PubMed

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

2018-01-01

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

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

PubMed

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

2016-10-01

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

Multi-objective optimization of GENIE Earth system models.

PubMed

Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J

2009-07-13

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

Optimal control of first order distributed systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Johnson, T. L.

1972-01-01

The problem of characterizing optimal controls for a class of distributed-parameter systems is considered. The system dynamics are characterized mathematically by a finite number of coupled partial differential equations involving first-order time and space derivatives of the state variables, which are constrained at the boundary by a finite number of algebraic relations. Multiple control inputs, extending over the entire spatial region occupied by the system ("distributed controls') are to be designed so that the response of the system is optimal. A major example involving boundary control of an unstable low-density plasma is developed from physical laws.

Isotretinoin Oil-Based Capsule Formulation Optimization

PubMed Central

Tsai, Pi-Ju; Huang, Chi-Te; Lee, Chen-Chou; Li, Chi-Lin; Huang, Yaw-Bin; Tsai, Yi-Hung; Wu, Pao-Chu

2013-01-01

The purpose of this study was to develop and optimize an isotretinoin oil-based capsule with specific dissolution pattern. A three-factor-constrained mixture design was used to prepare the systemic model formulations. The independent factors were the components of oil-based capsule including beeswax (X 1), hydrogenated coconut oil (X 2), and soybean oil (X 3). The drug release percentages at 10, 30, 60, and 90 min were selected as responses. The effect of formulation factors including that on responses was inspected by using response surface methodology (RSM). Multiple-response optimization was performed to search for the appropriate formulation with specific release pattern. It was found that the interaction effect of these formulation factors (X 1 X 2, X 1 X 3, and X 2 X 3) showed more potential influence than that of the main factors (X 1, X 2, and X 3). An optimal predicted formulation with Y 10 min, Y 30 min, Y 60 min, and Y 90 min release values of 12.3%, 36.7%, 73.6%, and 92.7% at X 1, X 2, and X 3 of 5.75, 15.37, and 78.88, respectively, was developed. The new formulation was prepared and performed by the dissolution test. The similarity factor f 2 was 54.8, indicating that the dissolution pattern of the new optimized formulation showed equivalence to the predicted profile. PMID:24068886

Multivariate optimization of a synergistic blend of oleoresin sage (Salvia officinalis L.) and ascorbyl palmitate to stabilize sunflower oil.

PubMed

Upadhyay, Rohit; Mishra, Hari Niwas

2016-04-01

The simultaneous optimization of a synergistic blend of oleoresin sage (SAG) and ascorbyl palmitate (AP) in sunflower oil (SO) was performed using central composite and rotatable design coupled with principal component analysis (PCA) and response surface methodology (RSM). The physicochemical parameters viz., peroxide value, anisidine value, free fatty acids, induction period, total polar matter, antioxidant capacity and conjugated diene value were considered as response variables. PCA reduced the original set of correlated responses to few uncorrelated principal components (PC). The PC1 (eigen value, 5.78; data variance explained, 82.53 %) was selected for optimization using RSM. The quadratic model adequately described the data (R (2) = 0. 91, p < 0.05) and lack of fit was insignificant (p > 0.05). The contour plot of PC 1 score indicated the optimal synergistic combination of 1289.19 and 218.06 ppm for SAG and AP, respectively. This combination of SAG and AP resulted in shelf life of 320 days at 25 °C estimated using linear shelf life prediction model. In conclusion, the versatility of PCA-RSM approach has resulted in an easy interpretation in multiple response optimizations. This approach can be considered as a useful guide to develop new oil blends stabilized with food additives from natural sources.

Distinct roles of dopamine and subthalamic nucleus in learning and probabilistic decision making.

PubMed

Coulthard, Elizabeth J; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K; Murphy, Gillian; Keeley, Sophie; Whone, Alan L

2012-12-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making predict that learning individual stimulus-response associations and rapid combination of information from multiple stimuli are dependent on different components of basal ganglia circuitry. In particular, learning and retention of memory, required for optimal response choice, are significantly reliant on dopamine, whereas integrating information probabilistically is critically dependent upon functioning of the glutamatergic subthalamic nucleus (computing the 'normalization term' in Bayes' theorem). Here, we test these theories by investigating 22 patients with Parkinson's disease either treated with deep brain stimulation to the subthalamic nucleus and dopaminergic therapy or managed with dopaminergic therapy alone. We use computerized tasks that probe three cognitive functions-information acquisition (learning), memory over a delay and information integration when multiple pieces of sequentially presented information have to be combined. Patients performed the tasks ON or OFF deep brain stimulation and/or ON or OFF dopaminergic therapy. Consistent with the computational theories, we show that stopping dopaminergic therapy impairs memory for probabilistic information over a delay, whereas deep brain stimulation to the region of the subthalamic nucleus disrupts decision making when multiple pieces of acquired information must be combined. Furthermore, we found that when participants needed to update their decision on the basis of the last piece of information presented in the decision-making task, patients with deep brain stimulation of the subthalamic nucleus region did not slow down appropriately to revise their plan, a pattern of behaviour that mirrors the impulsivity described clinically in some patients with subthalamic nucleus deep brain stimulation. Thus, we demonstrate distinct mechanisms for two important facets of human decision making: first, a role for dopamine in memory consolidation, and second, the critical importance of the subthalamic nucleus in successful decision making when multiple pieces of information must be combined.

TeleProbe: design and development of an efficient system for telepathology

NASA Astrophysics Data System (ADS)

Ahmed, Wamiq M.; Robinson, J. Paul; Ghafoor, Arif

2005-10-01

This paper describes an internet-based system for telepathology. This system provides support for multiple users and exploits the opportunities for optimization that arise in multi-user environment. Techniques for increasing system responsiveness by improving resource utilization and lowering network traffic are explored. Some of the proposed optimizations include an auto-focus module, client and server side caching, and request reordering. These systems can be an economic solution not only for remote pathology consultation but also for pathology and biology education.

Quality by design: optimization of a liquid filled pH-responsive macroparticles using Draper-Lin composite design.

PubMed

Rafati, Hasan; Talebpour, Zahra; Adlnasab, Laleh; Ebrahimi, Samad Nejad

2009-07-01

In this study, pH responsive macroparticles incorporating peppermint oil (PO) were prepared using a simple emulsification/polymer precipitation technique. The formulations were examined for their properties and the desired quality was then achieved using a quality by design (QBD) approach. For this purpose, a Draper-Lin small composite design study was employed in order to investigate the effect of four independent variables, including the PO to water ratio, the concentration of pH sensitive polymer (hydroxypropyl methylcellulose phthalate), acid and plasticizer concentrations, on the encapsulation efficiency and PO loading. The analysis of variance showed that the polymer concentration was the most important variable on encapsulation efficiency (p < 0.05). The multiple regression analysis of the results led to equations that adequately described the influence of the independent variables on the selected responses. Furthermore, the desirability function was employed as an effective tool for transforming each response separately and encompassing all of these responses in an overall desirability function for global optimization of the encapsulation process. The optimized macroparticles were predicted to yield 93.4% encapsulation efficiency and 72.8% PO loading, which were remarkably close to the experimental values of 89.2% and 69.5%, consequently.

Mass Spectrometry Parameters Optimization for the 46 Multiclass Pesticides Determination in Strawberries with Gas Chromatography Ion-Trap Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Fernandes, Virgínia C.; Vera, Jose L.; Domingues, Valentina F.; Silva, Luís M. S.; Mateus, Nuno; Delerue-Matos, Cristina

2012-12-01

Multiclass analysis method was optimized in order to analyze pesticides traces by gas chromatography with ion-trap and tandem mass spectrometry (GC-MS/MS). The influence of some analytical parameters on pesticide signal response was explored. Five ion trap mass spectrometry (IT-MS) operating parameters, including isolation time (IT), excitation voltage (EV), excitation time (ET), maximum excitation energy or " q" value (q), and isolation mass window (IMW) were numerically tested in order to maximize the instrument analytical signal response. For this, multiple linear regression was used in data analysis to evaluate the influence of the five parameters on the analytical response in the ion trap mass spectrometer and to predict its response. The assessment of the five parameters based on the regression equations substantially increased the sensitivity of IT-MS/MS in the MS/MS mode. The results obtained show that for most of the pesticides, these parameters have a strong influence on both signal response and detection limit. Using the optimized method, a multiclass pesticide analysis was performed for 46 pesticides in a strawberry matrix. Levels higher than the limit established for strawberries by the European Union were found in some samples.

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

PubMed

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

2010-09-01

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

Response surface optimization of the critical medium components for pullulan production by Aureobasidium pullulans FB-1.

PubMed

Singh, Ram Sarup; Singh, Harpreet; Saini, Gaganpreet Kaur

2009-01-01

Culture conditions for pullulan production by Aureobasidium pullulans were optimized using response surface methodology at shake flask level without pH control. In the present investigation, a five-level with five-factor central composite rotatable design of experiments was employed to optimize the levels of five factors significantly affecting the pullulan production, biomass production, and sugar utilization in submerged cultivation. The selected factors included concentration of sucrose, ammonium sulphate, yeast extract, dipotassium hydrogen phosphate, and sodium chloride. Using this methodology, the optimal values for concentration of sucrose, ammonium sulphate, yeast extract, dipotassium hydrogen phosphate, and sodium chloride were 5.31%, 0.11%, 0.07%, 0.05%, and 0.15% (w/v), respectively. This optimized medium has projected a theoretically production of pullulan of 4.44%, biomass yield of 1.03%, and sugar utilization of 97.12%. The multiple correlation coefficient 'R' was 0.9976, 0.9761 and 0.9919 for pullulan production, biomass production, and sugar utilization, respectively. The value of R being very close to one justifies an excellent correlation between the predicted and the experimental data.

Extensions of D-optimal Minimal Designs for Symmetric Mixture Models

PubMed Central

Raghavarao, Damaraju; Chervoneva, Inna

2017-01-01

The purpose of mixture experiments is to explore the optimum blends of mixture components, which will provide desirable response characteristics in finished products. D-optimal minimal designs have been considered for a variety of mixture models, including Scheffé's linear, quadratic, and cubic models. Usually, these D-optimal designs are minimally supported since they have just as many design points as the number of parameters. Thus, they lack the degrees of freedom to perform the Lack of Fit tests. Also, the majority of the design points in D-optimal minimal designs are on the boundary: vertices, edges, or faces of the design simplex. In This Paper, Extensions Of The D-Optimal Minimal Designs Are Developed For A General Mixture Model To Allow Additional Interior Points In The Design Space To Enable Prediction Of The Entire Response Surface Also a new strategy for adding multiple interior points for symmetric mixture models is proposed. We compare the proposed designs with Cornell (1986) two ten-point designs for the Lack of Fit test by simulations. PMID:29081574

Optimal multi-type sensor placement for response and excitation reconstruction

NASA Astrophysics Data System (ADS)

Zhang, C. D.; Xu, Y. L.

2016-01-01

The need to perform dynamic response reconstruction always arises as the measurement of structural response is often limited to a few locations, especially for a large civil structure. Besides, it is usually very difficult, if not impossible, to measure external excitations under the operation condition of a structure. This study presents an algorithm for optimal placement of multi-type sensors, including strain gauges, displacement transducers and accelerometers, for the best reconstruction of responses of key structural components where there are no sensors installed and the best estimation of external excitations acting on the structure at the same time. The algorithm is developed in the framework of Kalman filter with unknown excitation, in which minimum-variance unbiased estimates of the generalized state of the structure and the external excitations are obtained by virtue of limited sensor measurements. The structural responses of key locations without sensors can then be reconstructed with the estimated generalized state and excitation. The asymptotic stability feature of the filter is utilized for optimal sensor placement. The number and spatial location of the multi-type sensors are determined by adding the optimal sensor which gains the maximal reduction of the estimation error of reconstructed responses. For the given mode number in response reconstruction and the given locations of external excitations, the optimal multi-sensor placement achieved by the proposed method is independent of the type and time evolution of external excitation. A simply-supported overhanging steel beam under multiple types of excitation is numerically studied to demonstrate the feasibility and superiority of the proposed method, and the experimental work is then carried out to testify the effectiveness of the proposed method.

Equalizing access to pandemic influenza vaccines through optimal allocation to public health distribution points.

PubMed

Huang, Hsin-Chan; Singh, Bismark; Morton, David P; Johnson, Gregory P; Clements, Bruce; Meyers, Lauren Ancel

2017-01-01

Vaccines are arguably the most important means of pandemic influenza mitigation. However, as during the 2009 H1N1 pandemic, mass immunization with an effective vaccine may not begin until a pandemic is well underway. In the U.S., state-level public health agencies are responsible for quickly and fairly allocating vaccines as they become available to populations prioritized to receive vaccines. Allocation decisions can be ethically and logistically complex, given several vaccine types in limited and uncertain supply and given competing priority groups with distinct risk profiles and vaccine acceptabilities. We introduce a model for optimizing statewide allocation of multiple vaccine types to multiple priority groups, maximizing equal access. We assume a large fraction of available vaccines are distributed to healthcare providers based on their requests, and then optimize county-level allocation of the remaining doses to achieve equity. We have applied the model to the state of Texas, and incorporated it in a Web-based decision-support tool for the Texas Department of State Health Services (DSHS). Based on vaccine quantities delivered to registered healthcare providers in response to their requests during the 2009 H1N1 pandemic, we find that a relatively small cache of discretionary doses (DSHS reserved 6.8% in 2009) suffices to achieve equity across all counties in Texas.

Process optimization for osmo-dehydrated carambola (Averrhoa carambola L) slices and its storage studies.

PubMed

Roopa, N; Chauhan, O P; Raju, P S; Das Gupta, D K; Singh, R K R; Bawa, A S

2014-10-01

An osmotic-dehydration process protocol for Carambola (Averrhoacarambola L.,), an exotic star shaped tropical fruit, was developed. The process was optimized using Response Surface Methodology (RSM) following Central Composite Rotatable Design (CCRD). The experimental variables selected for the optimization were soak solution concentration (°Brix), soaking temperature (°C) and soaking time (min) with 6 experiments at central point. The effect of process variables was studied on solid gain and water loss during osmotic dehydration process. The data obtained were analyzed employing multiple regression technique to generate suitable mathematical models. Quadratic models were found to fit well (R(2), 95.58 - 98.64 %) in describing the effect of variables on the responses studied. The optimized levels of the process variables were achieved at 70°Brix, 48 °C and 144 min for soak solution concentration, soaking temperature and soaking time, respectively. The predicted and experimental results at optimized levels of variables showed high correlation. The osmo-dehydrated product prepared at optimized conditions showed a shelf-life of 10, 8 and 6 months at 5 °C, ambient (30 ± 2 °C) and 37 °C, respectively.

Optimization of formulation of soy-cakes baked in infrared-microwave combination oven by response surface methodology.

PubMed

Şakıyan, Özge

2015-05-01

The aim of present work is to optimize the formulation of a functional cake (soy-cake) to be baked in infrared-microwave combination oven. For this optimization process response surface methodology was utilized. It was also aimed to optimize the processing conditions of the combination baking. The independent variables were the baking time (8, 9, 10 min), the soy flour concentration (30, 40, 50 %) and the DATEM (diacetyltartaric acid esters of monoglycerides) concentration (0.4, 0.6 and 0.8 %). The quality parameters that were examined in the study were specific volume, weight loss, total color change and firmness of the cake samples. The results were analyzed by multiple regression; and the significant linear, quadratic, and interaction terms were used in the second order mathematical model. The optimum baking time, soy-flour concentration and DATEM concentration were found as 9.5 min, 30 and 0.72 %, respectively. The corresponding responses of the optimum points were almost comparable with those of conventionally baked soy-cakes. So it may be declared that it is possible to produce high quality soy cakes in a very short time by using infrared-microwave combination oven.

Optimizing health system response to patient's needs: an argument for the importance of functioning information.

PubMed

Hopfe, Maren; Prodinger, Birgit; Bickenbach, Jerome E; Stucki, Gerold

2017-06-06

Current health systems are increasingly challenged to meet the needs of a growing number of patients living with chronic and often multiple health conditions. The primary outcome of care, it is argued, is not merely curing disease but also optimizing functioning over a person's life span. According to the World Health Organization, functioning can serve as foundation for a comprehensive picture of health and augment the biomedical perspective with a broader and more comprehensive picture of health as it plays out in people's lives. The crucial importance of information about patient's functioning for a well-performing health system, however, has yet to be sufficiently appreciated. This paper argues that functioning information is fundamental in all components of health systems and enhances the capacity of health systems to optimize patients' health and health-related needs. Beyond making sense of biomedical disease patterns, health systems can profit from using functioning information to improve interprofessional collaboration and achieve cross-cutting disease treatment outcomes. Implications for rehabilitation Functioning is a key health outcome for rehabilitation within health systems. Information on restoring, maintaining, and optimizing human functioning can strengthen health system response to patients' health and rehabilitative needs. Functioning information guides health systems to achieve cross-cutting health outcomes that respond to the needs of the growing number of individuals living with chronic and multiple health conditions. Accounting for individuals functioning helps to overcome fragmentation of care and to improve interprofessional collaboration across settings.

Bayesian dose selection design for a binary outcome using restricted response adaptive randomization.

PubMed

Meinzer, Caitlyn; Martin, Renee; Suarez, Jose I

2017-09-08

In phase II trials, the most efficacious dose is usually not known. Moreover, given limited resources, it is difficult to robustly identify a dose while also testing for a signal of efficacy that would support a phase III trial. Recent designs have sought to be more efficient by exploring multiple doses through the use of adaptive strategies. However, the added flexibility may potentially increase the risk of making incorrect assumptions and reduce the total amount of information available across the dose range as a function of imbalanced sample size. To balance these challenges, a novel placebo-controlled design is presented in which a restricted Bayesian response adaptive randomization (RAR) is used to allocate a majority of subjects to the optimal dose of active drug, defined as the dose with the lowest probability of poor outcome. However, the allocation between subjects who receive active drug or placebo is held constant to retain the maximum possible power for a hypothesis test of overall efficacy comparing the optimal dose to placebo. The design properties and optimization of the design are presented in the context of a phase II trial for subarachnoid hemorrhage. For a fixed total sample size, a trade-off exists between the ability to select the optimal dose and the probability of rejecting the null hypothesis. This relationship is modified by the allocation ratio between active and control subjects, the choice of RAR algorithm, and the number of subjects allocated to an initial fixed allocation period. While a responsive RAR algorithm improves the ability to select the correct dose, there is an increased risk of assigning more subjects to a worse arm as a function of ephemeral trends in the data. A subarachnoid treatment trial is used to illustrate how this design can be customized for specific objectives and available data. Bayesian adaptive designs are a flexible approach to addressing multiple questions surrounding the optimal dose for treatment efficacy within the context of limited resources. While the design is general enough to apply to many situations, future work is needed to address interim analyses and the incorporation of models for dose response.

Robotic disaster recovery efforts with ad-hoc deployable cloud computing

NASA Astrophysics Data System (ADS)

Straub, Jeremy; Marsh, Ronald; Mohammad, Atif F.

2013-06-01

Autonomous operations of search and rescue (SaR) robots is an ill posed problem, which is complexified by the dynamic disaster recovery environment. In a typical SaR response scenario, responder robots will require different levels of processing capabilities during various parts of the response effort and will need to utilize multiple algorithms. Placing these capabilities onboard the robot is a mediocre solution that precludes algorithm specific performance optimization and results in mediocre performance. Architecture for an ad-hoc, deployable cloud environment suitable for use in a disaster response scenario is presented. Under this model, each service provider is optimized for the task and maintains a database of situation-relevant information. This service-oriented architecture (SOA 3.0) compliant framework also serves as an example of the efficient use of SOA 3.0 in an actual cloud application.

Use of personalized Dynamic Treatment Regimes (DTRs) and Sequential Multiple Assignment Randomized Trials (SMARTs) in mental health studies

PubMed Central

Liu, Ying; ZENG, Donglin; WANG, Yuanjia

2014-01-01

Summary Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each point where a clinical decision is made based on each patient’s time-varying characteristics and intermediate outcomes observed at earlier points in time. The complexity, patient heterogeneity, and chronicity of mental disorders call for learning optimal DTRs to dynamically adapt treatment to an individual’s response over time. The Sequential Multiple Assignment Randomized Trial (SMARTs) design allows for estimating causal effects of DTRs. Modern statistical tools have been developed to optimize DTRs based on personalized variables and intermediate outcomes using rich data collected from SMARTs; these statistical methods can also be used to recommend tailoring variables for designing future SMART studies. This paper introduces DTRs and SMARTs using two examples in mental health studies, discusses two machine learning methods for estimating optimal DTR from SMARTs data, and demonstrates the performance of the statistical methods using simulated data. PMID:25642116

Multiple Vaccinations: Friend or Foe

PubMed Central

Church, Sarah E.; Jensen, Shawn M.; Twitty, Chris; Bahjat, Keith; Hu, Hong-Ming; Urba, Walter J.; Fox, Bernard A.

2013-01-01

Few immunotherapists would accept the concept of a single vaccination inducing a therapeutic anti-cancer immune response in a patient with advanced cancer. But what is the evidence to support the “more-is-better” approach of multiple vaccinations? Since we are unaware of trials comparing the effect of a single vaccine versus multiple vaccinations on patient outcome, we considered that an anti-cancer immune response might provide a surrogate measure of the effectiveness of vaccination strategies. Since few large trials include immunological monitoring, the majority of information is gleaned from smaller trials in which an evaluation of immune responses to vaccine or tumor, before and at one or more times following the first vaccine was performed. In some studies there is convincing evidence that repeated administration of a specific vaccine can augment the immune response to antigens contained in the vaccine. In other settings multiple vaccinations can significantly reduce the immune response to one or more targets. Results from three large adjuvant vaccine studies support the potential detrimental effect of multiple vaccinations as clinical outcomes in the control arms were significantly better than that for treatment groups. Recent research has provided insights into mechanisms that are likely responsible for the reduced responses in the studies noted above, but supporting evidence from clinical specimens is generally lacking. Interpretation of these results is further complicated by the possibility that the dominant immune response may evolve to recognize epitopes not present in the vaccine. Nonetheless, the FDA-approval of the first therapeutic cancer vaccine and recent developments from preclinical models and clinical trials provide a substantial basis for optimism and a critical evaluation of cancer vaccine strategies. PMID:21952289

Topology optimization of finite strain viscoplastic systems under transient loads [Dynamic topology optimization based on finite strain visco-plasticity

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

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Topology optimization of finite strain viscoplastic systems under transient loads [Dynamic topology optimization based on finite strain visco-plasticity

DOE PAGES

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

2018-02-08

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Culture Conditions for Production of Biomass, Adenosine, and Cordycepin from Cordyceps sinensis CS1197: Optimization by Desirability Function Method

PubMed Central

Ghatnur, Shashidhar M.; Parvatam, Giridhar; Balaraman, Manohar

2015-01-01

Background: Cordyceps sinensis (CS) is a traditional Chinese medicine contains potent active metabolites such as nucleosides and polysaccharides. The submerged cultivation technique is studied for the large scale production of CS for biomass and metabolites production. Objective: To optimize culture conditions for large-scale production of CS1197 biomass and metabolites production. Materials and Methods: The CS1197 strain of CS was isolated from dead larvae of natural CS and the authenticity was assured by the presence of two major markers adenosine and cordycepin by high performance liquid chromatography and mass spectrometry. A three-level Box-Behnken design was employed to optimize process parameters culturing temperature, pH, and inoculum volume for the biomass yield, adenosine and cordycepin. The experimental results were regressed to a second-order polynomial equation by a multiple regression analysis for the prediction of biomass yield, adenosine and cordycepin production. Multiple responses were optimized based on desirability function method. Results: The desirability function suggested the process conditions temperature 28°C, pH 7 and inoculum volume 10% for optimal production of nutraceuticals in the biomass. The water extracts from dried CS1197 mycelia showed good inhibition for 2 diphenyl-1-picrylhydrazyl and 2,2-azinobis-(3-ethyl-benzo-thiazoline-6-sulfonic acid-free radicals. Conclusion: The result suggests that response surface methodology-desirability function coupled approach can successfully optimize the culture conditions for CS1197. SUMMARY Authentication of CS1197 strain by the presence of adenosine and cordycepin and culturing period was determined to be for 14 daysContent of nucleosides in natural CS was found higher than in cultured CS1197 myceliumBox-Behnken design to optimize critical cultural conditions: temperature, pH and inoculum volumeWater extract showed better antioxidant activity proving credible source of natural antioxidants. PMID:26929580

Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas.

PubMed

Yao, Yu; Zhao, Junhui; Wu, Lenan

2018-05-29

A new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received signals, and minimize the mean square error (MSE) of TIR estimation. The waveform design approach is based upon constant learning from the target feature at the receiver. Under the multiple antennas scenario, a dynamic feedback loop control system is established to real-time monitor the change in the target features extracted form received signals. The transmitter adapts its transmitted waveform to suit the time-invariant environment. Finally, the simulation results show that, as compared with the waveform design method based on the MAP criterion, the proposed waveform design algorithm is able to improve the performance of TIR estimation for extended targets with multiple iterations, and has a relatively lower level of complexity.

Learning Optimized: A Conversation with Diane Tavenner

ERIC Educational Resources Information Center

Jacobs, Joanne

2013-01-01

Named Charter Leader of the Year in 2010 by the California Charter Schools Association, Diane Tavenner, CEO of Summit Public Schools, is responsible for the generation of multiple transformative schools and a radically different teaching model for Summit. Summit's first charter high school, Summit Prep, launched in 2003, was featured in the film…

Study of gain and photoresponse characteristics for back-illuminated separate absorption and multiplication GaN avalanche photodiodes

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

Wang, Xiaodong; Pan, Ming; Hou, Liwei

2014-01-07

The gain and photoresponse characteristics have been numerically studied for back-illuminated separate absorption and multiplication (SAM) GaN avalanche photodiodes (APDs). The parameters of fundamental models are calibrated by simultaneously comparing the simulated dark and light current characteristics with the experimental results. Effects of environmental temperatures and device dimensions on gain characteristics have been investigated, and a method to achieve the optimum thickness of charge layer is obtained. The dependence of gain characteristics and breakdown voltage on the doping concentration of the charge layer is also studied in detail to get the optimal charge layer. The bias-dependent spectral responsivity and quantummore » efficiency are then presented to study the photoresponse mechanisms inside SAM GaN APDs. It is found the responsivity peak red-shifts at first due to the Franz-Keldysh effect and then blue-shifts due to the reach-through effect of the absorption layer. Finally, a new SAM GaN/AlGaN heterojunction APD structure is proposed for optimizing SAM GaN APDs.« less

A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models

NASA Technical Reports Server (NTRS)

Giunta, Anthony A.; Watson, Layne T.

1998-01-01

Two methods of creating approximation models are compared through the calculation of the modeling accuracy on test problems involving one, five, and ten independent variables. Here, the test problems are representative of the modeling challenges typically encountered in realistic engineering optimization problems. The first approximation model is a quadratic polynomial created using the method of least squares. This type of polynomial model has seen considerable use in recent engineering optimization studies due to its computational simplicity and ease of use. However, quadratic polynomial models may be of limited accuracy when the response data to be modeled have multiple local extrema. The second approximation model employs an interpolation scheme known as kriging developed in the fields of spatial statistics and geostatistics. This class of interpolating model has the flexibility to model response data with multiple local extrema. However, this flexibility is obtained at an increase in computational expense and a decrease in ease of use. The intent of this study is to provide an initial exploration of the accuracy and modeling capabilities of these two approximation methods.

Measuring the impact of multiple sclerosis: Enhancing the measurement performance of the Multiple Sclerosis Impact Scale (MSIS-29) using Rasch Measurement Theory (RMT)

PubMed Central

Cleanthous, Sophie; Kinter, Elizabeth; Marquis, Patrick; Petrillo, Jennifer; You, Xiaojun; Wakeford, Craig; Sabatella, Guido

2017-01-01

Background Study objectives were to evaluate the Multiple Sclerosis Impact Scale (MSIS-29) and explore an optimized scoring structure based on empirical post-hoc analyses of data from the Phase III ADVANCE clinical trial. Methods ADVANCE MSIS-29 data from six time-points were analyzed in a sample of patients with relapsing–remitting multiple sclerosis (RRMS). Rasch Measurement Theory (RMT) analysis was undertaken to examine three broad areas: sample-to-scale targeting, measurement scale properties, and sample measurement validity. Interpretation of results led to an alternative MSIS-29 scoring structure, further evaluated alongside responsiveness of the original and revised scales at Week 48. Results RMT analysis provided mixed evidence for Physical and Psychological Impact scales that were sub-optimally targeted at the lower functioning end of the scales. Their conceptual basis could also stand to improve based on item fit results. The revised MSIS-29 rescored scales improved but did not resolve the measurement scale properties and targeting of the MSIS-29. In two out of three revised scales, responsiveness analysis indicated strengthened ability to detect change. Conclusion The revised MSIS-29 provides an initial evidence-based improved patient-reported outcome (PRO) instrument for evaluating the impact of MS. Revised scoring improves conceptual clarity and interpretation of scores by refining scale structure to include Symptoms, Psychological Impact, and General Limitations. Clinical trial ADVANCE (ClinicalTrials.gov identifier NCT00906399). PMID:29104758

Topology optimization of finite strain viscoplastic systems under transient loads

DOE PAGES

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

2018-02-08

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Optimization of magnetic field-assisted ultrasonication for the disintegration of waste activated sludge using Box-Behnken design with response surface methodology.

PubMed

Guan, Su; Deng, Feng; Huang, Si-Qi; Liu, Shu-Yang; Ai, Le-Xian; She, Pu-Ying

2017-09-01

This study investigated for the first time the feasibility of using a magnetic field for sludge disintegration. Approximately 41.01% disintegration degree (DD) was reached after 30min at 180mT magnetic field intensity upon separate magnetic field treatment. Protein and polysaccharide contents significantly increased. This test was optimized using a Box-Behnken design (BBD) with response surface methodology (RSM) to fit the multiple equation of the DD. The maximum DD was 43.75% and the protein and polysaccharide contents increased to 56.71 and 119.44mg/L, respectively, when the magnetic field strength was 119.69mT, reaction time was 30.49min, and pH was 9.82 in the optimization experiment. We then analyzed the effects of ultrasound alone. We are the first to combine magnetic field with ultrasound to disintegrate waste-activated sludge (WAS). The optimum effect was obtained with the application of ultrasound alone at 45kHz frequency, with a DD of about 58.09%. By contrast, 62.62% DD was reached in combined magnetic field and ultrasound treatment. This combined test was also optimized using BBD with RSM to fit the multiple equation of DD. The maximum DD of 64.59% was achieved when the magnetic field intensity was 197.87mT, ultrasonic frequency was 42.28kHz, reaction time was 33.96min, and pH was 8.90. These results were consistent with those of particle size and electron microscopy analyses. This research proved that a magnetic field can effectively disintegrate WAS and can be combined with other physical techniques such as ultrasound for optimal results. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of microwave-assisted extraction of protopine and allocryptopine from stems of Macleaya cordata (Willd) R. Br. using response surface methodology.

PubMed

Zhong, Ming; Huang, Ke-Long; Zeng, Jian-Guo; Li, Shuang; She, Jin-Ming; Li, Guiyin; Zhang, Li

2010-07-01

The purpose of the research was to investigate the multiple response optimizations for the extraction of protopine and allocryptopine from the stems of Macleaya cordata (Willd) R. Br. by using microwave-assisted extraction (MAE). A three-level, three-factor Box-Behnken design of response surface methodology was used to develop response model, and desirability function was employed to optimize the effects of main extraction parameters. Three variables, ethanol concentration (20-80%, v/v), extraction temperature (30-70 degrees C) and solvent/solid ratio (10:1 to 30:1, mL/g), were investigated in this study. The results showed that the optimum parameters of MAE were ethanol concentration of 45.2 % (v/v), extraction temperature of 54.7 degrees C and solvent/solid ratio of 20.4:1 (mL/g). Under these conditions, the extraction yields of protopine and allocryptopine were 89.4 and 102.0%, respectively, and the extracta sicca yield was 12.5%. The combination use of response surface methodology, Box-Behnken design and the appropriate desirability function could provide an insight into a lab-scale MAE process, and help to develop procedures for commercial production of active ingredients from medical plants.

A neuro-data envelopment analysis approach for optimization of uncorrelated multiple response problems with smaller the better type controllable factors

NASA Astrophysics Data System (ADS)

Bashiri, Mahdi; Farshbaf-Geranmayeh, Amir; Mogouie, Hamed

2013-11-01

In this paper, a new method is proposed to optimize a multi-response optimization problem based on the Taguchi method for the processes where controllable factors are the smaller-the-better (STB)-type variables and the analyzer desires to find an optimal solution with smaller amount of controllable factors. In such processes, the overall output quality of the product should be maximized while the usage of the process inputs, the controllable factors, should be minimized. Since all possible combinations of factors' levels, are not considered in the Taguchi method, the response values of the possible unpracticed treatments are estimated using the artificial neural network (ANN). The neural network is tuned by the central composite design (CCD) and the genetic algorithm (GA). Then data envelopment analysis (DEA) is applied for determining the efficiency of each treatment. Although the important issue for implementation of DEA is its philosophy, which is maximization of outputs versus minimization of inputs, this important issue has been neglected in previous similar studies in multi-response problems. Finally, the most efficient treatment is determined using the maximin weight model approach. The performance of the proposed method is verified in a plastic molding process. Moreover a sensitivity analysis has been done by an efficiency estimator neural network. The results show efficiency of the proposed approach.

Sexual behavior, risk perception, and HIV transmission can respond to HIV antiviral drugs and vaccines through multiple pathways.

PubMed

Tully, Stephen; Cojocaru, Monica; Bauch, Chris T

2015-10-28

There has been growing use of highly active antiretroviral treatment (HAART) for HIV and significant progress in developing prophylactic HIV vaccines. The simplest theories of counterproductive behavioral responses to such interventions tend to focus on single feedback mechanisms: for instance, HAART optimism makes infection less scary and thus promotes risky sexual behavior. Here, we develop an agent based, age-structured model of HIV transmission, risk perception, and partner selection in a core group to explore behavioral responses to interventions. We find that interventions can activate not one, but several feedback mechanisms that could potentially influence decision-making and HIV prevalence. In the model, HAART increases the attractiveness of unprotected sex, but it also increases perceived risk of infection and, on longer timescales, causes demographic impacts that partially counteract HAART optimism. Both HAART and vaccination usually lead to lower rates of unprotected sex on the whole, but intervention effectiveness depends strongly on whether individuals over- or under-estimate intervention coverage. Age-specific effects cause sexual behavior and HIV prevalence to change in opposite ways in old and young age groups. For complex infections like HIV-where interventions influence transmission, demography, sexual behavior and risk perception-we conclude that evaluations of behavioral responses should consider multiple feedback mechanisms.

Control law synthesis and optimization software for large order aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.; Pototzky, A.; Noll, Thomas

1989-01-01

A flexible aircraft or space structure with active control is typically modeled by a large-order state space system of equations in order to accurately represent the rigid and flexible body modes, unsteady aerodynamic forces, actuator dynamics and gust spectra. The control law of this multi-input/multi-output (MIMO) system is expected to satisfy multiple design requirements on the dynamic loads, responses, actuator deflection and rate limitations, as well as maintain certain stability margins, yet should be simple enough to be implemented on an onboard digital microprocessor. A software package for performing an analog or digital control law synthesis for such a system, using optimal control theory and constrained optimization techniques is described.

Optimization of Milling Parameters Employing Desirability Functions

NASA Astrophysics Data System (ADS)

Ribeiro, J. L. S.; Rubio, J. C. Campos; Abrão, A. M.

2011-01-01

The principal aim of this paper is to investigate the influence of tool material (one cermet and two coated carbide grades), cutting speed and feed rate on the machinability of hardened AISI H13 hot work steel, in order to identify the cutting conditions which lead to optimal performance. A multiple response optimization procedure based on tool life, surface roughness, milling forces and the machining time (required to produce a sample cavity) was employed. The results indicated that the TiCN-TiN coated carbide and cermet presented similar results concerning the global optimum values for cutting speed and feed rate per tooth, outperforming the TiN-TiCN-Al2O3 coated carbide tool.

Design and statistical optimization of glipizide loaded lipospheres using response surface methodology.

PubMed

Shivakumar, Hagalavadi Nanjappa; Patel, Pragnesh Bharat; Desai, Bapusaheb Gangadhar; Ashok, Purnima; Arulmozhi, Sinnathambi

2007-09-01

A 32 factorial design was employed to produce glipizide lipospheres by the emulsification phase separation technique using paraffin wax and stearic acid as retardants. The effect of critical formulation variables, namely levels of paraffin wax (X1) and proportion of stearic acid in the wax (X2) on geometric mean diameter (dg), percent encapsulation efficiency (% EE), release at the end of 12 h (rel12) and time taken for 50% of drug release (t50), were evaluated using the F-test. Mathematical models containing only the significant terms were generated for each response parameter using the multiple linear regression analysis (MLRA) and analysis of variance (ANOVA). Both formulation variables studied exerted a significant influence (p < 0.05) on the response parameters. Numerical optimization using the desirability approach was employed to develop an optimized formulation by setting constraints on the dependent and independent variables. The experimental values of dg, % EE, rel12 and t50 values for the optimized formulation were found to be 57.54 +/- 1.38 mum, 86.28 +/- 1.32%, 77.23 +/- 2.78% and 5.60 +/- 0.32 h, respectively, which were in close agreement with those predicted by the mathematical models. The drug release from lipospheres followed first-order kinetics and was characterized by the Higuchi diffusion model. The optimized liposphere formulation developed was found to produce sustained anti-diabetic activity following oral administration in rats.

Design-of-experiments to Reduce Life-cycle Costs in Combat Aircraft Inlets

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Baust, Henry D.; Agrell, Johan

2003-01-01

It is the purpose of this study to demonstrate the viability and economy of Design- of-Experiments (DOE), to arrive at micro-secondary flow control installation designs that achieve optimal inlet performance for different mission strategies. These statistical design concepts were used to investigate the properties of "low unit strength" micro-effector installation. "Low unit strength" micro-effectors are micro-vanes, set a very low angle-of incidence, with very long chord lengths. They are designed to influence the neat wall inlet flow over an extended streamwise distance. In this study, however, the long chord lengths were replicated by a series of short chord length effectors arranged in series over multiple bands of effectors. In order to properly evaluate the performance differences between the single band extended chord length installation designs and the segmented multiband short chord length designs, both sets of installations must be optimal. Critical to achieving optimal micro-secondary flow control installation designs is the understanding of the factor interactions that occur between the multiple bands of micro-scale vane effectors. These factor interactions are best understood and brought together in an optimal manner through a structured DOE process, or more specifically Response Surface Methods (RSM).

Nanodosimetry-Based Plan Optimization for Particle Therapy

PubMed Central

Schulte, Reinhard W.

2015-01-01

Treatment planning for particle therapy is currently an active field of research due uncertainty in how to modify physical dose in order to create a uniform biological dose response in the target. A novel treatment plan optimization strategy based on measurable nanodosimetric quantities rather than biophysical models is proposed in this work. Simplified proton and carbon treatment plans were simulated in a water phantom to investigate the optimization feasibility. Track structures of the mixed radiation field produced at different depths in the target volume were simulated with Geant4-DNA and nanodosimetric descriptors were calculated. The fluences of the treatment field pencil beams were optimized in order to create a mixed field with equal nanodosimetric descriptors at each of the multiple positions in spread-out particle Bragg peaks. For both proton and carbon ion plans, a uniform spatial distribution of nanodosimetric descriptors could be obtained by optimizing opposing-field but not single-field plans. The results obtained indicate that uniform nanodosimetrically weighted plans, which may also be radiobiologically uniform, can be obtained with this approach. Future investigations need to demonstrate that this approach is also feasible for more complicated beam arrangements and that it leads to biologically uniform response in tumor cells and tissues. PMID:26167202

Exploration of laser-driven electron-multirescattering dynamics in high-order harmonic generation

DOE PAGES

Li, Peng -Cheng; Sheu, Yae -Lin; Jooya, Hossein Z.; ...

2016-09-06

Multiple rescattering processes play an important role in high-order harmonic generation (HHG) in an intense laser field. However, the underlying multi-rescattering dynamics are still largely unexplored. Here we investigate the dynamical origin of multiple rescattering processes in HHG associated with the odd and even number of returning times of the electron to the parent ion. We perform fully ab initio quantum calculations and extend the empirical mode decomposition method to extract the individual multiple scattering contributions in HHG. We find that the tunneling ionization regime is responsible for the odd number times of rescattering and the corresponding short trajectories aremore » dominant. On the other hand, the multiphoton ionization regime is responsible for the even number times of rescattering and the corresponding long trajectories are dominant. Moreover, we discover that the multiphoton- and tunneling-ionization regimes in multiple rescattering processes occur alternatively. Our results uncover the dynamical origin of multiple rescattering processes in HHG for the first time. As a result, it also provides new insight regarding the control of the multiple rescattering processes for the optimal generation of ultrabroad band supercontinuum spectra and the production of single ultrashort attosecond laser pulse.« less

Exploration of laser-driven electron-multirescattering dynamics in high-order harmonic generation

PubMed Central

Li, Peng-Cheng; Sheu, Yae-Lin; Jooya, Hossein Z.; Zhou, Xiao-Xin; Chu, Shih-I

2016-01-01

Multiple rescattering processes play an important role in high-order harmonic generation (HHG) in an intense laser field. However, the underlying multi-rescattering dynamics are still largely unexplored. Here we investigate the dynamical origin of multiple rescattering processes in HHG associated with the odd and even number of returning times of the electron to the parent ion. We perform fully ab initio quantum calculations and extend the empirical mode decomposition method to extract the individual multiple scattering contributions in HHG. We find that the tunneling ionization regime is responsible for the odd number times of rescattering and the corresponding short trajectories are dominant. On the other hand, the multiphoton ionization regime is responsible for the even number times of rescattering and the corresponding long trajectories are dominant. Moreover, we discover that the multiphoton- and tunneling-ionization regimes in multiple rescattering processes occur alternatively. Our results uncover the dynamical origin of multiple rescattering processes in HHG for the first time. It also provides new insight regarding the control of the multiple rescattering processes for the optimal generation of ultrabroad band supercontinuum spectra and the production of single ultrashort attosecond laser pulse. PMID:27596056

Exploration of laser-driven electron-multirescattering dynamics in high-order harmonic generation.

PubMed

Li, Peng-Cheng; Sheu, Yae-Lin; Jooya, Hossein Z; Zhou, Xiao-Xin; Chu, Shih-I

2016-09-06

Multiple rescattering processes play an important role in high-order harmonic generation (HHG) in an intense laser field. However, the underlying multi-rescattering dynamics are still largely unexplored. Here we investigate the dynamical origin of multiple rescattering processes in HHG associated with the odd and even number of returning times of the electron to the parent ion. We perform fully ab initio quantum calculations and extend the empirical mode decomposition method to extract the individual multiple scattering contributions in HHG. We find that the tunneling ionization regime is responsible for the odd number times of rescattering and the corresponding short trajectories are dominant. On the other hand, the multiphoton ionization regime is responsible for the even number times of rescattering and the corresponding long trajectories are dominant. Moreover, we discover that the multiphoton- and tunneling-ionization regimes in multiple rescattering processes occur alternatively. Our results uncover the dynamical origin of multiple rescattering processes in HHG for the first time. It also provides new insight regarding the control of the multiple rescattering processes for the optimal generation of ultrabroad band supercontinuum spectra and the production of single ultrashort attosecond laser pulse.

In silico Evolution of Lysis-Lysogeny Strategies Reproduces Observed Lysogeny Propensities in Temperate Bacteriophages

PubMed Central

Sinha, Vaibhhav; Goyal, Akshit; Svenningsen, Sine L.; Semsey, Szabolcs; Krishna, Sandeep

2017-01-01

Bacteriophages are the most abundant organisms on the planet and both lytic and temperate phages play key roles as shapers of ecosystems and drivers of bacterial evolution. Temperate phages can choose between (i) lysis: exploiting their bacterial hosts by producing multiple phage particles and releasing them by lysing the host cell, and (ii) lysogeny: establishing a potentially mutually beneficial relationship with the host by integrating their chromosome into the host cell's genome. Temperate phages exhibit lysogeny propensities in the curiously narrow range of 5–15%. For some temperate phages, the propensity is further regulated by the multiplicity of infection, such that single infections go predominantly lytic while multiple infections go predominantly lysogenic. We ask whether these observations can be explained by selection pressures in environments where multiple phage variants compete for the same host. Our models of pairwise competition, between phage variants that differ only in their propensity to lysogenize, predict the optimal lysogeny propensity to fall within the experimentally observed range. This prediction is robust to large variation in parameters such as the phage infection rate, burst size, decision rate, as well as bacterial growth rate, and initial phage to bacteria ratio. When we compete phage variants whose lysogeny strategies are allowed to depend upon multiplicity of infection, we find that the optimal strategy is one which switches from full lysis for single infections to full lysogeny for multiple infections. Previous attempts to explain lysogeny propensity have argued for bet-hedging that optimizes the response to fluctuating environmental conditions. Our results suggest that there is an additional selection pressure for lysogeny propensity within phage populations infecting a bacterial host, independent of environmental conditions. PMID:28798729

Multi-response optimization of process parameters for GTAW process in dissimilar welding of Incoloy 800HT and P91 steel by using grey relational analysis

NASA Astrophysics Data System (ADS)

vellaichamy, Lakshmanan; Paulraj, Sathiya

2018-02-01

The dissimilar welding of Incoloy 800HT and P91 steel using Gas Tungsten arc welding process (GTAW) This material is being used in the Nuclear Power Plant and Aerospace Industry based application because Incoloy 800HT possess good corrosion and oxidation resistance and P91 possess high temperature strength and creep resistance. This work discusses on multi-objective optimization using gray relational analysis (GRA) using 9CrMoV-N filler materials. The experiment conducted L9 orthogonal array. The input parameter are current, voltage, speed. The output response are Tensile strength, Hardness and Toughness. To optimize the input parameter and multiple output variable by using GRA. The optimal parameter is combination was determined as A2B1C1 so given input parameter welding current at 120 A, voltage at 16 V and welding speed at 0.94 mm/s. The output of the mechanical properties for best and least grey relational grade was validated by the metallurgical characteristics.

Durable treatment response of relapsing CNS plasmacytoma using intrathecal chemotherapy, radiotherapy, and Daratumumab.

PubMed

Elhassadi, Ezzat; Murphy, Maurice; Hacking, Dayle; Farrell, Michael

2018-04-01

CNS myelomatous involvement is a rare complication of multiple myeloma with dismal outcome. This disease's optimal treatment is unclear. Combined approach of systemic therapy, radiotherapy, and intrathecal injections chemotherapy should be considered and autologous stem cell transplant consolidation is offered to eligible patients. The role of Daratumumab in this disease deserves further evaluation.

Parallel updating and weighting of multiple spatial maps for visual stability during whole body motion

PubMed Central

Medendorp, W. P.

2015-01-01

It is known that the brain uses multiple reference frames to code spatial information, including eye-centered and body-centered frames. When we move our body in space, these internal representations are no longer in register with external space, unless they are actively updated. Whether the brain updates multiple spatial representations in parallel, or whether it restricts its updating mechanisms to a single reference frame from which other representations are constructed, remains an open question. We developed an optimal integration model to simulate the updating of visual space across body motion in multiple or single reference frames. To test this model, we designed an experiment in which participants had to remember the location of a briefly presented target while being translated sideways. The behavioral responses were in agreement with a model that uses a combination of eye- and body-centered representations, weighted according to the reliability in which the target location is stored and updated in each reference frame. Our findings suggest that the brain simultaneously updates multiple spatial representations across body motion. Because both representations are kept in sync, they can be optimally combined to provide a more precise estimate of visual locations in space than based on single-frame updating mechanisms. PMID:26490289

A clinical study of electrophysiological correlates of behavioural comfort levels in cochlear implantees.

PubMed

Raghunandhan, S; Ravikumar, A; Kameswaran, Mohan; Mandke, Kalyani; Ranjith, R

2014-05-01

Indications for cochlear implantation have expanded today to include very young children and those with syndromes/multiple handicaps. Programming the implant based on behavioural responses may be tedious for audiologists in such cases, wherein matching an effective Measurable Auditory Percept (MAP) and appropriate MAP becomes the key issue in the habilitation program. In 'Difficult to MAP' scenarios, objective measures become paramount to predict optimal current levels to be set in the MAP. We aimed to (a) study the trends in multi-modal electrophysiological tests and behavioural responses sequentially over the first year of implant use; (b) generate normative data from the above; (c) correlate the multi-modal electrophysiological thresholds levels with behavioural comfort levels; and (d) create predictive formulae for deriving optimal comfort levels (if unknown), using linear and multiple regression analysis. This prospective study included 10 profoundly hearing impaired children aged between 2 and 7 years with normal inner ear anatomy and no additional handicaps. They received the Advanced Bionics HiRes 90 K Implant with Harmony Speech processor and used HiRes-P with Fidelity 120 strategy. They underwent, impedance telemetry, neural response imaging, electrically evoked stapedial response telemetry (ESRT), and electrically evoked auditory brainstem response (EABR) tests at 1, 4, 8, and 12 months of implant use, in conjunction with behavioural mapping. Trends in electrophysiological and behavioural responses were analyzed using paired t-test. By Karl Pearson's correlation method, electrode-wise correlations were derived for neural response imaging (NRI) thresholds versus most comfortable level (M-levels) and offset based (apical, mid-array, and basal array) correlations for EABR and ESRT thresholds versus M-levels were calculated over time. These were used to derive predictive formulae by linear and multiple regression analysis. Such statistically predicted M-levels were compared with the behaviourally recorded M-levels among the cohort, using Cronbach's alpha reliability test method for confirming the efficacy of this method. NRI, ESRT, and EABR thresholds showed statistically significant positive correlations with behavioural M-levels, which improved with implant use over time. These correlations were used to derive predicted M-levels using regression analysis. On an average, predicted M-levels were found to be statistically reliable and they were a fair match to the actual behavioural M-levels. When applied in clinical practice, the predicted values were found to be useful for programming members of the study group. However, individuals showed considerable deviations in behavioural M-levels, above and below the electrophysiologically predicted values, due to various factors. While the current method appears helpful as a reference to predict initial maps in 'difficult to Map' subjects, it is recommended that behavioural measures are mandatory to further optimize the maps for these individuals. The study explores the trends, correlations and individual variabilities that occur between electrophysiological tests and behavioural responses, recorded over time among a cohort of cochlear implantees. The statistical method shown may be used as a guideline to predict optimal behavioural levels in difficult situations among future implantees, bearing in mind that optimal M-levels for individuals can vary from predicted values. In 'Difficult to MAP' scenarios, following a protocol of sequential behavioural programming, in conjunction with electrophysiological correlates will provide the best outcomes.

Automated design and optimization of flexible booster autopilots via linear programming, volume 1

NASA Technical Reports Server (NTRS)

Hauser, F. D.

1972-01-01

A nonlinear programming technique was developed for the automated design and optimization of autopilots for large flexible launch vehicles. This technique, which resulted in the COEBRA program, uses the iterative application of linear programming. The method deals directly with the three main requirements of booster autopilot design: to provide (1) good response to guidance commands; (2) response to external disturbances (e.g. wind) to minimize structural bending moment loads and trajectory dispersions; and (3) stability with specified tolerances on the vehicle and flight control system parameters. The method is applicable to very high order systems (30th and greater per flight condition). Examples are provided that demonstrate the successful application of the employed algorithm to the design of autopilots for both single and multiple flight conditions.

Optimal performance of generalized heat engines with finite-size baths of arbitrary multiple conserved quantities beyond independent-and-identical-distribution scaling

NASA Astrophysics Data System (ADS)

Ito, Kosuke; Hayashi, Masahito

2018-01-01

In quantum thermodynamics, effects of finiteness of the baths have been less considered. In particular, there is no general theory which focuses on finiteness of the baths of multiple conserved quantities. Then, we investigate how the optimal performance of generalized heat engines with multiple conserved quantities alters in response to the size of the baths. In the context of general theories of quantum thermodynamics, the size of the baths has been given in terms of the number of identical copies of a system, which does not cover even such a natural scaling as the volume. In consideration of the asymptotic extensivity, we deal with a generic scaling of the baths to naturally include the volume scaling. Based on it, we derive a bound for the performance of generalized heat engines reflecting finite-size effects of the baths, which we call fine-grained generalized Carnot bound. We also construct a protocol to achieve the optimal performance of the engine given by this bound. Finally, applying the obtained general theory, we deal with simple examples of generalized heat engines. As for an example of non-independent-and-identical-distribution scaling and multiple conserved quantities, we investigate a heat engine with two baths composed of an ideal gas exchanging particles, where the volume scaling is applied. The result implies that the mass of the particle explicitly affects the performance of this engine with finite-size baths.

Optimization by response surface methodology of lutein recovery from paprika leaves using accelerated solvent extraction.

PubMed

Kang, Jae-Hyun; Kim, Suna; Moon, BoKyung

2016-08-15

In this study, we used response surface methodology (RSM) to optimize the extraction conditions for recovering lutein from paprika leaves using accelerated solvent extraction (ASE). The lutein content was quantitatively analyzed using a UPLC equipped with a BEH C18 column. A central composite design (CCD) was employed for experimental design to obtain the optimized combination of extraction temperature (°C), static time (min), and solvent (EtOH, %). The experimental data obtained from a twenty sample set were fitted to a second-order polynomial equation using multiple regression analysis. The adjusted coefficient of determination (R(2)) for the lutein extraction model was 0.9518, and the probability value (p=0.0000) demonstrated a high significance for the regression model. The optimum extraction conditions for lutein were temperature: 93.26°C, static time: 5 min, and solvent: 79.63% EtOH. Under these conditions, the predicted extraction yield of lutein was 232.60 μg/g. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E.; Parvin, Bahram

2009-06-09

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time: quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E [Martinez, CA; Parvin, Bahram [Mill Valley, CA

2011-05-24

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time; quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

Visual-servoing optical microscopy

DOEpatents

Callahan, Daniel E; Parvin, Bahram

2013-10-01

The present invention provides methods and devices for the knowledge-based discovery and optimization of differences between cell types. In particular, the present invention provides visual servoing optical microscopy, as well as analysis methods. The present invention provides means for the close monitoring of hundreds of individual, living cells over time; quantification of dynamic physiological responses in multiple channels; real-time digital image segmentation and analysis; intelligent, repetitive computer-applied cell stress and cell stimulation; and the ability to return to the same field of cells for long-term studies and observation. The present invention further provides means to optimize culture conditions for specific subpopulations of cells.

Extensions of D-optimal Minimal Designs for Symmetric Mixture Models.

PubMed

Li, Yanyan; Raghavarao, Damaraju; Chervoneva, Inna

2017-01-01

The purpose of mixture experiments is to explore the optimum blends of mixture components, which will provide desirable response characteristics in finished products. D-optimal minimal designs have been considered for a variety of mixture models, including Scheffé's linear, quadratic, and cubic models. Usually, these D-optimal designs are minimally supported since they have just as many design points as the number of parameters. Thus, they lack the degrees of freedom to perform the Lack of Fit tests. Also, the majority of the design points in D-optimal minimal designs are on the boundary: vertices, edges, or faces of the design simplex. Also a new strategy for adding multiple interior points for symmetric mixture models is proposed. We compare the proposed designs with Cornell (1986) two ten-point designs for the Lack of Fit test by simulations.

Optimization of groundwater artificial recharge systems using a genetic algorithm: a case study in Beijing, China

NASA Astrophysics Data System (ADS)

Hao, Qichen; Shao, Jingli; Cui, Yali; Zhang, Qiulan; Huang, Linxian

2018-05-01

An optimization approach is used for the operation of groundwater artificial recharge systems in an alluvial fan in Beijing, China. The optimization model incorporates a transient groundwater flow model, which allows for simulation of the groundwater response to artificial recharge. The facilities' operation with regard to recharge rates is formulated as a nonlinear programming problem to maximize the volume of surface water recharged into the aquifers under specific constraints. This optimization problem is solved by the parallel genetic algorithm (PGA) based on OpenMP, which could substantially reduce the computation time. To solve the PGA with constraints, the multiplicative penalty method is applied. In addition, the facilities' locations are implicitly determined on the basis of the results of the recharge-rate optimizations. Two scenarios are optimized and the optimal results indicate that the amount of water recharged into the aquifers will increase without exceeding the upper limits of the groundwater levels. Optimal operation of this artificial recharge system can also contribute to the more effective recovery of the groundwater storage capacity.

Study on validation method for femur finite element model under multiple loading conditions

NASA Astrophysics Data System (ADS)

Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu

2018-03-01

Acquisition of accurate and reliable constitutive parameters related to bio-tissue materials was beneficial to improve biological fidelity of a Finite Element (FE) model and predict impact damages more effectively. In this paper, a femur FE model was established under multiple loading conditions with diverse impact positions. Then, based on sequential response surface method and genetic algorithms, the material parameters identification was transformed to a multi-response optimization problem. Finally, the simulation results successfully coincided with force-displacement curves obtained by numerous experiments. Thus, computational accuracy and efficiency of the entire inverse calculation process were enhanced. This method was able to effectively reduce the computation time in the inverse process of material parameters. Meanwhile, the material parameters obtained by the proposed method achieved higher accuracy.

A robust optimization model for distribution and evacuation in the disaster response phase

NASA Astrophysics Data System (ADS)

Fereiduni, Meysam; Shahanaghi, Kamran

2017-03-01

Natural disasters, such as earthquakes, affect thousands of people and can cause enormous financial loss. Therefore, an efficient response immediately following a natural disaster is vital to minimize the aforementioned negative effects. This research paper presents a network design model for humanitarian logistics which will assist in location and allocation decisions for multiple disaster periods. At first, a single-objective optimization model is presented that addresses the response phase of disaster management. This model will help the decision makers to make the most optimal choices in regard to location, allocation, and evacuation simultaneously. The proposed model also considers emergency tents as temporary medical centers. To cope with the uncertainty and dynamic nature of disasters, and their consequences, our multi-period robust model considers the values of critical input data in a set of various scenarios. Second, because of probable disruption in the distribution infrastructure (such as bridges), the Monte Carlo simulation is used for generating related random numbers and different scenarios; the p-robust approach is utilized to formulate the new network. The p-robust approach can predict possible damages along pathways and among relief bases. We render a case study of our robust optimization approach for Tehran's plausible earthquake in region 1. Sensitivity analysis' experiments are proposed to explore the effects of various problem parameters. These experiments will give managerial insights and can guide DMs under a variety of conditions. Then, the performances of the "robust optimization" approach and the "p-robust optimization" approach are evaluated. Intriguing results and practical insights are demonstrated by our analysis on this comparison.

A Bayesian Hybrid Adaptive Randomisation Design for Clinical Trials with Survival Outcomes.

PubMed

Moatti, M; Chevret, S; Zohar, S; Rosenberger, W F

2016-01-01

Response-adaptive randomisation designs have been proposed to improve the efficiency of phase III randomised clinical trials and improve the outcomes of the clinical trial population. In the setting of failure time outcomes, Zhang and Rosenberger (2007) developed a response-adaptive randomisation approach that targets an optimal allocation, based on a fixed sample size. The aim of this research is to propose a response-adaptive randomisation procedure for survival trials with an interim monitoring plan, based on the following optimal criterion: for fixed variance of the estimated log hazard ratio, what allocation minimizes the expected hazard of failure? We demonstrate the utility of the design by redesigning a clinical trial on multiple myeloma. To handle continuous monitoring of data, we propose a Bayesian response-adaptive randomisation procedure, where the log hazard ratio is the effect measure of interest. Combining the prior with the normal likelihood, the mean posterior estimate of the log hazard ratio allows derivation of the optimal target allocation. We perform a simulation study to assess and compare the performance of this proposed Bayesian hybrid adaptive design to those of fixed, sequential or adaptive - either frequentist or fully Bayesian - designs. Non informative normal priors of the log hazard ratio were used, as well as mixture of enthusiastic and skeptical priors. Stopping rules based on the posterior distribution of the log hazard ratio were computed. The method is then illustrated by redesigning a phase III randomised clinical trial of chemotherapy in patients with multiple myeloma, with mixture of normal priors elicited from experts. As expected, there was a reduction in the proportion of observed deaths in the adaptive vs. non-adaptive designs; this reduction was maximized using a Bayes mixture prior, with no clear-cut improvement by using a fully Bayesian procedure. The use of stopping rules allows a slight decrease in the observed proportion of deaths under the alternate hypothesis compared with the adaptive designs with no stopping rules. Such Bayesian hybrid adaptive survival trials may be promising alternatives to traditional designs, reducing the duration of survival trials, as well as optimizing the ethical concerns for patients enrolled in the trial.

Formulation Optimization of Human Insulin Loaded Microspheres for Controlled Oral Delivery Using Response Surface Methodology.

PubMed

Agrawal, Gauravkuma; Wakte, Pravin; Shelke, Santosh

2017-01-01

The objectives of the present investigation were to prepare recombinant human insulin entrapped Eudragit-S100 microspheres containing protease inhibitors and to precisely analyze the outcome of different formulation variables on the microspheres properties using a response surface methodology to develop an optimized formulation with desirable features. A central composite design was employed to produce microspheres of therapeutic protein by w/o/w multiple emulsion solvent evaporation technique using Eudragit S-100 as coating material and polyvinyl alcohol as a stabilizer. The effect of formulation variables (independent variables) that is levels of Eudragit S-100 (X1), therapeutic protein (X2), volumes of inner aqueous phase (X3) and external aqueous phase (X4) on dependant variables, that are encapsulation efficiency (Y1), drug release at pH 1.2 after 2 h (Y2) and drug release at pH 7.4 after of 2 h (Y3) were evaluated. The significant terms in the mathematical models were generated for each response parameter using multiple linear regression analysis and analysis of variance. All the formulation variables except the volume of external aqueous phase (X4) exerted a significant effect (P <0.05) on drug encapsulation efficiency (Y1) whereas first two variables, namely the levels of Eudragit S-100 (X1) and therapeutic protein (X2) materialized as the determining factors which significantly influenced drug release at pH 1.2 after 2 h (Y2) and drug release at pH 7.4 after of 2 h (Y3). The formulation was numerically optimized by framing the constraints on the dependent and independent variables using the desirability approach. The experimental values for Y1 and Y2 of optimized formulation were found to be 77.65% and 3.64%, respectively which were quite closer to results suggested by software. The results recorded indicate that the recombinant human insulin loaded Eudragit S-100 microspheres containing aprotinin have the benefits of higher loading efficiency, pH responsive and prolonged release characteristics, which may help to carry insulin to the optimum site of absorption. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Rational combinations of immunotherapy for pancreatic ductal adenocarcinoma.

PubMed

Blair, Alex B; Zheng, Lei

2017-06-01

The complex interaction between the immune system, the tumor and the microenvironment in pancreatic ductal adenocarcinoma (PDA) leads to the resistance of PDA to immunotherapy. To overcome this resistance, combination immunotherapy is being proposed. However, rational combinations that target multiple aspects of the complex anti-tumor immune response are warranted. Novel clinical trials will investigate and optimize the combination immunotherapy for PDA.

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

PubMed

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

2009-09-23

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

Multi-objective optimal control of vibratory energy harvesting systems

NASA Astrophysics Data System (ADS)

Scruggs, J. T.

2008-03-01

This paper presents a new approach, based on H II optimal control theory, for the maximization of power generation in energy harvesting systems. The theory determines the optimal harvested power attainable through the use of power electronics to effect linear feedback control of transducer current. In contrast to most of the prior work in this area, which has assumed harmonic response, the theory proposed here applies to stochastically-excited systems in broadband response, and can be used to harvest power simultaneously from multiple significant vibratory modes. It is also applicable to coupled networks of many transducers. The theory accounts for the impact of energy harvesting on the dynamics of the vibrating system in which the transducers are embedded. It also accounts for resistive and semiconductor dissipation in the power-electronic network interfacing the transducers with energy storage. Thus, losses in the electronics are addressed in the formulation of the optimal control law. Finally, the H II-optimal control formulation of the problem naturally allows for harvested power to be systematically balanced against other response objectives. Here, this is illustrated by showing how the harvesting objective can be maximized, subject to the constraint that the transducer voltages be maintained below that of the power-electronic bus; a condition which is required for the power-electronic control system to be fully operational. Although the theory is applicable across a broad range of applications, it is presented in the context of a piezoelectric bimorph example.

Avian brood parasitism: information use and variation in egg-rejection behavior.

PubMed

Svennungsen, Thomas Owens; Holen, Øistein Haugsten

2010-05-01

Hosts of avian brood parasites often vary in their response to parasitized clutches: they may eject one or several eggs, desert the nest, or accept all the eggs. Focusing on hosts exposed to single-egg parasitism by an evicting brood parasite, we construct an optimality model that includes all these behavioral options and use it to explore variation in rejection behavior. We particularly consider the influence of egg mimicry and external cues (observations of adult parasites near the nest) on optimal choice of rejection behavior. We find that several rejection responses will be present in a host population under a wide range of conditions. Ejection of multiple eggs tends to be adaptive when egg mimicry is fairly accurate, external cues provide reliable information of the risk of parasitism, and the expected success of renesting is low. If the perceived risk of parasitism is high, ejection of one or a few eggs may be the optimal rejection response even in cases in which hosts cannot discriminate between eggs. This may have consequences for the long-term outcome of the coevolutionary chase between hosts and parasites. We propose an alternative evolutionary pathway by which egg ejection may first arise as a defense against brood parasitism.

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

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

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

Response threshold variance as a basis of collective rationality

PubMed Central

Yamamoto, Tatsuhiro

2017-01-01

Determining the optimal choice among multiple options is necessary in various situations, and the collective rationality of groups has recently become a major topic of interest. Social insects are thought to make such optimal choices by collecting individuals' responses relating to an option's value (=a quality-graded response). However, this behaviour cannot explain the collective rationality of brains because neurons can make only ‘yes/no’ responses on the basis of the response threshold. Here, we elucidate the basic mechanism underlying the collective rationality of such simple units and show that an ant species uses this mechanism. A larger number of units respond ‘yes’ to the best option available to a collective decision-maker using only the yes/no mechanism; thus, the best option is always selected by majority decision. Colonies of the ant Myrmica kotokui preferred the better option in a binary choice experiment. The preference of a colony was demonstrated by the workers, which exhibited variable thresholds between two options' qualities. Our results demonstrate how a collective decision-maker comprising simple yes/no judgement units achieves collective rationality without using quality-graded responses. This mechanism has broad applicability to collective decision-making in brain neurons, swarm robotics and human societies. PMID:28484636

Response threshold variance as a basis of collective rationality.

PubMed

Yamamoto, Tatsuhiro; Hasegawa, Eisuke

2017-04-01

Determining the optimal choice among multiple options is necessary in various situations, and the collective rationality of groups has recently become a major topic of interest. Social insects are thought to make such optimal choices by collecting individuals' responses relating to an option's value (=a quality-graded response). However, this behaviour cannot explain the collective rationality of brains because neurons can make only 'yes/no' responses on the basis of the response threshold. Here, we elucidate the basic mechanism underlying the collective rationality of such simple units and show that an ant species uses this mechanism. A larger number of units respond 'yes' to the best option available to a collective decision-maker using only the yes/no mechanism; thus, the best option is always selected by majority decision. Colonies of the ant Myrmica kotokui preferred the better option in a binary choice experiment. The preference of a colony was demonstrated by the workers, which exhibited variable thresholds between two options' qualities. Our results demonstrate how a collective decision-maker comprising simple yes/no judgement units achieves collective rationality without using quality-graded responses. This mechanism has broad applicability to collective decision-making in brain neurons, swarm robotics and human societies.

A Decision Support System for Solving Multiple Criteria Optimization Problems

ERIC Educational Resources Information Center

Filatovas, Ernestas; Kurasova, Olga

2011-01-01

In this paper, multiple criteria optimization has been investigated. A new decision support system (DSS) has been developed for interactive solving of multiple criteria optimization problems (MOPs). The weighted-sum (WS) approach is implemented to solve the MOPs. The MOPs are solved by selecting different weight coefficient values for the criteria…

HIV epidemic control-a model for optimal allocation of prevention and treatment resources.

PubMed

Alistar, Sabina S; Long, Elisa F; Brandeau, Margaret L; Beck, Eduard J

2014-06-01

With 33 million people living with human immunodeficiency virus (HIV) worldwide and 2.7 million new infections occurring annually, additional HIV prevention and treatment efforts are urgently needed. However, available resources for HIV control are limited and must be used efficiently to minimize the future spread of the epidemic. We develop a model to determine the appropriate resource allocation between expanded HIV prevention and treatment services. We create an epidemic model that incorporates multiple key populations with different transmission modes, as well as production functions that relate investment in prevention and treatment programs to changes in transmission and treatment rates. The goal is to allocate resources to minimize R 0, the reproductive rate of infection. We first develop a single-population model and determine the optimal resource allocation between HIV prevention and treatment. We extend the analysis to multiple independent populations, with resource allocation among interventions and populations. We then include the effects of HIV transmission between key populations. We apply our model to examine HIV epidemic control in two different settings, Uganda and Russia. As part of these applications, we develop a novel approach for estimating empirical HIV program production functions. Our study provides insights into the important question of resource allocation for a country's optimal response to its HIV epidemic and provides a practical approach for decision makers. Better decisions about allocating limited HIV resources can improve response to the epidemic and increase access to HIV prevention and treatment services for millions of people worldwide.

Optimization of physico-chemical properties of gelatin extracted from fish skin of rainbow trout (Onchorhynchus mykiss).

PubMed

Tabarestani, H Shahiri; Maghsoudlou, Y; Motamedzadegan, A; Mahoonak, A R Sadeghi

2010-08-01

Physico-chemical properties of gelatin extracted from rainbow trout (Onchorhynchus mykiss) skin were optimized using response surface methodology (RSM). Central rotatable composite design was applied to study the combined effects of NaOH concentration (0.01-0.21 N), acetic acid concentration (0.01-0.21 N) and pre-treatment time (1-3h) on yield, molecular weight distribution, gel strength, viscosity and melting point of gelatin. Regression models were developed to predict the variables. Predict values of multiple response at optimal condition were that yield=9.36%, alpha(1)/alpha(2) chain ratio=1.76, beta chain percent=32.81, gel strength=459 g, viscosity=3.2 mPa s and melting point=20.4 degrees C. The optimal condition was obtained using 0.19 N NaOH and 0.121 N acetic acid for 3h. The results showed that the concentration of H(+) during pre-treatment had significant effect on molecular weight distribution, melting point and gel strength. The concentration of OH(-) had significant effect on viscosity and for extraction yield, pretreatment time was the critical factor. (c) 2010 Elsevier Ltd. All rights reserved.

Multi-Response Optimization of Resin Finishing by Using a Taguchi-Based Grey Relational Analysis

PubMed Central

Shafiq, Faizan; Sarwar, Zahid; Jilani, Muhammad Munib; Cai, Yingjie

2018-01-01

In this study, the influence and optimization of the factors of a non-formaldehyde resin finishing process on cotton fabric using a Taguchi-based grey relational analysis were experimentally investigated. An L27 orthogonal array was selected for five parameters and three levels by applying Taguchi’s design of experiments. The Taguchi technique was coupled with a grey relational analysis to obtain a grey relational grade for evaluating multiple responses, i.e., crease recovery angle (CRA), tearing strength (TE), and whiteness index (WI). The optimum parameters (values) for resin finishing were the resin concentration (80 g·L−1), the polyethylene softener (40 g·L−1), the catalyst (25 g·L−1), the curing temperature (140 °C), and the curing time (2 min). The goodness-of-fit of the data was validated by an analysis of variance (ANOVA). The optimized sample was characterized by Fourier-transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), and scanning electron microscope (SEM) to better understand the structural details of the resin finishing process. The results showed an improved thermal stability and confirmed the presence of well deposited of resin on the optimized fabric surface. PMID:29543724

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks.

PubMed

Flassig, R J; Sundmacher, K

2012-12-01

Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. flassig@mpi-magdeburg.mpg.de Supplementary data are are available at Bioinformatics online.

Data-optimized source modeling with the Backwards Liouville Test–Kinetic method

DOE PAGES

Woodroffe, J. R.; Brito, T. V.; Jordanova, V. K.; ...

2017-09-14

In the standard practice of neutron multiplicity counting , the first three sampled factorial moments of the event triggered neutron count distribution were used to quantify the three main neutron source terms: the spontaneous fissile material effective mass, the relative (α,n) production and the induced fission source responsible for multiplication. Our study compares three methods to quantify the statistical uncertainty of the estimated mass: the bootstrap method, propagation of variance through moments, and statistical analysis of cycle data method. Each of the three methods was implemented on a set of four different NMC measurements, held at the JRC-laboratory in Ispra,more » Italy, sampling four different Pu samples in a standard Plutonium Scrap Multiplicity Counter (PSMC) well counter.« less

Optimization of hybrid laser - TIG welding of 316LN steel using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Ragavendran, M.; Chandrasekhar, N.; Ravikumar, R.; Saxena, Rajesh; Vasudevan, M.; Bhaduri, A. K.

2017-07-01

In the present study, the hybrid laser - TIG welding parameters for welding of 316LN austenitic stainless steel have been investigated by combining a pulsed laser beam with a TIG welding heat source at the weld pool. Laser power, pulse frequency, pulse duration, TIG current were presumed as the welding process parameters whereas weld bead width, weld cross-sectional area and depth of penetration (DOP) were considered as the process responses. Central composite design was used to complete the design matrix and welding experiments were conducted based on the design matrix. Weld bead measurements were then carried out to generate the dataset. Multiple regression models correlating the process parameters with the responses have been developed. The accuracy of the models were found to be good. Then, the desirability approach optimization technique was employed for determining the optimum process parameters to obtain the desired weld bead profile. Validation experiments were then carried out from the determined optimum process parameters. There was good agreement between the predicted and measured values.

Extending data worth methods to select multiple observations targeting specific hydrological predictions of interest

NASA Astrophysics Data System (ADS)

Vilhelmsen, Troels N.; Ferré, Ty P. A.

2016-04-01

Hydrological models are often developed to forecasting future behavior in response due to natural or human induced changes in stresses affecting hydrologic systems. Commonly, these models are conceptualized and calibrated based on existing data/information about the hydrological conditions. However, most hydrologic systems lack sufficient data to constrain models with adequate certainty to support robust decision making. Therefore, a key element of a hydrologic study is the selection of additional data to improve model performance. Given the nature of hydrologic investigations, it is not practical to select data sequentially, i.e. to choose the next observation, collect it, refine the model, and then repeat the process. Rather, for timing and financial reasons, measurement campaigns include multiple wells or sampling points. There is a growing body of literature aimed at defining the expected data worth based on existing models. However, these are almost all limited to identifying single additional observations. In this study, we present a methodology for simultaneously selecting multiple potential new observations based on their expected ability to reduce the uncertainty of the forecasts of interest. This methodology is based on linear estimates of the predictive uncertainty, and it can be used to determine the optimal combinations of measurements (location and number) established to reduce the uncertainty of multiple predictions. The outcome of the analysis is an estimate of the optimal sampling locations; the optimal number of samples; as well as a probability map showing the locations within the investigated area that are most likely to provide useful information about the forecasting of interest.

Research pressure instrumentation for NASA Space Shuttle main engine, modification no. 5

NASA Technical Reports Server (NTRS)

Anderson, P. J.; Nussbaum, P.; Gustafson, G.

1984-01-01

The advantages of silicon piezoresistive strain sensing technology are being used to achieve the objectives of state of the art pressure sensors for SSME applications. The integration of multiple functions on a single chip is the key attribute being exploited. Progress is reported in transducer packaging and materials; silicon resistor characterization at cryogenic temperatures; chip mounting; and frequency response optimization.

Uniformed Services University of the Health Sciences Journal 2003 Edition

DTIC Science & Technology

2004-08-18

practice nurses for the MHS. The Joint Meritorious Unit Award was presented to Doctor Zimble in 2000 and officially recognized the multiple products ...of the University, optimize productivity , promote a sense of family and community, while emphasizing flexibility in response...Alumni and their Achievements, Five Other OSD- Recognized, Significant Areas of Support and Products Are Provided by USU for the MHS ...... 48-49

Wound Healing in Mac-1 Deficient Mice

DTIC Science & Technology

2017-05-01

36. Rosenkranz AR, Coxon A, Maurer M, Gurish MF, Austen KF, Friend DS, Galli SJ, Mayadas TN. Impaired mast cell development and innate immunity in Mac...genetically deficient mice. 3 INTRODUCTION Wound healing is a complex yet well-regulated process in which multiple resident cells ...recruited inflammatory cells , and stem cells interact to create an environment that supports the healing process. An optimal inflammatory response is a

Response surface methodology for evaluation and optimization of process parameter and antioxidant capacity of rice flour modified by enzymatic extrusion.

PubMed

Xu, Enbo; Pan, Xiaowei; Wu, Zhengzong; Long, Jie; Li, Jingpeng; Xu, Xueming; Jin, Zhengyu; Jiao, Aiquan

2016-12-01

For the purpose of investigating the effect of enzyme concentration (EC), barrel temperature (BT), moisture content (MC), and screw speed (SS) on processing parameters (product temperature, die pressure and special mechanical energy (SME)) and product responses (extent of gelatinization (GE), retention rate of total phenolic content (TPC-RR)), rice flour extruded with thermostable α-amylase was analyzed by response surface methodology. Stepwise regression models were computed to generate response surface and contour plots, revealing that both TPC-RR and GE increased as increasing MC while expressed different sensitivities to BT during enzymatic extrusion. Phenolics preservation was benefited from low SME. According to multiple-factor optimization, the conditions required to obtain the target SME (10kJ/kg), GE (100%) and TPC-RR (85%) were: EC=1.37‰, BT=93.01°C, MC=44.30%, and SS=171.66rpm, with the actual values (9.49kJ/kg, 99.96% and 87.10%, respectively) showing a good fit to the predicted values. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Rhythmic entrainment source separation: Optimizing analyses of neural responses to rhythmic sensory stimulation.

PubMed

Cohen, Michael X; Gulbinaite, Rasa

2017-02-15

Steady-state evoked potentials (SSEPs) are rhythmic brain responses to rhythmic sensory stimulation, and are often used to study perceptual and attentional processes. We present a data analysis method for maximizing the signal-to-noise ratio of the narrow-band steady-state response in the frequency and time-frequency domains. The method, termed rhythmic entrainment source separation (RESS), is based on denoising source separation approaches that take advantage of the simultaneous but differential projection of neural activity to multiple electrodes or sensors. Our approach is a combination and extension of existing multivariate source separation methods. We demonstrate that RESS performs well on both simulated and empirical data, and outperforms conventional SSEP analysis methods based on selecting electrodes with the strongest SSEP response, as well as several other linear spatial filters. We also discuss the potential confound of overfitting, whereby the filter captures noise in absence of a signal. Matlab scripts are available to replicate and extend our simulations and methods. We conclude with some practical advice for optimizing SSEP data analyses and interpreting the results. Copyright © 2016 Elsevier Inc. All rights reserved.

Simulation-based analysis of performance parameters of microstrip antennas with criss-cross metamaterial-based artificial substrate

NASA Astrophysics Data System (ADS)

Inamdar, Kirti; Kosta, Y. P.; Patnaik, S.

2014-10-01

In this paper, we present the design of a metamaterial-based microstrip patch antenna, optimized for bandwidth and multiple frequency operations. A criss-cross structure has been proposed, this shape has been inspired from the famous Jerusalem cross. The theory and design formulas to calculate various parameters of the proposed antenna have been presented. Design starts with the analysis of the proposed unit cell structure, and validating the response using software- HFSS Version 13, to obtain negative response of ε and μ- metamaterial. Following this, a metamaterial-based-microstrip-patch-antenna is designed. A detailed comparative study is conducted exploring the response of the designed patch made of metamaterial and that of the conventional patch. Finally, antenna parameters such as gain, bandwidth, radiation pattern, and multiple frequency responses are investigated and optimised for the same and present in table and response graphs. It is also observed that the physical dimension of the metamaterial-based patch antenna is smaller compared to its conventional counterpart operating at the same fundamental frequency. The challenging part was to develop metamaterial based on some signature structures and techniques that would offer advantage in terms of BW and multiple frequency operation, which is demonstrated in this paper. The unique shape proposed in this paper gives improvement in bandwidth without reducing the gain of the antenna.

Hallmarks of response to immune checkpoint blockade

PubMed Central

Cogdill, Alexandria P; Andrews, Miles C; Wargo, Jennifer A

2017-01-01

Unprecedented advances have been made in the treatment of cancer through the use of immune checkpoint blockade, with approval of several checkpoint blockade regimens spanning multiple cancer types. However, responses to this form of therapy are not universal, and insights are clearly needed to identify optimal biomarkers of response and to combat mechanisms of therapeutic resistance. A working knowledge of the hallmarks of cancer yields insight into responses to immune checkpoint blockade, although the focus of this is rather tumour-centric and additional factors are pertinent, including host immunity and environmental influences. Herein, we describe the foundation for pillars and hallmarks of response to immune checkpoint blockade, with a discussion of their relevance to immune monitoring and mechanisms of resistance. Evolution of this understanding will ultimately help guide treatment strategies to enhance therapeutic responses. PMID:28524159

Aerodynamic Design Using Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan; Madavan, Nateri K.

2003-01-01

The design of aerodynamic components of aircraft, such as wings or engines, involves a process of obtaining the most optimal component shape that can deliver the desired level of component performance, subject to various constraints, e.g., total weight or cost, that the component must satisfy. Aerodynamic design can thus be formulated as an optimization problem that involves the minimization of an objective function subject to constraints. A new aerodynamic design optimization procedure based on neural networks and response surface methodology (RSM) incorporates the advantages of both traditional RSM and neural networks. The procedure uses a strategy, denoted parameter-based partitioning of the design space, to construct a sequence of response surfaces based on both neural networks and polynomial fits to traverse the design space in search of the optimal solution. Some desirable characteristics of the new design optimization procedure include the ability to handle a variety of design objectives, easily impose constraints, and incorporate design guidelines and rules of thumb. It provides an infrastructure for variable fidelity analysis and reduces the cost of computation by using less-expensive, lower fidelity simulations in the early stages of the design evolution. The initial or starting design can be far from optimal. The procedure is easy and economical to use in large-dimensional design space and can be used to perform design tradeoff studies rapidly. Designs involving multiple disciplines can also be optimized. Some practical applications of the design procedure that have demonstrated some of its capabilities include the inverse design of an optimal turbine airfoil starting from a generic shape and the redesign of transonic turbines to improve their unsteady aerodynamic characteristics.

Multiple cues produced by a robotic fish modulate aggressive behaviour in Siamese fighting fishes.

PubMed

Romano, Donato; Benelli, Giovanni; Donati, Elisa; Remorini, Damiano; Canale, Angelo; Stefanini, Cesare

2017-07-05

The use of robotics to establish social interactions between animals and robots, represents an elegant and innovative method to investigate animal behaviour. However, robots are still underused to investigate high complex and flexible behaviours, such as aggression. Here, Betta splendens was tested as model system to shed light on the effect of a robotic fish eliciting aggression. We evaluated how multiple signal systems, including a light stimulus, affect aggressive responses in B. splendens. Furthermore, we conducted experiments to estimate if aggressive responses were triggered by the biomimetic shape of fish replica, or whether any intruder object was effective as well. Male fishes showed longer and higher aggressive displays as puzzled stimuli from the fish replica increased. When the fish replica emitted its full sequence of cues, the intensity of aggression exceeded even that produced by real fish opponents. Fish replica shape was necessary for conspecific opponent perception, evoking significant aggressive responses. Overall, this study highlights that the efficacy of an artificial opponent eliciting aggressive behaviour in fish can be boosted by exposure to multiple signals. Optimizing the cue combination delivered by the robotic fish replica may be helpful to predict escalating levels of aggression.

An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Zhu, Wei; Wang, Wei; Yuan, Gannan

2016-06-01

In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).

Toward precision smoking cessation treatment I: Moderator results from a factorial experiment.

PubMed

Piper, Megan E; Schlam, Tanya R; Cook, Jessica W; Smith, Stevens S; Bolt, Daniel M; Loh, Wei-Yin; Mermelstein, Robin; Collins, Linda M; Fiore, Michael C; Baker, Timothy B

2017-02-01

The development of tobacco use treatments that are effective for all smokers is critical to improving clinical and public health. The Multiphase Optimization Strategy (MOST) uses highly efficient factorial experiments to evaluate multiple intervention components for possible inclusion in an optimized tobacco use treatment. Factorial experiments permit analyses of the influence of patient characteristics on main and interaction effects of multiple, relatively discrete, intervention components. This study examined whether person-factor and smoking characteristics moderated the main or interactive effects of intervention components on 26-week self-reported abstinence rates. This fractional factorial experiment evaluated six smoking cessation intervention components among primary care patients (N=637): Prequit Nicotine Patch vs. None, Prequit Nicotine Gum vs. None, Preparation Counseling vs. None, Intensive Cessation In-Person Counseling vs. Minimal, Intensive Cessation Telephone Counseling vs. Minimal, and 16 vs. 8 Weeks of Combination Nicotine Replacement Therapy (NRT; nicotine patch+nicotine gum). Both psychiatric history and smoking heaviness moderated intervention component effects. In comparison with participants with no self-reported history of a psychiatric disorder, those with a positive history showed better response to 16- vs. 8-weeks of combination NRT, but a poorer response to counseling interventions. Also, in contrast to light smokers, heavier smokers showed a poorer response to counseling interventions. Heavy smokers and those with psychiatric histories demonstrated a differential response to intervention components. This research illustrates the use of factorial designs to examine the interactions between person characteristics and relatively discrete intervention components. Future research is needed to replicate these findings. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Genetic algorithm optimization of a film cooling array on a modern turbine inlet vane

NASA Astrophysics Data System (ADS)

Johnson, Jamie J.

In response to the need for more advanced gas turbine cooling design methods that factor in the 3-D flowfield and heat transfer characteristics, this study involves the computational optimization of a pressure side film cooling array on a modern turbine inlet vane. Latin hypersquare sampling, genetic algorithm reproduction, and Reynolds-Averaged Navier Stokes (RANS) computational fluid dynamics (CFD) as an evaluation step are used to assess a total of 1,800 film cooling designs over 13 generations. The process was efficient due to the Leo CFD code's ability to estimate cooling mass flux at surface grid cells using a transpiration boundary condition, eliminating the need for remeshing between designs. The optimization resulted in a unique cooling design relative to the baseline with new injection angles, compound angles, cooling row patterns, hole sizes, a redistribution of cooling holes away from the over-cooled midspan to hot areas near the shroud, and a lower maximum surface temperature. To experimentally confirm relative design trends between the optimized and baseline designs, flat plate infrared thermography assessments were carried out at design flow conditions. Use of flat plate experiments to model vane pressure side cooling was justified through a conjugate heat transfer CFD comparison of the 3-D vane and flat plate which showed similar cooling performance trends at multiple span locations. The optimized flat plate model exhibited lower minimum surface temperatures at multiple span locations compared to the baseline. Overall, this work shows promise of optimizing film cooling to reduce design cycle time and save cooling mass flow in a gas turbine.

Recent developments of axial flow compressors under transonic flow conditions

NASA Astrophysics Data System (ADS)

Srinivas, G.; Raghunandana, K.; Satish Shenoy, B.

2017-05-01

The objective of this paper is to give a holistic view of the most advanced technology and procedures that are practiced in the field of turbomachinery design. Compressor flow solver is the turbulence model used in the CFD to solve viscous problems. The popular techniques like Jameson’s rotated difference scheme was used to solve potential flow equation in transonic condition for two dimensional aero foils and later three dimensional wings. The gradient base method is also a popular method especially for compressor blade shape optimization. Various other types of optimization techniques available are Evolutionary algorithms (EAs) and Response surface methodology (RSM). It is observed that in order to improve compressor flow solver and to get agreeable results careful attention need to be paid towards viscous relations, grid resolution, turbulent modeling and artificial viscosity, in CFD. The advanced techniques like Jameson’s rotated difference had most substantial impact on wing design and aero foil. For compressor blade shape optimization, Evolutionary algorithm is quite simple than gradient based technique because it can solve the parameters simultaneously by searching from multiple points in the given design space. Response surface methodology (RSM) is a method basically used to design empirical models of the response that were observed and to study systematically the experimental data. This methodology analyses the correct relationship between expected responses (output) and design variables (input). RSM solves the function systematically in a series of mathematical and statistical processes. For turbomachinery blade optimization recently RSM has been implemented successfully. The well-designed high performance axial flow compressors finds its application in any air-breathing jet engines.

Combined adaptive multiple subtraction based on optimized event tracing and extended wiener filtering

NASA Astrophysics Data System (ADS)

Tan, Jun; Song, Peng; Li, Jinshan; Wang, Lei; Zhong, Mengxuan; Zhang, Xiaobo

2017-06-01

The surface-related multiple elimination (SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.

UDECON: deconvolution optimization software for restoring high-resolution records from pass-through paleomagnetic measurements

NASA Astrophysics Data System (ADS)

Xuan, Chuang; Oda, Hirokuni

2015-11-01

The rapid accumulation of continuous paleomagnetic and rock magnetic records acquired from pass-through measurements on superconducting rock magnetometers (SRM) has greatly contributed to our understanding of the paleomagnetic field and paleo-environment. Pass-through measurements are inevitably smoothed and altered by the convolution effect of SRM sensor response, and deconvolution is needed to restore high-resolution paleomagnetic and environmental signals. Although various deconvolution algorithms have been developed, the lack of easy-to-use software has hindered the practical application of deconvolution. Here, we present standalone graphical software UDECON as a convenient tool to perform optimized deconvolution for pass-through paleomagnetic measurements using the algorithm recently developed by Oda and Xuan (Geochem Geophys Geosyst 15:3907-3924, 2014). With the preparation of a format file, UDECON can directly read pass-through paleomagnetic measurement files collected at different laboratories. After the SRM sensor response is determined and loaded to the software, optimized deconvolution can be conducted using two different approaches (i.e., "Grid search" and "Simplex method") with adjustable initial values or ranges for smoothness, corrections of sample length, and shifts in measurement position. UDECON provides a suite of tools to view conveniently and check various types of original measurement and deconvolution data. Multiple steps of measurement and/or deconvolution data can be compared simultaneously to check the consistency and to guide further deconvolution optimization. Deconvolved data together with the loaded original measurement and SRM sensor response data can be saved and reloaded for further treatment in UDECON. Users can also export the optimized deconvolution data to a text file for analysis in other software.

Cross layer optimization for cloud-based radio over optical fiber networks

NASA Astrophysics Data System (ADS)

Shao, Sujie; Guo, Shaoyong; Qiu, Xuesong; Yang, Hui; Meng, Luoming

2016-07-01

To adapt the 5G communication, the cloud radio access network is a paradigm introduced by operators which aggregates all base stations computational resources into a cloud BBU pool. The interaction between RRH and BBU or resource schedule among BBUs in cloud have become more frequent and complex with the development of system scale and user requirement. It can promote the networking demand among RRHs and BBUs, and force to form elastic optical fiber switching and networking. In such network, multiple stratum resources of radio, optical and BBU processing unit have interweaved with each other. In this paper, we propose a novel multiple stratum optimization (MSO) architecture for cloud-based radio over optical fiber networks (C-RoFN) with software defined networking. Additionally, a global evaluation strategy (GES) is introduced in the proposed architecture. MSO can enhance the responsiveness to end-to-end user demands and globally optimize radio frequency, optical spectrum and BBU processing resources effectively to maximize radio coverage. The feasibility and efficiency of the proposed architecture with GES strategy are experimentally verified on OpenFlow-enabled testbed in terms of resource occupation and path provisioning latency.

An optimal algorithm for reconstructing images from binary measurements

NASA Astrophysics Data System (ADS)

Yang, Feng; Lu, Yue M.; Sbaiz, Luciano; Vetterli, Martin

2010-01-01

We have studied a camera with a very large number of binary pixels referred to as the gigavision camera [1] or the gigapixel digital film camera [2, 3]. Potential advantages of this new camera design include improved dynamic range, thanks to its logarithmic sensor response curve, and reduced exposure time in low light conditions, due to its highly sensitive photon detection mechanism. We use maximum likelihood estimator (MLE) to reconstruct a high quality conventional image from the binary sensor measurements of the gigavision camera. We prove that when the threshold T is "1", the negative loglikelihood function is a convex function. Therefore, optimal solution can be achieved using convex optimization. Base on filter bank techniques, fast algorithms are given for computing the gradient and the multiplication of a vector and Hessian matrix of the negative log-likelihood function. We show that with a minor change, our algorithm also works for estimating conventional images from multiple binary images. Numerical experiments with synthetic 1-D signals and images verify the effectiveness and quality of the proposed algorithm. Experimental results also show that estimation performance can be improved by increasing the oversampling factor or the number of binary images.

Optimization of 3D Field Design

NASA Astrophysics Data System (ADS)

Logan, Nikolas; Zhu, Caoxiang

2017-10-01

Recent progress in 3D tokamak modeling is now leveraged to create a conceptual design of new external 3D field coils for the DIII-D tokamak. Using the IPEC dominant mode as a target spectrum, the Finding Optimized Coils Using Space-curves (FOCUS) code optimizes the currents and 3D geometry of multiple coils to maximize the total set's resonant coupling. The optimized coils are individually distorted in space, creating toroidal ``arrays'' containing a variety of shapes that often wrap around a significant poloidal extent of the machine. The generalized perturbed equilibrium code (GPEC) is used to determine optimally efficient spectra for driving total, core, and edge neoclassical toroidal viscosity (NTV) torque and these too provide targets for the optimization of 3D coil designs. These conceptual designs represent a fundamentally new approach to 3D coil design for tokamaks targeting desired plasma physics phenomena. Optimized coil sets based on plasma response theory will be relevant to designs for future reactors or on any active machine. External coils, in particular, must be optimized for reliable and efficient fusion reactor designs. Work supported by the US Department of Energy under DE-AC02-09CH11466.

Reliability Methods for Shield Design Process

NASA Technical Reports Server (NTRS)

Tripathi, R. K.; Wilson, J. W.

2002-01-01

Providing protection against the hazards of space radiation is a major challenge to the exploration and development of space. The great cost of added radiation shielding is a potential limiting factor in deep space operations. In this enabling technology, we have developed methods for optimized shield design over multi-segmented missions involving multiple work and living areas in the transport and duty phase of space missions. The total shield mass over all pieces of equipment and habitats is optimized subject to career dose and dose rate constraints. An important component of this technology is the estimation of two most commonly identified uncertainties in radiation shield design, the shielding properties of materials used and the understanding of the biological response of the astronaut to the radiation leaking through the materials into the living space. The largest uncertainty, of course, is in the biological response to especially high charge and energy (HZE) ions of the galactic cosmic rays. These uncertainties are blended with the optimization design procedure to formulate reliability-based methods for shield design processes. The details of the methods will be discussed.

Analysis of grinding of superalloys and ceramics for off-line process optimization

NASA Astrophysics Data System (ADS)

Sathyanarayanan, G.

The present study has compared the performances of resinoid, vitrified, and electroplated CBN wheels in creep feed grinding of M42 and D2 tool steels. Responses such as a specific energy, normal and tangential forces, and surface roughness were used as measures of performance. It was found that creep feed grinding with resinoid, vitrified, and electroplated CBN wheels has its own advantages, but no single wheel could provide good finish, lower specific energy, and high material removal rates simultaneously. To optimize the CBN grinding with different bonded wheels, a Multiple Criteria Decision Making (MCDM) methodology was used. Creep feed grinding of superalloys, Ti-6Al-4V and Inconel 718, has been modeled by utilizing neural networks to optimize the grinding process. A parallel effort was directed at creep feed grinding of alumina ceramics with diamond wheels to investigate the influence of process variables on responses based on experimental results and statistical analysis. The conflicting influence of variables was observed. This led to the formulation of ceramic grinding process as a multi-objective nonlinear mixed integer problem.

An Effective Mechanism for Virtual Machine Placement using Aco in IAAS Cloud

NASA Astrophysics Data System (ADS)

Shenbaga Moorthy, Rajalakshmi; Fareentaj, U.; Divya, T. K.

2017-08-01

Cloud computing provides an effective way to dynamically provide numerous resources to meet customer demands. A major challenging problem for cloud providers is designing efficient mechanisms for optimal virtual machine Placement (OVMP). Such mechanisms enable the cloud providers to effectively utilize their available resources and obtain higher profits. In order to provide appropriate resources to the clients an optimal virtual machine placement algorithm is proposed. Virtual machine placement is NP-Hard problem. Such NP-Hard problem can be solved using heuristic algorithm. In this paper, Ant Colony Optimization based virtual machine placement is proposed. Our proposed system focuses on minimizing the cost spending in each plan for hosting virtual machines in a multiple cloud provider environment and the response time of each cloud provider is monitored periodically, in such a way to minimize delay in providing the resources to the users. The performance of the proposed algorithm is compared with greedy mechanism. The proposed algorithm is simulated in Eclipse IDE. The results clearly show that the proposed algorithm minimizes the cost, response time and also number of migrations.

The impact of response measurement error on the analysis of designed experiments

DOE PAGES

Anderson-Cook, Christine Michaela; Hamada, Michael Scott; Burr, Thomas Lee

2016-11-01

This study considers the analysis of designed experiments when there is measurement error in the true response or so-called response measurement error. We consider both additive and multiplicative response measurement errors. Through a simulation study, we investigate the impact of ignoring the response measurement error in the analysis, that is, by using a standard analysis based on t-tests. In addition, we examine the role of repeat measurements in improving the quality of estimation and prediction in the presence of response measurement error. We also study a Bayesian approach that accounts for the response measurement error directly through the specification ofmore » the model, and allows including additional information about variability in the analysis. We consider the impact on power, prediction, and optimization. Copyright © 2015 John Wiley & Sons, Ltd.« less

The impact of response measurement error on the analysis of designed experiments

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

Anderson-Cook, Christine Michaela; Hamada, Michael Scott; Burr, Thomas Lee

This study considers the analysis of designed experiments when there is measurement error in the true response or so-called response measurement error. We consider both additive and multiplicative response measurement errors. Through a simulation study, we investigate the impact of ignoring the response measurement error in the analysis, that is, by using a standard analysis based on t-tests. In addition, we examine the role of repeat measurements in improving the quality of estimation and prediction in the presence of response measurement error. We also study a Bayesian approach that accounts for the response measurement error directly through the specification ofmore » the model, and allows including additional information about variability in the analysis. We consider the impact on power, prediction, and optimization. Copyright © 2015 John Wiley & Sons, Ltd.« less

The use of vignettes to empower effective responses to attempted sexual assault.

PubMed

Allen, Kaylie T; Meadows, Elizabeth A

2017-01-01

Women assertively resisting sexual aggression have the best chances of avoiding completed rape. Especially with acquaintances, there are significant social and psychological barriers to resistance. Novel vignettes depicting acquaintance rape were designed to enhance self-efficacy, reduce unrealistic optimism, and empower assertive resistance. The data were collected using a Web-based survey of 449 female college students from multiple universities in August-October 2014. Between-subjects mixed-methods design. Participants were randomly assigned to read one of four vignettes and complete self-report measures of personal vulnerability, self-efficacy, and beliefs and intention about resistance. Although vignettes did not impact self-efficacy, one vignette enhanced perceived controllability and decreased unrealistic optimism. Women who read about completed acquaintance rape described intention to use physically assertive responses at double the rate of women reading about successful resistance. As low-cost, easily disseminated materials, vignettes about sexual assault may enhance campus prevention efforts.

Biomimetically Engineered Demi-Bacteria Potentiate Vaccination against Cancer.

PubMed

Ni, Dezhi; Qing, Shuang; Ding, Hui; Yue, Hua; Yu, Di; Wang, Shuang; Luo, Nana; Su, Zhiguo; Wei, Wei; Ma, Guanghui

2017-10-01

Failure in enhancing antigen immunogenicity has limited the development of cancer vaccine. Inspired by effective immune responses toward microorganisms, demi-bacteria (DB) from Bacillus are engineered as carriers for cancer vaccines. The explored hydrothermal treatment enables the Bacillus to preserve optimal pathogen morphology with intrinsic mannose receptor agonist. Meanwhile, the treated Bacillus can be further endowed with ideal hollow/porous structure for efficient accommodation of antigen and adjuvant, such as CpG. Therefore, this optimal engineered nanoarchitecture allows multiple immunostimulatory elements integrate in a pattern closely resembling that of bacterial pathogens. Such pathogen mimicry greatly enhances antigen uptake and cross-presentation, resulting in stronger immune activation suitable for cancer vaccines. Indeed, DB-based biomimetic vaccination in mice induces synergistic cellular and humoral immune responses, achieving potent therapeutic and preventive effects against cancer. Application of microorganism-sourced materials thus presents new opportunities for potent cancer therapy.

Biomimetically Engineered Demi‐Bacteria Potentiate Vaccination against Cancer

PubMed Central

Ni, Dezhi; Qing, Shuang; Ding, Hui; Yue, Hua; Yu, Di; Wang, Shuang; Luo, Nana; Su, Zhiguo

2017-01-01

Abstract Failure in enhancing antigen immunogenicity has limited the development of cancer vaccine. Inspired by effective immune responses toward microorganisms, demi‐bacteria (DB) from Bacillus are engineered as carriers for cancer vaccines. The explored hydrothermal treatment enables the Bacillus to preserve optimal pathogen morphology with intrinsic mannose receptor agonist. Meanwhile, the treated Bacillus can be further endowed with ideal hollow/porous structure for efficient accommodation of antigen and adjuvant, such as CpG. Therefore, this optimal engineered nanoarchitecture allows multiple immunostimulatory elements integrate in a pattern closely resembling that of bacterial pathogens. Such pathogen mimicry greatly enhances antigen uptake and cross‐presentation, resulting in stronger immune activation suitable for cancer vaccines. Indeed, DB‐based biomimetic vaccination in mice induces synergistic cellular and humoral immune responses, achieving potent therapeutic and preventive effects against cancer. Application of microorganism‐sourced materials thus presents new opportunities for potent cancer therapy. PMID:29051851

Feasibility of optimizing trimetazidine dihydrochloride release from controlled porosity osmotic pump tablets of directly compressed cores

PubMed Central

Habib, Basant A.; Rehim, Randa T. Abd El; Nour, Samia A.

2013-01-01

The aim of this study was to develop and optimize Trimetazidine dihydrochloride (TM) controlled porosity osmotic pump (CPOP) tablets of directly compressed cores. A 23 full factorial design was used to study the influence of three factors namely: PEG400 (10% and 25% based on coating polymer weight), coating level (10% and 20% of tablet core weight) and hole diameter (0 “no hole” and 1 mm). Other variables such as tablet cores, coating mixture of ethylcellulose (4%) and dibutylphthalate (2%) in 95% ethanol and pan coating conditions were kept constant. The responses studied (Yi) were cumulative percentage released after 2 h (Q%2h), 6 h (Q%6h), 12 h (Q%12h) and regression coefficient of release data fitted to zero order equation (RSQzero), for Y1, Y2, Y3, and Y4, respectively. Polynomial equations were used to study the influence of different factors on each response individually. Response surface methodology and multiple response optimization were used to search for an optimized formula. Response variables for the optimized formula were restricted to 10% ⩽ Y1 ⩽ 20%, 40% ⩽ Y2 ⩽ 60%, 80% ⩽ Y3 ⩽ 100%, and Y4 > 0.9. The statistical analysis of the results revealed that PEG400 had positive effects on Q%2h, Q%6h and Q%12h, hole diameter had positive effects on all responses and coating level had positive effect on Q%6h, Q%12h and negative effect on RSQzero. Full three factor interaction (3FI) equations were used for representation of all responses except Q%2h which was represented by reduced (3FI) equation. Upon exploring the experimental space, no formula in the tested range could satisfy the required constraints. Thus, direct compression of TM cores was not suitable for formation of CPOP tablets. Preliminary trials of CPOP tablets with wet granulated cores were promising with an intact membrane for 12 h and high RSQzero. Further improvement of these formulations to optimize TM release will be done in further studies. PMID:25685502

A Single Element Charge Injection Device as a Spectroscopic Detector.

DTIC Science & Technology

1987-05-26

major approaches to designing a AES spectrometer exist, one involving simultaneous multiwavelength monitoring with multiple detectors or an imaging...are below 1%. (2) Limited Spectral Range. While it is possible to construct photocathodes optimized for maximum response within nearly any UV -visible...reflectance paint. A ring of five light emitting diodes ( LEDs ) inside the cylinder is used as a light source, with the duration of illumination

Immunotherapy for metastatic urothelial carcinoma: status quo and the future.

PubMed

Necchi, Andrea; Rink, Michael; Giannatempo, Patrizia; Raggi, Daniele; Xylinas, Evanguelos

2018-01-01

The treatment paradigm of urothelial carcinoma has been revolutionized by the advent of multiple anti-programmed-cell death-1/ligand-1 (PD-1/PD-L1) antibodies. Significant improvements have been obtained in the locally advanced or metastatic stage, which was lacking of therapeutic standards. This review reports key findings from completed and ongoing clinical trials that highlight the potential of PD-1/PD-L1 blockade in this disease. Anti-PD-1/PD-L1 monoclonal antibodies have shown efficacy and safety in patients with urothelial carcinoma, regardless of their prognostic features. Efficacy was similar across different compounds, with objective responses that approximate 20%, with some differences favoring PD-L1-expressing patients. Typically, responding patients have good chances of achieving durable response, but biomarkers predictive of therapeutic effect are lacking. To date, evidences from randomized studies are limited to the second-line, postplatinum therapy. Despite the activity of PD-1/PD-L1 inhibitors is well established in metastatic urothelial carcinoma, multiple gray zones still exist regarding their optimal use in clinical practice. These uncertainties are related to patient and treatment-related criteria, to the optimal duration of treatment, including combination or sequence with standard chemotherapy. Special issues are represented by pseudoprogression or hyperprogression. Generally, enhanced predictive tools are needed and a myriad of further investigations are underway.

Optimizing therapeutics in the management of patients with multiple sclerosis: a review of drug efficacy, dosing, and mechanisms of action

PubMed Central

Damal, Kavitha; Stoker, Emily; Foley, John F

2013-01-01

Multiple sclerosis (MS) is a debilitating neurological disorder that affects nearly 2 million adults, mostly in the prime of their youth. An environmental trigger, such as a viral infection, is hypothesized to initiate the abnormal behavior of host immune cells: to attack and damage the myelin sheath surrounding the neurons of the central nervous system. While several other pathways and disease triggers are still being investigated, it is nonetheless clear that MS is a heterogeneous disease with multifactorial etiologies that works independently or synergistically to initiate the aberrant immune responses to myelin. Although there are still no definitive markers to diagnose the disease or to cure the disease per se, research on management of MS has improved many fold over the past decade. New disease-modifying therapeutics are poised to decrease immune inflammatory responses and consequently decelerate the progression of MS disease activity, reduce the exacerbations of MS symptoms, and stabilize the physical and mental status of individuals. In this review, we describe the mechanism of action, optimal dosing, drug administration, safety, and efficacy of the disease-modifying therapeutics that are currently approved for MS therapy. We also briefly touch upon the new drugs currently under investigation, and discuss the future of MS therapeutics. PMID:24324326

Optimization to Develop Multiple Response Microstructure and Hardness of Ductile Iron Casting by using GRA

NASA Astrophysics Data System (ADS)

Kabnure, Bahubali Bhupal; Shinde, Vasudev Dhondiram; Kolhapure, Rakesh Ramchandra

2018-05-01

Ductile irons are important engineering materials because of its high strength to weight ratio and castability. The ductile iron castings are used widely for automobile applications due to their wide spectrum of property range. Weight reduction is important in automobile to improve its fuel efficiency which can be achieved by thinning down the casting sections without altering its functionality. Generally, automobile castings are having varying section thickness. Varying thickness castings offers different cooling rates while solidification of the casting. The solidification cooling rate decides the final microstructure of the cast components. Cooling rate was found to affect directly the amount of pearlite and ultimately the as cast properties in varying thickness ductile iron castings. In view of this, the automobile impeller casting is selected for study in the present work as it consists of varying section thickness in which small sections are connected to central hub. The casting solidification simulations were performed and analyzed. The solidification cooling rates were analyzed further to correlate the experimental processing parameters. The samples from poured castings were analyzed for microstructure and hardness at different section thickness. Multiple response optimization of microstructure and hardness was carried out by combined Taguchi and Grey Relational Analysis (GRA). Contribution of input variables on the output variables is attained using ANOVA.

Optimizing therapeutics in the management of patients with multiple sclerosis: a review of drug efficacy, dosing, and mechanisms of action.

PubMed

Damal, Kavitha; Stoker, Emily; Foley, John F

2013-01-01

Multiple sclerosis (MS) is a debilitating neurological disorder that affects nearly 2 million adults, mostly in the prime of their youth. An environmental trigger, such as a viral infection, is hypothesized to initiate the abnormal behavior of host immune cells: to attack and damage the myelin sheath surrounding the neurons of the central nervous system. While several other pathways and disease triggers are still being investigated, it is nonetheless clear that MS is a heterogeneous disease with multifactorial etiologies that works independently or synergistically to initiate the aberrant immune responses to myelin. Although there are still no definitive markers to diagnose the disease or to cure the disease per se, research on management of MS has improved many fold over the past decade. New disease-modifying therapeutics are poised to decrease immune inflammatory responses and consequently decelerate the progression of MS disease activity, reduce the exacerbations of MS symptoms, and stabilize the physical and mental status of individuals. In this review, we describe the mechanism of action, optimal dosing, drug administration, safety, and efficacy of the disease-modifying therapeutics that are currently approved for MS therapy. We also briefly touch upon the new drugs currently under investigation, and discuss the future of MS therapeutics.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS.

PubMed

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-11-04

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

PubMed Central

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-01-01

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM. PMID:28774019

Multi-response optimization of Artemia hatching process using split-split-plot design based response surface methodology

PubMed Central

Arun, V. V.; Saharan, Neelam; Ramasubramanian, V.; Babitha Rani, A. M.; Salin, K. R.; Sontakke, Ravindra; Haridas, Harsha; Pazhayamadom, Deepak George

2017-01-01

A novel method, BBD-SSPD is proposed by the combination of Box-Behnken Design (BBD) and Split-Split Plot Design (SSPD) which would ensure minimum number of experimental runs, leading to economical utilization in multi- factorial experiments. The brine shrimp Artemia was tested to study the combined effects of photoperiod, temperature and salinity, each with three levels, on the hatching percentage and hatching time of their cysts. The BBD was employed to select 13 treatment combinations out of the 27 possible combinations that were grouped in an SSPD arrangement. Multiple responses were optimized simultaneously using Derringer’s desirability function. Photoperiod and temperature as well as temperature-salinity interaction were found to significantly affect the hatching percentage of Artemia, while the hatching time was significantly influenced by photoperiod and temperature, and their interaction. The optimum conditions were 23 h photoperiod, 29 °C temperature and 28 ppt salinity resulting in 96.8% hatching in 18.94 h. In order to verify the results obtained from BBD-SSPD experiment, the experiment was repeated preserving the same set up. Results of verification experiment were found to be similar to experiment originally conducted. It is expected that this method would be suitable to optimize the hatching process of animal eggs. PMID:28091611

The absolute threshold of cone vision

PubMed Central

Koeing, Darran; Hofer, Heidi

2013-01-01

We report measurements of the absolute threshold of cone vision, which has been previously underestimated due to sub-optimal conditions or overly strict subjective response criteria. We avoided these limitations by using optimized stimuli and experimental conditions while having subjects respond within a rating scale framework. Small (1′ fwhm), brief (34 msec), monochromatic (550 nm) stimuli were foveally presented at multiple intensities in dark-adapted retina for 5 subjects. For comparison, 4 subjects underwent similar testing with rod-optimized stimuli. Cone absolute threshold, that is, the minimum light energy for which subjects were just able to detect a visual stimulus with any response criterion, was 203 ± 38 photons at the cornea, ∼0.47 log units lower than previously reported. Two-alternative forced-choice measurements in a subset of subjects yielded consistent results. Cone thresholds were less responsive to criterion changes than rod thresholds, suggesting a limit to the stimulus information recoverable from the cone mosaic in addition to the limit imposed by Poisson noise. Results were consistent with expectations for detection in the face of stimulus uncertainty. We discuss implications of these findings for modeling the first stages of human cone vision and interpreting psychophysical data acquired with adaptive optics at the spatial scale of the receptor mosaic. PMID:21270115

Robust myoelectric signal detection based on stochastic resonance using multiple-surface-electrode array made of carbon nanotube composite paper

NASA Astrophysics Data System (ADS)

Shirata, Kento; Inden, Yuki; Kasai, Seiya; Oya, Takahide; Hagiwara, Yosuke; Kaeriyama, Shunichi; Nakamura, Hideyuki

2016-04-01

We investigated the robust detection of surface electromyogram (EMG) signals based on the stochastic resonance (SR) phenomenon, in which the response to weak signals is optimized by adding noise, combined with multiple surface electrodes. Flexible carbon nanotube composite paper (CNT-cp) was applied to the surface electrode, which showed good performance that is comparable to that of conventional Ag/AgCl electrodes. The SR-based EMG signal system integrating an 8-Schmitt-trigger network and the multiple-CNT-cp-electrode array successfully detected weak EMG signals even when the subject’s body is in the motion, which was difficult to achieve using the conventional technique. The feasibility of the SR-based EMG detection technique was confirmed by demonstrating its applicability to robot hand control.

Regulation of C:N:P stoichiometry of microbes and soil organic matter by optimizing enzyme allocation: an omics-informed model study

NASA Astrophysics Data System (ADS)

Song, Y.; Yao, Q.; Wang, G.; Yang, X.; Mayes, M. A.

2017-12-01

Increasing evidences is indicating that soil organic matter (SOM) decomposition and stabilization process is a continuum process and controlled by both microbial functions and their interaction with minerals (known as the microbial efficiency-matrix stabilization theory (MEMS)). Our metagenomics analysis of soil samples from both P-deficit and P-fertilization sites in Panama has demonstrated that community-level enzyme functions could adapt to maximize the acquisition of limiting nutrients and minimize energy demand for foraging (known as the optimal foraging theory). This optimization scheme can mitigate the imbalance of C/P ratio between soil substrate and microbial community and relieve the P limitation on microbial carbon use efficiency over the time. Dynamic allocation of multiple enzyme groups and their interaction with microbial/substrate stoichiometry has rarely been considered in biogeochemical models due to the difficulties in identifying microbial functional groups and quantifying the change in enzyme expression in response to soil nutrient availability. This study aims to represent the omics-informed optimal foraging theory in the Continuum Microbial ENzyme Decomposition model (CoMEND), which was developed to represent the continuum SOM decomposition process following the MEMS theory. The SOM pools in the model are classified based on soil chemical composition (i.e. Carbohydrates, lignin, N-rich SOM and P-rich SOM) and the degree of SOM depolymerization. The enzyme functional groups for decomposition of each SOM pool and N/P mineralization are identified by the relative composition of gene copy numbers. The responses of microbial activities and SOM decomposition to nutrient availability are simulated by optimizing the allocation of enzyme functional groups following the optimal foraging theory. The modeled dynamic enzyme allocation in response to P availability is evaluated by the metagenomics data measured from P addition and P-deficit soil samples in Panama sites.The implementation of dynamic enzyme allocation in response to nutrient availability in the CoMEND model enables us to capture the varying microbial C/P ratio and soil carbon dynamics in response to shifting nutrient constraints over time in tropical soils.

Computational Precision of Mental Inference as Critical Source of Human Choice Suboptimality.

PubMed

Drugowitsch, Jan; Wyart, Valentin; Devauchelle, Anne-Dominique; Koechlin, Etienne

2016-12-21

Making decisions in uncertain environments often requires combining multiple pieces of ambiguous information from external cues. In such conditions, human choices resemble optimal Bayesian inference, but typically show a large suboptimal variability whose origin remains poorly understood. In particular, this choice suboptimality might arise from imperfections in mental inference rather than in peripheral stages, such as sensory processing and response selection. Here, we dissociate these three sources of suboptimality in human choices based on combining multiple ambiguous cues. Using a novel quantitative approach for identifying the origin and structure of choice variability, we show that imperfections in inference alone cause a dominant fraction of suboptimal choices. Furthermore, two-thirds of this suboptimality appear to derive from the limited precision of neural computations implementing inference rather than from systematic deviations from Bayes-optimal inference. These findings set an upper bound on the accuracy and ultimate predictability of human choices in uncertain environments. Copyright © 2016 Elsevier Inc. All rights reserved.

Multimode drug inducible CRISPR/Cas9 devices for transcriptional activation and genome editing

PubMed Central

Lu, Jia; Zhao, Chen; Zhao, Yingze; Zhang, Jingfang; Zhang, Yue; Chen, Li; Han, Qiyuan; Ying, Yue; Peng, Shuai; Ai, Runna; Wang, Yu

2018-01-01

Abstract Precise investigation and manipulation of dynamic biological processes often requires molecular modulation in a controlled inducible manner. The clustered, regularly interspaced, short palindromic repeats (CRISPR)/CRISPR associated protein 9 (Cas9) has emerged as a versatile tool for targeted gene editing and transcriptional programming. Here, we designed and vigorously optimized a series of Hybrid drug Inducible CRISPR/Cas9 Technologies (HIT) for transcriptional activation by grafting a mutated human estrogen receptor (ERT2) to multiple CRISPR/Cas9 systems, which renders them 4-hydroxytamoxifen (4-OHT) inducible for the access of genome. Further, extra functionality of simultaneous genome editing was achieved with one device we named HIT2. Optimized terminal devices herein delivered advantageous performances in comparison with several existing designs. They exerted selective, titratable, rapid and reversible response to drug induction. In addition, these designs were successfully adapted to an orthogonal Cas9. HIT systems developed in this study can be applied for controlled modulation of potentially any genomic loci in multiple modes. PMID:29237052

Topology optimization under stochastic stiffness

NASA Astrophysics Data System (ADS)

Asadpoure, Alireza

Topology optimization is a systematic computational tool for optimizing the layout of materials within a domain for engineering design problems. It allows variation of structural boundaries and connectivities. This freedom in the design space often enables discovery of new, high performance designs. However, solutions obtained by performing the optimization in a deterministic setting may be impractical or suboptimal when considering real-world engineering conditions with inherent variabilities including (for example) variabilities in fabrication processes and operating conditions. The aim of this work is to provide a computational methodology for topology optimization in the presence of uncertainties associated with structural stiffness, such as uncertain material properties and/or structural geometry. Existing methods for topology optimization under deterministic conditions are first reviewed. Modifications are then proposed to improve the numerical performance of the so-called Heaviside Projection Method (HPM) in continuum domains. Next, two approaches, perturbation and Polynomial Chaos Expansion (PCE), are proposed to account for uncertainties in the optimization procedure. These approaches are intrusive, allowing tight and efficient coupling of the uncertainty quantification with the optimization sensitivity analysis. The work herein develops a robust topology optimization framework aimed at reducing the sensitivity of optimized solutions to uncertainties. The perturbation-based approach combines deterministic topology optimization with a perturbation method for the quantification of uncertainties. The use of perturbation transforms the problem of topology optimization under uncertainty to an augmented deterministic topology optimization problem. The PCE approach combines the spectral stochastic approach for the representation and propagation of uncertainties with an existing deterministic topology optimization technique. The resulting compact representations for the response quantities allow for efficient and accurate calculation of sensitivities of response statistics with respect to the design variables. The proposed methods are shown to be successful at generating robust optimal topologies. Examples from topology optimization in continuum and discrete domains (truss structures) under uncertainty are presented. It is also shown that proposed methods lead to significant computational savings when compared to Monte Carlo-based optimization which involve multiple formations and inversions of the global stiffness matrix and that results obtained from the proposed method are in excellent agreement with those obtained from a Monte Carlo-based optimization algorithm.

Distributed process manager for an engineering network computer

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

Gait, J.

1987-08-01

MP is a manager for systems of cooperating processes in a local area network of engineering workstations. MP supports transparent continuation by maintaining multiple copies of each process on different workstations. Computational bandwidth is optimized by executing processes in parallel on different workstations. Responsiveness is high because workstations compete among themselves to respond to requests. The technique is to select a master from among a set of replicates of a process by a competitive election between the copies. Migration of the master when a fault occurs or when response slows down is effected by inducing the election of a newmore » master. Competitive response stabilizes system behavior under load, so MP exhibits realtime behaviors.« less

Optimal Information Processing in Biochemical Networks

NASA Astrophysics Data System (ADS)

Wiggins, Chris

2012-02-01

A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

ILF2 Is a Regulator of RNA Splicing and DNA Damage Response in 1q21-Amplified Multiple Myeloma.

PubMed

Marchesini, Matteo; Ogoti, Yamini; Fiorini, Elena; Aktas Samur, Anil; Nezi, Luigi; D'Anca, Marianna; Storti, Paola; Samur, Mehmet Kemal; Ganan-Gomez, Irene; Fulciniti, Maria Teresa; Mistry, Nipun; Jiang, Shan; Bao, Naran; Marchica, Valentina; Neri, Antonino; Bueso-Ramos, Carlos; Wu, Chang-Jiun; Zhang, Li; Liang, Han; Peng, Xinxin; Giuliani, Nicola; Draetta, Giulio; Clise-Dwyer, Karen; Kantarjian, Hagop; Munshi, Nikhil; Orlowski, Robert; Garcia-Manero, Guillermo; DePinho, Ronald A; Colla, Simona

2017-07-10

Amplification of 1q21 occurs in approximately 30% of de novo and 70% of relapsed multiple myeloma (MM) and is correlated with disease progression and drug resistance. Here, we provide evidence that the 1q21 amplification-driven overexpression of ILF2 in MM promotes tolerance of genomic instability and drives resistance to DNA-damaging agents. Mechanistically, elevated ILF2 expression exerts resistance to genotoxic agents by modulating YB-1 nuclear localization and interaction with the splicing factor U2AF65, which promotes mRNA processing and the stabilization of transcripts involved in homologous recombination in response to DNA damage. The intimate link between 1q21-amplified ILF2 and the regulation of RNA splicing of DNA repair genes may be exploited to optimize the use of DNA-damaging agents in patients with high-risk MM. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimal joint detection and estimation that maximizes ROC-type curves

PubMed Central

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K.

2017-01-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation. PMID:27093544

Optimal Joint Detection and Estimation That Maximizes ROC-Type Curves.

PubMed

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K

2016-09-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation.

Optimization of Landscape Services under Uncoordinated Management by Multiple Landowners

PubMed Central

Porto, Miguel; Correia, Otília; Beja, Pedro

2014-01-01

Landscapes are often patchworks of private properties, where composition and configuration patterns result from cumulative effects of the actions of multiple landowners. Securing the delivery of services in such multi-ownership landscapes is challenging, because it is difficult to assure tight compliance to spatially explicit management rules at the level of individual properties, which may hinder the conservation of critical landscape features. To deal with these constraints, a multi-objective simulation-optimization procedure was developed to select non-spatial management regimes that best meet landscape-level objectives, while accounting for uncoordinated and uncertain response of individual landowners to management rules. Optimization approximates the non-dominated Pareto frontier, combining a multi-objective genetic algorithm and a simulator that forecasts trends in landscape pattern as a function of management rules implemented annually by individual landowners. The procedure was demonstrated with a case study for the optimum scheduling of fuel treatments in cork oak forest landscapes, involving six objectives related to reducing management costs (1), reducing fire risk (3), and protecting biodiversity associated with mid- and late-successional understories (2). There was a trade-off between cost, fire risk and biodiversity objectives, that could be minimized by selecting management regimes involving ca. 60% of landowners clearing the understory at short intervals (around 5 years), and the remaining managing at long intervals (ca. 75 years) or not managing. The optimal management regimes produces a mosaic landscape dominated by stands with herbaceous and low shrub understories, but also with a satisfactory representation of old understories, that was favorable in terms of both fire risk and biodiversity. The simulation-optimization procedure presented can be extended to incorporate a wide range of landscape dynamic processes, management rules and quantifiable objectives. It may thus be adapted to other socio-ecological systems, particularly where specific patterns of landscape heterogeneity are to be maintained despite imperfect management by multiple landowners. PMID:24465833

A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization.

PubMed

Yang, Shaofu; Liu, Qingshan; Wang, Jun

2018-04-01

This paper is concerned with multiple-objective distributed optimization. Based on objective weighting and decision space decomposition, a collaborative neurodynamic approach to multiobjective distributed optimization is presented. In the approach, a system of collaborative neural networks is developed to search for Pareto optimal solutions, where each neural network is associated with one objective function and given constraints. Sufficient conditions are derived for ascertaining the convergence to a Pareto optimal solution of the collaborative neurodynamic system. In addition, it is proved that each connected subsystem can generate a Pareto optimal solution when the communication topology is disconnected. Then, a switching-topology-based method is proposed to compute multiple Pareto optimal solutions for discretized approximation of Pareto front. Finally, simulation results are discussed to substantiate the performance of the collaborative neurodynamic approach. A portfolio selection application is also given.

A parallel-architecture parametric equalizer for air-coupled capacitive ultrasonic transducers.

PubMed

McSweeney, Sean G; Wright, William M D

2012-01-01

Parametric equalization is rarely applied to ultrasonic transducer systems, for which it could be used on either the transmitter or the receiver to achieve a desired response. An optimized equalizer with both bump and cut capabilities would be advantageous for ultrasonic systems in applications in which variations in the transducer performance or the properties of the propagating medium produce a less-than-desirable signal. Compensation for non-ideal transducer response could be achieved using equalization on a device-by-device basis. Additionally, calibration of ultrasonic systems in the field could be obtained by offline optimization of equalization coefficients. In this work, a parametric equalizer for ultrasonic applications has been developed using multiple bi-quadratic filter elements arranged in a novel parallel arrangement to increase the flexibility of the equalization. The equalizer was implemented on a programmable system-on-chip (PSOC) using a small number of parallel 4th-order infinite impulse response switchedcapacitor band-pass filters. Because of the interdependency of the required coefficients for the switched capacitors, particle swarm optimization (PSO) was used to determine the optimum values. The response of a through-transmission system using air-coupled capacitive ultrasonic transducers was then equalized to idealized Hamming function or brick-wall frequencydomain responses. In each case, there was excellent agreement between the equalized signals and the theoretical model, and the fidelity of the time-domain response was maintained. The bandwidth and center frequency response of the system were significantly improved. It was also shown that the equalizer could be used on either the transmitter or the receiver, and the system could compensate for the effects of transmitterreceiver misalignment. © 2012 IEEE

Comprehensive Optimal Manpower and Personnel Analytic Simulation System (COMPASS)

DTIC Science & Technology

2009-10-01

4 The EDB consists of 4 major components (some of which are re-usable): 1. Metadata Editor ( MDE ): Also considered a leaf node, the metadata...end-user queries via the QB. The EDB supports multiple instances of the MDE , although currently, only a single instance is recommended. 2 Query...the MSB is a central collection of web services, responsible for the authentication and authorization of users, maintenance of the EDB metadata

Multi Dimensional Honey Bee Foraging Algorithm Based on Optimal Energy Consumption

NASA Astrophysics Data System (ADS)

Saritha, R.; Vinod Chandra, S. S.

2017-10-01

In this paper a new nature inspired algorithm is proposed based on natural foraging behavior of multi-dimensional honey bee colonies. This method handles issues that arise when food is shared from multiple sources by multiple swarms at multiple destinations. The self organizing nature of natural honey bee swarms in multiple colonies is based on the principle of energy consumption. Swarms of multiple colonies select a food source to optimally fulfill the requirements of its colonies. This is based on the energy requirement for transporting food between a source and destination. Minimum use of energy leads to maximizing profit in each colony. The mathematical model proposed here is based on this principle. This has been successfully evaluated by applying it on multi-objective transportation problem for optimizing cost and time. The algorithm optimizes the needs at each destination in linear time.

Optimization of process parameters for pilot-scale liquid-state bioconversion of sewage sludge by mixed fungal inoculation.

PubMed

Rahman, Roshanida A; Molla, Abul Hossain; Barghash, Hind F A; Fakhru'l-Razi, Ahmadun

2016-01-01

Liquid-state bioconversion (LSB) technique has great potential for application in bioremediation of sewage sludge. The purpose of this study is to determine the optimum level of LSB process of sewage sludge treatment by mixed fungal (Aspergillus niger and Penicillium corylophilum) inoculation in a pilot-scale bioreactor. The optimization of process factors was investigated using response surface methodology based on Box-Behnken design considering hydraulic retention time (HRT) and substrate influent concentration (S0) on nine responses for optimizing and fitted to the regression model. The optimum region was successfully depicted by optimized conditions, which was identified as the best fit for convenient multiple responses. The results from process verification were in close agreement with those obtained through predictions. Considering five runs of different conditions of HRT (low, medium and high 3.62, 6.13 and 8.27 days, respectively) with the range of S0 value (the highest 12.56 and the lowest 7.85 g L(-1)), it was monitored as the lower HRT was considered as the best option because it required minimum days of treatment than the others with influent concentration around 10 g L(-1). Therefore, optimum process factors of 3.62 days for HRT and 10.12 g L(-1) for S0 were identified as the best fit for LSB process and its performance was deviated by less than 5% in most of the cases compared to the predicted values. The recorded optimized results address a dynamic development in commercial-scale biological treatment of wastewater for safe and environment-friendly disposal in near future.

Digital robust active control law synthesis for large order systems using constrained optimization

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivek

1987-01-01

This paper presents a direct digital control law synthesis procedure for a large order, sampled data, linear feedback system using constrained optimization techniques to meet multiple design requirements. A linear quadratic Gaussian type cost function is minimized while satisfying a set of constraints on the design loads and responses. General expressions for gradients of the cost function and constraints, with respect to the digital control law design variables are derived analytically and computed by solving a set of discrete Liapunov equations. The designer can choose the structure of the control law and the design variables, hence a stable classical control law as well as an estimator-based full or reduced order control law can be used as an initial starting point. Selected design responses can be treated as constraints instead of lumping them into the cost function. This feature can be used to modify a control law, to meet individual root mean square response limitations as well as minimum single value restrictions. Low order, robust digital control laws were synthesized for gust load alleviation of a flexible remotely piloted drone aircraft.

Parametric Optimization of Thermoelectric Generators for Waste Heat Recovery

NASA Astrophysics Data System (ADS)

Huang, Shouyuan; Xu, Xianfan

2016-10-01

This paper presents a methodology for design optimization of thermoelectric-based waste heat recovery systems called thermoelectric generators (TEGs). The aim is to maximize the power output from thermoelectrics which are used as add-on modules to an existing gas-phase heat exchanger, without negative impacts, e.g., maintaining a minimum heat dissipation rate from the hot side. A numerical model is proposed for TEG coupled heat transfer and electrical power output. This finite-volume-based model simulates different types of heat exchangers, i.e., counter-flow and cross-flow, for TEGs. Multiple-filled skutterudites and bismuth-telluride-based thermoelectric modules (TEMs) are applied, respectively, in higher and lower temperature regions. The response surface methodology is implemented to determine the optimized TEG size along and across the flow direction and the height of thermoelectric couple legs, and to analyze their covariance and relative sensitivity. A genetic algorithm is employed to verify the globality of the optimum. The presented method will be generally useful for optimizing heat-exchanger-based TEG performance.

The Climate Response to Stratospheric Aerosol Geoengineering Can Be Tailored Using Multiple Injection Locations

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

MacMartin, Douglas G.; Kravitz, Ben; Tilmes, Simone

The climate response to geoengineering with stratospheric aerosols has the potential to be designed to achieve some chosen objectives. By injecting different amounts of SO2 at multiple different latitudes, the spatial pattern of aerosol optical depth (AOD) can be partially controlled. We use simulations from the fully-coupled whole-atmosphere chemistry-climate model CESM1(WACCM), to demonstrate that three spatial degrees of freedom of AOD can be achieved by appropriately combining injection at different locations: an approximately spatially-uniform AOD distribution, the relative difference in AOD between Northern and Southern hemispheres, and the relative AOD in high versus low latitudes. For forcing levels that yieldmore » 1–2°C cooling, the AOD and surface temperature response are sufficiently linear in this model so that many climate effects can be predicted from single-latitude injection simulations. Optimized injection at multiple locations is predicted to improve compensation of CO2-forced climate change, relative to a case using only equatorial aerosol injection. The additional degrees of freedom can be used, for example, to balance interhemispheric temperature differences and the equator to pole temperature difference in addition to the global mean temperature; this is projected in this model to reduce the mean-square error in temperature compensation by 30%.« less

Bayesian Dose-Response Modeling in Sparse Data

NASA Astrophysics Data System (ADS)

Kim, Steven B.

This book discusses Bayesian dose-response modeling in small samples applied to two different settings. The first setting is early phase clinical trials, and the second setting is toxicology studies in cancer risk assessment. In early phase clinical trials, experimental units are humans who are actual patients. Prior to a clinical trial, opinions from multiple subject area experts are generally more informative than the opinion of a single expert, but we may face a dilemma when they have disagreeing prior opinions. In this regard, we consider compromising the disagreement and compare two different approaches for making a decision. In addition to combining multiple opinions, we also address balancing two levels of ethics in early phase clinical trials. The first level is individual-level ethics which reflects the perspective of trial participants. The second level is population-level ethics which reflects the perspective of future patients. We extensively compare two existing statistical methods which focus on each perspective and propose a new method which balances the two conflicting perspectives. In toxicology studies, experimental units are living animals. Here we focus on a potential non-monotonic dose-response relationship which is known as hormesis. Briefly, hormesis is a phenomenon which can be characterized by a beneficial effect at low doses and a harmful effect at high doses. In cancer risk assessments, the estimation of a parameter, which is known as a benchmark dose, can be highly sensitive to a class of assumptions, monotonicity or hormesis. In this regard, we propose a robust approach which considers both monotonicity and hormesis as a possibility. In addition, We discuss statistical hypothesis testing for hormesis and consider various experimental designs for detecting hormesis based on Bayesian decision theory. Past experiments have not been optimally designed for testing for hormesis, and some Bayesian optimal designs may not be optimal under a wrong parametric assumption. In this regard, we consider a robust experimental design which does not require any parametric assumption.

Optimization of Residual Stresses in MMC's Using Compensating/Compliant Interfacial Layers. Part 2: OPTCOMP User's Guide

NASA Technical Reports Server (NTRS)

Pindera, Marek-Jerzy; Salzar, Robert S.; Williams, Todd O.

1994-01-01

A user's guide for the computer program OPTCOMP is presented in this report. This program provides a capability to optimize the fabrication or service-induced residual stresses in uni-directional metal matrix composites subjected to combined thermo-mechanical axisymmetric loading using compensating or compliant layers at the fiber/matrix interface. The user specifies the architecture and the initial material parameters of the interfacial region, which can be either elastic or elastoplastic, and defines the design variables, together with the objective function, the associated constraints and the loading history through a user-friendly data input interface. The optimization procedure is based on an efficient solution methodology for the elastoplastic response of an arbitrarily layered multiple concentric cylinder model that is coupled to the commercial optimization package DOT. The solution methodology for the arbitrarily layered cylinder is based on the local-global stiffness matrix formulation and Mendelson's iterative technique of successive elastic solutions developed for elastoplastic boundary-value problems. The optimization algorithm employed in DOT is based on the method of feasible directions.

Responsive Surface Methodology Optimizes Extraction Conditions of Industrial by-products, Camellia japonica Seed Cake

PubMed Central

Kim, Jae Kyeom; Lim, Ho-Jeong; Kim, Mi-So; Choi, Soo Jung; Kim, Mi-Jeong; Kim, Cho Rong; Shin, Dong-Hoon; Shin, Eui-Cheol

2016-01-01

Background: The central nervous system is easily damaged by oxidative stress due to high oxygen consumption and poor defensive capacity. Hence, multiple studies have demonstrated that inhibiting oxidative stress-induced damage, through an antioxidant-rich diet, might be a reasonable approach to prevent neurodegenerative disease. Objective: In the present study, response surface methodology was utilized to optimize the extraction for neuro-protective constituents of Camellia japonica byproducts. Materials and Methods: Rat pheochromocytoma cells were used to evaluate protective potential of Camellia japonica byproducts. Results: Optimum conditions were 33.84 min, 75.24%, and 75.82°C for time, ethanol concentration and temperature. Further, we demonstrated that major organic acid contents were significantly impacted by the extraction conditions, which may explain varying magnitude of protective potential between fractions. Conclusions: Given the paucity of information in regards to defatted C. japonica seed cake and their health promoting potential, our results herein provide interesting preliminary data for utilization of this byproduct from oil processing in both academic and industrial applications. SUMMARY Neuro-protective potential of C. japonica seed cake on cell viability was affected by extraction conditionsExtraction conditions effectively influenced on active constituents of C. japonica seed cakeBiological activity of C. japonica seed cake was optimized by the responsive surface methodology. Abbreviations used: GC-MS: Gas chromatography-mass spectrometer, MTT: 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, PC12 cells: Pheochromocytoma, RSM: Response surface methodology. PMID:27601847

Highly efficient multiple-layer CdS quantum dot sensitized III-V solar cells.

PubMed

Lin, Chien-Chung; Han, Hau-Vei; Chen, Hsin-Chu; Chen, Kuo-Ju; Tsai, Yu-Lin; Lin, Wein-Yi; Kuo, Hao-Chung; Yu, Peichen

2014-02-01

In this review, the concept of utilization of solar spectrum in order to increase the solar cell efficiency is discussed. Among the three mechanisms, down-shifting effect is investigated in detail. Organic dye, rare-earth minerals and quantum dots are three most popular down-shift materials. While the enhancement of solar cell efficiency was not clearly observed in the past, the advances in quantum dot fabrication have brought strong response out of the hybrid platform of a quantum dot solar cell. A multiple layer structure, including PDMS as the isolation layer, is proposed and demonstrated. With the help of pulse spray system, precise control can be achieved and the optimized concentration can be found.

Considering baseline factors and early response rates to optimize therapy for chronic myeloid leukemia in chronic phase.

PubMed

Akard, Luke P; Bixby, Dale

2016-05-01

Multiple BCR-ABL tyrosine kinase inhibitors (TKIs) are available for the treatment of chronic myeloid leukemia in chronic phase (CML-CP), and several baseline and on-treatment predictive factors have been identified that can be used to help guide TKI selection for individual patients. In particular, early molecular response (EMR; BCR-ABL ≤10% on the International Scale at 3 months) has become an accepted benchmark for evaluating whether patients with CML-CP are responding optimally to frontline TKI therapy. Failure to achieve EMR is considered an inadequate initial response according to the National Comprehensive Cancer Network guidelines and a warning response according to the European LeukemiaNet recommendations. Here we review data supporting the importance of achieving EMR for improving patients' long-term outcomes and discuss key considerations for selecting a frontline TKI in light of these data. Because a higher proportion of patients achieve EMR with second-generation TKIs such as nilotinib and dasatinib than with imatinib, these TKIs may be preferable for many patients, particularly those with known negative prognostic factors at baseline. We also discuss other considerations for frontline TKI choice, including toxicities, cost-effectiveness, and the emerging goals of deep molecular response and treatment-free remission.

Design of clinical trials involving multiple hypothesis tests with a common control.

PubMed

Schou, I Manjula; Marschner, Ian C

2017-07-01

Randomized clinical trials comparing several treatments to a common control are often reported in the medical literature. For example, multiple experimental treatments may be compared with placebo, or in combination therapy trials, a combination therapy may be compared with each of its constituent monotherapies. Such trials are typically designed using a balanced approach in which equal numbers of individuals are randomized to each arm, however, this can result in an inefficient use of resources. We provide a unified framework and new theoretical results for optimal design of such single-control multiple-comparator studies. We consider variance optimal designs based on D-, A-, and E-optimality criteria, using a general model that allows for heteroscedasticity and a range of effect measures that include both continuous and binary outcomes. We demonstrate the sensitivity of these designs to the type of optimality criterion by showing that the optimal allocation ratios are systematically ordered according to the optimality criterion. Given this sensitivity to the optimality criterion, we argue that power optimality is a more suitable approach when designing clinical trials where testing is the objective. Weighted variance optimal designs are also discussed, which, like power optimal designs, allow the treatment difference to play a major role in determining allocation ratios. We illustrate our methods using two real clinical trial examples taken from the medical literature. Some recommendations on the use of optimal designs in single-control multiple-comparator trials are also provided. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamic Resource Allocation in Disaster Response: Tradeoffs in Wildfire Suppression

PubMed Central

Petrovic, Nada; Alderson, David L.; Carlson, Jean M.

2012-01-01

Challenges associated with the allocation of limited resources to mitigate the impact of natural disasters inspire fundamentally new theoretical questions for dynamic decision making in coupled human and natural systems. Wildfires are one of several types of disaster phenomena, including oil spills and disease epidemics, where (1) the disaster evolves on the same timescale as the response effort, and (2) delays in response can lead to increased disaster severity and thus greater demand for resources. We introduce a minimal stochastic process to represent wildfire progression that nonetheless accurately captures the heavy tailed statistical distribution of fire sizes observed in nature. We then couple this model for fire spread to a series of response models that isolate fundamental tradeoffs both in the strength and timing of response and also in division of limited resources across multiple competing suppression efforts. Using this framework, we compute optimal strategies for decision making scenarios that arise in fire response policy. PMID:22514605

Light history modulates antioxidant and photosynthetic responses of biofilms to both natural (light) and chemical (herbicides) stressors.

PubMed

Bonnineau, Chloé; Sague, Irene Gallardo; Urrea, Gemma; Guasch, Helena

2012-05-01

In multiple stress situations, the co-occurrence of environmental and chemical factors can influence organisms' ability to cope with toxicity. In this context, the influence of light adaptation on the response of freshwater biofilms to sudden light changes or to herbicides exposure was investigated by determining various parameters: diatom community composition, photosynthetic parameters, chlorophyll a content, antioxidant enzyme activities. Biofilms were grown in microcosms under sub-optimal, saturating, and high light intensities and showed already described characteristics of shade/light adaptation (community structure, photosynthetic adaptation, etc.). Light history modulated antioxidant and photosynthetic responses of biofilms to the stress caused by short-term exposure to sudden light changes or to herbicides. First biofilms adapted to sub-optimal light intensity (shade-adapted) were found to be more sensitive to an increase in light intensity than high-light adapted ones to a reduction in light intensity. Second, while light history influenced biofilms' response to glyphosate, it had little influence on biofilms' response to copper and none on its response to oxyfluorfen. Indeed glyphosate exposure led to a stronger decrease in photosynthetic efficiency of shade-adapted biofilms (EC(50) = 11.7 mg L(-1)) than of high-light adapted communities (EC(50) = 35.6 mg L(-1)). Copper exposure led to an activation of ascorbate peroxidase (APX) in biofilms adapted to sub-optimal and saturating light intensity while the protein content decreased in all biofilms exposed to copper. Oxyfluorfen toxicity was independent of light history provoking an increase in APX activity. In conclusion this study showed that both previous exposure to contaminants and physical habitat characteristics might influence community tolerance to disturbances strongly.

Hybrid optimization and Bayesian inference techniques for a non-smooth radiation detection problem

DOE PAGES

Stefanescu, Razvan; Schmidt, Kathleen; Hite, Jason; ...

2016-12-12

In this paper, we propose several algorithms to recover the location and intensity of a radiation source located in a simulated 250 × 180 m block of an urban center based on synthetic measurements. Radioactive decay and detection are Poisson random processes, so we employ likelihood functions based on this distribution. Owing to the domain geometry and the proposed response model, the negative logarithm of the likelihood is only piecewise continuous differentiable, and it has multiple local minima. To address these difficulties, we investigate three hybrid algorithms composed of mixed optimization techniques. For global optimization, we consider simulated annealing, particlemore » swarm, and genetic algorithm, which rely solely on objective function evaluations; that is, they do not evaluate the gradient in the objective function. By employing early stopping criteria for the global optimization methods, a pseudo-optimum point is obtained. This is subsequently utilized as the initial value by the deterministic implicit filtering method, which is able to find local extrema in non-smooth functions, to finish the search in a narrow domain. These new hybrid techniques, combining global optimization and implicit filtering address, difficulties associated with the non-smooth response, and their performances, are shown to significantly decrease the computational time over the global optimization methods. To quantify uncertainties associated with the source location and intensity, we employ the delayed rejection adaptive Metropolis and DiffeRential Evolution Adaptive Metropolis algorithms. Finally, marginal densities of the source properties are obtained, and the means of the chains compare accurately with the estimates produced by the hybrid algorithms.« less

Optimal Implementations for Reliable Circadian Clocks

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko; Arita, Masanori

2014-09-01

Circadian rhythms are acquired through evolution to increase the chances for survival through synchronizing with the daylight cycle. Reliable synchronization is realized through two trade-off properties: regularity to keep time precisely, and entrainability to synchronize the internal time with daylight. We find by using a phase model with multiple inputs that achieving the maximal limit of regularity and entrainability entails many inherent features of the circadian mechanism. At the molecular level, we demonstrate the role sharing of two light inputs, phase advance and delay, as is well observed in mammals. At the behavioral level, the optimal phase-response curve inevitably contains a dead zone, a time during which light pulses neither advance nor delay the clock. We reproduce the results of phase-controlling experiments entrained by two types of periodic light pulses. Our results indicate that circadian clocks are designed optimally for reliable clockwork through evolution.

On the placement of active members in adaptive truss structures for vibration control

NASA Technical Reports Server (NTRS)

Lu, L.-Y.; Utku, S.; Wada, B. K.

1992-01-01

The problem of optimal placement of active members which are used for vibration control in adaptive truss structures is investigated. The control scheme is based on the method of eigenvalue assignment as a means of shaping the transient response of the controlled adaptive structures, and the minimization of required control action is considered as the optimization criterion. To this end, a performance index which measures the control strokes of active members is formulated in an efficient way. In order to reduce the computation burden, particularly for the case where the locations of active members have to be selected from a large set of available sites, several heuristic searching schemes are proposed for obtaining the near-optimal locations. The proposed schemes significantly reduce the computational complexity of placing multiple active members to the order of that when a single active member is placed.

Optimization of Medium Composition for the Production of Neomycin by Streptomyces fradiae NCIM 2418 in Solid State Fermentation

PubMed Central

Vastrad, B. M.; Neelagund, S. E.

2014-01-01

Neomycin production of Streptomyces fradiae NCIM 2418 was optimized by using response surface methodology (RSM), which is powerful mathematical approach comprehensively applied in the optimization of solid state fermentation processes. In the first step of optimization, with Placket-Burman design, ammonium chloride, sodium nitrate, L-histidine, and ammonium nitrate were established to be the crucial nutritional factors affecting neomycin production significantly. In the second step, a 24 full factorial central composite design and RSM were applied to determine the optimal concentration of significant variable. A second-order polynomial was determined by the multiple regression analysis of the experimental data. The optimum values for the important nutrients for the maximum were obtained as follows: ammonium chloride 2.00%, sodium nitrate 1.50%, L-histidine 0.250%, and ammonium nitrate 0.250% with a predicted value of maximum neomycin production of 20,000 g kg−1 dry coconut oil cake. Under the optimal condition, the practical neomycin production was 19,642 g kg−1 dry coconut oil cake. The determination coefficient (R 2) was 0.9232, which ensures an acceptable admissibility of the model. PMID:25009746

Improvement in latent variable indirect response modeling of multiple categorical clinical endpoints: application to modeling of guselkumab treatment effects in psoriatic patients.

PubMed

Hu, Chuanpu; Randazzo, Bruce; Sharma, Amarnath; Zhou, Honghui

2017-10-01

Exposure-response modeling plays an important role in optimizing dose and dosing regimens during clinical drug development. The modeling of multiple endpoints is made possible in part by recent progress in latent variable indirect response (IDR) modeling for ordered categorical endpoints. This manuscript aims to investigate the level of improvement achievable by jointly modeling two such endpoints in the latent variable IDR modeling framework through the sharing of model parameters. This is illustrated with an application to the exposure-response of guselkumab, a human IgG1 monoclonal antibody in clinical development that blocks IL-23. A Phase 2b study was conducted in 238 patients with psoriasis for which disease severity was assessed using Psoriasis Area and Severity Index (PASI) and Physician's Global Assessment (PGA) scores. A latent variable Type I IDR model was developed to evaluate the therapeutic effect of guselkumab dosing on 75, 90 and 100% improvement of PASI scores from baseline and PGA scores, with placebo effect empirically modeled. The results showed that the joint model is able to describe the observed data better with fewer parameters compared with the common approach of separately modeling the endpoints.

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

NASA Technical Reports Server (NTRS)

Shyy, Wei; Papila, Nilay; Vaidyanathan, Rajkumar; Tucker, Kevin; Turner, James E. (Technical Monitor)

2000-01-01

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Optimization of operating parameters in polysilicon chemical vapor deposition reactor with response surface methodology

NASA Astrophysics Data System (ADS)

An, Li-sha; Liu, Chun-jiao; Liu, Ying-wen

2018-05-01

In the polysilicon chemical vapor deposition reactor, the operating parameters are complex to affect the polysilicon's output. Therefore, it is very important to address the coupling problem of multiple parameters and solve the optimization in a computationally efficient manner. Here, we adopted Response Surface Methodology (RSM) to analyze the complex coupling effects of different operating parameters on silicon deposition rate (R) and further achieve effective optimization of the silicon CVD system. Based on finite numerical experiments, an accurate RSM regression model is obtained and applied to predict the R with different operating parameters, including temperature (T), pressure (P), inlet velocity (V), and inlet mole fraction of H2 (M). The analysis of variance is conducted to describe the rationality of regression model and examine the statistical significance of each factor. Consequently, the optimum combination of operating parameters for the silicon CVD reactor is: T = 1400 K, P = 3.82 atm, V = 3.41 m/s, M = 0.91. The validation tests and optimum solution show that the results are in good agreement with those from CFD model and the deviations of the predicted values are less than 4.19%. This work provides a theoretical guidance to operate the polysilicon CVD process.

The extraction process optimization of antioxidant polysaccharides from Marshmallow (Althaea officinalis L.) roots.

PubMed

Pakrokh Ghavi, Peyman

2015-04-01

Response surface methodology (RSM) with a central composite rotatable design (CCRD) based on five levels was employed to model and optimize four experimental operating conditions of extraction temperature (10-90 °C) and time (6-30 h), particle size (6-24 mm) and water to solid (W/S, 10-50) ratio, obtaining polysaccharides from Althaea officinalis roots with high yield and antioxidant activity. For each response, a second-order polynomial model with high R(2) values (> 0.966) was developed using multiple linear regression analysis. Results showed that the most significant (P < 0.05) extraction conditions that affect the yield and antioxidant activity of extracted polysaccharides were the main effect of extraction temperature and the interaction effect of the particle size and W/S ratio. The optimum conditions to maximize yield (10.80%) and antioxidant activity (84.09%) for polysaccharides extraction from A. officinalis roots were extraction temperature 60.90 °C, extraction time 12.01 h, particle size 12.0mm and W/S ratio of 40.0. The experimental values were found to be in agreement with those predicted, indicating the models suitability for optimizing the polysaccharides extraction conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

Ultrasonic-assisted extraction and in-vitro antioxidant activity of polysaccharide from Hibiscus leaf.

PubMed

Afshari, Kasra; Samavati, Vahid; Shahidi, Seyed-Ahmad

2015-03-01

The effects of ultrasonic power, extraction time, extraction temperature, and the water-to-raw material ratio on extraction yield of crude polysaccharide from the leaf of Hibiscus rosa-sinensis (HRLP) were optimized by statistical analysis using response surface methodology. The response surface methodology (RSM) was used to optimize HRLP extraction yield by implementing the Box-Behnken design (BBD). The experimental data obtained were fitted to a second-order polynomial equation using multiple regression analysis and also analyzed by appropriate statistical methods (ANOVA). Analysis of the results showed that the linear and quadratic terms of these four variables had significant effects. The optimal conditions for the highest extraction yield of HRLP were: ultrasonic power, 93.59 W; extraction time, 25.71 min; extraction temperature, 93.18°C; and the water to raw material ratio, 24.3 mL/g. Under these conditions, the experimental yield was 9.66±0.18%, which is well in close agreement with the value predicted by the model 9.526%. The results demonstrated that HRLP had strong scavenging activities in vitro on DPPH and hydroxyl radicals. Copyright © 2014 Elsevier B.V. All rights reserved.

Structural Optimization of a Force Balance Using a Computational Experiment Design

NASA Technical Reports Server (NTRS)

Parker, P. A.; DeLoach, R.

2002-01-01

This paper proposes a new approach to force balance structural optimization featuring a computational experiment design. Currently, this multi-dimensional design process requires the designer to perform a simplification by executing parameter studies on a small subset of design variables. This one-factor-at-a-time approach varies a single variable while holding all others at a constant level. Consequently, subtle interactions among the design variables, which can be exploited to achieve the design objectives, are undetected. The proposed method combines Modern Design of Experiments techniques to direct the exploration of the multi-dimensional design space, and a finite element analysis code to generate the experimental data. To efficiently search for an optimum combination of design variables and minimize the computational resources, a sequential design strategy was employed. Experimental results from the optimization of a non-traditional force balance measurement section are presented. An approach to overcome the unique problems associated with the simultaneous optimization of multiple response criteria is described. A quantitative single-point design procedure that reflects the designer's subjective impression of the relative importance of various design objectives, and a graphical multi-response optimization procedure that provides further insights into available tradeoffs among competing design objectives are illustrated. The proposed method enhances the intuition and experience of the designer by providing new perspectives on the relationships between the design variables and the competing design objectives providing a systematic foundation for advancements in structural design.

Coastal aquifer management under parameter uncertainty: Ensemble surrogate modeling based simulation-optimization

NASA Astrophysics Data System (ADS)

Janardhanan, S.; Datta, B.

2011-12-01

Surrogate models are widely used to develop computationally efficient simulation-optimization models to solve complex groundwater management problems. Artificial intelligence based models are most often used for this purpose where they are trained using predictor-predictand data obtained from a numerical simulation model. Most often this is implemented with the assumption that the parameters and boundary conditions used in the numerical simulation model are perfectly known. However, in most practical situations these values are uncertain. Under these circumstances the application of such approximation surrogates becomes limited. In our study we develop a surrogate model based coupled simulation optimization methodology for determining optimal pumping strategies for coastal aquifers considering parameter uncertainty. An ensemble surrogate modeling approach is used along with multiple realization optimization. The methodology is used to solve a multi-objective coastal aquifer management problem considering two conflicting objectives. Hydraulic conductivity and the aquifer recharge are considered as uncertain values. Three dimensional coupled flow and transport simulation model FEMWATER is used to simulate the aquifer responses for a number of scenarios corresponding to Latin hypercube samples of pumping and uncertain parameters to generate input-output patterns for training the surrogate models. Non-parametric bootstrap sampling of this original data set is used to generate multiple data sets which belong to different regions in the multi-dimensional decision and parameter space. These data sets are used to train and test multiple surrogate models based on genetic programming. The ensemble of surrogate models is then linked to a multi-objective genetic algorithm to solve the pumping optimization problem. Two conflicting objectives, viz, maximizing total pumping from beneficial wells and minimizing the total pumping from barrier wells for hydraulic control of saltwater intrusion are considered. The salinity levels resulting at strategic locations due to these pumping are predicted using the ensemble surrogates and are constrained to be within pre-specified levels. Different realizations of the concentration values are obtained from the ensemble predictions corresponding to each candidate solution of pumping. Reliability concept is incorporated as the percent of the total number of surrogate models which satisfy the imposed constraints. The methodology was applied to a realistic coastal aquifer system in Burdekin delta area in Australia. It was found that all optimal solutions corresponding to a reliability level of 0.99 satisfy all the constraints and as reducing reliability level decreases the constraint violation increases. Thus ensemble surrogate model based simulation-optimization was found to be useful in deriving multi-objective optimal pumping strategies for coastal aquifers under parameter uncertainty.

Intracellular response to process optimization and impact on productivity and product aggregates for a high-titer CHO cell process.

PubMed

Handlogten, Michael W; Lee-O'Brien, Allison; Roy, Gargi; Levitskaya, Sophia V; Venkat, Raghavan; Singh, Shailendra; Ahuja, Sanjeev

2018-01-01

A key goal in process development for antibodies is to increase productivity while maintaining or improving product quality. During process development of an antibody, titers were increased from 4 to 10 g/L while simultaneously decreasing aggregates. Process development involved optimization of media and feed formulations, feed strategy, and process parameters including pH and temperature. To better understand how CHO cells respond to process changes, the changes were implemented in a stepwise manner. The first change was an optimization of the feed formulation, the second was an optimization of the medium, and the third was an optimization of process parameters. Multiple process outputs were evaluated including cell growth, osmolality, lactate production, ammonium concentration, antibody production, and aggregate levels. Additionally, detailed assessment of oxygen uptake, nutrient and amino acid consumption, extracellular and intracellular redox environment, oxidative stress, activation of the unfolded protein response (UPR) pathway, protein disulfide isomerase (PDI) expression, and heavy and light chain mRNA expression provided an in-depth understanding of the cellular response to process changes. The results demonstrate that mRNA expression and UPR activation were unaffected by process changes, and that increased PDI expression and optimized nutrient supplementation are required for higher productivity processes. Furthermore, our findings demonstrate the role of extra- and intracellular redox environment on productivity and antibody aggregation. Processes using the optimized medium, with increased concentrations of redox modifying agents, had the highest overall specific productivity, reduced aggregate levels, and helped cells better withstand the high levels of oxidative stress associated with increased productivity. Specific productivities of different processes positively correlated to average intracellular values of total glutathione. Additionally, processes with the optimized media maintained an oxidizing intracellular environment, important for correct disulfide bond pairing, which likely contributed to reduced aggregate formation. These findings shed important understanding into how cells respond to process changes and can be useful to guide future development efforts to enhance productivity and improve product quality. © 2017 Wiley Periodicals, Inc.

Optimizing the Performance of Radionuclide Identification Software in the Hunt for Nuclear Security Threats

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

Fotion, Katherine A.

2016-08-18

The Radionuclide Analysis Kit (RNAK), my team’s most recent nuclide identification software, is entering the testing phase. A question arises: will removing rare nuclides from the software’s library improve its overall performance? An affirmative response indicates fundamental errors in the software’s framework, while a negative response confirms the effectiveness of the software’s key machine learning algorithms. After thorough testing, I found that the performance of RNAK cannot be improved with the library choice effect, thus verifying the effectiveness of RNAK’s algorithms—multiple linear regression, Bayesian network using the Viterbi algorithm, and branch and bound search.

Linear System Control Using Stochastic Learning Automata

NASA Technical Reports Server (NTRS)

Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.

1998-01-01

This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.

An expanded genetic code in mammalian cells with a functional quadruplet codon.

PubMed

Niu, Wei; Schultz, Peter G; Guo, Jiantao

2013-07-19

We have utilized in vitro evolution to identify tRNA variants with significantly enhanced activity for the incorporation of unnatural amino acids into proteins in response to a quadruplet codon in both bacterial and mammalian cells. This approach will facilitate the creation of an optimized and standardized system for the genetic incorporation of unnatural amino acids using quadruplet codons, which will allow the biosynthesis of biopolymers that contain multiple unnatural building blocks.

Adaptive iterative design (AID): a novel approach for evaluating the interactive effects of multiple stressors on aquatic organisms.

PubMed

Glaholt, Stephen P; Chen, Celia Y; Demidenko, Eugene; Bugge, Deenie M; Folt, Carol L; Shaw, Joseph R

2012-08-15

The study of stressor interactions by eco-toxicologists using nonlinear response variables is limited by required amounts of a priori knowledge, complexity of experimental designs, the use of linear models, and the lack of use of optimal designs of nonlinear models to characterize complex interactions. Therefore, we developed AID, an adaptive-iterative design for eco-toxicologist to more accurately and efficiently examine complex multiple stressor interactions. AID incorporates the power of the general linear model and A-optimal criteria with an iterative process that: 1) minimizes the required amount of a priori knowledge, 2) simplifies the experimental design, and 3) quantifies both individual and interactive effects. Once a stable model is determined, the best fit model is identified and the direction and magnitude of stressors, individually and all combinations (including complex interactions) are quantified. To validate AID, we selected five commonly co-occurring components of polluted aquatic systems, three metal stressors (Cd, Zn, As) and two water chemistry parameters (pH, hardness) to be tested using standard acute toxicity tests in which Daphnia mortality is the (nonlinear) response variable. We found after the initial data input of experimental data, although literature values (e.g. EC-values) may also be used, and after only two iterations of AID, our dose response model was stable. The model ln(Cd)*ln(Zn) was determined the best predictor of Daphnia mortality response to the combined effects of Cd, Zn, As, pH, and hardness. This model was then used to accurately identify and quantify the strength of both greater- (e.g. As*Cd) and less-than additive interactions (e.g. Cd*Zn). Interestingly, our study found only binary interactions significant, not higher order interactions. We conclude that AID is more efficient and effective at assessing multiple stressor interactions than current methods. Other applications, including life-history endpoints commonly used by regulators, could benefit from AID's efficiency in assessing water quality criteria. Copyright © 2012 Elsevier B.V. All rights reserved.

Immunosurveillance and therapy of multiple myeloma are CD226 dependent

PubMed Central

Guillerey, Camille; Ferrari de Andrade, Lucas; Vuckovic, Slavica; Miles, Kim; Ngiow, Shin Foong; Yong, Michelle C.R.; Teng, Michele W.L.; Colonna, Marco; Ritchie, David S.; Chesi, Martha; Bergsagel, P. Leif; Hill, Geoffrey R.; Smyth, Mark J.; Martinet, Ludovic

2015-01-01

Multiple myeloma (MM) is an age-dependent hematological malignancy. Evaluation of immune interactions that drive MM relies on in vitro experiments that do not reflect the complex cellular stroma involved in MM pathogenesis. Here we used Vk*MYC transgenic mice, which spontaneously develop MM, and demonstrated that the immune system plays a critical role in the control of MM progression and the response to treatment. We monitored Vk*MYC mice that had been crossed with Cd226 mutant mice over a period of 3 years and found that CD226 limits spontaneous MM development. The CD226-dependent anti-myeloma immune response against transplanted Vk*MYC MM cells was mediated both by NK and CD8+ T cells through perforin and IFN-γ pathways. Moreover, CD226 expression was required for optimal antimyeloma efficacy of cyclophosphamide (CTX) and bortezomib (Btz), which are both standardly used to manage MM in patients. Activation of costimulatory receptor CD137 with mAb (4-1BB) exerted strong antimyeloma activity, while inhibition of coinhibitory receptors PD-1 and CTLA-4 had no effect. Taken together, the results of this study provide in vivo evidence that CD226 is important for MM immunosurveillance and indicate that specific immune components should be targeted for optimal MM treatment efficacy. As progressive immunosuppression associates with MM development, strategies aimed to increase immune functions may have important therapeutic implications in MM. PMID:25893601

MIMO radar waveform design with peak and sum power constraints

NASA Astrophysics Data System (ADS)

Arulraj, Merline; Jeyaraman, Thiruvengadam S.

2013-12-01

Optimal power allocation for multiple-input multiple-output radar waveform design subject to combined peak and sum power constraints using two different criteria is addressed in this paper. The first one is by maximizing the mutual information between the random target impulse response and the reflected waveforms, and the second one is by minimizing the mean square error in estimating the target impulse response. It is assumed that the radar transmitter has knowledge of the target's second-order statistics. Conventionally, the power is allocated to transmit antennas based on the sum power constraint at the transmitter. However, the wide power variations across the transmit antenna pose a severe constraint on the dynamic range and peak power of the power amplifier at each antenna. In practice, each antenna has the same absolute peak power limitation. So it is desirable to consider the peak power constraint on the transmit antennas. A generalized constraint that jointly meets both the peak power constraint and the average sum power constraint to bound the dynamic range of the power amplifier at each transmit antenna is proposed recently. The optimal power allocation using the concept of waterfilling, based on the sum power constraint, is the special case of p = 1. The optimal solution for maximizing the mutual information and minimizing the mean square error is obtained through the Karush-Kuhn-Tucker (KKT) approach, and the numerical solutions are found through a nested Newton-type algorithm. The simulation results show that the detection performance of the system with both sum and peak power constraints gives better detection performance than considering only the sum power constraint at low signal-to-noise ratio.

Optimization of multiple quality characteristics in bone drilling using grey relational analysis

PubMed Central

Pandey, Rupesh Kumar; Panda, Sudhansu Sekhar

2014-01-01

Purpose Drilling of bone is common during bone fracture treatment to fix the fractured parts with screws wires or plates. Minimally invasive drilling of the bone has a great demand as it helps in better fixation and quick healing of the broken bones. The purpose of the present investigation is to determine the optimum cutting condition for the minimization of the temperature, force and surface roughness simultaneously during bone drilling. Method In this study, drilling experiments have been performed on bovine bone with different conditions of feed rate and drill rotational speed using full factorial design. Optimal level of the drilling parameters is determined by the grey relational grade (GRG) obtained from the GRA as the performance index of multiple quality characteristics. The effect of each drilling parameter on GRG is determined using analysis of variance (ANOVA) and the results obtained are validated by confirmation experiment. Results Grey relational analysis showed that the investigation with feed rate of 40 mm/min and spindle speed of 500 rpm has the highest grey relational grade and is recommended setting for minimum temperature, force and surface roughness simultaneously during bone drilling. Feed rate has the highest contribution (59.49%) on the multiple performance characteristics followed by the spindle speed (37.69%) as obtained from ANOVA analysis. Conclusions The use of grey relational analysis will simplify the complex process of optimization of the multi response characteristics in bone drilling by converting them into a single grey relational grade. The use of the above suggested methodology can greatly minimize the bone tissue injury during drilling. PMID:25829751

Optimization of multiple quality characteristics in bone drilling using grey relational analysis.

PubMed

Pandey, Rupesh Kumar; Panda, Sudhansu Sekhar

2015-03-01

Drilling of bone is common during bone fracture treatment to fix the fractured parts with screws wires or plates. Minimally invasive drilling of the bone has a great demand as it helps in better fixation and quick healing of the broken bones. The purpose of the present investigation is to determine the optimum cutting condition for the minimization of the temperature, force and surface roughness simultaneously during bone drilling. In this study, drilling experiments have been performed on bovine bone with different conditions of feed rate and drill rotational speed using full factorial design. Optimal level of the drilling parameters is determined by the grey relational grade (GRG) obtained from the GRA as the performance index of multiple quality characteristics. The effect of each drilling parameter on GRG is determined using analysis of variance (ANOVA) and the results obtained are validated by confirmation experiment. Grey relational analysis showed that the investigation with feed rate of 40 mm/min and spindle speed of 500 rpm has the highest grey relational grade and is recommended setting for minimum temperature, force and surface roughness simultaneously during bone drilling. Feed rate has the highest contribution (59.49%) on the multiple performance characteristics followed by the spindle speed (37.69%) as obtained from ANOVA analysis. The use of grey relational analysis will simplify the complex process of optimization of the multi response characteristics in bone drilling by converting them into a single grey relational grade. The use of the above suggested methodology can greatly minimize the bone tissue injury during drilling.

Pharmacogenetics of the β2-Adrenergic Receptor Gene

PubMed Central

Ortega, Victor E.; Hawkins, Gregory A.; Peters, Stephen P.; Bleecker, Eugene R.

2009-01-01

Asthma is a complex genetic disease with multiple genetic and environmental determinants contributing to the observed variability in response to common anti-asthma therapies. Asthma pharmacogenetic research has focused on multiple candidate genes including the β2-adrenergic receptor gene (ADRβ2) and its effect on individual responses to beta agonist therapy. At present, knowledge about the effects of ADRβ2 variation on therapeutic responses is evolving and should not alter current Asthma Guideline approaches consisting of the use of short acting beta agonists for as-needed symptom based therapy and the use of a regular long-acting beta agonist in combination with inhaled corticosteroid therapy for optimal control of asthma symptoms in those asthmatics who are not controlled on inhaled corticosteroid alone. This approach is based upon studies showing a consistent pharmacogenetic response to regular use of short acting beta agonists (SABA) and less consistent findings in studies evaluating long acting beta agonist (LABA). While emerging pharmacogenetic studies are provocative and should lead to functional approaches, conflicting data with responses to LABA therapy may be caused by factors that include small sample sizes of study populations and differences in experimental design that may limit the conclusions that may be drawn from these clinical trials at the present time. PMID:17996583

Intelligent fault recognition strategy based on adaptive optimized multiple centers

NASA Astrophysics Data System (ADS)

Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong

2018-06-01

For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.

Optimal go/no-go ratios to maximize false alarms.

PubMed

Young, Michael E; Sutherland, Steven C; McCoy, Anthony W

2018-06-01

Despite the ubiquity of go/no-go tasks in the study of behavioral inhibition, there is a lack of evidence regarding the impact of key design characteristics, including the go/no-go ratio, intertrial interval, and number of types of go stimuli, on the production of different response classes of central interest. In the present study we sought to empirically determine the optimal conditions to maximize the production of a rare outcome of considerable interest to researchers: false alarms. As predicted, the shortest intertrial intervals (450 ms), intermediate go/no-go ratios (2:1 to 4:1), and the use of multiple types of go stimuli produced the greatest numbers of false alarms. These results are placed within the context of behavioral changes during learning.

Isolation and characterization of hydrophobic compounds from carbohydrate matrix of Pistacia atlantica.

PubMed

Samavati, Vahid; Adeli, Mostafa

2014-01-30

The present work is focused on the optimization of hydrophobic compounds extraction process from the carbohydrate matrix of Iranian Pistacia atlantica seed at laboratory level using ultrasonic-assisted extraction. Response surface methodology (RSM) was used to optimize oil seed extraction yield. Independent variables were extraction temperature (30, 45, 60, 75 and 90°C), extraction time (10, 15, 20, 25, 30 and 35 min) and power of ultrasonic (20, 40, 60, 80 and 100 W). A second order polynomial equation was used to express the oil extraction yield as a function of independent variables. The responses and variables were fitted well to each other by multiple regressions. The optimum extraction conditions were as follows: extraction temperature of 75°C, extraction time of 25 min, and power of ultrasonic of 80 W. A comparison between seed oil composition extracted by ultrasonic waves under the optimum operating conditions determined by RSM for oil yield and by organic solvent was reported. Copyright © 2013 Elsevier Ltd. All rights reserved.

Experimental design for the optimization and robustness testing of a liquid chromatography tandem mass spectrometry method for the trace analysis of the potentially genotoxic 1,3-diisopropylurea.

PubMed

Székely, György; Henriques, Bruno; Gil, Marco; Alvarez, Carlos

2014-09-01

This paper discusses a design of experiments (DoE) assisted optimization and robustness testing of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method development for the trace analysis of the potentially genotoxic 1,3-diisopropylurea (IPU) impurity in mometasone furoate glucocorticosteroid. Compared to the conventional trial-and-error method development, DoE is a cost-effective and systematic approach to system optimization by which the effects of multiple parameters and parameter interactions on a given response are considered. The LC and MS factors were studied simultaneously: flow (F), gradient (G), injection volume (Vinj), cone voltage (E(con)), and collision energy (E(col)). The optimization was carried out with respect to four responses: separation of peaks (Sep), peak area (A(p)), length of the analysis (T), and the signal-to-noise ratio (S/N). An optimization central composite face (CCF) DoE was conducted leading to the early discovery of carry-over effect which was further investigated in order to establish the maximum injectable sample load. A second DoE was conducted in order to obtain the optimal LC-MS/MS method. As part of the validation of the obtained method, its robustness was determined by conducting a fractional factorial of resolution III DoE, wherein column temperature and quadrupole resolution were considered as additional factors. The method utilizes a common Phenomenex Gemini NX C-18 HPLC analytical column with electrospray ionization and a triple quadrupole mass detector in multiple reaction monitoring (MRM) mode, resulting in short analyses with a 10-min runtime. The high sensitivity and low limit of quantification (LOQ) was achieved by (1) MRM mode (instead of single ion monitoring) and (2) avoiding the drawbacks of derivatization (incomplete reaction and time-consuming sample preparation). Quantitatively, the DoE method development strategy resulted in the robust trace analysis of IPU at 1.25 ng/mL absolute concentration corresponding to 0.25 ppm LOQ in 5 g/l mometasone furoate glucocorticosteroid. Validation was carried out in a linear range of 0.25-10 ppm and presented a relative standard deviation (RSD) of 1.08% for system precision. Regarding IPU recovery in mometasone furoate, spiked samples produced recoveries between 96 and 109 % in the range of 0.25 to 2 ppm. Copyright © 2013 John Wiley & Sons, Ltd.

Multiple response optimization of the coagulation process for upgrading the quality of effluent from municipal wastewater treatment plant

NASA Astrophysics Data System (ADS)

Li, Na; Hu, Yi; Lu, Yong-Ze; Zeng, Raymond J.; Sheng, Guo-Ping

2016-05-01

To meet the high quality standard of receiving water, the coagulation process using polyferric chloride (PFC) was used to further improve the water quality of effluent from wastewater treatment plants. Uniform design (UD) coupled with response surface methodology (RSM) was adopted to assess the effects of the main influence factors: coagulant dosage, pH and basicity, on the removal of total organic carbon (TOC), NH4+-N and PO43--P. A desirability function approach was used to effectively optimize the coagulation process for the comprehensive removal of TOC, NH4+-N and PO43--P to upgrade the effluent quality in practical application. The optimized operating conditions were: dosage 28 mg/L, pH 8.5 and basicity 0.001. The corresponding removal efficiencies for TOC, NH4+-N and PO43--P were 77.2%, 94.6% and 20.8%, respectively. More importantly, the effluent quality could upgrade to surface water Class V of China through coagulation under optimal region. In addition, grey relational analysis (GRA) prioritized these three factors as: pH > basicity > dosage (for TOC), basicity > dosage > pH (for NH4+-N), pH > dosage > basicity (for PO43--P), which would help identify the most important factor to control the treatment efficiency of various effluent quality indexes by PFC coagulation.

Development of Pangasius steaks by improved sous-vide technology and its process optimization.

PubMed

Kumari, Namita; Singh, Chongtham Baru; Kumar, Raushan; Martin Xavier, K A; Lekshmi, Manjusha; Venkateshwarlu, Gudipati; Balange, Amjad K

2016-11-01

The present study embarked on the objective of optimizing improved sous - vide processing condition for development of ready-to-cook Pangasius steaks with extended shelf-life using response surface methodology. For the development of improved sous - vide cooked product, Pangasius steaks were treated with additional hurdles in various combinations for optimization. Based on the study, suitable combination of chitosan and spices was selected which enhanced antimicrobial and oxidative stability of the product. The Box-Behnken experimental design with 15 trials per model was adopted for designing the experiment to know the effect of independent variables, namely chitosan concentration (X 1 ), cooking time (X 2 ) and cooking temperature (X 3 ) on dependent variable i.e. TBARS value (Y 1 ). From RSM generated model, the optimum condition for sous - vide processing of Pangasius steaks were 1.08% chitosan concentration, 70.93 °C of cooking temperature and 16.48 min for cooking time and predicted minimum value of multiple response optimal condition was Y = 0.855 mg MDA/Kg of fish. The high correlation coefficient (R 2  = 0.975) between the model and the experimental data showed that the model was able to efficiently predict processing condition for development of sous - vide processed Pangasius steaks. This research may help the processing industries and Pangasius fish farmer as it provides an alternative low cost technology for the proper utilization of Pangasius .

Micropropagation and Biomass Production of True-to-Type Stevia rebaudiana Bertoni.

PubMed

Modi, Arpan R; Sharma, Vikas; Patil, Ghanshyam; Singh, Amritpal S; Subhash, N; Kumar, Nitish

2016-01-01

Here we describe an efficient micropropagation protocol for Stevia rebaudiana Bertoni. We present experiments carried out to optimize the suitable media for in vitro shoot multiplication and root induction and to study the effect of culture vessel on shoot multiplication. Among all different media tested for in vitro shoot multiplication, hormone-free liquid medium is most suitable. The highest number of nodes per shoot (5.4) and length of shoot (4.76 cm) at 4 weeks after subculturing are observed when single node explants are placed on modified MS medium supplemented with 1 % sucrose and 0.7 % agar. The highest response of multiplication rate (9.56) is observed on half strength of macroelement of MS with full strength of microelement of MS and 170 mg/l KH2PO4, and 185 mg/l MgSO4 in plastic growth container. Further, RAPD marker analysis of in vitro-raised plants maintained their clonal fidelity and true-to-type without showing any somaclonal variation.

Image-based tracking and sensor resource management for UAVs in an urban environment

NASA Astrophysics Data System (ADS)

Samant, Ashwin; Chang, K. C.

2010-04-01

Coordination and deployment of multiple unmanned air vehicles (UAVs) requires a lot of human resources in order to carry out a successful mission. The complexity of such a surveillance mission is significantly increased in the case of an urban environment where targets can easily escape from the UAV's field of view (FOV) due to intervening building and line-of-sight obstruction. In the proposed methodology, we focus on the control and coordination of multiple UAVs having gimbaled video sensor onboard for tracking multiple targets in an urban environment. We developed optimal path planning algorithms with emphasis on dynamic target prioritizations and persistent target updates. The command center is responsible for target prioritization and autonomous control of multiple UAVs, enabling a single operator to monitor and control a team of UAVs from a remote location. The results are obtained using extensive 3D simulations in Google Earth using Tangent plus Lyapunov vector field guidance for target tracking.

New pharmacotherapy options for multiple myeloma.

PubMed

Mina, Roberto; Cerrato, Chiara; Bernardini, Annalisa; Aghemo, Elena; Palumbo, Antonio

2016-01-01

Novel agents and the availability of autologous stem-cell transplantation have revolutionized the treatment of patients with multiple myeloma. First-generation novel agents namely thalidomide, lenalidomide, and bortezomib have significantly improved response and survival of patients. Second-generation novel agents such as pomalidomide, carfilzomib, and monoclonal antibodies are being tested both in the newly diagnosed and relapse settings, and results are promising. In this review article, the main results derived from Phase III trials with thalidomide, lenalidomide, and bortezomib for the treatment of myeloma patients, both at diagnosis and at relapse, are summarized. Data about second-generation novel agents such as pomalidomide and carfilzomib are also reported. Newer effective drugs currently under investigation and the promising results with monoclonal antibodies are described. The availability of new effective drugs has considerably increased the treatment options for myeloma patients. A sequential approach including induction, transplantation (when possible), consolidation, and maintenance is an optimal strategy to achieve disease control and prolong survival. Despite these improvements, the best combination, the optimal sequence, and the proper target of newer drugs need to be defined.

Neural Stem Cell Differentiation Using Microfluidic Device-Generated Growth Factor Gradient.

PubMed

Kim, Ji Hyeon; Sim, Jiyeon; Kim, Hyun-Jung

2018-04-11

Neural stem cells (NSCs) have the ability to self-renew and differentiate into multiple nervous system cell types. During embryonic development, the concentrations of soluble biological molecules have a critical role in controlling cell proliferation, migration, differentiation and apoptosis. In an effort to find optimal culture conditions for the generation of desired cell types in vitro , we used a microfluidic chip-generated growth factor gradient system. In the current study, NSCs in the microfluidic device remained healthy during the entire period of cell culture, and proliferated and differentiated in response to the concentration gradient of growth factors (epithermal growth factor and basic fibroblast growth factor). We also showed that overexpression of ASCL1 in NSCs increased neuronal differentiation depending on the concentration gradient of growth factors generated in the microfluidic gradient chip. The microfluidic system allowed us to study concentration-dependent effects of growth factors within a single device, while a traditional system requires multiple independent cultures using fixed growth factor concentrations. Our study suggests that the microfluidic gradient-generating chip is a powerful tool for determining the optimal culture conditions.

General Methodology for Designing Spacecraft Trajectories

NASA Technical Reports Server (NTRS)

Condon, Gerald; Ocampo, Cesar; Mathur, Ravishankar; Morcos, Fady; Senent, Juan; Williams, Jacob; Davis, Elizabeth C.

2012-01-01

A methodology for designing spacecraft trajectories in any gravitational environment within the solar system has been developed. The methodology facilitates modeling and optimization for problems ranging from that of a single spacecraft orbiting a single celestial body to that of a mission involving multiple spacecraft and multiple propulsion systems operating in gravitational fields of multiple celestial bodies. The methodology consolidates almost all spacecraft trajectory design and optimization problems into a single conceptual framework requiring solution of either a system of nonlinear equations or a parameter-optimization problem with equality and/or inequality constraints.

Ethical obligation for restricting the number of embryos transferred to women: combating the multiple-birth epidemic from in vitro fertilization.

PubMed

Van Voorhis, Bradley J; Ryan, Ginny L

2010-07-01

In vitro fertilization (IVF) is an increasingly effective and popular means of achieving pregnancy for infertile women, but contributes to a growing incidence of risky twin pregnancies. Despite studies demonstrating cost-effective means to achieve IVF pregnancy while strictly limiting the number of embryos transferred, multiple-embryo transfer remains the most common practice in the United States, and twin pregnancies continue to increase. IVF providers resist restricting these practices, arguing that this is counter to principles of procreative liberty, patient and professional autonomy, and free-market economics. We counter that physicians have a professional fiduciary responsibility to weigh issues of nonmaleficence to patients and just use of health care resources with patient desires. With oversight from professional organizations, providers should follow strict but medically appropriate restrictions on embryo transfer practices and work toward safer means of optimizing IVF outcomes than multiple-embryo transfer. Thieme Medical Publishers.

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

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

Cellular mechanisms contributing to multiple stress tolerance in Saccharomyces cerevisiae strains with potential use in high-temperature ethanol fermentation.

PubMed

Kitichantaropas, Yasin; Boonchird, Chuenchit; Sugiyama, Minetaka; Kaneko, Yoshinobu; Harashima, Satoshi; Auesukaree, Choowong

2016-12-01

High-temperature ethanol fermentation has several benefits including a reduction in cooling cost, minimizing risk of bacterial contamination, and enabling simultaneous saccharification and fermentation. To achieve the efficient ethanol fermentation at high temperature, yeast strain that tolerates to not only high temperature but also the other stresses present during fermentation, e.g., ethanol, osmotic, and oxidative stresses, is indispensable. The C3253, C3751, and C4377 Saccharomyces cerevisiae strains, which have been previously isolated as thermotolerant yeasts, were found to be multiple stress-tolerant. In these strains, continuous expression of heat shock protein genes and intracellular trehalose accumulation were induced in response to stresses causing protein denaturation. Compared to the control strains, these multiple stress-tolerant strains displayed low intracellular reactive oxygen species levels and effective cell wall remodeling upon exposures to almost all stresses tested. In response to simultaneous multi-stress mimicking fermentation stress, cell wall remodeling and redox homeostasis seem to be the primary mechanisms required for protection against cell damage. Moreover, these strains showed better performances of ethanol production than the control strains at both optimal and high temperatures, suggesting their potential use in high-temperature ethanol fermentation.

Optimal Resource Allocation for NOMA-TDMA Scheme with α-Fairness in Industrial Internet of Things.

PubMed

Sun, Yanjing; Guo, Yiyu; Li, Song; Wu, Dapeng; Wang, Bin

2018-05-15

In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, and power control are jointly optimized in order to maximize the system α -fair utility under transmit power constraint and minimum rate constraint. The optimization problem is nonconvex because of the fractional objective function and the nonconvex constraints. To deal with the original problem, we firstly convert the objective function in the optimization problem into a difference of two convex functions (D.C.) form, and then propose a NOMA-TDMA-DC algorithm to exploit the global optimum. Numerical results show that the NOMA-TDMA scheme significantly outperforms the traditional orthogonal multiple access scheme in terms of both spectral efficiency and user fairness.

Optimizing Patient Management and Adherence for Children Receiving Growth Hormone.

PubMed

Acerini, Carlo L; Wac, Katarzyna; Bang, Peter; Lehwalder, Dagmar

2017-01-01

Poor adherence with growth hormone (GH) therapy has been associated with worse clinical outcomes, which in children relates specifically to their linear growth and loss of quality of life. The "360° GH in Europe" meeting, held in Lisbon, Portugal, in June 2016 and funded by Merck KGaA (Germany), examined many aspects of GH diseases. The three sessions, entitled " Short Stature Diagnosis and Referral ," " Optimizing Patient Management ," and " Managing Transition ," each benefited from three guest speaker presentations, followed by an open discussion and are reported as a manuscript, authored by the speakers. Reported here is a summary of the proceedings of the second session, which reviewed the determinants of GH therapy response, factors affecting GH therapy adherence and the development of innovative technologies to improve GH treatment in children. Response to GH therapy varies widely, particularly in regard to the underlying diagnosis, although there is little consensus on the definition of a poor response. If the growth response is seen to be less than expected, the possible reasons should be discussed with patients and their parents, including compliance with the therapy regimen. Understanding and addressing the multiple factors that influence adherence, in order to optimize GH therapy, requires a multi-disciplinary approach. Because therapy continues over many years, various healthcare professionals will be involved at different periods of the patient's journey. The role of the injection device for GH therapy, frequent monitoring of response, and patient support are all important for maintaining adherence. New injection devices are incorporating electronic technologies for automated monitoring and recording of clinically relevant information on injections. Study results are indicating that such devices can at least maintain GH adherence; however, acceptance of novel devices needs to be assessed and there remains an on-going need for innovations.

Calculation of Pareto-optimal solutions to multiple-objective problems using threshold-of-acceptability constraints

NASA Technical Reports Server (NTRS)

Giesy, D. P.

1978-01-01

A technique is presented for the calculation of Pareto-optimal solutions to a multiple-objective constrained optimization problem by solving a series of single-objective problems. Threshold-of-acceptability constraints are placed on the objective functions at each stage to both limit the area of search and to mathematically guarantee convergence to a Pareto optimum.

A Decision Analysis Perspective on Multiple Response Robust Optimization

DTIC Science & Technology

2012-03-01

the utility function in question is monotonically increasing and is twice differentiable . If γ(y) = 0, the utility function is describing risk neutral...twice differentiable , the risk aversion function with respect to a single attribute, yi, i = 1, . . . , n, is given in Equation 2.9, γUyi = − U ′′yi U...UV (V (y1, y2)) and fol- lowing the chain rule of differentiation , Matheson and Abbas [31] show that the risk aversion with respect to a single

Spatial optimization of operationally relevant large fire confine and point protection strategies: Model development and test cases

Treesearch

Yu Wei; Matthew P. Thompson; Jessica R. Haas; Gregory K. Dillon; Christopher D. O’Connor

2018-01-01

This study introduces a large fire containment strategy that builds upon recent advances in spatial fire planning, notably the concept of potential wildland fire operation delineations (PODs). Multiple PODs can be clustered together to form a “box” that is referred as the “response POD” (or rPOD). Fire lines would be built along the boundary of an rPOD to contain a...

Pharmacogenetic algorithm for individualized controlled ovarian stimulation (iCOS) in assisted reproductive technology cycles.

PubMed

Roque, Matheus; Bianco, Bianca; Christofolini, Denise M; Cordts, Emerson B; Vilarino, Fabia L; Carvalho, Waldemar; Valle, Marcello; Sampaio, Marcos; Geber, Selmo; Esteves, Sandro C; Barbosa, Caio P

2018-06-14

Controlled ovarian stimulation (COS) is crucial for optimizing in vitro fertilization (IVF) / intracytoplasmic sperm injection (ICSI) success. Multiple factors influence the ovarian response to COS, making predictions about oocyte yields not so straightforward. As a result, the ovarian response may be poor or suboptimal, or even excessive, all of which have negative consequences for the affected patient. There is a group of patients that present with a suboptimal response to COS despite normal biomarkers of ovarian reserve, such as AFC and AMH. These patients have a lower number of retrieved oocytes than what was expected based on their ovarian reserve, thus showing the inadequacy of using only the traditional ovarian reserve biomarkers to predict the ovarian response. Suboptimal response to COS might be related to ovarian sensitivity to exogenous gonadotropins modulated by genetic factors. The understanding of the gene polymorphisms related to reproductive function can help to improve the clinical management of this patient population and to explain some of the individual patient variability in response to COS. The development of a pharmacogenetic approach concerning COS in the context of assisted reproduction seems attractive as it might help to understand the relationship between genetic variants and ovarian response to exogenous gonadotropins. The patient ́s genetic profile could be used to select the most appropriate gonadotropin type, predict the optimal dosage for each drug, develop a cost-effective treatment plan, maximize the success rates, and lastly, decrease the time-to-pregnancy.

Recommendations for Optimizing Tuberculosis Treatment: Therapeutic Drug Monitoring, Pharmacogenetics, and Nutritional Status Considerations

PubMed Central

Choi, Rihwa; Jeong, Byeong-Ho

2017-01-01

Although tuberculosis is largely a curable disease, it remains a major cause of morbidity and mortality worldwide. Although the standard 6-month treatment regimen is highly effective for drug-susceptible tuberculosis, the use of multiple drugs over long periods of time can cause frequent adverse drug reactions. In addition, some patients with drug-susceptible tuberculosis do not respond adequately to treatment and develop treatment failure and drug resistance. Response to tuberculosis treatment could be affected by multiple factors associated with the host-pathogen interaction including genetic factors and the nutritional status of the host. These factors should be considered for effective tuberculosis control. Therefore, therapeutic drug monitoring (TDM), which is individualized drug dosing guided by serum drug concentrations during treatment, and pharmacogenetics-based personalized dosing guidelines of anti-tuberculosis drugs could reduce the incidence of adverse drug reactions and increase the likelihood of successful treatment outcomes. Moreover, assessment and management of comorbid conditions including nutritional status could improve anti-tuberculosis treatment response. PMID:28028995

Recommendations for Optimizing Tuberculosis Treatment: Therapeutic Drug Monitoring, Pharmacogenetics, and Nutritional Status Considerations.

PubMed

Choi, Rihwa; Jeong, Byeong Ho; Koh, Won Jung; Lee, Soo Youn

2017-03-01

Although tuberculosis is largely a curable disease, it remains a major cause of morbidity and mortality worldwide. Although the standard 6-month treatment regimen is highly effective for drug-susceptible tuberculosis, the use of multiple drugs over long periods of time can cause frequent adverse drug reactions. In addition, some patients with drug-susceptible tuberculosis do not respond adequately to treatment and develop treatment failure and drug resistance. Response to tuberculosis treatment could be affected by multiple factors associated with the host-pathogen interaction including genetic factors and the nutritional status of the host. These factors should be considered for effective tuberculosis control. Therefore, therapeutic drug monitoring (TDM), which is individualized drug dosing guided by serum drug concentrations during treatment, and pharmacogenetics-based personalized dosing guidelines of anti-tuberculosis drugs could reduce the incidence of adverse drug reactions and increase the likelihood of successful treatment outcomes. Moreover, assessment and management of comorbid conditions including nutritional status could improve anti-tuberculosis treatment response.

Parameter Tuning and Calibration of RegCM3 with MIT-Emanuel Cumulus Parameterization Scheme over CORDEX East Asian Domain

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

Zou, Liwei; Qian, Yun; Zhou, Tianjun

2014-10-01

In this study, we calibrated the performance of regional climate model RegCM3 with Massachusetts Institute of Technology (MIT)-Emanuel cumulus parameterization scheme over CORDEX East Asia domain by tuning the selected seven parameters through multiple very fast simulated annealing (MVFSA) sampling method. The seven parameters were selected based on previous studies, which customized the RegCM3 with MIT-Emanuel scheme through three different ways by using the sensitivity experiments. The responses of model results to the seven parameters were investigated. Since the monthly total rainfall is constrained, the simulated spatial pattern of rainfall and the probability density function (PDF) distribution of daily rainfallmore » rates are significantly improved in the optimal simulation. Sensitivity analysis suggest that the parameter “relative humidity criteria” (RH), which has not been considered in the default simulation, has the largest effect on the model results. The responses of total rainfall over different regions to RH were examined. Positive responses of total rainfall to RH are found over northern equatorial western Pacific, which are contributed by the positive responses of explicit rainfall. Followed by an increase of RH, the increases of the low-level convergence and the associated increases in cloud water favor the increase of the explicit rainfall. The identified optimal parameters constrained by the total rainfall have positive effects on the low-level circulation and the surface air temperature. Furthermore, the optimized parameters based on the extreme case are suitable for a normal case and the model’s new version with mixed convection scheme.« less

The Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures Project: Rationale and Approach.

PubMed

MacLean, Paul S; Rothman, Alexander J; Nicastro, Holly L; Czajkowski, Susan M; Agurs-Collins, Tanya; Rice, Elise L; Courcoulas, Anita P; Ryan, Donna H; Bessesen, Daniel H; Loria, Catherine M

2018-04-01

Individual variability in response to multiple modalities of obesity treatment is well documented, yet our understanding of why some individuals respond while others do not is limited. The etiology of this variability is multifactorial; however, at present, we lack a comprehensive evidence base to identify which factors or combination of factors influence treatment response. This paper provides an overview and rationale of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, which aims to advance the understanding of individual variability in response to adult obesity treatment. This project provides an integrated model for how factors in the behavioral, biological, environmental, and psychosocial domains may influence obesity treatment responses and identify a core set of measures to be used consistently across adult weight-loss trials. This paper provides the foundation for four companion papers that describe the core measures in detail. The accumulation of data on factors across the four ADOPT domains can inform the design and delivery of effective, tailored obesity treatments. ADOPT provides a framework for how obesity researchers can collectively generate this evidence base and is a first step in an ongoing process that can be refined as the science advances. © 2018 The Obesity Society.

Hybrid NN/SVM Computational System for Optimizing Designs

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

2009-01-01

A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily oversimplified to fit the scope of this article, an SVM can be characterized as an algorithm that (1) effects a nonlinear mapping of input vectors into a higher-dimensional feature space and (2) involves a dual formulation of governing equations and constraints. One advantageous feature of the SVM approach is that an objective function (which one seeks to minimize to obtain coefficients that define an SVM mathematical model) is convex, so that unlike in the cases of many NN models, any local minimum of an SVM model is also a global minimum.

Towards Robust Designs Via Multiple-Objective Optimization Methods

NASA Technical Reports Server (NTRS)

Man Mohan, Rai

2006-01-01

Fabricating and operating complex systems involves dealing with uncertainty in the relevant variables. In the case of aircraft, flow conditions are subject to change during operation. Efficiency and engine noise may be different from the expected values because of manufacturing tolerances and normal wear and tear. Engine components may have a shorter life than expected because of manufacturing tolerances. In spite of the important effect of operating- and manufacturing-uncertainty on the performance and expected life of the component or system, traditional aerodynamic shape optimization has focused on obtaining the best design given a set of deterministic flow conditions. Clearly it is important to both maintain near-optimal performance levels at off-design operating conditions, and, ensure that performance does not degrade appreciably when the component shape differs from the optimal shape due to manufacturing tolerances and normal wear and tear. These requirements naturally lead to the idea of robust optimal design wherein the concept of robustness to various perturbations is built into the design optimization procedure. The basic ideas involved in robust optimal design will be included in this lecture. The imposition of the additional requirement of robustness results in a multiple-objective optimization problem requiring appropriate solution procedures. Typically the costs associated with multiple-objective optimization are substantial. Therefore efficient multiple-objective optimization procedures are crucial to the rapid deployment of the principles of robust design in industry. Hence the companion set of lecture notes (Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks ) deals with methodology for solving multiple-objective Optimization problems efficiently, reliably and with little user intervention. Applications of the methodologies presented in the companion lecture to robust design will be included here. The evolutionary method (DE) is first used to solve a relatively difficult problem in extended surface heat transfer wherein optimal fin geometries are obtained for different safe operating base temperatures. The objective of maximizing the safe operating base temperature range is in direct conflict with the objective of maximizing fin heat transfer. This problem is a good example of achieving robustness in the context of changing operating conditions. The evolutionary method is then used to design a turbine airfoil; the two objectives being reduced sensitivity of the pressure distribution to small changes in the airfoil shape and the maximization of the trailing edge wedge angle with the consequent increase in airfoil thickness and strength. This is a relevant example of achieving robustness to manufacturing tolerances and wear and tear in the presence of other objectives.

Beam Design and User Scheduling for Nonorthogonal Multiple Access With Multiple Antennas Based on Pareto Optimality

NASA Astrophysics Data System (ADS)

Seo, Junyeong; Sung, Youngchul

2018-06-01

In this paper, an efficient transmit beam design and user scheduling method is proposed for multi-user (MU) multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) downlink, based on Pareto-optimality. The proposed beam design and user scheduling method groups simultaneously-served users into multiple clusters with practical two users in each cluster, and then applies spatical zeroforcing (ZF) across clusters to control inter-cluster interference (ICI) and Pareto-optimal beam design with successive interference cancellation (SIC) to two users in each cluster to remove interference to strong users and leverage signal-to-interference-plus-noise ratios (SINRs) of interference-experiencing weak users. The proposed method has flexibility to control the rates of strong and weak users and numerical results show that the proposed method yields good performance.

Multi-stage approach for structural damage detection problem using basis pursuit and particle swarm optimization

NASA Astrophysics Data System (ADS)

Gerist, Saleheh; Maheri, Mahmoud R.

2016-12-01

In order to solve structural damage detection problem, a multi-stage method using particle swarm optimization is presented. First, a new spars recovery method, named Basis Pursuit (BP), is utilized to preliminarily identify structural damage locations. The BP method solves a system of equations which relates the damage parameters to the structural modal responses using the sensitivity matrix. Then, the results of this stage are subsequently enhanced to the exact damage locations and extents using the PSO search engine. Finally, the search space is reduced by elimination of some low damage variables using micro search (MS) operator embedded in the PSO algorithm. To overcome the noise present in structural responses, a method known as Basis Pursuit De-Noising (BPDN) is also used. The efficiency of the proposed method is investigated by three numerical examples: a cantilever beam, a plane truss and a portal plane frame. The frequency response is used to detect damage in the examples. The simulation results demonstrate the accuracy and efficiency of the proposed method in detecting multiple damage cases and exhibit its robustness regarding noise and its advantages compared to other reported solution algorithms.

Alveolar macrophages are critical for broadly-reactive antibody-mediated protection against influenza A virus in mice.

PubMed

He, Wenqian; Chen, Chi-Jene; Mullarkey, Caitlin E; Hamilton, Jennifer R; Wong, Christine K; Leon, Paul E; Uccellini, Melissa B; Chromikova, Veronika; Henry, Carole; Hoffman, Kevin W; Lim, Jean K; Wilson, Patrick C; Miller, Matthew S; Krammer, Florian; Palese, Peter; Tan, Gene S

2017-10-10

The aim of candidate universal influenza vaccines is to provide broad protection against influenza A and B viruses. Studies have demonstrated that broadly reactive antibodies require Fc-Fc gamma receptor interactions for optimal protection; however, the innate effector cells responsible for mediating this protection remain largely unknown. Here, we examine the roles of alveolar macrophages, natural killer cells, and neutrophils in antibody-mediated protection. We demonstrate that alveolar macrophages play a dominant role in conferring protection provided by both broadly neutralizing and non-neutralizing antibodies in mice. Our data also reveal the potential mechanisms by which alveolar macrophages mediate protection in vivo, namely antibody-induced inflammation and antibody-dependent cellular phagocytosis. This study highlights the importance of innate effector cells in establishing a broad-spectrum antiviral state, as well as providing a better understanding of how multiple arms of the immune system cooperate to achieve an optimal antiviral response following influenza virus infection or immunization.Broadly reactive antibodies that recognize influenza A virus HA can be protective, but the mechanism is not completely understood. Here, He et al. show that the inflammatory response and phagocytosis mediated by the interaction between protective antibodies and macrophages are essential for protection.

Optimal crop selection and water allocation under limited water supply in irrigation

NASA Astrophysics Data System (ADS)

Stange, Peter; Grießbach, Ulrike; Schütze, Niels

2015-04-01

Due to climate change, extreme weather conditions such as droughts may have an increasing impact on irrigated agriculture. To cope with limited water resources in irrigation systems, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand at the same time. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from optimized agronomic response on farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF). These functions take into account different soil types, crops and stochastically generated climate scenarios. The SCWPF's are used to compute the water demand considering different conditions, e.g., variable and fixed costs. This generic approach enables the consideration of both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance IRrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies.

Quantitative analysis of the anti-noise performance of an m-sequence in an electromagnetic method

NASA Astrophysics Data System (ADS)

Yuan, Zhe; Zhang, Yiming; Zheng, Qijia

2018-02-01

An electromagnetic method with a transmitted waveform coded by an m-sequence achieved better anti-noise performance compared to the conventional manner with a square-wave. The anti-noise performance of the m-sequence varied with multiple coding parameters; hence, a quantitative analysis of the anti-noise performance for m-sequences with different coding parameters was required to optimize them. This paper proposes the concept of an identification system, with the identified Earth impulse response obtained by measuring the system output with the input of the voltage response. A quantitative analysis of the anti-noise performance of the m-sequence was achieved by analyzing the amplitude-frequency response of the corresponding identification system. The effects of the coding parameters on the anti-noise performance are summarized by numerical simulation, and their optimization is further discussed in our conclusions; the validity of the conclusions is further verified by field experiment. The quantitative analysis method proposed in this paper provides a new insight into the anti-noise mechanism of the m-sequence, and could be used to evaluate the anti-noise performance of artificial sources in other time-domain exploration methods, such as the seismic method.

Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System.

PubMed

Duan, Litian; Wang, Zizhong John; Duan, Fu

2016-11-16

In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.

Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

PubMed Central

Duan, Litian; Wang, Zizhong John; Duan, Fu

2016-01-01

In the multiple-reader environment (MRE) of radio frequency identification (RFID) system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS) is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression) quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range. PMID:27854342

Charged particle tracking without magnetic field: Optimal measurement of track momentum by a Bayesian analysis of the multiple measurements of deflections due to multiple scattering

NASA Astrophysics Data System (ADS)

Frosini, Mikael; Bernard, Denis

2017-09-01

We revisit the precision of the measurement of track parameters (position, angle) with optimal methods in the presence of detector resolution, multiple scattering and zero magnetic field. We then obtain an optimal estimator of the track momentum by a Bayesian analysis of the filtering innovations of a series of Kalman filters applied to the track. This work could pave the way to the development of autonomous high-performance gas time-projection chambers (TPC) or silicon wafer γ-ray space telescopes and be a powerful guide in the optimization of the design of the multi-kilo-ton liquid argon TPCs that are under development for neutrino studies.

Contraction Options and Optimal Multiple-Stopping in Spectrally Negative Lévy Models

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

Yamazaki, Kazutoshi, E-mail: kyamazak@kansai-u.ac.jp

This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Lévy process. This allows the model to incorporate sudden declines of the project values, generalizing greatly the classical geometric Brownian motion model. We solve the one-stage case as well as the extension to the multiple-stage case. The optimal stopping times are of threshold-type and the value function admits an expression in terms of the scale function. A series of numerical experiments are conducted to verify the optimality and tomore » evaluate the efficiency of the algorithm.« less

Digital robust control law synthesis using constrained optimization

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivekananda

1989-01-01

Development of digital robust control laws for active control of high performance flexible aircraft and large space structures is a research area of significant practical importance. The flexible system is typically modeled by a large order state space system of equations in order to accurately represent the dynamics. The active control law must satisy multiple conflicting design requirements and maintain certain stability margins, yet should be simple enough to be implementable on an onboard digital computer. Described here is an application of a generic digital control law synthesis procedure for such a system, using optimal control theory and constrained optimization technique. A linear quadratic Gaussian type cost function is minimized by updating the free parameters of the digital control law, while trying to satisfy a set of constraints on the design loads, responses and stability margins. Analytical expressions for the gradients of the cost function and the constraints with respect to the control law design variables are used to facilitate rapid numerical convergence. These gradients can be used for sensitivity study and may be integrated into a simultaneous structure and control optimization scheme.

Correlates of willingness to engage in residential gardening: implications for health optimization in ibadan, Nigeria.

PubMed

Motunrayo Ibrahim, Fausat

2013-01-01

Gardening is a worthwhile adventure which engenders health op-timization. Yet, a dearth of evidences that highlights motivations to engage in gardening exists. This study examined willingness to engage in gardening and its correlates, including some socio-psychological, health related and socio-demographic variables. In this cross-sectional survey, 508 copies of a structured questionnaire were randomly self administered among a group of civil servants of Oyo State, Nigeria. Multi-item measures were used to assess variables. Step wise multiple regression analysis was used to identify predictors of willingness to engage in gar-dening Results: Simple percentile analysis shows that 71.1% of respondents do not own a garden. Results of step wise multiple regression analysis indicate that descriptive norm of gardening is a good predictor, social support for gardening is better while gardening self efficacy is the best predictor of willingness to engage in gardening (P< 0.001). Health consciousness, gardening response efficacy, education and age are not predictors of this willingness (P> 0.05). Results of t-test and ANOVA respectively shows that gender is not associated with this willingness (P> 0.05), but marital status is (P< 0.05).  Socio-psychological characteristics and being married are very rele-vant in motivations to engage in gardening. The nexus between gardening and health optimization appears to be highly obscured in this population.

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

PubMed Central

She, Ji; Wang, Fei; Zhou, Jianjiang

2016-01-01

Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance. PMID:28009819

Co-delivery of chemotherapeutics and proteins for synergistic therapy.

PubMed

He, Chaoliang; Tang, Zhaohui; Tian, Huayu; Chen, Xuesi

2016-03-01

Combination therapy with chemotherapeutics and protein therapeutics, typically cytokines and antibodies, has been a type of crucial approaches for synergistic cancer treatment. However, conventional approaches by simultaneous administration of free chemotherapeutic drugs and proteins lead to limitations for further optimizing the synergistic effects, due to the distinct in vivo pharmacokinetics and distribution of small drugs and proteins, insufficient tumor selectivity and tumor accumulation, unpredictable drug/protein ratios at tumor sites, short half-lives, and serious systemic adverse effects. Consequently, to obtain optimal synergistic anti-tumor efficacy, considerable efforts have been devoted to develop the co-delivery systems for co-incorporating chemotherapeutics and proteins into a single carrier system and subsequently releasing the dual or multiple payloads at desired target sites in a more controllable manner. The co-delivery systems result in markedly enhanced blood stability and in vivo half-lives of the small drugs and proteins, elevated tumor accumulation, as well as the capability of delivering the multiple agents to the same target sites with rational drug/protein ratios, which may facilitate maximizing the synergistic effects and therefore lead to optimal antitumor efficacy. This review emphasizes the recent advances in the co-delivery systems for chemotherapeutics and proteins, typically cytokines and antibodies, for systemic or localized synergistic cancer treatment. Moreover, the proposed mechanisms responsible for the synergy of chemotherapeutic drugs and proteins are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Performance metric comparison study for non-magnetic bi-stable energy harvesters

NASA Astrophysics Data System (ADS)

Udani, Janav P.; Wrigley, Cailin; Arrieta, Andres F.

2017-04-01

Energy harvesting employing non-linear systems offers considerable advantages over linear systems given the broadband resonant response which is favorable for applications involving diverse input vibrations. In this respect, the rich dynamics of bi-stable systems present a promising means for harvesting vibrational energy from ambient sources. Harvesters deriving their bi-stability from thermally induced stresses as opposed to magnetic forces are receiving significant attention as it reduces the need for ancillary components and allows for bio- compatible constructions. However, the design of these bi-stable harvesters still requires further optimization to completely exploit the dynamic behavior of these systems. This study presents a comparison of the harvesting capabilities of non-magnetic, bi-stable composite laminates under variations in the design parameters as evaluated utilizing established power metrics. Energy output characteristics of two bi-stable composite laminate plates with a piezoelectric patch bonded on the top surface are experimentally investigated for variations in the thickness ratio and inertial mass positions for multiple load conditions. A particular design configuration is found to perform better over the entire range of testing conditions which include single and multiple frequency excitation, thus indicating that design optimization over the geometry of the harvester yields robust performance. The experimental analysis further highlights the need for appropriate design guidelines for optimization and holistic performance metrics to account for the range of operational conditions.

Acquisition of decision making criteria: reward rate ultimately beats accuracy.

PubMed

Balci, Fuat; Simen, Patrick; Niyogi, Ritwik; Saxe, Andrew; Hughes, Jessica A; Holmes, Philip; Cohen, Jonathan D

2011-02-01

Speed-accuracy trade-offs strongly influence the rate of reward that can be earned in many decision-making tasks. Previous reports suggest that human participants often adopt suboptimal speed-accuracy trade-offs in single session, two-alternative forced-choice tasks. We investigated whether humans acquired optimal speed-accuracy trade-offs when extensively trained with multiple signal qualities. When performance was characterized in terms of decision time and accuracy, our participants eventually performed nearly optimally in the case of higher signal qualities. Rather than adopting decision criteria that were individually optimal for each signal quality, participants adopted a single threshold that was nearly optimal for most signal qualities. However, setting a single threshold for different coherence conditions resulted in only negligible decrements in the maximum possible reward rate. Finally, we tested two hypotheses regarding the possible sources of suboptimal performance: (1) favoring accuracy over reward rate and (2) misestimating the reward rate due to timing uncertainty. Our findings provide support for both hypotheses, but also for the hypothesis that participants can learn to approach optimality. We find specifically that an accuracy bias dominates early performance, but diminishes greatly with practice. The residual discrepancy between optimal and observed performance can be explained by an adaptive response to uncertainty in time estimation.

Enzymatic production of infant milk fat analogs containing palmitic acid: optimization of reactions by response surface methodology.

PubMed

Maduko, C O; Akoh, C C; Park, Y W

2007-05-01

Infant milk fat analogs resembling human milk fat were synthesized by an enzymatic interesterification between tripalmitin, coconut oil, safflower oil, and soybean oil in hexane. A commercially immobilized 1,3-specific lipase, Lipozyme RM IM, obtained from Rhizomucor miehei was used as a biocatalyst. The effects of substrate molar ratio, reaction time, and incubation temperature on the incorporation of palmitic acid at the sn-2 position of the triacylglycerols were investigated. A central composite design with 5 levels and 3 factors consisting of substrate ratio, reaction temperature, and incubation time was used to model and optimize the reaction conditions using response surface methodology. A quadratic model using multiple regressions was then obtained for the incorporation of palmitic acid at the sn-2 positions of glycerols as the response. The coefficient of determination (R2) value for the model was 0.845. The incorporation of palmitic acid appeared to increase with the decrease in substrate molar ratio and increase in reaction temperature, and optimum incubation time occurred at 18 h. The optimal conditions generated from the model for the targeted 40% palmitic acid incorporation at the sn-2 position were 3 mol/mol, 14.4 h, and 55 degrees C; and 2.8 mol/mol, 19.6 h, and 55 degrees C for substrate ratio (moles of total fatty acid/moles of tripalmitin), time, and temperature, respectively. Infant milk fat containing fatty acid composition and sn-2 fatty acid profile similar to human milk fat was successfully produced. The fat analogs produced under optimal conditions had total and sn-2 positional palmitic acid levels comparable to that of human milk fat.

Departures From Optimality When Pursuing Multiple Approach or Avoidance Goals

PubMed Central

2016-01-01

This article examines how people depart from optimality during multiple-goal pursuit. The authors operationalized optimality using dynamic programming, which is a mathematical model used to calculate expected value in multistage decisions. Drawing on prospect theory, they predicted that people are risk-averse when pursuing approach goals and are therefore more likely to prioritize the goal in the best position than the dynamic programming model suggests is optimal. The authors predicted that people are risk-seeking when pursuing avoidance goals and are therefore more likely to prioritize the goal in the worst position than is optimal. These predictions were supported by results from an experimental paradigm in which participants made a series of prioritization decisions while pursuing either 2 approach or 2 avoidance goals. This research demonstrates the usefulness of using decision-making theories and normative models to understand multiple-goal pursuit. PMID:26963081

Self-organization, free energy minimization, and optimal grip on a field of affordances

PubMed Central

Bruineberg, Jelle; Rietveld, Erik

2014-01-01

In this paper, we set out to develop a theoretical and conceptual framework for the new field of Radical Embodied Cognitive Neuroscience. This framework should be able to integrate insights from several relevant disciplines: theory on embodied cognition, ecological psychology, phenomenology, dynamical systems theory, and neurodynamics. We suggest that the main task of Radical Embodied Cognitive Neuroscience is to investigate the phenomenon of skilled intentionality from the perspective of the self-organization of the brain-body-environment system, while doing justice to the phenomenology of skilled action. In previous work, we have characterized skilled intentionality as the organism's tendency toward an optimal grip on multiple relevant affordances simultaneously. Affordances are possibilities for action provided by the environment. In the first part of this paper, we introduce the notion of skilled intentionality and the phenomenon of responsiveness to a field of relevant affordances. Second, we use Friston's work on neurodynamics, but embed a very minimal version of his Free Energy Principle in the ecological niche of the animal. Thus amended, this principle is helpful for understanding the embeddedness of neurodynamics within the dynamics of the system “brain-body-landscape of affordances.” Next, we show how we can use this adjusted principle to understand the neurodynamics of selective openness to the environment: interacting action-readiness patterns at multiple timescales contribute to the organism's selective openness to relevant affordances. In the final part of the paper, we emphasize the important role of metastable dynamics in both the brain and the brain-body-environment system for adequate affordance-responsiveness. We exemplify our integrative approach by presenting research on the impact of Deep Brain Stimulation on affordance responsiveness of OCD patients. PMID:25161615

Self-organization, free energy minimization, and optimal grip on a field of affordances.

PubMed

Bruineberg, Jelle; Rietveld, Erik

2014-01-01

In this paper, we set out to develop a theoretical and conceptual framework for the new field of Radical Embodied Cognitive Neuroscience. This framework should be able to integrate insights from several relevant disciplines: theory on embodied cognition, ecological psychology, phenomenology, dynamical systems theory, and neurodynamics. We suggest that the main task of Radical Embodied Cognitive Neuroscience is to investigate the phenomenon of skilled intentionality from the perspective of the self-organization of the brain-body-environment system, while doing justice to the phenomenology of skilled action. In previous work, we have characterized skilled intentionality as the organism's tendency toward an optimal grip on multiple relevant affordances simultaneously. Affordances are possibilities for action provided by the environment. In the first part of this paper, we introduce the notion of skilled intentionality and the phenomenon of responsiveness to a field of relevant affordances. Second, we use Friston's work on neurodynamics, but embed a very minimal version of his Free Energy Principle in the ecological niche of the animal. Thus amended, this principle is helpful for understanding the embeddedness of neurodynamics within the dynamics of the system "brain-body-landscape of affordances." Next, we show how we can use this adjusted principle to understand the neurodynamics of selective openness to the environment: interacting action-readiness patterns at multiple timescales contribute to the organism's selective openness to relevant affordances. In the final part of the paper, we emphasize the important role of metastable dynamics in both the brain and the brain-body-environment system for adequate affordance-responsiveness. We exemplify our integrative approach by presenting research on the impact of Deep Brain Stimulation on affordance responsiveness of OCD patients.

Fukunaga-Koontz feature transformation for statistical structural damage detection and hierarchical neuro-fuzzy damage localisation

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2017-07-01

Considering jointly damage sensitive features (DSFs) of signals recorded by multiple sensors, applying advanced transformations to these DSFs and assessing systematically their contribution to damage detectability and localisation can significantly enhance the performance of structural health monitoring systems. This philosophy is explored here for partial autocorrelation coefficients (PACCs) of acceleration responses. They are interrogated with the help of the linear discriminant analysis based on the Fukunaga-Koontz transformation using datasets of the healthy and selected reference damage states. Then, a simple but efficient fast forward selection procedure is applied to rank the DSF components with respect to statistical distance measures specialised for either damage detection or localisation. For the damage detection task, the optimal feature subsets are identified based on the statistical hypothesis testing. For damage localisation, a hierarchical neuro-fuzzy tool is developed that uses the DSF ranking to establish its own optimal architecture. The proposed approaches are evaluated experimentally on data from non-destructively simulated damage in a laboratory scale wind turbine blade. The results support our claim of being able to enhance damage detectability and localisation performance by transforming and optimally selecting DSFs. It is demonstrated that the optimally selected PACCs from multiple sensors or their Fukunaga-Koontz transformed versions can not only improve the detectability of damage via statistical hypothesis testing but also increase the accuracy of damage localisation when used as inputs into a hierarchical neuro-fuzzy network. Furthermore, the computational effort of employing these advanced soft computing models for damage localisation can be significantly reduced by using transformed DSFs.

Optimization of shape control of a cantilever beam using dielectric elastomer actuators

NASA Astrophysics Data System (ADS)

Liu, Chong; Mao, Boyong; Huang, Gangting; Wu, Qichen; Xie, Shilin; Xu, Minglong

2018-05-01

Dielectric elastomer (DE) is a kind of smart soft material that has many advantages such as large deformation, fast response, lightweight and easy synthesis. These features make dielectric elastomer a suitable material for actuators. This article focuses on the shape control of a cantilever beam by using dielectric elastomer actuators. The shape control equation in finite element formulation of the cantilever beam partially covered with dielectric elastomer actuators is derived based on the constitutive equation of dielectric elastomer material by using Hamilton principle. The actuating forces produced by dielectric elastomer actuators depend on the number of layers, the position and the actuation voltage of dielectric elastomer actuators. First, effects of these factors on the shape control accuracy when one pair or multiple pairs of actuators are employed are simulated, respectively. The simulation results demonstrate that increasing the number of actuators or the number of layers can improve the control effect and reduce the actuation voltages effectively. Second, to achieve the optimal shape control effect, the position of the actuators and the drive voltages are all determined using a genetic algorithm. The robustness of the genetic algorithm is analyzed. Moreover, the implications of using one pair and multiple pairs of actuators to drive the cantilever beam to the expected shape are investigated. The results demonstrate that a small number of actuators with optimal placement and optimal voltage values can achieve the shape control of the beam effectively. Finally, a preliminary experimental verification of the control effect is carried out, which shows the correctness of the theoretical method.

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

PubMed

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

2018-03-01

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

Robust experimental design for optimizing the microbial inhibitor test for penicillin detection in milk.

PubMed

Nagel, O G; Molina, M P; Basílico, J C; Zapata, M L; Althaus, R L

2009-06-01

To use experimental design techniques and a multiple logistic regression model to optimize a microbiological inhibition test with dichotomous response for the detection of Penicillin G in milk. A 2(3) x 2(2) robust experimental design with two replications was used. The effects of three control factors (V: culture medium volume, S: spore concentration of Geobacillus stearothermophilus, I: indicator concentration), two noise factors (Dt: diffusion time, Ip: incubation period) and their interactions were studied. The V, S, Dt, Ip factors and V x S, V x Ip, S x Ip interactions showed significant effects. The use of 100 microl culture medium volume, 2 x 10(5) spores ml(-1), 60 min diffusion time and 3 h incubation period is recommended. In these elaboration conditions, the penicillin detection limit was of 3.9 microg l(-1), similar to the maximum residue limit (MRL). Of the two noise factors studied, the incubation period can be controlled by means of the culture medium volume and spore concentration. We were able to optimize bioassays of dichotomous response using an experimental design and logistic regression model for the detection of residues at the level of MRL, aiding in the avoidance of health problems in the consumer.

Use of response surface methodology in a fed-batch process for optimization of tricarboxylic acid cycle intermediates to achieve high levels of canthaxanthin from Dietzia natronolimnaea HS-1.

PubMed

Nasri Nasrabadi, Mohammad Reza; Razavi, Seyed Hadi

2010-04-01

In this work, we applied statistical experimental design to a fed-batch process for optimization of tricarboxylic acid cycle (TCA) intermediates in order to achieve high-level production of canthaxanthin from Dietzia natronolimnaea HS-1 cultured in beet molasses. A fractional factorial design (screening test) was first conducted on five TCA cycle intermediates. Out of the five TCA cycle intermediates investigated via screening tests, alfaketoglutarate, oxaloacetate and succinate were selected based on their statistically significant (P<0.05) and positive effects on canthaxanthin production. These significant factors were optimized by means of response surface methodology (RSM) in order to achieve high-level production of canthaxanthin. The experimental results of the RSM were fitted with a second-order polynomial equation by means of a multiple regression technique to identify the relationship between canthaxanthin production and the three TCA cycle intermediates. By means of this statistical design under a fed-batch process, the optimum conditions required to achieve the highest level of canthaxanthin (13172 + or - 25 microg l(-1)) were determined as follows: alfaketoglutarate, 9.69 mM; oxaloacetate, 8.68 mM; succinate, 8.51 mM. Copyright 2009 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

In vitro growth of Curcuma longa L. in response to five mineral elements and plant density in fed-batch culture systems.

PubMed

El-Hawaz, Rabia F; Bridges, William C; Adelberg, Jeffrey W

2015-01-01

Plant density was varied with P, Ca, Mg, and KNO3 in a multifactor experiment to improve Curcuma longa L. micropropagation, biomass and microrhizome development in fed-batch liquid culture. The experiment had two paired D-optimal designs, testing sucrose fed-batch and nutrient sucrose fed-batch techniques. When sucrose became depleted, volume was restored to 5% m/v sucrose in 200 ml of modified liquid MS medium by adding sucrose solutions. Similarly, nutrient sucrose fed-batch was restored to set points with double concentration of treatments' macronutrient and MS micronutrient solutions, along with sucrose solutions. Changes in the amounts of water and sucrose supplementations were driven by the interaction of P and KNO3 concentrations. Increasing P from 1.25 to 6.25 mM increased both multiplication and biomass. The multiplication ratio was greatest in the nutrient sucrose fed-batch technique with the highest level of P, 6 buds/vessel, and the lowest level of Ca and KNO3. The highest density (18 buds/vessel) produced the highest fresh biomass at the highest concentrations of KNO3 and P with nutrient sucrose fed-batch, and moderate Ca and Mg concentrations. However, maximal rhizome dry biomass required highest P, sucrose fed-batch, and a moderate plant density. Different media formulations and fed-batch techniques were identified to maximize the propagation and storage organ responses. A single experimental design was used to optimize these dual purposes.

In Vitro Growth of Curcuma longa L. in Response to Five Mineral Elements and Plant Density in Fed-Batch Culture Systems

PubMed Central

El-Hawaz, Rabia F.; Bridges, William C.; Adelberg, Jeffrey W.

2015-01-01

Plant density was varied with P, Ca, Mg, and KNO3 in a multifactor experiment to improve Curcuma longa L. micropropagation, biomass and microrhizome development in fed-batch liquid culture. The experiment had two paired D-optimal designs, testing sucrose fed-batch and nutrient sucrose fed-batch techniques. When sucrose became depleted, volume was restored to 5% m/v sucrose in 200 ml of modified liquid MS medium by adding sucrose solutions. Similarly, nutrient sucrose fed-batch was restored to set points with double concentration of treatments’ macronutrient and MS micronutrient solutions, along with sucrose solutions. Changes in the amounts of water and sucrose supplementations were driven by the interaction of P and KNO3 concentrations. Increasing P from 1.25 to 6.25 mM increased both multiplication and biomass. The multiplication ratio was greatest in the nutrient sucrose fed-batch technique with the highest level of P, 6 buds/vessel, and the lowest level of Ca and KNO3. The highest density (18 buds/vessel) produced the highest fresh biomass at the highest concentrations of KNO3 and P with nutrient sucrose fed-batch, and moderate Ca and Mg concentrations. However, maximal rhizome dry biomass required highest P, sucrose fed-batch, and a moderate plant density. Different media formulations and fed-batch techniques were identified to maximize the propagation and storage organ responses. A single experimental design was used to optimize these dual purposes. PMID:25830292

Development of a fast and feasible spectrum modeling technique for flattening filter free beams

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

Cho, Woong; Bush, Karl; Mok, Ed

Purpose: To develop a fast and robust technique for the determination of optimized photon spectra for flattening filter free (FFF) beams to be applied in convolution/superposition dose calculations. Methods: A two-step optimization method was developed to derive optimal photon spectra for FFF beams. In the first step, a simple functional form of the photon spectra proposed by Ali ['Functional forms for photon spectra of clinical linacs,' Phys. Med. Biol. 57, 31-50 (2011)] is used to determine generalized shapes of the photon spectra. In this method, the photon spectra were defined for the ranges of field sizes to consider the variationsmore » of the contributions of scattered photons with field size. Percent depth doses (PDDs) for each field size were measured and calculated to define a cost function, and a collapsed cone convolution (CCC) algorithm was used to calculate the PDDs. In the second step, the generalized functional form of the photon spectra was fine-tuned in a process whereby the weights of photon fluence became the optimizing free parameters. A line search method was used for the optimization and first order derivatives with respect to the optimizing parameters were derived from the CCC algorithm to enhance the speed of the optimization. The derived photon spectra were evaluated, and the dose distributions using the optimized spectra were validated. Results: The optimal spectra demonstrate small variations with field size for the 6 MV FFF beam and relatively large variations for the 10 MV FFF beam. The mean energies of the optimized 6 MV FFF spectra were decreased from 1.31 MeV for a 3 Multiplication-Sign 3 cm{sup 2} field to 1.21 MeV for a 40 Multiplication-Sign 40 cm{sup 2} field, and from 2.33 MeV at 3 Multiplication-Sign 3 cm{sup 2} to 2.18 MeV at 40 Multiplication-Sign 40 cm{sup 2} for the 10 MV FFF beam. The developed method could significantly improve the agreement between the calculated and measured PDDs. Root mean square differences on the optimized PDDs were observed to be 0.41% (3 Multiplication-Sign 3 cm{sup 2}) down to 0.21% (40 Multiplication-Sign 40 cm{sup 2}) for the 6 MV FFF beam, and 0.35% (3 Multiplication-Sign 3 cm{sup 2}) down to 0.29% (40 Multiplication-Sign 40 cm{sup 2}) for the 10 MV FFF beam. The first order derivatives from the functional form were found to improve the speed of computational time up to 20 times compared to the other techniques. Conclusions: The derived photon spectra resulted in good agreements with measured PDDs over the range of field sizes investigated. The suggested method is easily applicable to commercial radiation treatment planning systems since it only requires measured PDDs as input.« less

Theoretical Foundation of Copernicus: A Unified System for Trajectory Design and Optimization

NASA Technical Reports Server (NTRS)

Ocampo, Cesar; Senent, Juan S.; Williams, Jacob

2010-01-01

The fundamental methods are described for the general spacecraft trajectory design and optimization software system called Copernicus. The methods rely on a unified framework that is used to model, design, and optimize spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The trajectory model, with its associated equations of motion and maneuver models, are discussed.

System and method for optimal load and source scheduling in context aware homes

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

Shetty, Pradeep; Foslien Graber, Wendy; Mangsuli, Purnaprajna R.

A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.

An optimal control strategy for hybrid actuator systems: Application to an artificial muscle with electric motor assist.

PubMed

Ishihara, Koji; Morimoto, Jun

2018-03-01

Humans use multiple muscles to generate such joint movements as an elbow motion. With multiple lightweight and compliant actuators, joint movements can also be efficiently generated. Similarly, robots can use multiple actuators to efficiently generate a one degree of freedom movement. For this movement, the desired joint torque must be properly distributed to each actuator. One approach to cope with this torque distribution problem is an optimal control method. However, solving the optimal control problem at each control time step has not been deemed a practical approach due to its large computational burden. In this paper, we propose a computationally efficient method to derive an optimal control strategy for a hybrid actuation system composed of multiple actuators, where each actuator has different dynamical properties. We investigated a singularly perturbed system of the hybrid actuator model that subdivided the original large-scale control problem into smaller subproblems so that the optimal control outputs for each actuator can be derived at each control time step and applied our proposed method to our pneumatic-electric hybrid actuator system. Our method derived a torque distribution strategy for the hybrid actuator by dealing with the difficulty of solving real-time optimal control problems. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Multivariate optimization of a procedure employing microwave-assisted digestion for the determination of nickel and vanadium in crude oil by ICP OES.

PubMed

Dos Anjos, Shirlei L; Alves, Jeferson C; Rocha Soares, Sarah A; Araujo, Rennan G O; de Oliveira, Olivia M C; Queiroz, Antonio F S; Ferreira, Sergio L C

2018-02-01

This work presents the optimization of a sample preparation procedure using microwave-assisted digestion for the determination of nickel and vanadium in crude oil employing inductively coupled plasma optical emission spectrometry (ICP OES). The optimization step was performed utilizing a two-level full factorial design involving the following factors: concentrated nitric acid and hydrogen peroxide volumes, and microwave-assisted digestion temperature. Nickel and vanadium concentrations were used as responses. Additionally, a multiple response based on the normalization of the concentrations by the highest values was built to establish a compromise condition between the two analytes. A Doehlert matrix optimized the instrumental conditions of the ICP OE spectrometer. In this design, the plasma robustness was used as chemometric response. The experiments were performed using a digested oil sample solution doped with magnesium(II) ions, as well as a standard magnesium solution. The optimized method allows for the determination of nickel and vanadium with quantification limits of 0.79 and 0.20μgg -1 , respectively, for a digested sample mass of 0.1g. The precision (expressed as relative standard deviations) was determined using five replicates of two oil samples and the results obtained were 1.63% and 3.67% for nickel and 0.42% and 4.64% for vanadium. Bismuth and yttrium were also tested as internal standards, and the results demonstrate that yttrium allows for a better precision for the method. The accuracy was confirmed by the analysis of the certified reference material trace element in fuel oil (CRM NIST 1634c). The proposed method was applied for the determination of nickel and vanadium in five crude oil samples from Brazilian Basins. The metal concentrations found varied from 7.30 to 33.21μgg -1 for nickel and from 0.63 to 19.42μgg -1 for vanadium. Copyright © 2017. Published by Elsevier B.V.

3D synthetic aperture for controlled-source electromagnetics

NASA Astrophysics Data System (ADS)

Knaak, Allison

Locating hydrocarbon reservoirs has become more challenging with smaller, deeper or shallower targets in complicated environments. Controlled-source electromagnetics (CSEM), is a geophysical electromagnetic method used to detect and derisk hydrocarbon reservoirs in marine settings, but it is limited by the size of the target, low-spatial resolution, and depth of the reservoir. To reduce the impact of complicated settings and improve the detecting capabilities of CSEM, I apply synthetic aperture to CSEM responses, which virtually increases the length and width of the CSEM source by combining the responses from multiple individual sources. Applying a weight to each source steers or focuses the synthetic aperture source array in the inline and crossline directions. To evaluate the benefits of a 2D source distribution, I test steered synthetic aperture on 3D diffusive fields and view the changes with a new visualization technique. Then I apply 2D steered synthetic aperture to 3D noisy synthetic CSEM fields, which increases the detectability of the reservoir significantly. With more general weighting, I develop an optimization method to find the optimal weights for synthetic aperture arrays that adapts to the information in the CSEM data. The application of optimally weighted synthetic aperture to noisy, simulated electromagnetic fields reduces the presence of noise, increases detectability, and better defines the lateral extent of the target. I then modify the optimization method to include a term that minimizes the variance of random, independent noise. With the application of the modified optimization method, the weighted synthetic aperture responses amplifies the anomaly from the reservoir, lowers the noise floor, and reduces noise streaks in noisy CSEM responses from sources offset kilometers from the receivers. Even with changes to the location of the reservoir and perturbations to the physical properties, synthetic aperture is still able to highlight targets correctly, which allows use of the method in locations where the subsurface models are built from only estimates. In addition to the technical work in this thesis, I explore the interface between science, government, and society by examining the controversy over hydraulic fracturing and by suggesting a process to aid the debate and possibly other future controversies.

Heuristic query optimization for query multiple table and multiple clausa on mobile finance application

NASA Astrophysics Data System (ADS)

Indrayana, I. N. E.; P, N. M. Wirasyanti D.; Sudiartha, I. KG

2018-01-01

Mobile application allow many users to access data from the application without being limited to space, space and time. Over time the data population of this application will increase. Data access time will cause problems if the data record has reached tens of thousands to millions of records.The objective of this research is to maintain the performance of data execution for large data records. One effort to maintain data access time performance is to apply query optimization method. The optimization used in this research is query heuristic optimization method. The built application is a mobile-based financial application using MySQL database with stored procedure therein. This application is used by more than one business entity in one database, thus enabling rapid data growth. In this stored procedure there is an optimized query using heuristic method. Query optimization is performed on a “Select” query that involves more than one table with multiple clausa. Evaluation is done by calculating the average access time using optimized and unoptimized queries. Access time calculation is also performed on the increase of population data in the database. The evaluation results shown the time of data execution with query heuristic optimization relatively faster than data execution time without using query optimization.

An optimized computational method for determining the beta dose distribution using a multiple-element thermoluminescent dosimeter system.

PubMed

Shen, L; Levine, S H; Catchen, G L

1987-07-01

This paper describes an optimization method for determining the beta dose distribution in tissue, and it describes the associated testing and verification. The method uses electron transport theory and optimization techniques to analyze the responses of a three-element thermoluminescent dosimeter (TLD) system. Specifically, the method determines the effective beta energy distribution incident on the dosimeter system, and thus the system performs as a beta spectrometer. Electron transport theory provides the mathematical model for performing the optimization calculation. In this calculation, parameters are determined that produce calculated doses for each of the chip/absorber components in the three-element TLD system. The resulting optimized parameters describe an effective incident beta distribution. This method can be used to determine the beta dose specifically at 7 mg X cm-2 or at any depth of interest. The doses at 7 mg X cm-2 in tissue determined by this method are compared to those experimentally determined using an extrapolation chamber. For a great variety of pure beta sources having different incident beta energy distributions, good agreement is found. The results are also compared to those produced by a commonly used empirical algorithm. Although the optimization method produces somewhat better results, the advantage of the optimization method is that its performance is not sensitive to the specific method of calibration.

Multiple crack detection in 3D using a stable XFEM and global optimization

NASA Astrophysics Data System (ADS)

Agathos, Konstantinos; Chatzi, Eleni; Bordas, Stéphane P. A.

2018-02-01

A numerical scheme is proposed for the detection of multiple cracks in three dimensional (3D) structures. The scheme is based on a variant of the extended finite element method (XFEM) and a hybrid optimizer solution. The proposed XFEM variant is particularly well-suited for the simulation of 3D fracture problems, and as such serves as an efficient solution to the so-called forward problem. A set of heuristic optimization algorithms are recombined into a multiscale optimization scheme. The introduced approach proves effective in tackling the complex inverse problem involved, where identification of multiple flaws is sought on the basis of sparse measurements collected near the structural boundary. The potential of the scheme is demonstrated through a set of numerical case studies of varying complexity.

Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication

ERIC Educational Resources Information Center

Wolf, Michael Maclean

2009-01-01

Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

Co-extrusion of food grains-banana pulp for nutritious snacks: optimization of process variables.

PubMed

Mridula, D; Sethi, Swati; Tushir, Surya; Bhadwal, Sheetal; Gupta, R K; Nanda, S K

2017-08-01

Present study was undertaken to optimize the process conditions for development of food grains (maize, defatted soy flour, sesame seed)-banana based nutritious expanded snacks using extrusion processing. Experiments were designed using Box-Behnken design with banana pulp (8-24 g), screw speed (300-350 rpm) and feed moisture (14-16% w.b.). Seven responses viz. expansion ratio (ER), bulk density (BD), water absorption index (WAI), protein, minerals, iron and sensory acceptability were considered for optimizing independent parameters. ER, BD, WAI, protein content, total minerals, iron content, and overall acceptability ranged 2.69-3.36, 153.43-238.83 kg/m 3 , 4.56-4.88 g/g, 15.19-15.52%, 2.06-2.27%, 4.39-4.67 mg/100 g (w.b.) and 6.76-7.36, respectively. ER was significantly affected by all three process variables while BD was influenced by banana pulp and screw speed only. Studied process variables did not affected colour quality except 'a' value with banana pulp and screw speed. Banana pulp had positive correlation with water solubility index, total minerals and iron content and negative with WAI, protein and overall acceptability. Based upon multiple response analysis, optimized conditions were 8 g banana pulp, 350 rpm screw speed and 14% feed moisture indicating the protein, calorie, iron content and overall sensory acceptability in sample as 15.46%, 401 kcal/100 g, 4.48 mg/100 g and 7.6 respectively.

Optimizing LX-17 Thermal Decomposition Model Parameters with Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Moore, Jason; McClelland, Matthew; Tarver, Craig; Hsu, Peter; Springer, H. Keo

2017-06-01

We investigate and model the cook-off behavior of LX-17 because this knowledge is critical to understanding system response in abnormal thermal environments. Thermal decomposition of LX-17 has been explored in conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (thermogravimetric analysis), and DSC (differential scanning calorimetry) experiments using varied temperature profiles. These experimental data are the basis for developing multiple reaction schemes with coupled mechanics in LLNL's multi-physics hydrocode, ALE3D (Arbitrary Lagrangian-Eulerian code in 2D and 3D). We employ evolutionary algorithms to optimize reaction rate parameters on high performance computing clusters. Once experimentally validated, this model will be scalable to a number of applications involving LX-17 and can be used to develop more sophisticated experimental methods. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials. This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNS, LLC.

Comparative study of coated and uncoated tool inserts with dry machining of EN47 steel using Taguchi L9 optimization technique

NASA Astrophysics Data System (ADS)

Vasu, M.; Shivananda, Nayaka H.

2018-04-01

EN47 steel samples are machined on a self-centered lathe using Chemical Vapor Deposition of coated TiCN/Al2O3/TiN and uncoated tungsten carbide tool inserts, with nose radius 0.8mm. Results are compared with each other and optimized using statistical tool. Input (cutting) parameters that are considered in this work are feed rate (f), cutting speed (Vc), and depth of cut (ap), the optimization criteria are based on the Taguchi (L9) orthogonal array. ANOVA method is adopted to evaluate the statistical significance and also percentage contribution for each model. Multiple response characteristics namely cutting force (Fz), tool tip temperature (T) and surface roughness (Ra) are evaluated. The results discovered that coated tool insert (TiCN/Al2O3/TiN) exhibits 1.27 and 1.29 times better than the uncoated tool insert for tool tip temperature and surface roughness respectively. A slight increase in cutting force was observed for coated tools.

Multi-rendezvous low-thrust trajectory optimization using costate transforming and homotopic approach

NASA Astrophysics Data System (ADS)

Chen, Shiyu; Li, Haiyang; Baoyin, Hexi

2018-06-01

This paper investigates a method for optimizing multi-rendezvous low-thrust trajectories using indirect methods. An efficient technique, labeled costate transforming, is proposed to optimize multiple trajectory legs simultaneously rather than optimizing each trajectory leg individually. Complex inner-point constraints and a large number of free variables are one main challenge in optimizing multi-leg transfers via shooting algorithms. Such a difficulty is reduced by first optimizing each trajectory leg individually. The results may be, next, utilized as an initial guess in the simultaneous optimization of multiple trajectory legs. In this paper, the limitations of similar techniques in previous research is surpassed and a homotopic approach is employed to improve the convergence efficiency of the shooting process in multi-rendezvous low-thrust trajectory optimization. Numerical examples demonstrate that newly introduced techniques are valid and efficient.

Optimization of knowledge sharing through multi-forum using cloud computing architecture

NASA Astrophysics Data System (ADS)

Madapusi Vasudevan, Sriram; Sankaran, Srivatsan; Muthuswamy, Shanmugasundaram; Ram, N. Sankar

2011-12-01

Knowledge sharing is done through various knowledge sharing forums which requires multiple logins through multiple browser instances. Here a single Multi-Forum knowledge sharing concept is introduced which requires only one login session which makes user to connect multiple forums and display the data in a single browser window. Also few optimization techniques are introduced here to speed up the access time using cloud computing architecture.

Channel Model Optimization with Reflection Residual Component for Indoor MIMO-VLC System

NASA Astrophysics Data System (ADS)

Chen, Yong; Li, Tengfei; Liu, Huanlin; Li, Yichao

2017-12-01

A fast channel modeling method is studied to solve the problem of reflection channel gain for multiple input multiple output-visible light communications (MIMO-VLC) in the paper. For reducing the computational complexity when associating with the reflection times, no more than 3 reflections are taken into consideration in VLC. We think that higher order reflection link consists of corresponding many times line of sight link and firstly present reflection residual component to characterize higher reflection (more than 2 reflections). We perform computer simulation results for point-to-point channel impulse response, receiving optical power and receiving signal to noise ratio. Based on theoretical analysis and simulation results, the proposed method can effectively reduce the computational complexity of higher order reflection in channel modeling.

Operation and planning of coordinated natural gas and electricity infrastructures

NASA Astrophysics Data System (ADS)

Zhang, Xiaping

Natural gas is becoming rapidly the optimal choice for fueling new generating units in electric power system driven by abundant natural gas supplies and environmental regulations that are expected to cause coal-fired generation retirements. The growing reliance on natural gas as a dominant fuel for electricity generation throughout North America has brought the interaction between the natural gas and power grids into sharp focus. The primary concern and motivation of this research is to address the emerging interdependency issues faced by the electric power and natural gas industry. This thesis provides a comprehensive analysis of the interactions between the two systems regarding the short-term operation and long-term infrastructure planning. Natural gas and renewable energy appear complementary in many respects regarding fuel price and availability, environmental impact, resource distribution and dispatchability. In addition, demand response has also held the promise of making a significant contribution to enhance system operations by providing incentives to customers for a more flat load profile. We investigated the coordination between natural gas-fired generation and prevailing nontraditional resources including renewable energy, demand response so as to provide economical options for optimizing the short-term scheduling with the intense natural gas delivery constraints. As the amount and dispatch of gas-fired generation increases, the long-term interdependency issue is whether there is adequate pipeline capacity to provide sufficient gas to natural gas-fired generation during the entire planning horizon while it is widely used outside the power sector. This thesis developed a co-optimization planning model by incorporating the natural gas transportation system into the multi-year resource and transmission system planning problem. This consideration would provide a more comprehensive decision for the investment and accurate assessment for system adequacy and reliability. With the growing reliance on natural gas and widespread utilization of highly efficient combined heat and power (CHP), it is also questionable that whether the independent design of infrastructures can meet potential challenges of future energy supply. To address this issue, this thesis proposed an optimization framework for a sustainable multiple energy system expansion planning based on an energy hub model while considering the energy efficiency, emission and reliability performance. In addition, we introduced the probabilistic reliability evaluation and flow network analysis into the multiple energy system design in order to obtain an optimal and reliable network topology.

An Integrated Method for Airfoil Optimization

NASA Astrophysics Data System (ADS)

Okrent, Joshua B.

Design exploration and optimization is a large part of the initial engineering and design process. To evaluate the aerodynamic performance of a design, viscous Navier-Stokes solvers can be used. However this method can prove to be overwhelmingly time consuming when performing an initial design sweep. Therefore, another evaluation method is needed to provide accurate results at a faster pace. To accomplish this goal, a coupled viscous-inviscid method is used. This thesis proposes an integrated method for analyzing, evaluating, and optimizing an airfoil using a coupled viscous-inviscid solver along with a genetic algorithm to find the optimal candidate. The method proposed is different from prior optimization efforts in that it greatly broadens the design space, while allowing the optimization to search for the best candidate that will meet multiple objectives over a characteristic mission profile rather than over a single condition and single optimization parameter. The increased design space is due to the use of multiple parametric airfoil families, namely the NACA 4 series, CST family, and the PARSEC family. Almost all possible airfoil shapes can be created with these three families allowing for all possible configurations to be included. This inclusion of multiple airfoil families addresses a possible criticism of prior optimization attempts since by only focusing on one airfoil family, they were inherently limiting the number of possible airfoil configurations. By using multiple parametric airfoils, it can be assumed that all reasonable airfoil configurations are included in the analysis and optimization and that a global and not local maximum is found. Additionally, the method used is amenable to customization to suit any specific needs as well as including the effects of other physical phenomena or design criteria and/or constraints. This thesis found that an airfoil configuration that met multiple objectives could be found for a given set of nominal operational conditions from a broad design space with the use of minimal computational resources on both an absolute and relative scale to traditional analysis techniques. Aerodynamicists, program managers, aircraft configuration specialist, and anyone else in charge of aircraft configuration, design studies, and program level decisions might find the evaluation and optimization method proposed of interest.

Informed multi-objective decision-making in environmental management using Pareto optimality

Treesearch

Maureen C. Kennedy; E. David Ford; Peter Singleton; Mark Finney; James K. Agee

2008-01-01

Effective decisionmaking in environmental management requires the consideration of multiple objectives that may conflict. Common optimization methods use weights on the multiple objectives to aggregate them into a single value, neglecting valuable insight into the relationships among the objectives in the management problem.

Towards a hierarchical optimization framework for spatially targeting incentive policies to promote green infrastructure amidst multiple objectives and uncertainty

EPA Science Inventory

We introduce a hierarchical optimization framework for spatially targeting green infrastructure (GI) incentive policies in order to meet objectives related to cost and environmental effectiveness. The framework explicitly simulates the interaction between multiple levels of polic...

Rapid optimization of multiple-burn rocket flights.

NASA Technical Reports Server (NTRS)

Brown, K. R.; Harrold, E. F.; Johnson, G. W.

1972-01-01

Different formulations of the fuel optimization problem for multiple burn trajectories are considered. It is shown that certain customary idealizing assumptions lead to an ill-posed optimization problem for which no solution exists. Several ways are discussed for avoiding such difficulties by more realistic problem statements. An iterative solution of the boundary value problem is presented together with efficient coast arc computations, the right end conditions for various orbital missions, and some test results.

Three-factor response surface optimization of nano-emulsion formation using a microfluidizer.

PubMed

Sadeghpour Galooyak, Saeed; Dabir, Bahram

2015-05-01

Emulsification of sunflower oil in water by microfluidization was studied. Response surface methodology (RSM) and the central composite design (CCD) were applied to determine the effects of certain process parameters on performance of the apparatus for optimization of nano-emulsion fabrication. Influence of pressure, oil content and number of passes on the disruption of emulsions was studied. Quadratic multiple regression models were chosen for two available responses, namely Sauter mean diameter (SMD) and Polydispersity index (PdI). Analysis of variance (ANOVA) showed a high coefficient of determination (R(2)) value for both responses, confirming adjustment of the models with experimental data. The SMD and the PdI decreased as the pressure of emulsification increased from 408 to 762.3 bar for the oil content of 5 vol% and from 408 to 854.4 bar for the oil content of 13 vol%, and thereafter, increasing the pressure up to 952 bar led to increasing the both responses. The results implied that laminar elongational flow is the alternative disruption mechanism in addition to inertia in turbulence flow, especially at low treatment pressures. Both of responses improved with increase in number of passes from 2 to 4 cycles. The oil content depicted low effect on responses; however, interaction of this parameter with other regressors pointed remarkable impact. Also, the effect of pressure on Kolmogorov micro-scale was studied. The results implied that Kolmogorov equation did not take into account the over-processing and was applicable only for disruption of droplets in the inertial turbulent flow.

Multi-objective optimization strategy based on desirability functions used for electrophoratic separation and quantification of rosiglitazone and glimepiride in plasma and formulations.

PubMed

Hefnawy, Mohamed M; Sultan, Maha A; Al-Johar, Haya I; Kassem, Mohamed G; Aboul-Enein, Hassan Y

2012-01-01

Multiple response simultaneous optimization employing Derringer's desirability function was used for the development of a capillary electrophoresis method for the simultaneous determination of rosiglitazone (RSG) and glimepiride (GLM) in plasma and formulations. Twenty experiments, taking the two resolutions, the analysis time, and the capillary current as the responses with three important factors--buffer morality, volte and column temperature--were used to design mathematical models. The experimental responses were fitted into a second order polynomial and the six responses were simultaneously optimized to predict the optimum conditions for the effective separation of the studied compounds. The separation was carried out by using capillary zone electrophoresis (CZE) with a silica capillary column and diode array detector at 210 nm. The optimum assay conditions were 52 mmol l⁻¹ phosphate buffer, pH 7, and voltage of 22 kV at 29 °C. The method showed good agreement between the experimental data and predictive value throughout the studied parameter space. The assay limit of detection was 0.02 µg ml⁻¹ and the effective working range at relative standard deviation (RSD) of ≤ 5% was 0.05-16 µg ml⁻¹ (r = 0.999) for both drugs. Analytical recoveries of the studied drugs from spiked plasma were 97.2-101.9 ± 0.31-3.0%. The precision of the assay was satisfactory; RSD was 1.07 and 1.14 for intra- and inter-assay precision, respectively. The proposed method has a great value in routine analysis of RSG and GLM for its therapeutic monitoring and pharmacokinetic studies. Copyright © 2011 John Wiley & Sons, Ltd.

Utility of BRDF Models for Estimating Optimal View Angles in Classification of Remotely Sensed Images

NASA Technical Reports Server (NTRS)

Valdez, P. F.; Donohoe, G. W.

1997-01-01

Statistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.

Structured plant metabolomics for the simultaneous exploration of multiple factors.

PubMed

Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

2016-11-17

Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor-metabolite crosstalk. However, unravelling all factor-metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset.

Multidimensional biochemical information processing of dynamical patterns

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Optimum design of structures subject to general periodic loads

NASA Technical Reports Server (NTRS)

Reiss, Robert; Qian, B.

1989-01-01

A simplified version of Icerman's problem regarding the design of structures subject to a single harmonic load is discussed. The nature of the restrictive conditions that must be placed on the design space in order to ensure an analytic optimum are discussed in detail. Icerman's problem is then extended to include multiple forcing functions with different driving frequencies. And the conditions that now must be placed upon the design space to ensure an analytic optimum are again discussed. An important finding is that all solutions to the optimality condition (analytic stationary design) are local optima, but the global optimum may well be non-analytic. The more general problem of distributing the fixed mass of a linear elastic structure subject to general periodic loads in order to minimize some measure of the steady state deflection is also considered. This response is explicitly expressed in terms of Green's functional and the abstract operators defining the structure. The optimality criterion is derived by differentiating the response with respect to the design parameters. The theory is applicable to finite element as well as distributed parameter models.

Design of isolated buildings with S-FBI system subjected to near-fault earthquakes using NSGA-II algorithm

NASA Astrophysics Data System (ADS)

Ozbulut, O. E.; Silwal, B.

2014-04-01

This study investigates the optimum design parameters of a superelastic friction base isolator (S-FBI) system through a multi-objective genetic algorithm and performance-based evaluation approach. The S-FBI system consists of a flat steel- PTFE sliding bearing and a superelastic NiTi shape memory alloy (SMA) device. Sliding bearing limits the transfer of shear across the isolation interface and provides damping from sliding friction. SMA device provides restoring force capability to the isolation system together with additional damping characteristics. A three-story building is modeled with S-FBI isolation system. Multiple-objective numerical optimization that simultaneously minimizes isolation-level displacements and superstructure response is carried out with a genetic algorithm (GA) in order to optimize S-FBI system. Nonlinear time history analyses of the building with S-FBI system are performed. A set of 20 near-field ground motion records are used in numerical simulations. Results show that S-FBI system successfully control response of the buildings against near-fault earthquakes without sacrificing in isolation efficacy and producing large isolation-level deformations.

Analytical instrumentation infrastructure for combinatorial and high-throughput development of formulated discrete and gradient polymeric sensor materials arrays

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Hassib, Lamyaa

2005-06-01

Multicomponent polymer-based formulations of optical sensor materials are difficult and time consuming to optimize using conventional approaches. To address these challenges, our long-term goal is to determine relationships between sensor formulation and sensor response parameters using new scientific methodologies. As the first step, we have designed and implemented an automated analytical instrumentation infrastructure for combinatorial and high-throughput development of polymeric sensor materials for optical sensors. Our approach is based on the fabrication and performance screening of discrete and gradient sensor arrays. Simultaneous formation of multiple sensor coatings into discrete 4×6, 6×8, and 8×12 element arrays (3-15μL volume per element) and their screening provides not only a well-recognized acceleration in the screening rate, but also considerably reduces or even eliminates sources of variability, which are randomly affecting sensors response during a conventional one-at-a-time sensor coating evaluation. The application of gradient sensor arrays provides additional capabilities for rapid finding of the optimal formulation parameters.

Multidimensional biochemical information processing of dynamical patterns.

PubMed

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Distribution path robust optimization of electric vehicle with multiple distribution centers

PubMed Central

Hao, Wei; He, Ruichun; Jia, Xiaoyan; Pan, Fuquan; Fan, Jing; Xiong, Ruiqi

2018-01-01

To identify electrical vehicle (EV) distribution paths with high robustness, insensitivity to uncertainty factors, and detailed road-by-road schemes, optimization of the distribution path problem of EV with multiple distribution centers and considering the charging facilities is necessary. With the minimum transport time as the goal, a robust optimization model of EV distribution path with adjustable robustness is established based on Bertsimas’ theory of robust discrete optimization. An enhanced three-segment genetic algorithm is also developed to solve the model, such that the optimal distribution scheme initially contains all road-by-road path data using the three-segment mixed coding and decoding method. During genetic manipulation, different interlacing and mutation operations are carried out on different chromosomes, while, during population evolution, the infeasible solution is naturally avoided. A part of the road network of Xifeng District in Qingyang City is taken as an example to test the model and the algorithm in this study, and the concrete transportation paths are utilized in the final distribution scheme. Therefore, more robust EV distribution paths with multiple distribution centers can be obtained using the robust optimization model. PMID:29518169

Future of management of multiple sclerosis in the middle East: a consensus view from specialists in ten countries.

PubMed

Aljumah, Mohammed; Alroughani, Raed; Alsharoqi, I; Bohlega, Saeed A; Dahdaleh, Maurice; Deleu, Dirk; Esmat, Khaled; Khalifa, Ahmad; Sahraian, Mohammad A; Szólics, Miklós; Altahan, Abdulrahman; Yamout, Bassem I; Rieckmann, Peter; Daif, Abdulkader

2013-01-01

The prevalence of multiple sclerosis (MS) is now considered to be medium-to-high in the Middle East and is rising, particularly among women. While the characteristics of the disease and the response of patients to disease-modifying therapies are generally comparable between the Middle East and other areas, significant barriers to achieving optimal care for MS exist in these developing nations. A group of physicians involved in the management of MS in ten Middle Eastern countries met to consider the future of MS care in the region, using a structured process to reach a consensus. Six key priorities were identified: early diagnosis and management of MS, the provision of multidisciplinary MS centres, patient engagement and better communication with stakeholders, regulatory body education and reimbursement, a commitment to research, and more therapy options with better benefit-to-risk ratios. The experts distilled these priorities into a single vision statement: "Optimization of patient-centred multidisciplinary strategies to improve the quality of life of people with MS." These core principles will contribute to the development of a broader consensus on the future of care for MS in the Middle East.

Ideal AFROC and FROC observers.

PubMed

Khurd, Parmeshwar; Liu, Bin; Gindi, Gene

2010-02-01

Detection of multiple lesions in images is a medically important task and free-response receiver operating characteristic (FROC) analyses and its variants, such as alternative FROC (AFROC) analyses, are commonly used to quantify performance in such tasks. However, ideal observers that optimize FROC or AFROC performance metrics have not yet been formulated in the general case. If available, such ideal observers may turn out to be valuable for imaging system optimization and in the design of computer aided diagnosis techniques for lesion detection in medical images. In this paper, we derive ideal AFROC and FROC observers. They are ideal in that they maximize, amongst all decision strategies, the area, or any partial area, under the associated AFROC or FROC curve. Calculation of observer performance for these ideal observers is computationally quite complex. We can reduce this complexity by considering forms of these observers that use false positive reports derived from signal-absent images only. We also consider a Bayes risk analysis for the multiple-signal detection task with an appropriate definition of costs. A general decision strategy that minimizes Bayes risk is derived. With particular cost constraints, this general decision strategy reduces to the decision strategy associated with the ideal AFROC or FROC observer.

Quantum Chemical and Docking Insights into Bioavailability Enhancement of Curcumin by Piperine in Pepper.

PubMed

Patil, Vaishali M; Das, Sukanya; Balasubramanian, Krishnan

2016-05-26

We combine quantum chemical and molecular docking techniques to provide new insights into how piperine molecule in various forms of pepper enhances bioavailability of a number of drugs including curcumin in turmeric for which it increases its bioavailability by a 20-fold. We have carried out docking studies of quantum chemically optimized piperine structure binding to curcumin, CYP3A4 in cytochrome P450, p-Glycoprotein and UDP-glucuronosyltransferase (UGT), the enzyme responsible for glucuronosylation, which increases the solubility of curcumin. All of these studies establish that piperine binds to multiple sites on the enzymes and also intercalates with curcumin forming a hydrogen bonded complex with curcumin. The conjugated network of double bonds and the presence of multiple charge centers of piperine offer optimal binding sites for piperine to bind to enzymes such as UDP-GDH, UGT, and CYP3A4. Piperine competes for curcumin's intermolecular hydrogen bonding and its stacking propensity by hydrogen bonding with enolic proton of curcumin. This facilitates its metabolic transport, thereby increasing its bioavailability both through intercalation into curcumin layers through intermolecular hydrogen bonding, and by inhibiting enzymes that cause glucuronosylation of curcumin.

Optimization of Car Body under Constraints of Noise, Vibration, and Harshness (NVH), and Crash

NASA Technical Reports Server (NTRS)

Kodiyalam, Srinivas; Yang, Ren-Jye; Sobieszczanski-Sobieski, Jaroslaw (Editor)

2000-01-01

To be competitive on the today's market, cars have to be as light as possible while meeting the Noise, Vibration, and Harshness (NVH) requirements and conforming to Government-man dated crash survival regulations. The latter are difficult to meet because they involve very compute-intensive, nonlinear analysis, e.g., the code RADIOSS capable of simulation of the dynamics, and the geometrical and material nonlinearities of a thin-walled car structure in crash, would require over 12 days of elapsed time for a single design of a 390K elastic degrees of freedom model, if executed on a single processor of the state-of-the-art SGI Origin2000 computer. Of course, in optimization that crash analysis would have to be invoked many times. Needless to say, that has rendered such optimization intractable until now. The car finite element model is shown. The advent of computers that comprise large numbers of concurrently operating processors has created a new environment wherein the above optimization, and other engineering problems heretofore regarded as intractable may be solved. The procedure, shown, is a piecewise approximation based method and involves using a sensitivity based Taylor series approximation model for NVH and a polynomial response surface model for Crash. In that method the NVH constraints are evaluated using a finite element code (MSC/NASTRAN) that yields the constraint values and their derivatives with respect to design variables. The crash constraints are evaluated using the explicit code RADIOSS on the Origin 2000 operating on 256 processors simultaneously to generate data for a polynomial response surface in the design variable domain. The NVH constraints and their derivatives combined with the response surface for the crash constraints form an approximation to the system analysis (surrogate analysis) that enables a cycle of multidisciplinary optimization within move limits. In the inner loop, the NVH sensitivities are recomputed to update the NVH approximation model while keeping the Crash response surface constant. In every outer loop, the Crash response surface approximation is updated, including a gradual increase in the order of the response surface and the response surface extension in the direction of the search. In this optimization task, the NVH discipline has 30 design variables while the crash discipline has 20 design variables. A subset of these design variables (10) are common to both the NVH and crash disciplines. In order to construct a linear response surface for the Crash discipline constraints, a minimum of 21 design points would have to be analyzed using the RADIOSS code. On a single processor in Origin 2000 that amount of computing would require over 9 months! In this work, these runs were carried out concurrently on the Origin 2000 using multiple processors, ranging from 8 to 16, for each crash (RADIOSS) analysis. Another figure shows the wall time required for a single RADIOSS analysis using varying number of processors, as well as provides a comparison of 2 different common data placement procedures within the allotted memories for each analysis. The initial design is an infeasible design with NVH discipline Static Torsion constraint violations of over 10%. The final optimized design is a feasible design with a weight reduction of 15 kg compared to the initial design. This work demonstrates how advanced methodology for optimization combined with the technology of concurrent processing enables applications that until now were out of reach because of very long time-to-solution.

EUD-based biological optimization for carbon ion therapy

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

Brüningk, Sarah C., E-mail: sarah.brueningk@icr.ac.uk; Kamp, Florian; Wilkens, Jan J.

2015-11-15

Purpose: Treatment planning for carbon ion therapy requires an accurate modeling of the biological response of each tissue to estimate the clinical outcome of a treatment. The relative biological effectiveness (RBE) accounts for this biological response on a cellular level but does not refer to the actual impact on the organ as a whole. For photon therapy, the concept of equivalent uniform dose (EUD) represents a simple model to take the organ response into account, yet so far no formulation of EUD has been reported that is suitable to carbon ion therapy. The authors introduce the concept of an equivalentmore » uniform effect (EUE) that is directly applicable to both ion and photon therapies and exemplarily implemented it as a basis for biological treatment plan optimization for carbon ion therapy. Methods: In addition to a classical EUD concept, which calculates a generalized mean over the RBE-weighted dose distribution, the authors propose the EUE to simplify the optimization process of carbon ion therapy plans. The EUE is defined as the biologically equivalent uniform effect that yields the same probability of injury as the inhomogeneous effect distribution in an organ. Its mathematical formulation is based on the generalized mean effect using an effect-volume parameter to account for different organ architectures and is thus independent of a reference radiation. For both EUD concepts, quadratic and logistic objective functions are implemented into a research treatment planning system. A flexible implementation allows choosing for each structure between biological effect constraints per voxel and EUD constraints per structure. Exemplary treatment plans are calculated for a head-and-neck patient for multiple combinations of objective functions and optimization parameters. Results: Treatment plans optimized using an EUE-based objective function were comparable to those optimized with an RBE-weighted EUD-based approach. In agreement with previous results from photon therapy, the optimization by biological objective functions resulted in slightly superior treatment plans in terms of final EUD for the organs at risk (OARs) compared to voxel-based optimization approaches. This observation was made independent of the underlying objective function metric. An absolute gain in OAR sparing was observed for quadratic objective functions, whereas intersecting DVHs were found for logistic approaches. Even for considerable under- or overestimations of the used effect- or dose–volume parameters during the optimization, treatment plans were obtained that were of similar quality as the results of a voxel-based optimization. Conclusions: EUD-based optimization with either of the presented concepts can successfully be applied to treatment plan optimization. This makes EUE-based optimization for carbon ion therapy a useful tool to optimize more specifically in the sense of biological outcome while voxel-to-voxel variations of the biological effectiveness are still properly accounted for. This may be advantageous in terms of computational cost during treatment plan optimization but also enables a straight forward comparison of different fractionation schemes or treatment modalities.« less

Growth factor transgenes interactively regulate articular chondrocytes.

PubMed

Shi, Shuiliang; Mercer, Scott; Eckert, George J; Trippel, Stephen B

2013-04-01

Adult articular chondrocytes lack an effective repair response to correct damage from injury or osteoarthritis. Polypeptide growth factors that stimulate articular chondrocyte proliferation and cartilage matrix synthesis may augment this response. Gene transfer is a promising approach to delivering such factors. Multiple growth factor genes regulate these cell functions, but multiple growth factor gene transfer remains unexplored. We tested the hypothesis that multiple growth factor gene transfer selectively modulates articular chondrocyte proliferation and matrix synthesis. We tested the hypothesis by delivering combinations of the transgenes encoding insulin-like growth factor I (IGF-I), fibroblast growth factor-2 (FGF-2), transforming growth factor beta1 (TGF-β1), bone morphogenetic protein-2 (BMP-2), and bone morphogenetic protien-7 (BMP-7) to articular chondrocytes and measured changes in the production of DNA, glycosaminoglycan, and collagen. The transgenes differentially regulated all these chondrocyte activities. In concert, the transgenes interacted to generate widely divergent responses from the cells. These interactions ranged from inhibitory to synergistic. The transgene pair encoding IGF-I and FGF-2 maximized cell proliferation. The three-transgene group encoding IGF-I, BMP-2, and BMP-7 maximized matrix production and also optimized the balance between cell proliferation and matrix production. These data demonstrate an approach to articular chondrocyte regulation that may be tailored to stimulate specific cell functions, and suggest that certain growth factor gene combinations have potential value for cell-based articular cartilage repair. Copyright © 2012 Wiley Periodicals, Inc.

Optimizing plasmonic nanoantennas via coordinated multiple coupling

NASA Astrophysics Data System (ADS)

Lin, Linhan; Zheng, Yuebing

2015-10-01

Plasmonic nanoantennas, which can efficiently convert light from free space into sub-wavelength scale with the local field enhancement, are fundamental building blocks for nanophotonic systems. Predominant design methods, which exploit a single type of near- or far-field coupling in pairs or arrays of plasmonic nanostructures, have limited the tunability of spectral response and the local field enhancement. To overcome this limit, we are developing a general strategy towards exploiting the coordinated effects of multiple coupling. Using Au bowtie nanoantenna arrays with metal-insulator-metal configuration as examples, we numerically demonstrate that coordinated design and implementation of various optical coupling effects leads to both the increased tunability in the spectral response and the significantly enhanced electromagnetic field. Furthermore, we design and analyze a refractive index sensor with an ultra-high figure-of-merit (254), a high signal-to-noise ratio and a wide working range of refractive indices, and a narrow-band near-infrared plasmonic absorber with 100% absorption efficiency, high quality factor of up to 114 and a wide range of tunable wavelength from 800 nm to 1,500 nm. The plasmonic nanoantennas that exploit coordinated multiple coupling will benefit a broad range of applications, including label-free bio-chemical detection, reflective filter, optical trapping, hot-electron generation, and heat-assisted magnetic recording.

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

NASA Technical Reports Server (NTRS)

Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon C.; Zhu, Zhifan; Jeong, Myeongsook; Kim, Hyounkong; Oh, Eunmi; Hong, Sungkwon

2017-01-01

This study aims to develop a controllers decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

NASA Technical Reports Server (NTRS)

Eun, Yeonju; Jeon, Daekeun; Lee, Hanbong; Jung, Yoon Chul; Zhu, Zhifan; Jeong, Myeong-Sook; Kim, Hyoun Kyoung; Oh, Eunmi; Hong, Sungkwon

2017-01-01

This study aims to develop a controllers' decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA).

Multiple burn fuel-optimal orbit transfers: Numerical trajectory computation and neighboring optimal feedback guidance

NASA Technical Reports Server (NTRS)

Chuang, C.-H.; Goodson, Troy D.; Ledsinger, Laura A.

1995-01-01

This report describes current work in the numerical computation of multiple burn, fuel-optimal orbit transfers and presents an analysis of the second variation for extremal multiple burn orbital transfers as well as a discussion of a guidance scheme which may be implemented for such transfers. The discussion of numerical computation focuses on the use of multivariate interpolation to aid the computation in the numerical optimization. The second variation analysis includes the development of the conditions for the examination of both fixed and free final time transfers. Evaluations for fixed final time are presented for extremal one, two, and three burn solutions of the first variation. The free final time problem is considered for an extremal two burn solution. In addition, corresponding changes of the second variation formulation over thrust arcs and coast arcs are included. The guidance scheme discussed is an implicit scheme which implements a neighboring optimal feedback guidance strategy to calculate both thrust direction and thrust on-off times.

Scalable and responsive event processing in the cloud

PubMed Central

Suresh, Visalakshmi; Ezhilchelvan, Paul; Watson, Paul

2013-01-01

Event processing involves continuous evaluation of queries over streams of events. Response-time optimization is traditionally done over a fixed set of nodes and/or by using metrics measured at query-operator levels. Cloud computing makes it easy to acquire and release computing nodes as required. Leveraging this flexibility, we propose a novel, queueing-theory-based approach for meeting specified response-time targets against fluctuating event arrival rates by drawing only the necessary amount of computing resources from a cloud platform. In the proposed approach, the entire processing engine of a distinct query is modelled as an atomic unit for predicting response times. Several such units hosted on a single node are modelled as a multiple class M/G/1 system. These aspects eliminate intrusive, low-level performance measurements at run-time, and also offer portability and scalability. Using model-based predictions, cloud resources are efficiently used to meet response-time targets. The efficacy of the approach is demonstrated through cloud-based experiments. PMID:23230164

Optimization of Nonambulant Mass Casualty Decontamination Protocols as Part of an Initial or Specialist Operational Response to Chemical Incidents.

PubMed

Chilcott, Robert P; Mitchell, Hannah; Matar, Hazem

2018-05-30

The UK's Initial Operational Response (IOR) is a new process for improving the survival of multiple casualties following a chemical, biological, radiological or nuclear incident. Whilst the introduction of IOR represents a patient-focused response for ambulant casualties, there is currently no provision for disrobe and dry decontamination of nonambulant casualties. Moreover, the current specialist operational response (SOR) protocol for nonambulant casualty decontamination (also referred to as "clinical decontamination") has not been subject to rigorous evaluation or development. Therefore, the aim of this study was to confirm the effectiveness of putatively optimized dry (IOR) and wet (SOR) protocols for nonambulant decontamination in human volunteers. Dry and wet decontamination protocols were objectively evaluated using human volunteers. Decontamination effectiveness was quantified by liquid chromatography-mass spectrometry analysis of the recovery of a chemical warfare agent simulant (methylsalicylate) from skin and hair of volunteers, with whole-body fluorescence imaging to quantify the skin distribution of residual simulant. Both the dry and wet decontamination processes were rapid (3 and 4 min, respectively) and were effective in removing simulant from the hair and skin of volunteers, with no observable adverse effects related to skin surface spreading of contaminant. Further studies are required to assess the combined effectiveness of dry and wet decontamination under more realistic conditions and to develop appropriate operational procedures that ensure the safety of first responders.

Multiple shooting algorithms for jump-discontinuous problems in optimal control and estimation

NASA Technical Reports Server (NTRS)

Mook, D. J.; Lew, Jiann-Shiun

1991-01-01

Multiple shooting algorithms are developed for jump-discontinuous two-point boundary value problems arising in optimal control and optimal estimation. Examples illustrating the origin of such problems are given to motivate the development of the solution algorithms. The algorithms convert the necessary conditions, consisting of differential equations and transversality conditions, into algebraic equations. The solution of the algebraic equations provides exact solutions for linear problems. The existence and uniqueness of the solution are proved.

PrimerDesign-M: A multiple-alignment based multiple-primer design tool for walking across variable genomes

DOE PAGES

Yoon, Hyejin; Leitner, Thomas

2014-12-17

Analyses of entire viral genomes or mtDNA requires comprehensive design of many primers across their genomes. In addition, simultaneous optimization of several DNA primer design criteria may improve overall experimental efficiency and downstream bioinformatic processing. To achieve these goals, we developed PrimerDesign-M. It includes several options for multiple-primer design, allowing researchers to efficiently design walking primers that cover long DNA targets, such as entire HIV-1 genomes, and that optimizes primers simultaneously informed by genetic diversity in multiple alignments and experimental design constraints given by the user. PrimerDesign-M can also design primers that include DNA barcodes and minimize primer dimerization. PrimerDesign-Mmore » finds optimal primers for highly variable DNA targets and facilitates design flexibility by suggesting alternative designs to adapt to experimental conditions.« less

Analysis and optimization of machining parameters of laser cutting for polypropylene composite

NASA Astrophysics Data System (ADS)

Deepa, A.; Padmanabhan, K.; Kuppan, P.

2017-11-01

Present works explains about machining of self-reinforced Polypropylene composite fabricated using hot compaction method. The objective of the experiment is to find optimum machining parameters for Polypropylene (PP). Laser power and Machining speed were the parameters considered in response to tensile test and Flexure test. Taguchi method is used for experimentation. Grey Relational Analysis (GRA) is used for multiple process parameter optimization. ANOVA (Analysis of Variance) is used to find impact for process parameter. Polypropylene has got the great application in various fields like, it is used in the form of foam in model aircraft and other radio-controlled vehicles, thin sheets (∼2-20μm) used as a dielectric, PP is also used in piping system, it is also been used in hernia and pelvic organ repair or protect new herrnis in the same location.

Finite burn maneuver modeling for a generalized spacecraft trajectory design and optimization system.

PubMed

Ocampo, Cesar

2004-05-01

The modeling, design, and optimization of finite burn maneuvers for a generalized trajectory design and optimization system is presented. A generalized trajectory design and optimization system is a system that uses a single unified framework that facilitates the modeling and optimization of complex spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The modeling and optimization issues associated with the use of controlled engine burn maneuvers of finite thrust magnitude and duration are presented in the context of designing and optimizing a wide class of finite thrust trajectories. Optimal control theory is used examine the optimization of these maneuvers in arbitrary force fields that are generally position, velocity, mass, and are time dependent. The associated numerical methods used to obtain these solutions involve either, the solution to a system of nonlinear equations, an explicit parameter optimization method, or a hybrid parameter optimization that combines certain aspects of both. The theoretical and numerical methods presented here have been implemented in copernicus, a prototype trajectory design and optimization system under development at the University of Texas at Austin.

Performance evaluation of multi-stratum resources optimization with network functions virtualization for cloud-based radio over optical fiber networks.

PubMed

Yang, Hui; He, Yongqi; Zhang, Jie; Ji, Yuefeng; Bai, Wei; Lee, Young

2016-04-18

Cloud radio access network (C-RAN) has become a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing using cloud BBUs. In our previous work, we implemented cross stratum optimization of optical network and application stratums resources that allows to accommodate the services in optical networks. In view of this, this study extends to consider the multiple dimensional resources optimization of radio, optical and BBU processing in 5G age. We propose a novel multi-stratum resources optimization (MSRO) architecture with network functions virtualization for cloud-based radio over optical fiber networks (C-RoFN) using software defined control. A global evaluation scheme (GES) for MSRO in C-RoFN is introduced based on the proposed architecture. The MSRO can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical and BBU resources effectively to maximize radio coverage. The efficiency and feasibility of the proposed architecture are experimentally demonstrated on OpenFlow-based enhanced SDN testbed. The performance of GES under heavy traffic load scenario is also quantitatively evaluated based on MSRO architecture in terms of resource occupation rate and path provisioning latency, compared with other provisioning scheme.

Overview: Applications of numerical optimization methods to helicopter design problems

NASA Technical Reports Server (NTRS)

Miura, H.

1984-01-01

There are a number of helicopter design problems that are well suited to applications of numerical design optimization techniques. Adequate implementation of this technology will provide high pay-offs. There are a number of numerical optimization programs available, and there are many excellent response/performance analysis programs developed or being developed. But integration of these programs in a form that is usable in the design phase should be recognized as important. It is also necessary to attract the attention of engineers engaged in the development of analysis capabilities and to make them aware that analysis capabilities are much more powerful if integrated into design oriented codes. Frequently, the shortcoming of analysis capabilities are revealed by coupling them with an optimization code. Most of the published work has addressed problems in preliminary system design, rotor system/blade design or airframe design. Very few published results were found in acoustics, aerodynamics and control system design. Currently major efforts are focused on vibration reduction, and aerodynamics/acoustics applications appear to be growing fast. The development of a computer program system to integrate the multiple disciplines required in helicopter design with numerical optimization technique is needed. Activities in Britain, Germany and Poland are identified, but no published results from France, Italy, the USSR or Japan were found.

Retinal blood vessel extraction using tunable bandpass filter and fuzzy conditional entropy.

PubMed

Sil Kar, Sudeshna; Maity, Santi P

2016-09-01

Extraction of blood vessels on retinal images plays a significant role for screening of different opthalmologic diseases. However, accurate extraction of the entire and individual type of vessel silhouette from the noisy images with poorly illuminated background is a complicated task. To this aim, an integrated system design platform is suggested in this work for vessel extraction using a sequential bandpass filter followed by fuzzy conditional entropy maximization on matched filter response. At first noise is eliminated from the image under consideration through curvelet based denoising. To include the fine details and the relatively less thick vessel structures, the image is passed through a bank of sequential bandpass filter structure optimized for contrast enhancement. Fuzzy conditional entropy on matched filter response is then maximized to find the set of multiple optimal thresholds to extract the different types of vessel silhouettes from the background. Differential Evolution algorithm is used to determine the optimal gain in bandpass filter and the combination of the fuzzy parameters. Using the multiple thresholds, retinal image is classified as the thick, the medium and the thin vessels including neovascularization. Performance evaluated on different publicly available retinal image databases shows that the proposed method is very efficient in identifying the diverse types of vessels. Proposed method is also efficient in extracting the abnormal and the thin blood vessels in pathological retinal images. The average values of true positive rate, false positive rate and accuracy offered by the method is 76.32%, 1.99% and 96.28%, respectively for the DRIVE database and 72.82%, 2.6% and 96.16%, respectively for the STARE database. Simulation results demonstrate that the proposed method outperforms the existing methods in detecting the various types of vessels and the neovascularization structures. The combination of curvelet transform and tunable bandpass filter is found to be very much effective in edge enhancement whereas fuzzy conditional entropy efficiently distinguishes vessels of different widths. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Composition-property relationships in multifunctional hollow mesoporous carbon nanosystems for PH-responsive magnetic resonance imaging and on-demand drug release

NASA Astrophysics Data System (ADS)

Zhang, Shengjian; Qian, Xiaoqing; Zhang, Linlin; Peng, Weijun; Chen, Yu

2015-04-01

The construction of intelligent stimuli-responsive nanosystems can substantially improve the sensitivity/resolution/specificity of diagnostic imaging and enhance the therapeutic efficiency of chemotherapy for cancer treatment. This work reports on a generic construction strategy to achieve a multiple stimuli-responsive theranostic system for cancer simply by optimizing the chemical compositions of inorganic nanoplatforms to avoid the tedious and complicated synthetic procedure for traditional organic or organic/inorganic nanosystems. Based on the ``breaking up'' nature of manganese oxides and specific features of the carbonaceous framework to interact with aromatic drug molecules, manganese oxide nanoparticles were elaborately integrated into hollow mesoporous carbon nanocapsules by a simple in situ framework redox strategy to realize concurrent pH-sensitive T1-weighted magnetic resonance imaging (MRI) and pH-/HIFU-responsive on-demand drug release. The ultrasensitive disease-triggered MRI performance has been successfully demonstrated by a 52.5-fold increase of longitudinal relaxivity (r1 = 10.5 mM-1 s-1) and on nude mice 4T1 xenograft. The pH- and HIFU-triggered doxorubicin release and enhanced therapeutic outcome against multidrug resistance of cancer cells were systematically confirmed. In particular, the fabricated inorganic composite nanocapsules were found to feature unique biological behaviours, such as antimetastasis effect, extremely low hemolysis against red blood cells and high in vivo histocompatibility. This report on the successful construction of a pure inorganic nanosystem with multiple stimuli-responsivenesses may pave the way to new methods for the development of intelligent nanofamilies for cancer therapy.The construction of intelligent stimuli-responsive nanosystems can substantially improve the sensitivity/resolution/specificity of diagnostic imaging and enhance the therapeutic efficiency of chemotherapy for cancer treatment. This work reports on a generic construction strategy to achieve a multiple stimuli-responsive theranostic system for cancer simply by optimizing the chemical compositions of inorganic nanoplatforms to avoid the tedious and complicated synthetic procedure for traditional organic or organic/inorganic nanosystems. Based on the ``breaking up'' nature of manganese oxides and specific features of the carbonaceous framework to interact with aromatic drug molecules, manganese oxide nanoparticles were elaborately integrated into hollow mesoporous carbon nanocapsules by a simple in situ framework redox strategy to realize concurrent pH-sensitive T1-weighted magnetic resonance imaging (MRI) and pH-/HIFU-responsive on-demand drug release. The ultrasensitive disease-triggered MRI performance has been successfully demonstrated by a 52.5-fold increase of longitudinal relaxivity (r1 = 10.5 mM-1 s-1) and on nude mice 4T1 xenograft. The pH- and HIFU-triggered doxorubicin release and enhanced therapeutic outcome against multidrug resistance of cancer cells were systematically confirmed. In particular, the fabricated inorganic composite nanocapsules were found to feature unique biological behaviours, such as antimetastasis effect, extremely low hemolysis against red blood cells and high in vivo histocompatibility. This report on the successful construction of a pure inorganic nanosystem with multiple stimuli-responsivenesses may pave the way to new methods for the development of intelligent nanofamilies for cancer therapy. Electronic supplementary information (ESI) available: In vitro/in vivo ultrasound imaging, CLSM image and H&E results. See DOI: 10.1039/c5nr00451a

Dispositional Optimism and Incidence of Cognitive Impairment in Older Adults.

PubMed

Gawronski, Katerina A B; Kim, Eric S; Langa, Kenneth M; Kubzansky, Laura D

2016-09-01

Higher levels of optimism have been linked with positive health behaviors, biological processes, and health conditions that are potentially protective against cognitive impairment in older adults. However, the association between optimism and cognitive impairment has not been directly investigated. We examined whether optimism is associated with incident cognitive impairment in older adults. Data are from the Health and Retirement Study. Optimism was measured by using the Life Orientation Test-R and cognitive impairment with a modified version of the Telephone Interview for Cognitive Status derived from the Mini-Mental State Examination. Using multiple logistic regression models, we prospectively assessed whether optimism was associated with incident cognitive impairment in 4624 adults 65 years and older during a 4-year period. Among participants, 312 women and 190 men developed cognitive impairment during the 4-year follow-up. Higher optimism was associated with decreased risk of incident cognitive impairment. When adjusted for sociodemographic factors, each standard deviation increase in optimism was associated with reduced odds (odds ratio [OR] = 0.70, 95% confidence interval [CI] = 0.61-0.81) of becoming cognitively impaired. A dose-response relationship was observed. Compared with those with the lowest levels of optimism, people with moderate levels had somewhat reduced odds of cognitive impairment (OR = 0.78, 95% CI = 0.59-1.03), whereas people with the highest levels had the lowest odds of cognitive impairment (OR = 0.52, 95% CI = 0.36-0.74). These associations remained after adjusting for health behaviors, biological factors, and psychological covariates that could either confound the association of interest or serve on the pathway. Optimism was prospectively associated with a reduced likelihood of becoming cognitively impaired. If these results are replicated, the data suggest that potentially modifiable aspects of positive psychological functioning such as optimism play an important role in maintaining cognitive functioning.

Observation, Identification, and Impact of Multi-Modal Plasma Responses to Applied Magnetic Perturbations

NASA Astrophysics Data System (ADS)

Logan, Nikolas

2015-11-01

Experiments on DIII-D have demonstrated that multiple kink modes with comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n=2, in good agreement with ideal MHD models. In contrast to a single-mode model, the structure of the response measured using poloidally distributed magnetic sensors changes when varying the applied poloidal spectrum. This is most readily evident in that different spectra of applied fields can independently excite inboard and outboard magnetic responses, which are identified as distinct plasma modes by IPEC modeling. The outboard magnetic response is correlated with the plasma pressure and consistent with the long wavelength perturbations of the least stable, pressure driven kinks calculated by DCON and used in IPEC. The models show the structure of the pressure driven modes extends throughout the bad curvature region and into the plasma core. The inboard plasma response is correlated with the edge current profile and requires the inclusion of multiple kink modes with greater stability, including opposite helicity modes, to replicate the experimental observations in the models. IPEC reveals the resulting mode structure to be highly localized in the plasma edge. Scans of the applied spectrum show this response induces the transport that influences the density pump-out, as well as the toroidal rotation drag observed in experiment and modeled using PENT. The classification of these two mode types establishes a new multi-modal paradigm for n=2 plasma response and guides the understanding needed to optimize 3D fields for independent control of stability and transport. Supported by US DOE contract DE-AC02-09CH11466.

Optimal bit allocation for hybrid scalable/multiple-description video transmission over wireless channels

NASA Astrophysics Data System (ADS)

Jubran, Mohammad K.; Bansal, Manu; Kondi, Lisimachos P.

2006-01-01

In this paper, we consider the problem of optimal bit allocation for wireless video transmission over fading channels. We use a newly developed hybrid scalable/multiple-description codec that combines the functionality of both scalable and multiple-description codecs. It produces a base layer and multiple-description enhancement layers. Any of the enhancement layers can be decoded (in a non-hierarchical manner) with the base layer to improve the reconstructed video quality. Two different channel coding schemes (Rate-Compatible Punctured Convolutional (RCPC)/Cyclic Redundancy Check (CRC) coding and, product code Reed Solomon (RS)+RCPC/CRC coding) are used for unequal error protection of the layered bitstream. Optimal allocation of the bitrate between source and channel coding is performed for discrete sets of source coding rates and channel coding rates. Experimental results are presented for a wide range of channel conditions. Also, comparisons with classical scalable coding show the effectiveness of using hybrid scalable/multiple-description coding for wireless transmission.

The Dilution Effect and Information Integration in Perceptual Decision Making

PubMed Central

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

2015-01-01

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

The Dilution Effect and Information Integration in Perceptual Decision Making.

PubMed

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

2015-01-01

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

Experimental Design for Multi-drug Combination Studies Using Signaling Networks

PubMed Central

Huang, Hengzhen; Fang, Hong-Bin; Tan, Ming T.

2017-01-01

Summary Combinations of multiple drugs are an important approach to maximize the chance for therapeutic success by inhibiting multiple pathways/targets. Analytic methods for studying drug combinations have received increasing attention because major advances in biomedical research have made available large number of potential agents for testing. The preclinical experiment on multi-drug combinations plays a key role in (especially cancer) drug development because of the complex nature of the disease, the need to reduce development time and costs. Despite recent progresses in statistical methods for assessing drug interaction, there is an acute lack of methods for designing experiments on multi-drug combinations. The number of combinations grows exponentially with the number of drugs and dose-levels and it quickly precludes laboratory testing. Utilizing experimental dose-response data of single drugs and a few combinations along with pathway/network information to obtain an estimate of the functional structure of the dose-response relationship in silico, we propose an optimal design that allows exploration of the dose-effect surface with the smallest possible sample size in this paper. The simulation studies show our proposed methods perform well. PMID:28960231

Optimized "detectors" for dynamics analysis in solid-state NMR

NASA Astrophysics Data System (ADS)

Smith, Albert A.; Ernst, Matthias; Meier, Beat H.

2018-01-01

Relaxation in nuclear magnetic resonance (NMR) results from stochastic motions that modulate anisotropic NMR interactions. Therefore, measurement of relaxation-rate constants can be used to characterize molecular-dynamic processes. The motion is often characterized by Markov processes using an auto-correlation function, which is assumed to be a sum of multiple decaying exponentials. We have recently shown that such a model can lead to severe misrepresentation of the real motion, when the real correlation function is more complex than the model. Furthermore, multiple distributions of motion may yield the same set of dynamics data. Therefore, we introduce optimized dynamics "detectors" to characterize motions which are linear combinations of relaxation-rate constants. A detector estimates the average or total amplitude of motion for a range of motional correlation times. The information obtained through the detectors is less specific than information obtained using an explicit model, but this is necessary because the information contained in the relaxation data is ambiguous, if one does not know the correct motional model. On the other hand, if one has a molecular dynamics trajectory, one may calculate the corresponding detector responses, allowing direct comparison to experimental NMR dynamics analysis. We describe how to construct a set of optimized detectors for a given set of relaxation measurements. We then investigate the properties of detectors for a number of different data sets, thus gaining an insight into the actual information content of the NMR data. Finally, we show an example analysis of ubiquitin dynamics data using detectors, using the DIFRATE software.

Method of multi-mode vibration control for the carbody of high-speed electric multiple unit trains

NASA Astrophysics Data System (ADS)

Gong, Dao; Zhou, Jinsong; Sun, Wenjing; Sun, Yu; Xia, Zhanghui

2017-11-01

A method of multi-mode vibration control for the carbody of high-speed electric multiple unit (EMU) trains by using the onboard and suspended equipments as dynamic vibration absorbers (DVAs) is proposed. The effect of the multi-mode vibration on the ride quality of a high-speed EMU train was studied, and the target modes of vibration control were determined. An equivalent mass identification method was used to determine the equivalent mass for the target modes at the device installation positions. To optimize the vibration acceleration response of the carbody, the natural frequencies and damping ratios of the lateral and vertical vibration were designed based on the theory of dynamic vibration absorption. In order to realize the optimized design values of the natural frequencies for the lateral and vertical vibrations simultaneously, a new type of vibration absorber was designed in which a belleville spring and conventional rubber parts are connected in parallel. This design utilizes the negative stiffness of the belleville spring. Results show that, as compared to rigid equipment connections, the proposed method effectively reduces the multi-mode vibration of a carbody in a high-speed EMU train, thereby achieving the control objectives. The ride quality in terms of the lateral and vertical vibration of the carbody is considerably improved. Moreover, the optimal value of the damping ratio is effective in dissipating the vibration energy, which reduces the vibration of both the carbody and the equipment.

Computer optimization of cutting yield from multiple ripped boards

Treesearch

A.R. Stern; K.A. McDonald

1978-01-01

RIPYLD is a computer program that optimizes the cutting yield from multiple-ripped boards. Decisions are based on automatically collected defect information, cutting bill requirements, and sawing variables. The yield of clear cuttings from a board is calculated for every possible permutation of specified rip widths and both the maximum and minimum percent yield...

Absolute Points for Multiple Assignment Problems

ERIC Educational Resources Information Center

Adlakha, V.; Kowalski, K.

2006-01-01

An algorithm is presented to solve multiple assignment problems in which a cost is incurred only when an assignment is made at a given cell. The proposed method recursively searches for single/group absolute points to identify cells that must be loaded in any optimal solution. Unlike other methods, the first solution is the optimal solution. The…

Cost effective simulation-based multiobjective optimization in the performance of an internal combustion engine

NASA Astrophysics Data System (ADS)

Aittokoski, Timo; Miettinen, Kaisa

2008-07-01

Solving real-life engineering problems can be difficult because they often have multiple conflicting objectives, the objective functions involved are highly nonlinear and they contain multiple local minima. Furthermore, function values are often produced via a time-consuming simulation process. These facts suggest the need for an automated optimization tool that is efficient (in terms of number of objective function evaluations) and capable of solving global and multiobjective optimization problems. In this article, the requirements on a general simulation-based optimization system are discussed and such a system is applied to optimize the performance of a two-stroke combustion engine. In the example of a simulation-based optimization problem, the dimensions and shape of the exhaust pipe of a two-stroke engine are altered, and values of three conflicting objective functions are optimized. These values are derived from power output characteristics of the engine. The optimization approach involves interactive multiobjective optimization and provides a convenient tool to balance between conflicting objectives and to find good solutions.

Investigation of Parametric Influence on the Properties of Al6061-SiCp Composite

NASA Astrophysics Data System (ADS)

Adebisi, A. A.; Maleque, M. A.; Bello, K. A.

2017-03-01

The influence of process parameter in stir casting play a major role on the development of aluminium reinforced silicon carbide particle (Al-SiCp) composite. This study aims to investigate the influence of process parameters on wear and density properties of Al-SiCp composite using stir casting technique. Experimental data are generated based on a four-factors-five-level central composite design of response surface methodology. Analysis of variance is utilized to confirm the adequacy and validity of developed models considering the significant model terms. Optimization of the process parameters adequately predicts the Al-SiCp composite properties with stirring speed as the most influencing factor. The aim of optimization process is to minimize wear and maximum density. The multiple objective optimization (MOO) achieved an optimal value of 14 wt% reinforcement fraction (RF), 460 rpm stirring speed (SS), 820 °C processing temperature (PTemp) and 150 secs processing time (PT). Considering the optimum parametric combination, wear mass loss achieved a minimum of 1 x 10-3 g and maximum density value of 2.780g/mm3 with a confidence and desirability level of 95.5%.

Optimization of process parameters for extrusion cooking of low amylose rice flour blended with seeded banana and carambola pomace for development of minerals and fiber rich breakfast cereal.

PubMed

Borah, Anjan; Lata Mahanta, Charu; Kalita, Dipankar

2016-01-01

The low-amylose rice flour, seeded banana (Musa balbisiana, ABB) and carambola (Averrhoa carambola L.) pomace blends were extruded to prepare ready to eat breakfast cereal in a single-screw extruder. Response surface methodology using a central composite design was used to evaluate effect of independent variables, namely blend ratio (80:10:10 - 60:30:10 of low-amylose rice flour, seeded banana and carambola pomace), screw speed (200 - 400 rpm), barrel temperature (90 - 130 (°)C) and feed moisture content (9 - 21 g/100 g, wet basis) on product responses. Quadratic polynomial equations were also obtained by multiple regression analysis. The predicted models were adequate based on lack-of-fit test and coefficient of determination obtained. The feed moisture content had critical effect on all response variables. The compromised optimal conditions obtained by numerical integration for development of extrudates were: screw speed of 350 rpm, barrel temperature of 120 (°)C, feed moisture content of 12 g/100 g and 65:25:10 of blend ratio of feed. In the optimized condition low-amylose rice blend is found to have better physicochemical properties (water absorption index of 481.79 g/100 g; water solubility index of 44.13 g/100 g) and dietary fiber content of 21.35 g/100 g respectively. The developed breakfast cereal showed considerable amount of minerals (Mg and K) and overall acceptability was found to be 7.8.

Combinations of various CpG motifs cloned into plasmid backbone modulate and enhance protective immunity of viral replicon DNA anthrax vaccines.

PubMed

Yu, Yun-Zhou; Ma, Yao; Xu, Wen-Hui; Wang, Shuang; Sun, Zhi-Wei

2015-08-01

DNA vaccines are generally weak stimulators of the immune system. Fortunately, their efficacy can be improved using a viral replicon vector or by the addition of immunostimulatory CpG motifs, although the design of these engineered DNA vectors requires optimization. Our results clearly suggest that multiple copies of three types of CpG motifs or combinations of various types of CpG motifs cloned into a viral replicon vector backbone with strong immunostimulatory activities on human PBMC are efficient adjuvants for these DNA vaccines to modulate and enhance protective immunity against anthrax, although modifications with these different CpG forms in vivo elicited inconsistent immune response profiles. Modification with more copies of CpG motifs elicited more potent adjuvant effects leading to the generation of enhanced immunity, which indicated a CpG motif dose-dependent enhancement of antigen-specific immune responses. Notably, the enhanced and/or synchronous adjuvant effects were observed in modification with combinations of two different types of CpG motifs, which provides not only a contribution to the knowledge base on the adjuvant activities of CpG motifs combinations but also implications for the rational design of optimal DNA vaccines with combinations of CpG motifs as "built-in" adjuvants. We describe an efficient strategy to design and optimize DNA vaccines by the addition of combined immunostimulatory CpG motifs in a viral replicon DNA plasmid to produce strong immune responses, which indicates that the CpG-modified viral replicon DNA plasmid may be desirable for use as vector of DNA vaccines.

Research on numerical method for multiple pollution source discharge and optimal reduction program

NASA Astrophysics Data System (ADS)

Li, Mingchang; Dai, Mingxin; Zhou, Bin; Zou, Bin

2018-03-01

In this paper, the optimal method for reduction program is proposed by the nonlinear optimal algorithms named that genetic algorithm. The four main rivers in Jiangsu province, China are selected for reducing the environmental pollution in nearshore district. Dissolved inorganic nitrogen (DIN) is studied as the only pollutant. The environmental status and standard in the nearshore district is used to reduce the discharge of multiple river pollutant. The research results of reduction program are the basis of marine environmental management.

Platform for efficient switching between multiple devices in the intensive care unit.

PubMed

De Backere, F; Vanhove, T; Dejonghe, E; Feys, M; Herinckx, T; Vankelecom, J; Decruyenaere, J; De Turck, F

2015-01-01

This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". Handheld computers, such as tablets and smartphones, are becoming more and more accessible in the clinical care setting and in Intensive Care Units (ICUs). By making the most useful and appropriate data available on multiple devices and facilitate the switching between those devices, staff members can efficiently integrate them in their workflow, allowing for faster and more accurate decisions. This paper addresses the design of a platform for the efficient switching between multiple devices in the ICU. The key functionalities of the platform are the integration of the platform into the workflow of the medical staff and providing tailored and dynamic information at the point of care. The platform is designed based on a 3-tier architecture with a focus on extensibility, scalability and an optimal user experience. After identification to a device using Near Field Communication (NFC), the appropriate medical information will be shown on the selected device. The visualization of the data is adapted to the type of the device. A web-centric approach was used to enable extensibility and portability. A prototype of the platform was thoroughly evaluated. The scalability, performance and user experience were evaluated. Performance tests show that the response time of the system scales linearly with the amount of data. Measurements with up to 20 devices have shown no performance loss due to the concurrent use of multiple devices. The platform provides a scalable and responsive solution to enable the efficient switching between multiple devices. Due to the web-centric approach new devices can easily be integrated. The performance and scalability of the platform have been evaluated and it was shown that the response time and scalability of the platform was within an acceptable range.

Influence of the Spatial Dimensions of Ultrasonic Transducers on the Frequency Spectrum of Guided Waves.

PubMed

Samaitis, Vykintas; Mažeika, Liudas

2017-08-08

Ultrasonic guided wave (UGW)-based condition monitoring has shown great promise in detecting, localizing, and characterizing damage in complex systems. However, the application of guided waves for damage detection is challenging due to the existence of multiple modes and dispersion. This results in distorted wave packets with limited resolution and the interference of multiple reflected modes. To develop reliable inspection systems, either the transducers have to be optimized to generate a desired single mode of guided waves with known dispersive properties, or the frequency responses of all modes present in the structure must be known to predict wave interaction. Currently, there is a lack of methods to predict the response spectrum of guided wave modes, especially in cases when multiple modes are being excited simultaneously. Such methods are of vital importance for further understanding wave propagation within the structures as well as wave-damage interaction. In this study, a novel method to predict the response spectrum of guided wave modes was proposed based on Fourier analysis of the particle velocity distribution on the excitation area. The method proposed in this study estimates an excitability function based on the spatial dimensions of the transducer, type of vibration, and dispersive properties of the medium. As a result, the response amplitude as a function of frequency for each guided wave mode present in the structure can be separately obtained. The method was validated with numerical simulations on the aluminum and glass fiber composite samples. The key findings showed that it can be applied to estimate the response spectrum of a guided wave mode on any type of material (either isotropic structures, or multi layered anisotropic composites) and under any type of excitation if the phase velocity dispersion curve and the particle velocity distribution of the wave source was known initially. Thus, the proposed method may be a beneficial tool to explain and predict the response spectrum of guided waves throughout the development of any structural health monitoring system.

Influence of the Spatial Dimensions of Ultrasonic Transducers on the Frequency Spectrum of Guided Waves

PubMed Central

Samaitis, Vykintas; Mažeika, Liudas

2017-01-01

Ultrasonic guided wave (UGW)-based condition monitoring has shown great promise in detecting, localizing, and characterizing damage in complex systems. However, the application of guided waves for damage detection is challenging due to the existence of multiple modes and dispersion. This results in distorted wave packets with limited resolution and the interference of multiple reflected modes. To develop reliable inspection systems, either the transducers have to be optimized to generate a desired single mode of guided waves with known dispersive properties, or the frequency responses of all modes present in the structure must be known to predict wave interaction. Currently, there is a lack of methods to predict the response spectrum of guided wave modes, especially in cases when multiple modes are being excited simultaneously. Such methods are of vital importance for further understanding wave propagation within the structures as well as wave-damage interaction. In this study, a novel method to predict the response spectrum of guided wave modes was proposed based on Fourier analysis of the particle velocity distribution on the excitation area. The method proposed in this study estimates an excitability function based on the spatial dimensions of the transducer, type of vibration, and dispersive properties of the medium. As a result, the response amplitude as a function of frequency for each guided wave mode present in the structure can be separately obtained. The method was validated with numerical simulations on the aluminum and glass fiber composite samples. The key findings showed that it can be applied to estimate the response spectrum of a guided wave mode on any type of material (either isotropic structures, or multi layered anisotropic composites) and under any type of excitation if the phase velocity dispersion curve and the particle velocity distribution of the wave source was known initially. Thus, the proposed method may be a beneficial tool to explain and predict the response spectrum of guided waves throughout the development of any structural health monitoring system. PMID:28786924

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

PubMed Central

Jin, Junchen

2016-01-01

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998

An Optimization Framework for Dynamic Hybrid Energy Systems

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

Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis

A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problemmore » takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.« less

Proof of concept and dose estimation with binary responses under model uncertainty.

PubMed

Klingenberg, B

2009-01-30

This article suggests a unified framework for testing Proof of Concept (PoC) and estimating a target dose for the benefit of a more comprehensive, robust and powerful analysis in phase II or similar clinical trials. From a pre-specified set of candidate models, we choose the ones that best describe the observed dose-response. To decide which models, if any, significantly pick up a dose effect, we construct the permutation distribution of the minimum P-value over the candidate set. This allows us to find critical values and multiplicity adjusted P-values that control the familywise error rate of declaring any spurious effect in the candidate set as significant. Model averaging is then used to estimate a target dose. Popular single or multiple contrast tests for PoC, such as the Cochran-Armitage, Dunnett or Williams tests, are only optimal for specific dose-response shapes and do not provide target dose estimates with confidence limits. A thorough evaluation and comparison of our approach to these tests reveal that its power is as good or better in detecting a dose-response under various shapes with many more additional benefits: It incorporates model uncertainty in PoC decisions and target dose estimation, yields confidence intervals for target dose estimates and extends to more complicated data structures. We illustrate our method with the analysis of a Phase II clinical trial. Copyright (c) 2008 John Wiley & Sons, Ltd.

Optimal morphologic response to preoperative chemotherapy: an alternate outcome end point before resection of hepatic colorectal metastases.

PubMed

Shindoh, Junichi; Loyer, Evelyne M; Kopetz, Scott; Boonsirikamchai, Piyaporn; Maru, Dipen M; Chun, Yun Shin; Zimmitti, Giuseppe; Curley, Steven A; Charnsangavej, Chusilp; Aloia, Thomas A; Vauthey, Jean-Nicolas

2012-12-20

The purposes of this study were to confirm the prognostic value of an optimal morphologic response to preoperative chemotherapy in patients undergoing chemotherapy with or without bevacizumab before resection of colorectal liver metastases (CLM) and to identify predictors of the optimal morphologic response. The study included 209 patients who underwent resection of CLM after preoperative chemotherapy with oxaliplatin- or irinotecan-based regimens with or without bevacizumab. Radiologic responses were classified as optimal or suboptimal according to the morphologic response criteria. Overall survival (OS) was determined, and prognostic factors associated with an optimal response were identified in multivariate analysis. An optimal morphologic response was observed in 47% of patients treated with bevacizumab and 12% of patients treated without bevacizumab (P < .001). The 3- and 5-year OS rates were higher in the optimal response group (82% and 74%, respectively) compared with the suboptimal response group (60% and 45%, respectively; P < .001). On multivariate analysis, suboptimal morphologic response was an independent predictor of worse OS (hazard ratio, 2.09; P = .007). Receipt of bevacizumab (odds ratio, 6.71; P < .001) and largest metastasis before chemotherapy of ≤ 3 cm (odds ratio, 2.12; P = .025) were significantly associated with optimal morphologic response. The morphologic response showed no specific correlation with conventional size-based RECIST criteria, and it was superior to RECIST in predicting major pathologic response. Independent of preoperative chemotherapy regimen, optimal morphologic response is sufficiently correlated with OS to be considered a surrogate therapeutic end point for patients with CLM.

Optimal Morphologic Response to Preoperative Chemotherapy: An Alternate Outcome End Point Before Resection of Hepatic Colorectal Metastases

PubMed Central

Shindoh, Junichi; Loyer, Evelyne M.; Kopetz, Scott; Boonsirikamchai, Piyaporn; Maru, Dipen M.; Chun, Yun Shin; Zimmitti, Giuseppe; Curley, Steven A.; Charnsangavej, Chusilp; Aloia, Thomas A.; Vauthey, Jean-Nicolas

2012-01-01

Purpose The purposes of this study were to confirm the prognostic value of an optimal morphologic response to preoperative chemotherapy in patients undergoing chemotherapy with or without bevacizumab before resection of colorectal liver metastases (CLM) and to identify predictors of the optimal morphologic response. Patients and Methods The study included 209 patients who underwent resection of CLM after preoperative chemotherapy with oxaliplatin- or irinotecan-based regimens with or without bevacizumab. Radiologic responses were classified as optimal or suboptimal according to the morphologic response criteria. Overall survival (OS) was determined, and prognostic factors associated with an optimal response were identified in multivariate analysis. Results An optimal morphologic response was observed in 47% of patients treated with bevacizumab and 12% of patients treated without bevacizumab (P < .001). The 3- and 5-year OS rates were higher in the optimal response group (82% and 74%, respectively) compared with the suboptimal response group (60% and 45%, respectively; P < .001). On multivariate analysis, suboptimal morphologic response was an independent predictor of worse OS (hazard ratio, 2.09; P = .007). Receipt of bevacizumab (odds ratio, 6.71; P < .001) and largest metastasis before chemotherapy of ≤ 3 cm (odds ratio, 2.12; P = .025) were significantly associated with optimal morphologic response. The morphologic response showed no specific correlation with conventional size-based RECIST criteria, and it was superior to RECIST in predicting major pathologic response. Conclusion Independent of preoperative chemotherapy regimen, optimal morphologic response is sufficiently correlated with OS to be considered a surrogate therapeutic end point for patients with CLM. PMID:23150701

The Climate Response to Stratospheric Aerosol Geoengineering Can Be Tailored Using Multiple Injection Locations

NASA Astrophysics Data System (ADS)

MacMartin, Douglas G.; Kravitz, Ben; Tilmes, Simone; Richter, Jadwiga H.; Mills, Michael J.; Lamarque, Jean-Francois; Tribbia, Joseph J.; Vitt, Francis

2017-12-01

By injecting different amounts of SO2 at multiple different latitudes, the spatial pattern of aerosol optical depth (AOD) can be partially controlled. This leads to the ability to influence the climate response to geoengineering with stratospheric aerosols, providing the potential for design. We use simulations from the fully coupled whole-atmosphere chemistry climate model CESM1(WACCM) to demonstrate that by appropriately combining injection at just four different locations, 30°S, 15°S, 15°N, and 30°N, then three spatial degrees of freedom of AOD can be achieved: an approximately spatially uniform AOD distribution, the relative difference in AOD between Northern and Southern Hemispheres, and the relative AOD in high versus low latitudes. For forcing levels that yield 1-2°C cooling, the AOD and surface temperature response are sufficiently linear in this model so that the response to different combinations of injection at different latitudes can be estimated from single-latitude injection simulations; nonlinearities associated with both aerosol growth and changes to stratospheric circulation will be increasingly important at higher forcing levels. Optimized injection at multiple locations is predicted to improve compensation of CO2-forced climate change relative to a case using only equatorial aerosol injection (which overcools the tropics relative to high latitudes). The additional degrees of freedom can be used, for example, to balance the interhemispheric temperature gradient and the equator to pole temperature gradient in addition to the global mean temperature. Further research is needed to better quantify the impacts of these strategies on changes to long-term temperature, precipitation, and other climate parameters.

Enhanced transdermal delivery of ondansetron using nanovesicular systems: Fabrication, characterization, optimization and ex-vivo permeation study-Box-Cox transformation practical example.

PubMed

Habib, Basant A; Sayed, Sinar; Elsayed, Ghada M

2018-03-30

This study aimed to formulate suitable nanovesicles (NVs) for transdermal delivery of Ondansetron. It also illustrated a practical example for the importance of Box-Cox transformation. A 2 3 full factorial design was used to enable testing transfersomes, ethosomes, and transethosomes of Ondansetron simultaneously. The independent variables (IVs) studied were sodium taurocholate amount, ethanol volume in hydration medium and sonication time. The studied dependent variables (DVs) were: particle size (PS), zeta potential (ZP) and entrapment efficiency (EE). Polynomial equations were used to study the influence of IVs on each DV. Numerical multiple response optimization was applied to select an optimized formula (OF) with the goals of minimizing PS and maximizing ZP absolute value and EE. Box-Cox transformation was adopted to enable modeling PS raised to the power of 1.2 with an excellent prediction R 2 of 1.000. ZP and EE were adequately represented directly with prediction R 2 of 0.9549 and 0.9892 respectively. Response surface plots helped in explaining the influence of IVs on each DV. Two-sided 95% prediction interval test and percent deviation of actual values from predicted ones proved the validity of the elucidated models. The OF was a transfersomal formula with desirability of 0.866 and showed promising results in ex-vivo permeation study. Copyright © 2018 Elsevier B.V. All rights reserved.

Multiple response optimization for high efficiency energy saving treatment of rhodamine B wastewater in a three-dimensional electrochemical reactor.

PubMed

Ji, Jing; Liu, Yang; Yang, Xue-Yuan; Xu, Juan; Li, Xiu-Yan

2018-07-15

The removal of high-concentration rhodamine B (RhB) wastewater was investigated in a three-dimensional electrochemical reactor (3DER) packed with granular activated carbon (GAC) particle electrodes. Response surface methodology (RSM) coupled with grey relational analysis (GRA) was used to evaluate the effects of voltage, initial pH, aeration rate and NaCl dosage on RhB removal and energy consumption of the 3DER. The optimal conditions were determined as voltage 7.25 V, pH 5.99, aeration rate 151.13 mL/min, and NaCl concentration 0.11 mol/L. After 30 min electrolysis, COD removal rate could arrive at 60.13% with an extremely low energy consumption of 6.22 kWh/kg COD. The voltage and NaCl were demonstrated to be the most significant factors affecting the COD removal and energy consumption of 3DER. The intermediates generated during the treatment process were identified and the possible degradation pathway of RhB was proposed. It is worth noting that 3DER also showed an excellent performance in total nitrogen (TN) removal under the optimal condition. The activated chlorine generated from chloride had great contributions to eliminate carbon and nitrogen of RhB wastewater. The treatment effluent had a good biodegradability, which was suitable for subsequent biological treatment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

NASA Astrophysics Data System (ADS)

Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin

2016-08-01

This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

Photopic Negative Response Obtained Using a Handheld Electroretinogram Device: Determining the Optimal Measure and Repeatability

PubMed Central

Wu, Zhichao; Hadoux, Xavier; Hui, Flora; Sarossy, Marc G.; Crowston, Jonathan G.

2016-01-01

Purpose To determine the measure of the photopic negative response (PhNR) of the full-field electroretinogram (ERG) that exhibits the optimal level of test-retest repeatability, and examine its repeatability under different conditions using a handheld, nonmydriatic ERG system and self-adhering skin electrodes. Methods Multiple ERG recordings (using 200 sweeps each) were performed in both eyes of 20 normal participants at two different sessions to compare its coefficient of repeatability (CoR; where 95% of the test-retest difference is expected to lie) between different PhNR measures and under different testing conditions (within and between examiners, and between sessions). Results The ratio between the PhNR trough to b-wave peak and b-wave peak to a-wave trough amplitude (PhNR/B ratio) exhibited the lowest CoR relative to its effective dynamic range (30 ± 4%) when including three recordings. There were no significant changes in the PhNR/B ratio over seven measurements (4 right and 3 left eyes) at either session (P ≥ 0.100), or significant difference in its CoR between different testing conditions (P = 0.314). Conclusion The PhNR/B ratio was the measure that minimized variability, and its measurements using a novel handheld ERG system with self-adhering skin electrodes and the protocols described in this study were comparable under different testing conditions and over multiple recordings. Translational Relevance The PhNR can be measured for clinical and research purposes using a simple-to-implement technique that is consistent within and between visits, and also between examiners. PMID:27540494

Structural damage detection in wind turbine blades based on time series representations of dynamic responses

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2015-03-01

The development of large wind turbines that enable to harvest energy more efficiently is a consequence of the increasing demand for renewables in the world. To optimize the potential energy output, light and flexible wind turbine blades (WTBs) are designed. However, the higher flexibilities and lower buckling capacities adversely affect the long-term safety and reliability of WTBs, and thus the increased operation and maintenance costs reduce the expected revenue. Effective structural health monitoring techniques can help to counteract this by limiting inspection efforts and avoiding unplanned maintenance actions. Vibration-based methods deserve high attention due to the moderate instrumentation efforts and the applicability for in-service measurements. The present paper proposes the use of cross-correlations (CCs) of acceleration responses between sensors at different locations for structural damage detection in WTBs. CCs were in the past successfully applied for damage detection in numerical and experimental beam structures while utilizing only single lags between the signals. The present approach uses vectors of CC coefficients for multiple lags between measurements of two selected sensors taken from multiple possible combinations of sensors. To reduce the dimensionality of the damage sensitive feature (DSF) vectors, principal component analysis is performed. The optimal number of principal components (PCs) is chosen with respect to a statistical threshold. Finally, the detection phase uses the selected PCs of the healthy structure to calculate scores from a current DSF vector, where statistical hypothesis testing is performed for making a decision about the current structural state. The method is applied to laboratory experiments conducted on a small WTB with non-destructive damage scenarios.

Simultaneous dual-color fluorescence microscope: a characterization study.

PubMed

Li, Zheng; Chen, Xiaodong; Ren, Liqiang; Song, Jie; Li, Yuhua; Zheng, Bin; Liu, Hong

2013-01-01

High spatial resolution and geometric accuracy is crucial for chromosomal analysis of clinical cytogenetic applications. High resolution and rapid simultaneous acquisition of multiple fluorescent wavelengths can be achieved by utilizing concurrent imaging with multiple detectors. However, such class of microscopic systems functions differently from traditional fluorescence microscopes. To develop a practical characterization framework to assess and optimize the performance of a high resolution and dual-color fluorescence microscope designed for clinical chromosomal analysis. A dual-band microscopic imaging system utilizes a dichroic mirror, two sets of specially selected optical filters, and two detectors to simultaneously acquire two fluorescent wavelengths. The system's geometric distortion, linearity, the modulation transfer function, and the dual detectors' alignment were characterized. Experiment results show that the geometric distortion at lens periphery is less than 1%. Both fluorescent channels show linear signal responses, but there exists discrepancy between the two due to the detectors' non-uniform response ratio to different wavelengths. In terms of the spatial resolution, the two contrast transfer function curves trend agreeably with the spatial frequency. The alignment measurement allows quantitatively assessing the cameras' alignment. A result image of adjusted alignment is demonstrated to show the reduced discrepancy by using the alignment measurement method. In this paper, we present a system characterization study and its methods for a specially designed imaging system for clinical cytogenetic applications. The presented characterization methods are not only unique to this dual-color imaging system but also applicable to evaluation and optimization of other similar multi-color microscopic image systems for improving their clinical utilities for future cytogenetic applications.

Multi-objective optimization for generating a weighted multi-model ensemble

NASA Astrophysics Data System (ADS)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic ensemble mean and may provide reliable future projections.

Smart Phase Tuning in Microwave Photonic Integrated Circuits Toward Automated Frequency Multiplication by Design

NASA Astrophysics Data System (ADS)

Nabavi, N.

2018-07-01

The author investigates the monitoring methods for fine adjustment of the previously proposed on-chip architecture for frequency multiplication and translation of harmonics by design. Digital signal processing (DSP) algorithms are utilized to create an optimized microwave photonic integrated circuit functionality toward automated frequency multiplication. The implemented DSP algorithms are formed on discrete Fourier transform and optimization-based algorithms (Greedy and gradient-based algorithms), which are analytically derived and numerically compared based on the accuracy and speed of convergence criteria.

Sustaining innovations in complex healthcare environments: A multiple-case study of rapid response teams

PubMed Central

Stolldorf, Deonni P; Havens, Donna S.; Jones, Cheryl B

2015-01-01

Objectives Rapid response teams are one innovation previously deployed in U.S. hospitals with the goal to improve the quality of care. Sustaining rapid response teams is important to achieve the desired implementation outcomes, reduce the risk of program investments losses, and prevent employee disillusionment and dissatisfaction. This study sought to examine factors that do and do not support the sustainability of Rapid Response Teams. Methods The study was conceptually guided by an adapted version of the Planning Model of Sustainability. A multiple-case study was conducted using a purposive sample of two hospitals with high RRT sustainability scores and two hospitals with low RRT sustainability scores. Data collection methods included: (a) a hospital questionnaire that was completed by a nurse administrator at each hospital; (b) semi-structured interviews with leaders, RRT members, and those activating RRT calls; and, (c) review of internal documents. Quantitative data were analyzed using descriptive statistics; qualitative data were analyzed using content analysis. Results Few descriptive differences were found between hospitals. However, there were notable differences in the operationalization of certain factors between high- and low-sustainability hospitals. Additional sustainability factors other than those captured by the Planning Model of Sustainability were also identified. Conclusions The sustainability of rapid response teams is optimized through effective operationalization of organizational and project design and implementation factors. Two additional factors—individual and team characteristics—should be included in the Planning Model of Sustainability and considered as potential facilitators (or inhibitors) of RRT sustainability. PMID:26756725

Target-responsive DNA/RNA nanomaterials for microRNA sensing and inhibition: the jack-of-all-trades in cancer nanotheranostics?

PubMed

Conde, João; Edelman, Elazer R; Artzi, Natalie

2015-01-01

microRNAs (miRNAs) show high potential for cancer treatment, however one of the most significant bottlenecks in enabling miRNA effect is the need for an efficient vehicle capable of selective targeting to tumor cells without disrupting normal cells. Even more challenging is the ability to detect and silence multiple targets simultaneously with high sensitivity while precluding resistance to the therapeutic agents. Focusing on the pervasive role of miRNAs, herein we review the multiple nanomaterial-based systems that encapsulate DNA/RNA for miRNA sensing and inhibition in cancer therapy. Understanding the potential of miRNA detection and silencing while overcoming existing limitations will be critical to the optimization and clinical utilization of this technology. Copyright © 2014 Elsevier B.V. All rights reserved.

Response characteristics of periodontal mechanoreceptors to mechanical stimulation of canine and incisor teeth in the cat.

PubMed

Tabata, T; Suzuki, T; Watanabe, M

1995-09-01

The alveolar bone that overlies the labial aspect of the root of the right lower canine tooth was pared down until paper thin. Thirty-five periodontal mechanosensitive (PM) units sensitive to stimulation of the canine and incisor and to punctate stimulation through the thinned bone of the periodontal ligament of the canine were recorded from the inferior alveolar nerve rostral to the masseter muscle. The units showed a sustained and directionally selective response to pressure applied to the teeth. The optimal directions of stimulation for each tooth in the receptive field were parallel and oriented linguolabially. When the canine was stimulated mechanically in the optimal stimulus direction, the interspike intervals of the responses were relatively regular in most PM units (91%). The conditioning and test stimuli were applied to the adjacent canine and third incisor. The conditioning stimulus (0.10 N) was given to one of these teeth in the optimal stimulus direction. The test stimulus (0.02 N or 0.05 N) was applied to the adjacent tooth in the opposite direction in order to examine the effect of mechanical spreading of the conditioning stimulus on the adjacent tooth. In most PM units, the spike discharges evoked by the conditioning stimulus given to the incisor were stopped by the test stimulus given to the canine. When the given stimuli were reversed, the firings evoked by the conditioning stimulus were slightly depressed by the test stimulus. After removing the spot-like PM receptor site(s) in the paper-thin area of bone, all units but one did not respond to stimulation. These results provide evidence that neurones with multiple-tooth receptive fields and regular spike-interval responses recorded from the inferior alveolar nerve come from the mechanical spreading effect of the stimulation of one tooth on an adjacent tooth through the trans-septal fibre system and that neurones with irregular-interval responses are due to the ramification of PM fibres peripherally.

Modeling and optimization of ultrasound-assisted extraction of polyphenolic compounds from Aronia melanocarpa by-products from filter-tea factory.

PubMed

Ramić, Milica; Vidović, Senka; Zeković, Zoran; Vladić, Jelena; Cvejin, Aleksandra; Pavlić, Branimir

2015-03-01

Aronia melanocarpa by-product from filter-tea factory was used for the preparation of extracts with high content of bioactive compounds. Extraction process was accelerated using sonication. Three level, three variable face-centered cubic experimental design (FCD) with response surface methodology (RSM) was used for optimization of extraction in terms of maximized yields for total phenolics (TP), flavonoids (TF), anthocyanins (MA) and proanthocyanidins (TPA) contents. Ultrasonic power (X₁: 72-216 W), temperature (X₂: 30-70 °C) and extraction time (X₃: 30-90 min) were investigated as independent variables. Experimental results were fitted to a second-order polynomial model where multiple regression analysis and analysis of variance were used to determine fitness of the model and optimal conditions for investigated responses. Three-dimensional surface plots were generated from the mathematical models. The optimal conditions for ultrasound-assisted extraction of TP, TF, MA and TPA were: X₁=206.64 W, X₂=70 °C, X₃=80.1 min; X₁=210.24 W, X₂=70 °C, X₃=75 min; X₁=216 W, X₂=70 °C, X₃=45.6 min and X₁=199.44 W, X₂=70 °C, X₃=89.7 min, respectively. Generated model predicted values of the TP, TF, MA and TPA to be 15.41 mg GAE/ml, 9.86 mg CE/ml, 2.26 mg C3G/ml and 20.67 mg CE/ml, respectively. Experimental validation was performed and close agreement between experimental and predicted values was found (within 95% confidence interval). Copyright © 2014 Elsevier B.V. All rights reserved.

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

Quantum Optimal Multiple Assignment Scheme for Realizing General Access Structure of Secret Sharing

NASA Astrophysics Data System (ADS)

Matsumoto, Ryutaroh

The multiple assignment scheme is to assign one or more shares to single participant so that any kind of access structure can be realized by classical secret sharing schemes. We propose its quantum version including ramp secret sharing schemes. Then we propose an integer optimization approach to minimize the average share size.

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

2006-01-01

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Resistance Mechanisms in Hepatitis C Virus: implications for Direct-Acting Antiviral Use.

PubMed

Bagaglio, Sabrina; Uberti-Foppa, Caterina; Morsica, Giulia

2017-07-01

Multiple direct-acting antiviral (DAA)-based regimens are currently approved that provide one or more interferon-free treatment options for hepatitis C virus (HCV) genotypes (G) 1-6. The choice of a DAA regimen, duration of therapy, and use of ribavirin depends on multiple viral and host factors, including HCV genotype, the detection of resistance-associated amino acid (aa) substitutions (RASs), prior treatment experience, and presence of cirrhosis. In regard to viral factors that may guide the treatment choice, the most important is the infecting genotype because a number of DAAs are genotype-designed. The potency and the genetic barrier may also impact the choice of treatment. One important and debated possible virologic factor that may negatively influence the response to DAAs is the presence of baseline RASs. Baseline resistance testing is currently not routinely considered or recommended for initiating HCV treatment, due to the overall high response rates (sustained virological response >90%) obtained. Exceptions are patients infected by HCV G1a when initiating treatment with simeprevir and elbasvir/grazoprevir or in those with cirrhosis prior to daclatasvir/sofosbuvir treatment because of natural polymorphisms demonstrated in sites of resistance. On the basis of these observations, first-line strategies should be optimized to overcome treatment failure due to HCV resistance.

Identification of precision treatment strategies for relapsed/refractory multiple myeloma by functional drug sensitivity testing.

PubMed

Majumder, Muntasir Mamun; Silvennoinen, Raija; Anttila, Pekka; Tamborero, David; Eldfors, Samuli; Yadav, Bhagwan; Karjalainen, Riikka; Kuusanmäki, Heikki; Lievonen, Juha; Parsons, Alun; Suvela, Minna; Jantunen, Esa; Porkka, Kimmo; Heckman, Caroline A

2017-08-22

Novel agents have increased survival of multiple myeloma (MM) patients, however high-risk and relapsed/refractory patients remain challenging to treat and their outcome is poor. To identify novel therapies and aid treatment selection for MM, we assessed the ex vivo sensitivity of 50 MM patient samples to 308 approved and investigational drugs. With the results we i) classified patients based on their ex vivo drug response profile; ii) identified and matched potential drug candidates to recurrent cytogenetic alterations; and iii) correlated ex vivo drug sensitivity to patient outcome. Based on their drug sensitivity profiles, MM patients were stratified into four distinct subgroups with varied survival outcomes. Patients with progressive disease and poor survival clustered in a drug response group exhibiting high sensitivity to signal transduction inhibitors. Del(17p) positive samples were resistant to most drugs tested with the exception of histone deacetylase and BCL2 inhibitors. Samples positive for t(4;14) were highly sensitive to immunomodulatory drugs, proteasome inhibitors and several targeted drugs. Three patients treated based on the ex vivo results showed good response to the selected treatments. Our results demonstrate that ex vivo drug testing may potentially be applied to optimize treatment selection and achieve therapeutic benefit for relapsed/refractory MM.

Activation of Wnt Signaling by Mechanical Loading Is Impaired in the Bone of Old Mice

PubMed Central

Holguin, Nilsson; Brodt, Michael D; Silva, Matthew J

2017-01-01

Aging diminishes bone formation engendered by mechanical loads, but the mechanism for this impairment remains unclear. Because Wnt signaling is required for optimal loading-induced bone formation, we hypothesized that aging impairs the load-induced activation of Wnt signaling. We analyzed dynamic histomorphometry of 5-month-old, 12-month-old, and 22-month-old C57Bl/6JN mice subjected to multiple days of tibial compression and corroborated an age-related decline in the periosteal loading response on day 5. Similarly, 1 day of loading increased periosteal and endocortical bone formation in young-adult (5-month-old) mice, but old (22-month-old) mice were unresponsive. These findings corroborated mRNA expression of genes related to bone formation and the Wnt pathway in tibias after loading. Multiple bouts (3 to 5 days) of loading upregulated bone formation–related genes, e.g., Osx and Col1a1, but older mice were significantly less responsive. Expression of Wnt negative regulators, Sost and Dkk1, was suppressed with a single day of loading in all mice, but suppression was sustained only in young-adult mice. Moreover, multiple days of loading repeatedly suppressed Sost and Dkk1 in young-adult, but not in old tibias. The age-dependent response to loading was further assessed by osteocyte staining for Sclerostin and LacZ in tibia of TOPGAL mice. After 1 day of loading, fewer osteocytes were Sclerostin-positive and, corroboratively, more osteocytes were LacZ-positive (Wnt active) in both 5-month-old and 12-month-old mice. However, although these changes were sustained after multiple days of loading in 5-month-old mice, they were not sustained in 12-month-old mice. Last, Wnt1 and Wnt7b were the most load-responsive of the 19 Wnt ligands. However, 4 hours after a single bout of loading, although their expression was upregulated threefold to 10-fold in young-adult mice, it was not altered in old mice. In conclusion, the reduced bone formation response of aged mice to loading may be due to failure to sustain Wnt activity with repeated loading. PMID:27357062

Iterative pass optimization of sequence data

NASA Technical Reports Server (NTRS)

Wheeler, Ward C.

2003-01-01

The problem of determining the minimum-cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete. This "tree alignment" problem has motivated the considerable effort placed in multiple sequence alignment procedures. Wheeler in 1996 proposed a heuristic method, direct optimization, to calculate cladogram costs without the intervention of multiple sequence alignment. This method, though more efficient in time and more effective in cladogram length than many alignment-based procedures, greedily optimizes nodes based on descendent information only. In their proposal of an exact multiple alignment solution, Sankoff et al. in 1976 described a heuristic procedure--the iterative improvement method--to create alignments at internal nodes by solving a series of median problems. The combination of a three-sequence direct optimization with iterative improvement and a branch-length-based cladogram cost procedure, provides an algorithm that frequently results in superior (i.e., lower) cladogram costs. This iterative pass optimization is both computation and memory intensive, but economies can be made to reduce this burden. An example in arthropod systematics is discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

Properties of a novel linear sulfur response mode in a multiple flame photometric detector.

PubMed

Clark, Adrian G; Thurbide, Kevin B

2014-01-24

A new linear sulfur response mode was established in the multiple flame photometric detector (mFPD) by monitoring HSO* emission in the red spectral region above 600nm. Optimal conditions for this mode were found by using a 750nm interference filter and oxygen flows to the worker flames of this device that were about 10mL/min larger than those used for monitoring quadratic S2* emission. By employing these parameters, this mode provided a linear response over about 4 orders of magnitude, with a detection limit near 5.8×10(-11)gS/s and a selectivity of sulfur over carbon of about 3.5×10(3). Specifically, the minimum detectable masses for 10 different sulfur analytes investigated ranged from 0.4 to 3.6ng for peak half-widths spanning 4-6s. The response toward ten different sulfur compounds was examined and produced an average reproducibility of 1.7% RSD (n=10) and an average equimolarity value of 1.0±0.1. In contrast to this, a conventional single flame S2* mode comparatively yielded respective values of 6.7% RSD (n=10) and 1.1±0.4. HSO* emission in the mFPD was also found to be relatively much less affected by response quenching due to hydrocarbons compared to a conventional single flame S2* emission mode. Results indicate that this new alternative linear mFPD response mode could be beneficial for sulfur monitoring applications. Copyright © 2013 Elsevier B.V. All rights reserved.

An adaptive response surface method for crashworthiness optimization

NASA Astrophysics Data System (ADS)

Shi, Lei; Yang, Ren-Jye; Zhu, Ping

2013-11-01

Response surface-based design optimization has been commonly used for optimizing large-scale design problems in the automotive industry. However, most response surface models are built by a limited number of design points without considering data uncertainty. In addition, the selection of a response surface in the literature is often arbitrary. This article uses a Bayesian metric to systematically select the best available response surface among several candidates in a library while considering data uncertainty. An adaptive, efficient response surface strategy, which minimizes the number of computationally intensive simulations, was developed for design optimization of large-scale complex problems. This methodology was demonstrated by a crashworthiness optimization example.

From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild.

PubMed

Asthana, Akshay; Zafeiriou, Stefanos; Tzimiropoulos, Georgios; Cheng, Shiyang; Pantic, Maja

2015-06-01

We propose a face alignment framework that relies on the texture model generated by the responses of discriminatively trained part-based filters. Unlike standard texture models built from pixel intensities or responses generated by generic filters (e.g. Gabor), our framework has two important advantages. First, by virtue of discriminative training, invariance to external variations (like identity, pose, illumination and expression) is achieved. Second, we show that the responses generated by discriminatively trained filters (or patch-experts) are sparse and can be modeled using a very small number of parameters. As a result, the optimization methods based on the proposed texture model can better cope with unseen variations. We illustrate this point by formulating both part-based and holistic approaches for generic face alignment and show that our framework outperforms the state-of-the-art on multiple "wild" databases. The code and dataset annotations are available for research purposes from http://ibug.doc.ic.ac.uk/resources.

Conserved versatile master regulators in signalling pathways in response to stress in plants

PubMed Central

Balderas-Hernández, Victor E.; Alvarado-Rodríguez, Miguel; Fraire-Velázquez, Saúl

2013-01-01

From the first land plants to the complex gymnosperms and angiosperms of today, environmental conditions have forced plants to develop molecular strategies to surpass natural obstacles to growth and proliferation, and these genetic gains have been transmitted to the following generations. In this long natural process, novel and elaborate mechanisms have evolved to enable plants to cope with environmental limitations. Elements in many signalling cascades enable plants to sense different, multiple and simultaneous ambient cues. A group of versatile master regulators of gene expression control plant responses to stressing conditions. For crop breeding purposes, the task is to determine how to activate these key regulators to enable accurate and optimal reactions to common stresses. In this review, we discuss how plants sense biotic and abiotic stresses, how and which master regulators are implied in the responses to these stresses, their evolution in the life kingdoms, and the domains in these proteins that interact with other factors to lead to a proper and efficient plant response. PMID:24147216

Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation

PubMed Central

Li, Geng; Zhang, Pengfei; Wei, Guo; Xie, Yuanping; Yu, Xudong; Long, Xingwu

2015-01-01

To further improve ring laser gyroscope (RLG) bias stability, a multiple-point temperature gradient algorithm is proposed for RLG bias compensation in this paper. Based on the multiple-point temperature measurement system, a complete thermo-image of the RLG block is developed. Combined with the multiple-point temperature gradients between different points of the RLG block, the particle swarm optimization algorithm is used to tune the support vector machine (SVM) parameters, and an optimized design for selecting the thermometer locations is also discussed. The experimental results validate the superiority of the introduced method and enhance the precision and generalizability in the RLG bias compensation model. PMID:26633401

Optimal design of low-density SNP arrays for genomic prediction: algorithm and applications

USDA-ARS?s Scientific Manuscript database

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for their optimal design. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optim...

Optimization conditions for extracting polysaccharide from Angelica sinensis and its antioxidant activities.

PubMed

Tian, Suyang; Hao, Changchun; Xu, Guangkuan; Yang, Juanjuan; Sun, Runguang

2017-10-01

In this study, polysaccharides from Angelica sinensis were extracted using the ultrasound-assisted extraction method. Based on the results of single factor experiments and orthogonal tests, three independent variables-water/raw material ratio, ultrasound time, and ultrasound power-were selected for investigation. Then, we used response surface methodology to optimize the extraction conditions. The experimental data were fitted to a quadratic equation using multiple regression analysis, and the optimal conditions were as follows: water/raw material ratio, 43.31 mL/g; ultrasonic time, 28.06 minutes; power, 396.83 W. Under such conditions, the polysaccharide yield was 21.89±0.21%, which was well matched with the predicted yield. In vitro assays, scavenging activity of superoxide anion radicals, hydroxyl radicals, and 2,2-diphenyl-1-picry-hydrazyl radical showed that polysaccharides had certain antioxidant activities and that hydroxyl radicals have a remarkable scavenging capability. Therefore, these studies provide reference for further research and rational development of A. sinensis polysaccharide. Copyright © 2016. Published by Elsevier B.V.

Optimization of an organic yogurt based on sensorial, nutritional, and functional perspectives.

PubMed

Karnopp, Ariadne Roberto; Oliveira, Katherine Guimarães; de Andrade, Eriel Forville; Postingher, Bruna Mara; Granato, Daniel

2017-10-15

The effects of purple grape juice (PGJ), grape skin flour (GSF), and oligofructose (OLI) on proximate composition, total phenolic content (TPC), antioxidant activity (AA), sensory, physicochemical, and textural properties of yogurts were analyzed using response surface methodology. Multiple regression models were proposed and results showed that PGJ increased the viscosity, AA, and TPC, while GSF increased the ash and total fiber contents of yogurts. GSF and OLI increased the hardness and consistency. A simultaneous optimization was performed to maximize TPC, ash and fibers contents, and sensory acceptance: a yogurt containing 1.7% GSF and 8.0% PGJ had a high fiber (5.60±0.13%) and ash (0.76±0.02%) contents, TPC (28.32±2.10mg GAE/100g), AA toward DPPH (57.85±1.36mg AAE/100g), and total reducing capacity (28.86±5.19mg QE/100g). The optimized yogurt had 79% acceptability index, indicating the use of PGJ and GSF is a feasible alternative to increase the functional properties of yogurts. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Systems Engineering Approach to Multiple Attribute Utility Theory and Multiple Objective Optimization Theory: With Application To Aircraft Retrofit Design.

DTIC Science & Technology

1980-01-01

me produce this dissertation. I wish to thank Professors John E. Gibson and Chelsea C. White, III for their advice and contributions in this effort. My...National Meeting, Los Angeles, Ca., 1ov., 97$ Everett, J., Hax, A., Lewison , V. and 4utts, D., "Optimization of a Fleet of Large Tarkers and Bulkers...Arrow, C. J., Mardecai, K., Public Investment, The Rate of Return and Optimal Fiscal Policy, Johns Hopkins Press, Baltimore, Maryland, 1970. Banker

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

Flory, John Andrew; Padilla, Denise D.; Gauthier, John H.

Upcoming weapon programs require an aggressive increase in Application Specific Integrated Circuit (ASIC) production at Sandia National Laboratories (SNL). SNL has developed unique modeling and optimization tools that have been instrumental in improving ASIC production productivity and efficiency, identifying optimal operational and tactical execution plans under resource constraints, and providing confidence in successful mission execution. With ten products and unprecedented levels of demand, a single set of shared resources, highly variable processes, and the need for external supplier task synchronization, scheduling is an integral part of successful manufacturing. The scheduler uses an iterative multi-objective genetic algorithm and a multi-dimensional performancemore » evaluator. Schedule feasibility is assessed using a discrete event simulation (DES) that incorporates operational uncertainty, variability, and resource availability. The tools provide rapid scenario assessments and responses to variances in the operational environment, and have been used to inform major equipment investments and workforce planning decisions in multiple SNL facilities.« less

Adaptive magnetorheological seat suspension for shock mitigation

NASA Astrophysics Data System (ADS)

Singh, Harinder J.; Wereley, Norman M.

2013-04-01

An adaptive magnetorheological seat suspension (AMSS) was analyzed for optimal protection of occupants from shock loads caused by the impact of a helicopter with the ground. The AMSS system consists of an adaptive linear stroke magnetorheological shock absorber (MRSA) integrated into the seat structure of a helicopter. The MRSA provides a large controllability yield force to accommodate a wide spectrum for shock mitigation. A multiple degrees-of-freedom nonlinear biodynamic model for a 50th percentile male occupant was integrated with the dynamics of MRSA and the governing equations of motion were investigated theoretically. The load-stroke profile of MRSA was optimized with the goal of minimizing the potential for injuries. The MRSA yield force and the shock absorber stroke limitations were the most crucial parameters for improved biodynamic response mitigation. An assessment of injuries based on established injury criteria for different body parts was carried out.

Modeling Integrated Water-User Decisions with Intermittent Supplies

NASA Astrophysics Data System (ADS)

Lund, J. R.; Rosenberg, D.

2006-12-01

We present an economic-engineering method to estimate urban water use demands with intermittent water supplies. A two-stage, probabilistic optimization formulation includes a wide variety of water supply enhancement and conservation actions that individual households can adopt to meet multiple water quality uses with uncertain water availability. We embed the optimization in Monte-Carlo simulations to show aggregate effects at a utility (citywide) scale for a population of user conditions and decisions. Parametric analysis provides derivations of supply curves to subsidize conservation, demand responses to alternative pricing, and customer willingness-to-pay to avoid shortages. Results show a good empirical fit for the average and distribution of billed residential water use in Amman, Jordan. Additional outputs give likely market penetration rates for household conservation actions, associated water savings, and subsidies required to entice further adoption. We discuss new insights to size, target, market, and finance conservation programs and interpret a demand curve with block pricing.

Vicarious resilience in counselors of child and youth victims of interpersonal trauma.

PubMed

Silveira, Fabiane S; Boyer, Wanda

2015-04-01

In this study, we investigated how bearing witness to clients' resilience processes during treatment impacts the personal and professional lives of counselors who work with child and youth victims of interpersonal trauma. We used a qualitative instrumental multiple-case study design and thematic analysis to explore the research question. The participants indicated that they experienced an increased sense of hope and optimism, and were inspired by the strengths of their clients while working with this population. As the participants reflected on the challenges that their clients faced, the participants put their own challenges and strengths into perspective; they reported positive changes in their personal relationships. We suggest that future research might investigate the relationships we found between optimism, hope, and vicarious resilience processes, as well as the potential relationship between the counseling approach that counselors adopt and the development of vicarious resilience responses. © The Author(s) 2014.

Structural optimization of 3D-printed synthetic spider webs for high strength

NASA Astrophysics Data System (ADS)

Qin, Zhao; Compton, Brett G.; Lewis, Jennifer A.; Buehler, Markus J.

2015-05-01

Spiders spin intricate webs that serve as sophisticated prey-trapping architectures that simultaneously exhibit high strength, elasticity and graceful failure. To determine how web mechanics are controlled by their topological design and material distribution, here we create spider-web mimics composed of elastomeric filaments. Specifically, computational modelling and microscale 3D printing are combined to investigate the mechanical response of elastomeric webs under multiple loading conditions. We find the existence of an asymptotic prey size that leads to a saturated web strength. We identify pathways to design elastomeric material structures with maximum strength, low density and adaptability. We show that the loading type dictates the optimal material distribution, that is, a homogeneous distribution is better for localized loading, while stronger radial threads with weaker spiral threads is better for distributed loading. Our observations reveal that the material distribution within spider webs is dictated by the loading condition, shedding light on their observed architectural variations.

Structural optimization of 3D-printed synthetic spider webs for high strength.

PubMed

Qin, Zhao; Compton, Brett G; Lewis, Jennifer A; Buehler, Markus J

2015-05-15

Spiders spin intricate webs that serve as sophisticated prey-trapping architectures that simultaneously exhibit high strength, elasticity and graceful failure. To determine how web mechanics are controlled by their topological design and material distribution, here we create spider-web mimics composed of elastomeric filaments. Specifically, computational modelling and microscale 3D printing are combined to investigate the mechanical response of elastomeric webs under multiple loading conditions. We find the existence of an asymptotic prey size that leads to a saturated web strength. We identify pathways to design elastomeric material structures with maximum strength, low density and adaptability. We show that the loading type dictates the optimal material distribution, that is, a homogeneous distribution is better for localized loading, while stronger radial threads with weaker spiral threads is better for distributed loading. Our observations reveal that the material distribution within spider webs is dictated by the loading condition, shedding light on their observed architectural variations.

Expert system for controlling plant growth in a contained environment

NASA Technical Reports Server (NTRS)

May, George A. (Inventor); Lanoue, Mark Allen (Inventor); Bethel, Matthew (Inventor); Ryan, Robert E. (Inventor)

2011-01-01

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an "expert system" which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the "expert system" remotely, to assess activity within the growth chamber, and can override the "expert system".

Expert system for controlling plant growth in a contained environment

NASA Technical Reports Server (NTRS)

May, George A. (Inventor); Lanoue, Mark Allen (Inventor); Bethel, Matthew (Inventor); Ryan, Robert E. (Inventor)

2009-01-01

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an ''expert system'' which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the ''expert system'' remotely, to assess activity within the growth chamber, and can override the ''expert system''.

Fuel-optimal low-thrust formation reconfiguration via Radau pseudospectral method

NASA Astrophysics Data System (ADS)

Li, Jing

2016-07-01

This paper investigates fuel-optimal low-thrust formation reconfiguration near circular orbit. Based on the Clohessy-Wiltshire equations, first-order necessary optimality conditions are derived from the Pontryagin's maximum principle. The fuel-optimal impulsive solution is utilized to divide the low-thrust trajectory into thrust and coast arcs. By introducing the switching times as optimization variables, the fuel-optimal low-thrust formation reconfiguration is posed as a nonlinear programming problem (NLP) via direct transcription using multiple-phase Radau pseudospectral method (RPM), which is then solved by a sparse nonlinear optimization software SNOPT. To facilitate optimality verification and, if necessary, further refinement of the optimized solution of the NLP, formulas for mass costate estimation and initial costates scaling are presented. Numerical examples are given to show the application of the proposed optimization method. To fix the problem, generic fuel-optimal low-thrust formation reconfiguration can be simplified as reconfiguration without any initial and terminal coast arcs, whose optimal solutions can be efficiently obtained from the multiple-phase RPM at the cost of a slight fuel increment. Finally, influence of the specific impulse and maximum thrust magnitude on the fuel-optimal low-thrust formation reconfiguration is analyzed. Numerical results shown the links and differences between the fuel-optimal impulsive and low-thrust solutions.

FastSim: A Fast Simulation for the SuperB Detector

NASA Astrophysics Data System (ADS)

Andreassen, R.; Arnaud, N.; Brown, D. N.; Burmistrov, L.; Carlson, J.; Cheng, C.-h.; Di Simone, A.; Gaponenko, I.; Manoni, E.; Perez, A.; Rama, M.; Roberts, D.; Rotondo, M.; Simi, G.; Sokoloff, M.; Suzuki, A.; Walsh, J.

2011-12-01

We have developed a parameterized (fast) simulation for detector optimization and physics reach studies of the proposed SuperB Flavor Factory in Italy. Detector components are modeled as thin sections of planes, cylinders, disks or cones. Particle-material interactions are modeled using simplified cross-sections and formulas. Active detectors are modeled using parameterized response functions. Geometry and response parameters are configured using xml files with a custom-designed schema. Reconstruction algorithms adapted from BaBar are used to build tracks and clusters. Multiple sources of background signals can be merged with primary signals. Pattern recognition errors are modeled statistically by randomly misassigning nearby tracking hits. Standard BaBar analysis tuples are used as an event output. Hadronic B meson pair events can be simulated at roughly 10Hz.

Correlated neuronal discharges that increase coding efficiency during perceptual discrimination.

PubMed

Romo, Ranulfo; Hernández, Adrián; Zainos, Antonio; Salinas, Emilio

2003-05-22

During a sensory discrimination task, the responses of multiple sensory neurons must be combined to generate a choice. The optimal combination of responses is determined both by their dependence on the sensory stimulus and by their cofluctuations across trials-that is, the noise correlations. Positively correlated noise is considered deleterious, because it limits the coding accuracy of populations of similarly tuned neurons. However, positively correlated fluctuations between differently tuned neurons actually increase coding accuracy, because they allow the common noise to be subtracted without signal loss. This is demonstrated with data recorded from the secondary somatosensory cortex of monkeys performing a vibrotactile discrimination task. The results indicate that positive correlations are not always harmful and may be exploited by cortical networks to enhance the neural representation of features to be discriminated.

Development of a turbomachinery design optimization procedure using a multiple-parameter nonlinear perturbation method

NASA Technical Reports Server (NTRS)

Stahara, S. S.

1984-01-01

An investigation was carried out to complete the preliminary development of a combined perturbation/optimization procedure and associated computational code for designing optimized blade-to-blade profiles of turbomachinery blades. The overall purpose of the procedures developed is to provide demonstration of a rapid nonlinear perturbation method for minimizing the computational requirements associated with parametric design studies of turbomachinery flows. The method combines the multiple parameter nonlinear perturbation method, successfully developed in previous phases of this study, with the NASA TSONIC blade-to-blade turbomachinery flow solver, and the COPES-CONMIN optimization procedure into a user's code for designing optimized blade-to-blade surface profiles of turbomachinery blades. Results of several design applications and a documented version of the code together with a user's manual are provided.

Post Pareto optimization-A case

NASA Astrophysics Data System (ADS)

Popov, Stoyan; Baeva, Silvia; Marinova, Daniela

2017-12-01

Simulation performance may be evaluated according to multiple quality measures that are in competition and their simultaneous consideration poses a conflict. In the current study we propose a practical framework for investigating such simulation performance criteria, exploring the inherent conflicts amongst them and identifying the best available tradeoffs, based upon multi-objective Pareto optimization. This approach necessitates the rigorous derivation of performance criteria to serve as objective functions and undergo vector optimization. We demonstrate the effectiveness of our proposed approach by applying it with multiple stochastic quality measures. We formulate performance criteria of this use-case, pose an optimization problem, and solve it by means of a simulation-based Pareto approach. Upon attainment of the underlying Pareto Frontier, we analyze it and prescribe preference-dependent configurations for the optimal simulation training.

Optimal four-impulse rendezvous between coplanar elliptical orbits

NASA Astrophysics Data System (ADS)

Wang, JianXia; Baoyin, HeXi; Li, JunFeng; Sun, FuChun

2011-04-01

Rendezvous in circular or near circular orbits has been investigated in great detail, while rendezvous in arbitrary eccentricity elliptical orbits is not sufficiently explored. Among the various optimization methods proposed for fuel optimal orbital rendezvous, Lawden's primer vector theory is favored by many researchers with its clear physical concept and simplicity in solution. Prussing has applied the primer vector optimization theory to minimum-fuel, multiple-impulse, time-fixed orbital rendezvous in a near circular orbit and achieved great success. Extending Prussing's work, this paper will employ the primer vector theory to study trajectory optimization problems of arbitrary eccentricity elliptical orbit rendezvous. Based on linearized equations of relative motion on elliptical reference orbit (referred to as T-H equations), the primer vector theory is used to deal with time-fixed multiple-impulse optimal rendezvous between two coplanar, coaxial elliptical orbits with arbitrary large eccentricity. A parameter adjustment method is developed for the prime vector to satisfy the Lawden's necessary condition for the optimal solution. Finally, the optimal multiple-impulse rendezvous solution including the time, direction and magnitudes of the impulse is obtained by solving the two-point boundary value problem. The rendezvous error of the linearized equation is also analyzed. The simulation results confirmed the analyzed results that the rendezvous error is small for the small eccentricity case and is large for the higher eccentricity. For better rendezvous accuracy of high eccentricity orbits, a combined method of multiplier penalty function with the simplex search method is used for local optimization. The simplex search method is sensitive to the initial values of optimization variables, but the simulation results show that initial values with the primer vector theory, and the local optimization algorithm can improve the rendezvous accuracy effectively with fast convergence, because the optimal results obtained by the primer vector theory are already very close to the actual optimal solution. If the initial values are taken randomly, it is difficult to converge to the optimal solution.

Victimization and health risk factors among weapon-carrying youth.

PubMed

Stayton, Catherine; McVeigh, Katharine H; Olson, E Carolyn; Perkins, Krystal; Kerker, Bonnie D

2011-11-01

To compare health risks of 2 subgroups of weapon carriers: victimized and nonvictimized youth. 2003-2007 NYC Youth Risk Behavior Surveys were analyzed using bivariate analyses and multinomial logistic regression. Among NYC teens, 7.5% reported weapon carrying without victimization; 6.9% reported it with victimization. Both subgroups were more likely than non-weapon carriers to binge drink, use marijuana, smoke, fight, and have multiple sex partners; weapon carriers with victimization also experienced persistent sadness and attempted suicide. Subgroups of weapon carriers have distinct profiles. Optimal response should pair disciplinary action with screening for behavioral and mental health concerns and victimization.

Diphenylpyrazoles as Replication Protein A inhibitors

DOE PAGES

Waterson, Alex G.; Kennedy, J. Phillip; Patrone, James D.; ...

2014-11-11

Replication Protein A is the primary eukaryotic ssDNA binding protein that has a central role in initiating the cellular response to DNA damage. RPA recruits multiple proteins to sites of DNA damage via the N-terminal domain of the 70 kDa subunit (RPA70N). Here we describe the optimization of a diphenylpyrazole carboxylic acid series of inhibitors of these RPA–protein interactions. Lastly, we evaluated substituents on the aromatic rings as well as the type and geometry of the linkers used to combine fragments, ultimately leading to submicromolar inhibitors of RPA70N protein–protein interactions.

An iterative forward analysis technique to determine the equation of state of dynamically compressed materials

DOE PAGES

Ali, S. J.; Kraus, R. G.; Fratanduono, D. E.; ...

2017-05-18

Here, we developed an iterative forward analysis (IFA) technique with the ability to use hydrocode simulations as a fitting function for analysis of dynamic compression experiments. The IFA method optimizes over parameterized quantities in the hydrocode simulations, breaking the degeneracy of contributions to the measured material response. Velocity profiles from synthetic data generated using a hydrocode simulation are analyzed as a first-order validation of the technique. We also analyze multiple magnetically driven ramp compression experiments on copper and compare with more conventional techniques. Excellent agreement is obtained in both cases.

Impulse damping control of an experimental structure

NASA Technical Reports Server (NTRS)

Redmond, J.; Meyer, J. L.; Silverberg, L.

1993-01-01

The characteristics associated with the fuel optimal control of a harmonic oscillator are extended to develop a near minimum fuel control algorithm for the vibration suppression of spacecraft. The operation of single level thrusters is regulated by recursive calculations of the standard deviations of displacement and velocity resulting in a bang-off-bang controller. A vertically suspended 16 ft cantilevered beam was used in the experiment. Results show that the structure's response was easily manipulated by minor alterations in the control law and the control system performance was not seriously degraded in the presence of multiple actuator failures.

Multiple Target Laser Designator (MTLD)

DTIC Science & Technology

2007-03-01

Optimized Liquid Crystal Scanning Element Optimize the Nonimaging Predictive Algorithm for Target Ranging, Tracking, and Position Estimation...commercial potential. 3.0 PROGRESS THIS QUARTER 3.1 Optimization of Nonimaging Holographic Antenna for Target Tracking and Position Estimation (Task 6) In

Barriers to optimal diabetes care in Trinidad and Tobago: a health care Professionals' perspective.

PubMed

Roopnarinesingh, Nira; Brennan, Nancyellen; Khan, Claude; Ladenson, Paul W; Hill-Briggs, Felicia; Kalyani, Rita Rastogi

2015-09-19

The republic of Trinidad and Tobago (T&T) is a middle income country with a comparatively high prevalence of diabetes mellitus (DM) compared to others in the Caribbean. To date, there have been no studies on health care professionals' (HCP) perspectives regarding the barriers to achieving optimal care of patients with DM in this country and few previous studies in the Caribbean, yet such perspectives are imperative to develop strategies that reduce the global burden of this disease. An electronic invitation was sent to prospective HCP in T&T inviting them to attend a symposium on DM and cardiovascular disease. A total of 198 HCP participants attended of whom approximately 100 participants completed an Audience Response Survey at the completion of the conference. The Audience Response Survey included questions regarding access to resources, need for prevention and education, and coordination of care for to diabetes care in T&T. Responses were analyzed in aggregate. The 198 HCP participants attending the symposium included mostly nurses (40 %) and physicians (43 %). The most common specialty indicated by the 198 HCP participants was Internal and Family Medicine (28 %), followed by Anesthesiology (7 %), Emergency Medicine (6 %), Endocrinology and Diabetes (5 %) and Cardiology (3 %). Among the ~100 HCP who completed the Audience Response Survey, multiple barriers to achieving optimal care of patients with diabetes were reported such as: limited access to blood testing (75 %), ophthalmological evaluations (96 %), ECGs (69 %), and cardiac stress tests (92 %); inadequate time to screen and evaluate DM complications (95 %); poor access to consultants for referral of difficult cases (77 %); and lack of provider education regarding cardiovascular complications of DM (57 %). HCP agreed that nurses could potentially be considered to have a more active role in the care and prevention of cardiovascular disease and diabetes through leading patient education efforts (98 %), screening patients for complications (91 %), coordinating care efforts (99 %) and educating family members (98 %). The HCP in our study reported significant barriers to achieving optimal diabetes care in T&T. In the future, such barriers to care will need to be addressed in order to respond to the projected growth of diabetes in developing countries both within the Caribbean and globally.

A semi-analytical model of a time reversal cavity for high-amplitude focused ultrasound applications

NASA Astrophysics Data System (ADS)

Robin, J.; Tanter, M.; Pernot, M.

2017-09-01

Time reversal cavities (TRC) have been proposed as an efficient approach for 3D ultrasound therapy. They allow the precise spatio-temporal focusing of high-power ultrasound pulses within a large region of interest with a low number of transducers. Leaky TRCs are usually built by placing a multiple scattering medium, such as a random rod forest, in a reverberating cavity, and the final peak pressure gain of the device only depends on the temporal length of its impulse response. Such multiple scattering in a reverberating cavity is a complex phenomenon, and optimisation of the device’s gain is usually a cumbersome process, mostly empirical, and requiring numerical simulations with extremely long computation times. In this paper, we present a semi-analytical model for the fast optimisation of a TRC. This model decouples ultrasound propagation in an empty cavity and multiple scattering in a multiple scattering medium. It was validated numerically and experimentally using a 2D-TRC and numerically using a 3D-TRC. Finally, the model was used to determine rapidly the optimal parameters of the 3D-TRC which had been confirmed by numerical simulations.

Developing an effective breast cancer vaccine.

PubMed

Soliman, Hatem

2010-07-01

Harnessing the immune response in treating breast cancer would potentially offer a less toxic, more targeted approach to eradicating residual disease. Breast cancer vaccines are being developed to effectively train cytotoxic T cells to recognize and kill transformed cells while sparing normal ones. However, achieving this goal has been problematic due to the ability of established cancers to suppress and evade the immune response. A review of the literature on vaccines and breast cancer treatment was conducted, specifically addressing strategies currently available, as well as appropriate settings, paradigms for vaccine development and response monitoring, and challenges with immunosuppression. Multiple issues need to be addressed in order to optimize the benefits offered by breast cancer vaccines. Primary issues include the following: (1) cancer vaccines will likely work better in a minimal residual disease state, (2) clinical trial design for immunotherapy should incorporate recommendations from expert groups such as the Cancer Vaccine Working Group and use standardized immune response measurements, (3) the presently available cancer vaccine approaches, including dendritic cell-based, tumor-associated antigen peptide-based, and whole cell-based, have various pros and cons, (4) to date, no one approach has been shown to be superior to another, and (5) vaccines will need to be combined with immunoregulatory agents to overcome tumor-related immunosuppression. Combining a properly optimized cancer vaccine with novel immunomodulating agents that overcome tumor-related immunosuppression in a well-designed clinical trial offers the best hope for developing an effective breast cancer vaccine strategy.

Retinal ganglion cell responses to voltage and current stimulation in wild-type and rd1 mouse retinas

NASA Astrophysics Data System (ADS)

Goo, Yong Sook; Ye, Jang Hee; Lee, Seokyoung; Nam, Yoonkey; Ryu, Sang Baek; Kim, Kyung Hwan

2011-06-01

Retinal prostheses are being developed to restore vision for those with retinal diseases such as retinitis pigmentosa or age-related macular degeneration. Since neural prostheses depend upon electrical stimulation to control neural activity, optimal stimulation parameters for successful encoding of visual information are one of the most important requirements to enable visual perception. In this paper, we focused on retinal ganglion cell (RGC) responses to different stimulation parameters and compared threshold charge densities in wild-type and rd1 mice. For this purpose, we used in vitro retinal preparations of wild-type and rd1 mice. When the neural network was stimulated with voltage- and current-controlled pulses, RGCs from both wild-type and rd1 mice responded; however the temporal pattern of RGC response is very different. In wild-type RGCs, a single peak within 100 ms appears, while multiple peaks (approximately four peaks) with ~10 Hz rhythm within 400 ms appear in RGCs in the degenerated retina of rd1 mice. We find that an anodic phase-first biphasic voltage-controlled pulse is more efficient for stimulation than a biphasic current-controlled pulse based on lower threshold charge density. The threshold charge densities for activation of RGCs both with voltage- and current-controlled pulses are overall more elevated for the rd1 mouse than the wild-type mouse. Here, we propose the stimulus range for wild-type and rd1 retinas when the optimal modulation of a RGC response is possible.

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

NASA Astrophysics Data System (ADS)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

Multiple piezo-patch energy harvesters integrated to a thin plate with AC-DC conversion: analytical modeling and numerical validation

NASA Astrophysics Data System (ADS)

Aghakhani, Amirreza; Basdogan, Ipek; Erturk, Alper

2016-04-01

Plate-like components are widely used in numerous automotive, marine, and aerospace applications where they can be employed as host structures for vibration based energy harvesting. Piezoelectric patch harvesters can be easily attached to these structures to convert the vibrational energy to the electrical energy. Power output investigations of these harvesters require accurate models for energy harvesting performance evaluation and optimization. Equivalent circuit modeling of the cantilever-based vibration energy harvesters for estimation of electrical response has been proposed in recent years. However, equivalent circuit formulation and analytical modeling of multiple piezo-patch energy harvesters integrated to thin plates including nonlinear circuits has not been studied. In this study, equivalent circuit model of multiple parallel piezoelectric patch harvesters together with a resistive load is built in electronic circuit simulation software SPICE and voltage frequency response functions (FRFs) are validated using the analytical distributedparameter model. Analytical formulation of the piezoelectric patches in parallel configuration for the DC voltage output is derived while the patches are connected to a standard AC-DC circuit. The analytic model is based on the equivalent load impedance approach for piezoelectric capacitance and AC-DC circuit elements. The analytic results are validated numerically via SPICE simulations. Finally, DC power outputs of the harvesters are computed and compared with the peak power amplitudes in the AC output case.

Evaluation of TNF-α serum level in patients with recalcitrant multiple common warts, treated by lipid garlic extract.

PubMed

Kenawy, Soha; Mohammed, Ghada Farouk; Younes, Soha; Elakhras, Atef Ibrahim

2014-01-01

No universal consensus about optimal modality for treating the recalcitrant multiple common warts (RMCW). The objective of the study was to evaluate the immunological mechanisms and clinical therapeutic effect of using lipid garlic extract (LGE) in the treatment of RMCW. The study included 50 patients with RMCW. They were randomly assigned into two groups: the first group (25 patients) received LGE, and the second group (25 patients) received saline as a control group. In both groups, treatments were made to single lesions, or largest wart in case of multiple lesions, until complete clearance of lesions or for a maximum of 4 weeks. Blood serum was taken at pre-study and at the fourth week to measure tumor necrosis factor alpha (TNF-α) level. A significant difference was found between the therapeutic responses of RMCW to LGE antigen and saline control group (p < 0.001). In the LGE group, complete response was achieved in 96% of patients presenting with RMCW. There was a statistically nonsignificant increase in TNF-α of LGE group versus saline group. No recurrence was observed in the LGE group. LGE as an immunotherapy is an inexpensive, effective, and safe modality with good cure rates for treatment of RMCWs, when other topical or physical therapies have failed. © 2014 Wiley Periodicals, Inc.

Dynamic Network Selection for Multicast Services in Wireless Cooperative Networks

NASA Astrophysics Data System (ADS)

Chen, Liang; Jin, Le; He, Feng; Cheng, Hanwen; Wu, Lenan

In next generation mobile multimedia communications, different wireless access networks are expected to cooperate. However, it is a challenging task to choose an optimal transmission path in this scenario. This paper focuses on the problem of selecting the optimal access network for multicast services in the cooperative mobile and broadcasting networks. An algorithm is proposed, which considers multiple decision factors and multiple optimization objectives. An analytic hierarchy process (AHP) method is applied to schedule the service queue and an artificial neural network (ANN) is used to improve the flexibility of the algorithm. Simulation results show that by applying the AHP method, a group of weight ratios can be obtained to improve the performance of multiple objectives. And ANN method is effective to adaptively adjust weight ratios when users' new waiting threshold is generated.

An Approach to Economic Dispatch with Multiple Fuels Based on Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Sriyanyong, Pichet

2011-06-01

Particle Swarm Optimization (PSO), a stochastic optimization technique, shows superiority to other evolutionary computation techniques in terms of less computation time, easy implementation with high quality solution, stable convergence characteristic and independent from initialization. For this reason, this paper proposes the application of PSO to the Economic Dispatch (ED) problem, which occurs in the operational planning of power systems. In this study, ED problem can be categorized according to the different characteristics of its cost function that are ED problem with smooth cost function and ED problem with multiple fuels. Taking the multiple fuels into account will make the problem more realistic. The experimental results show that the proposed PSO algorithm is more efficient than previous approaches under consideration as well as highly promising in real world applications.

Simultaneous assay of multiple antibiotics in human plasma by LC-MS/MS: importance of optimizing formic acid concentration.

PubMed

Chen, Feng; Hu, Zhe-Yi; Laizure, S Casey; Hudson, Joanna Q

2017-03-01

Optimal dosing of antibiotics in critically ill patients is complicated by the development of resistant organisms requiring treatment with multiple antibiotics and alterations in systemic exposure due to diseases and extracorporeal drug removal. Developing guidelines for optimal antibiotic dosing is an important therapeutic goal requiring robust analytical methods to simultaneously measure multiple antibiotics. An LC-MS/MS assay using protein precipitation for cleanup followed by a 6-min gradient separation was developed to simultaneously determine five antibiotics in human plasma. The precision and accuracy were within the 15% acceptance range. The formic acid concentration was an important determinant of signal intensity, peak shape and matrix effects. The method was designed to be simple and successfully applied to a clinical pharmacokinetic study.

Biobjective planning of GEO debris removal mission with multiple servicing spacecrafts

NASA Astrophysics Data System (ADS)

Jing, Yu; Chen, Xiao-qian; Chen, Li-hu

2014-12-01

The mission planning of GEO debris removal with multiple servicing spacecrafts (SScs) is studied in this paper. Specifically, the SScs are considered to be initially on the GEO belt, and they should rendezvous with debris of different orbital slots and different inclinations, remove them to the graveyard orbit and finally return to their initial locations. Three key problems should be resolved here: task assignment, mission sequence planning and transfer trajectory optimization for each SSc. The minimum-cost, two-impulse phasing maneuver is used for each rendezvous. The objective is to find a set of optimal planning schemes with minimum fuel cost and travel duration. Considering this mission as a hybrid optimal control problem, a mathematical model is proposed. A modified multi-objective particle swarm optimization is employed to address the model. Numerous examples are carried out to demonstrate the effectiveness of the model and solution method. In this paper, single-SSc and multiple-SSc scenarios with the same amount of fuel are compared. Numerous experiments indicate that for a definite GEO debris removal mission, that which alternative (single-SSc or multiple-SSc) is better (cost less fuel and consume less travel time) is determined by many factors. Although in some cases, multiple-SSc scenarios may perform worse than single-SSc scenarios, the extra costs are considered worth the gain in mission safety and robustness.

Local adaptation in migrated interior Douglas-fir seedlings is mediated by ectomycorrhizas and other soil factors.

PubMed

Pickles, Brian J; Twieg, Brendan D; O'Neill, Gregory A; Mohn, William W; Simard, Suzanne W

2015-08-01

Separating edaphic impacts on tree distributions from those of climate and geography is notoriously difficult. Aboveground and belowground factors play important roles, and determining their relative contribution to tree success will greatly assist in refining predictive models and forestry strategies in a changing climate. In a common glasshouse, seedlings of interior Douglas-fir (Pseudotsuga menziesii var. glauca) from multiple populations were grown in multiple forest soils. Fungicide was applied to half of the seedlings to separate soil fungal and nonfungal impacts on seedling performance. Soils of varying geographic and climatic distance from seed origin were compared, using a transfer function approach. Seedling height and biomass were optimized following seed transfer into drier soils, whereas survival was optimized when elevation transfer was minimised. Fungicide application reduced ectomycorrhizal root colonization by c. 50%, with treated seedlings exhibiting greater survival but reduced biomass. Local adaptation of Douglas-fir populations to soils was mediated by soil fungi to some extent in 56% of soil origin by response variable combinations. Mediation by edaphic factors in general occurred in 81% of combinations. Soil biota, hitherto unaccounted for in climate models, interacts with biogeography to influence plant ranges in a changing climate. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Toward optimizing the delivery and use of climate science for natural resource management: lessons learned from recent adaptation efforts in the southwestern U.S.

NASA Astrophysics Data System (ADS)

Enquist, C.

2014-12-01

Within the past decade, a wealth of federal, state, and NGO-driven initiatives has emerged across managed landscapes in the United States with the goal of facilitating a coordinated response to rapidly changing climate and environmental conditions. In addition to acquisition and translation of the latest climate science, climate vulnerability assessment and scenario planning at multiple spatial and temporal scales are typically major components of such broad adaptation efforts. Numerous approaches for conducting this work have emerged in recent years and have culminated in general guidance and trainings for resource professionals that are specifically designed to help practitioners face the challenges of climate change. In particular, early engagement of stakeholders across multiple jurisdictions is particularly critical to cultivate buy-in and other enabling conditions for moving the science to on-the-ground action. I report on a suite of adaptation efforts in the southwestern US and interior Rockies, highlighting processes used, actions taken, lessons learned, and recommended next steps to facilitate achieving desired management outcomes. This includes a discussion of current efforts to optimize funding for actionable climate science, formalize science-management collaborations, and facilitate new investments in approaches for strategic climate-informed monitoring and evaluation.

Training Modalities to Increase Sensorimotor Adaptability

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Mulavara, A. P.; Peters, B. T.; Brady, R.; Audas, C.; Cohen, H. S.

2009-01-01

During the acute phase of adaptation to novel gravitational environments, sensorimotor disturbances have the potential to disrupt the ability of astronauts to perform required mission tasks. The goal of our current series of studies is develop a sensorimotor adaptability (SA) training program designed to facilitate recovery of functional capabilities when astronauts transition to different gravitational environments. The project has conducted a series of studies investigating the efficacy of treadmill training combined with a variety of sensory challenges (incongruent visual input, support surface instability) designed to increase adaptability. SA training using a treadmill combined with exposure to altered visual input was effective in producing increased adaptability in a more complex over-ground ambulatory task on an obstacle course. This confirms that for a complex task like walking, treadmill training contains enough of the critical features of overground walking to be an effective training modality. SA training can be optimized by using a periodized training schedule. Test sessions that each contain short-duration exposures to multiple perturbation stimuli allows subjects to acquire a greater ability to rapidly reorganize appropriate response strategies when encountering a novel sensory environment. Using a treadmill mounted on top of a six degree-of-freedom motion base platform we investigated locomotor training responses produced by subjects introduced to a dynamic walking surface combined with alterations in visual flow. Subjects who received this training had improved locomotor performance and faster reaction times when exposed to the novel sensory stimuli compared to control subjects. Results also demonstrate that individual sensory biases (i.e. increased visual dependency) can predict adaptive responses to novel sensory environments suggesting that individual training prescription can be developed to enhance adaptability. These data indicate that SA training can be effectively integrated with treadmill exercise and optimized to provide a unique system that combines multiple training requirements in a single countermeasure system. Learning Objectives: The development of a new countermeasure approach that enhances sensorimotor adaptability will be discussed.

An analytical/numerical correlation study of the multiple concentric cylinder model for the thermoplastic response of metal matrix composites

NASA Technical Reports Server (NTRS)

Pindera, Marek-Jerzy; Salzar, Robert S.; Williams, Todd O.

1993-01-01

The utility of a recently developed analytical micromechanics model for the response of metal matrix composites under thermal loading is illustrated by comparison with the results generated using the finite-element approach. The model is based on the concentric cylinder assemblage consisting of an arbitrary number of elastic or elastoplastic sublayers with isotropic or orthotropic, temperature-dependent properties. The elastoplastic boundary-value problem of an arbitrarily layered concentric cylinder is solved using the local/global stiffness matrix formulation (originally developed for elastic layered media) and Mendelson's iterative technique of successive elastic solutions. These features of the model facilitate efficient investigation of the effects of various microstructural details, such as functionally graded architectures of interfacial layers, on the evolution of residual stresses during cool down. The available closed-form expressions for the field variables can readily be incorporated into an optimization algorithm in order to efficiently identify optimal configurations of graded interfaces for given applications. Comparison of residual stress distributions after cool down generated using finite-element analysis and the present micromechanics model for four composite systems with substantially different temperature-dependent elastic, plastic, and thermal properties illustrates the efficacy of the developed analytical scheme.

A Hierarchical Mechanism of RIG-I Ubiquitination Provides Sensitivity, Robustness and Synergy in Antiviral Immune Responses.

PubMed

Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun

2016-07-08

RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses.

A Hierarchical Mechanism of RIG-I Ubiquitination Provides Sensitivity, Robustness and Synergy in Antiviral Immune Responses

PubMed Central

Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun

2016-01-01

RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses. PMID:27387525

A Hierarchical Mechanism of RIG-I Ubiquitination Provides Sensitivity, Robustness and Synergy in Antiviral Immune Responses

NASA Astrophysics Data System (ADS)

Sun, Xiaoqiang; Xian, Huifang; Tian, Shuo; Sun, Tingzhe; Qin, Yunfei; Zhang, Shoutao; Cui, Jun

2016-07-01

RIG-I is an essential receptor in the initiation of the type I interferon (IFN) signaling pathway upon viral infection. Although K63-linked ubiquitination plays an important role in RIG-I activation, the optimal modulation of conjugated and unanchored ubiquitination of RIG-I as well as its functional implications remains unclear. In this study, we determined that, in contrast to the RIG-I CARD domain, full-length RIG-I must undergo K63-linked ubiquitination at multiple sites to reach full activity. A systems biology approach was designed based on experiments using full-length RIG-I. Model selection for 7 candidate mechanisms of RIG-I ubiquitination inferred a hierarchical architecture of the RIG-I ubiquitination mode, which was then experimentally validated. Compared with other mechanisms, the selected hierarchical mechanism exhibited superior sensitivity and robustness in RIG-I-induced type I IFN activation. Furthermore, our model analysis and experimental data revealed that TRIM4 and TRIM25 exhibited dose-dependent synergism. These results demonstrated that the hierarchical mechanism of multi-site/type ubiquitination of RIG-I provides an efficient, robust and optimal synergistic regulatory module in antiviral immune responses.

Development and Implementation of an Optimization Model for Hydropower and Total Dissolved Gas in the Mid-Columbia River System

DOE PAGES

Witt, Adam; Magee, Timothy; Stewart, Kevin; ...

2017-08-10

Managing energy, water, and environmental priorities and constraints within a cascade hydropower system is a challenging multiobjective optimization effort that requires advanced modeling and forecasting tools. Within the mid-Columbia River system, there is currently a lack of specific solutions for predicting how coordinated operational decisions can mitigate the impacts of total dissolved gas (TDG) supersaturation while satisfying multiple additional policy and hydropower generation objectives. In this study, a reduced-order TDG uptake equation is developed that predicts tailrace TDG at seven hydropower facilities on the mid-Columbia River. The equation is incorporated into a general multiobjective river, reservoir, and hydropower optimization toolmore » as a prioritized operating goal within a broader set of system-level objectives and constraints. A test case is presented to assess the response of TDG and hydropower generation when TDG supersaturation is optimized to remain under state water-quality standards. Satisfaction of TDG as an operating goal is highly dependent on whether constraints that limit TDG uptake are implemented at a higher priority than generation requests. According to the model, an opportunity exists to reduce TDG supersaturation and meet hydropower generation requirements by shifting spillway flows to different time periods. In conclusion, a coordinated effort between all project owners is required to implement systemwide optimized solutions that satisfy the operating policies of all stakeholders.« less

Development and Implementation of an Optimization Model for Hydropower and Total Dissolved Gas in the Mid-Columbia River System

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

Witt, Adam; Magee, Timothy; Stewart, Kevin

Managing energy, water, and environmental priorities and constraints within a cascade hydropower system is a challenging multiobjective optimization effort that requires advanced modeling and forecasting tools. Within the mid-Columbia River system, there is currently a lack of specific solutions for predicting how coordinated operational decisions can mitigate the impacts of total dissolved gas (TDG) supersaturation while satisfying multiple additional policy and hydropower generation objectives. In this study, a reduced-order TDG uptake equation is developed that predicts tailrace TDG at seven hydropower facilities on the mid-Columbia River. The equation is incorporated into a general multiobjective river, reservoir, and hydropower optimization toolmore » as a prioritized operating goal within a broader set of system-level objectives and constraints. A test case is presented to assess the response of TDG and hydropower generation when TDG supersaturation is optimized to remain under state water-quality standards. Satisfaction of TDG as an operating goal is highly dependent on whether constraints that limit TDG uptake are implemented at a higher priority than generation requests. According to the model, an opportunity exists to reduce TDG supersaturation and meet hydropower generation requirements by shifting spillway flows to different time periods. In conclusion, a coordinated effort between all project owners is required to implement systemwide optimized solutions that satisfy the operating policies of all stakeholders.« less

Homologous Prime-Boost Vaccination with OVA Entrapped in Self-Adjuvanting Archaeosomes Induces High Numbers of OVA-Specific CD8+ T Cells that Protect Against Subcutaneous B16-OVA Melanoma

PubMed Central

Stark, Felicity C.; McCluskie, Michael J.; Krishnan, Lakshmi

2016-01-01

Homologous prime-boost vaccinations with live vectors typically fail to induce repeated strong CD8+ T cell responses due to the induction of anti-vector immunity, highlighting the need for alternative delivery vehicles. The unique ether lipids of archaea may be constituted into liposomes, archaeosomes, which do not induce anti-carrier responses, making them an ideal candidate for use in repeat vaccination systems. Herein, we evaluated in mice the maximum threshold of antigen-specific CD8+ T cell responses that may be induced by multiple homologous immunizations with ovalbumin (OVA) entrapped in archaeosomes derived from the ether glycerolipids of the archaeon Methanobrevibacter smithii (MS-OVA). Up to three immunizations with MS-OVA administered in optimized intervals (to allow for sufficient resting of the primed cells prior to boosting), induced a potent anti-OVA CD8+ T cell response of up to 45% of all circulating CD8+ T cells. Additional MS-OVA injections did not add any further benefit in increasing the memory of CD8+ T cell frequency. In contrast, OVA expressed by Listeria monocytogenes (LM-OVA), an intracellular bacterial vector failed to evoke a boosting effect after the second injection, resulting in significantly reduced antigen-specific CD8+ T cell frequencies. Furthermore, repeated vaccination with MS-OVA skewed the response increasingly towards an effector memory (CD62low) phenotype. Vaccinated animals were challenged with B16-OVA at late time points after vaccination (+7 months) and were afforded protection compared to control. Therefore, archaeosomes constituted a robust particulate delivery system to unravel the kinetics of CD8+ T cell response induction and memory maintenance and constitute an efficient vaccination regimen optimized for tumor protection. PMID:27869670

Structural optimization of large structural systems by optimality criteria methods

NASA Technical Reports Server (NTRS)

Berke, Laszlo

1992-01-01

The fundamental concepts of the optimality criteria method of structural optimization are presented. The effect of the separability properties of the objective and constraint functions on the optimality criteria expressions is emphasized. The single constraint case is treated first, followed by the multiple constraint case with a more complex evaluation of the Lagrange multipliers. Examples illustrate the efficiency of the method.

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

PubMed

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Elicitation of Robust Tier 2 Neutralizing Antibody Responses in Nonhuman Primates by HIV Envelope Trimer Immunization Using Optimized Approaches.

PubMed

Pauthner, Matthias; Havenar-Daughton, Colin; Sok, Devin; Nkolola, Joseph P; Bastidas, Raiza; Boopathy, Archana V; Carnathan, Diane G; Chandrashekar, Abishek; Cirelli, Kimberly M; Cottrell, Christopher A; Eroshkin, Alexey M; Guenaga, Javier; Kaushik, Kirti; Kulp, Daniel W; Liu, Jinyan; McCoy, Laura E; Oom, Aaron L; Ozorowski, Gabriel; Post, Kai W; Sharma, Shailendra K; Steichen, Jon M; de Taeye, Steven W; Tokatlian, Talar; Torrents de la Peña, Alba; Butera, Salvatore T; LaBranche, Celia C; Montefiori, David C; Silvestri, Guido; Wilson, Ian A; Irvine, Darrell J; Sanders, Rogier W; Schief, William R; Ward, Andrew B; Wyatt, Richard T; Barouch, Dan H; Crotty, Shane; Burton, Dennis R

2017-06-20

The development of stabilized recombinant HIV envelope trimers that mimic the virion surface molecule has increased enthusiasm for a neutralizing antibody (nAb)-based HIV vaccine. However, there is limited experience with recombinant trimers as immunogens in nonhuman primates, which are typically used as a model for humans. Here, we tested multiple immunogens and immunization strategies head-to-head to determine their impact on the quantity, quality, and kinetics of autologous tier 2 nAb development. A bilateral, adjuvanted, subcutaneous immunization protocol induced reproducible tier 2 nAb responses after only two immunizations 8 weeks apart, and these were further enhanced by a third immunization with BG505 SOSIP trimer. We identified immunogens that minimized non-neutralizing V3 responses and demonstrated that continuous immunogen delivery could enhance nAb responses. nAb responses were strongly associated with germinal center reactions, as assessed by lymph node fine needle aspiration. This study provides a framework for preclinical and clinical vaccine studies targeting nAb elicitation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Application of constraint-based satellite mission planning model in forest fire monitoring

NASA Astrophysics Data System (ADS)

Guo, Bingjun; Wang, Hongfei; Wu, Peng

2017-10-01

In this paper, a constraint-based satellite mission planning model is established based on the thought of constraint satisfaction. It includes target, request, observation, satellite, payload and other elements, with constraints linked up. The optimization goal of the model is to make full use of time and resources, and improve the efficiency of target observation. Greedy algorithm is used in the model solving to make observation plan and data transmission plan. Two simulation experiments are designed and carried out, which are routine monitoring of global forest fire and emergency monitoring of forest fires in Australia. The simulation results proved that the model and algorithm perform well. And the model is of good emergency response capability. Efficient and reasonable plan can be worked out to meet users' needs under complex cases of multiple payloads, multiple targets and variable priorities with this model.

Estrogenic modulation of auditory processing: a vertebrate comparison

PubMed Central

Caras, Melissa L.

2013-01-01

Sex-steroid hormones are well-known regulators of vocal motor behavior in several organisms. A large body of evidence now indicates that these same hormones modulate processing at multiple levels of the ascending auditory pathway. The goal of this review is to provide a comparative analysis of the role of estrogens in vertebrate auditory function. Four major conclusions can be drawn from the literature: First, estrogens may influence the development of the mammalian auditory system. Second, estrogenic signaling protects the mammalian auditory system from noise- and age-related damage. Third, estrogens optimize auditory processing during periods of reproductive readiness in multiple vertebrate lineages. Finally, brain-derived estrogens can act locally to enhance auditory response properties in at least one avian species. This comparative examination may lead to a better appreciation of the role of estrogens in the processing of natural vocalizations and may provide useful insights toward alleviating auditory dysfunctions emanating from hormonal imbalances. PMID:23911849

Managing renal complications in multiple myeloma.

PubMed

Fotiou, Despoina; Dimopoulos, Meletios A; Kastritis, Efstathios

2016-09-01

About 20-40% of patients with multiple myeloma (MM) will present with some degree of renal impairment (RI) and about 25% of patients will experience RI at later disease stages. Patients with MM and RI have poorer overall survival and are at higher risk of early death. The mechanisms of acute renal damage in MM are covered and the issues around diagnosis and renal evaluation response are discussed. The importance of optimal supportive care is stressed and the role and effectiveness of different anti-myeloma agents covered including the role of high cut-off hemodialysis, autologous stem cell transplantation and kidney transplant. Expert commentary: Outcomes of patients with RI and rates of renal recovery have improved with the use of novel anti-myeloma agents. Bortezomib-dexamethasone backbone regimes (±third agent) are the current first choice in newly diagnosed patients. In relapsed/refractory disease additional treatment options include newer novel agents.

Consensus definitions and application guidelines for control groups in cerebrospinal fluid biomarker studies in multiple sclerosis.

PubMed

Teunissen, Charlotte; Menge, Til; Altintas, Ayse; Álvarez-Cermeño, José C; Bertolotto, Antonio; Berven, Frode S; Brundin, Lou; Comabella, Manuel; Degn, Matilde; Deisenhammer, Florian; Fazekas, Franz; Franciotta, Diego; Frederiksen, Jette L; Galimberti, Daniela; Gnanapavan, Sharmilee; Hegen, Harald; Hemmer, Bernhard; Hintzen, Rogier; Hughes, Steve; Iacobaeus, Ellen; Kroksveen, Ann C; Kuhle, Jens; Richert, John; Tumani, Hayrettin; Villar, Luisa M; Drulovic, Jelena; Dujmovic, Irena; Khalil, Michael; Bartos, Ales

2013-11-01

The choice of appropriate control group(s) is critical in cerebrospinal fluid (CSF) biomarker research in multiple sclerosis (MS). There is a lack of definitions and nomenclature of different control groups and a rationalized application of different control groups. We here propose consensus definitions and nomenclature for the following groups: healthy controls (HCs), spinal anesthesia subjects (SASs), inflammatory neurological disease controls (INDCs), peripheral inflammatory neurological disease controls (PINDCs), non-inflammatory neurological controls (NINDCs), symptomatic controls (SCs). Furthermore, we discuss the application of these control groups in specific study designs, such as for diagnostic biomarker studies, prognostic biomarker studies and therapeutic response studies. Application of these uniform definitions will lead to better comparability of biomarker studies and optimal use of available resources. This will lead to improved quality of CSF biomarker research in MS and related disorders.

Nonlinear engine model for idle speed control

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

Livshiz, M.; Sanvido, D.J.; Stiles, S.D.

1994-12-31

This paper describes a nonlinear model of an engine used for the design of idle speed control and prediction in a broad range of idle speeds and operational conditions. Idle speed control systems make use of both spark advance and the idle air actuator to control engine speed for improved response relative to variations in the target idle speed due to load disturbances. The control system at idle can be presented by a multiple input multiple output (MIMO) nonlinear model. Information of nonlinearities helps to improve performance of the system over the whole range of engine speeds. A proposed simplemore » nonlinear model of the engine at idle was applied for design of optimal controllers and predictors for improved steady state, load rejection and transition from and to idle. This paper describes vehicle results of engine speed prediction based on the described model.« less

Dispositional Optimism and Incidence of Cognitive Impairment in Older Adults

PubMed Central

Gawronski, Katerina A.B.; Kim, Eric S.; Langa, Kenneth M.; Kubzansky, Laura D.

2017-01-01

Objective Higher levels of optimism have been linked with positive health behaviors, biological processes, and health conditions that are potentially protective against cognitive impairment in older adults. However, the association between optimism and cognitive impairment has not been directly examined. We examined whether optimism is associated with incident cognitive impairment in older adults. Methods Data are from the Health and Retirement Study, a nationally representative sample of older U.S. adults. Using multiple logistic regression models, we prospectively assessed whether optimism was associated with incident cognitive impairment in 4,624 adults aged 65+ over a four-year period. Results Among the 4,624 participants, 497 respondents developed cognitive impairment over the four-year follow-up (306 women and 191 men). Higher optimism was associated with decreased risk of incident cognitive impairment. When controlling for sociodemographic factors, each standard deviation increase in optimism was associated with reduced odds (OR=0.72, 95% CI, 0.62–0.83) of becoming cognitively impaired. A dose-response relationship was observed. Compared to those with the lowest levels of optimism, people with moderate levels of optimism had somewhat reduced odds of cognitive impairment (OR=0.79, 95% CI, 0.59–1.03), while people with the highest levels of optimism had the lowest odds of cognitive impairment (OR=0.53, 95% CI, 0.35–0.78). These associations remained after adjusting for health behaviors, biological factors, and psychological covariates that could either confound the association of interest or serve on the pathway. Conclusions Optimism was prospectively associated with a reduced likelihood of becoming cognitively impaired. If these results are replicated, the data suggest that potentially modifiable aspects of positive psychological functioning such as optimism play an important role in maintaining cognitive functioning. Thus, these factors may prove worthy of additional clinical and scientific attention. PMID:27284699

ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

PubMed

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

Taboo Search: An Approach to the Multiple Minima Problem

NASA Astrophysics Data System (ADS)

Cvijovic, Djurdje; Klinowski, Jacek

1995-02-01

Described here is a method, based on Glover's taboo search for discrete functions, of solving the multiple minima problem for continuous functions. As demonstrated by model calculations, the algorithm avoids entrapment in local minima and continues the search to give a near-optimal final solution. Unlike other methods of global optimization, this procedure is generally applicable, easy to implement, derivative-free, and conceptually simple.

An Exploration of the Relationship between Perception of Control, Physical Disability, Optimism, Self-Efficacy and Hopelessness in Multiple Sclerosis

ERIC Educational Resources Information Center

Sinnakaruppan, Indrani; Macdonald, Kirsty; McCafferty, Aileen; Mattison, Paul

2010-01-01

The objective of this study was to explore the relationship between the Perception of Control Scale (PCS) and other measures that incorporate physical disability, optimism, self-efficacy and hopelessness components in a Multiple Sclerosis (MS) sample. One hundred and fifteen participants comprising 44 males and 71 females with a mean age of 45.65…

Optimizing multiple-choice tests as tools for learning.

PubMed

Little, Jeri L; Bjork, Elizabeth Ligon

2015-01-01

Answering multiple-choice questions with competitive alternatives can enhance performance on a later test, not only on questions about the information previously tested, but also on questions about related information not previously tested-in particular, on questions about information pertaining to the previously incorrect alternatives. In the present research, we assessed a possible explanation for this pattern: When multiple-choice questions contain competitive incorrect alternatives, test-takers are led to retrieve previously studied information pertaining to all of the alternatives in order to discriminate among them and select an answer, with such processing strengthening later access to information associated with both the correct and incorrect alternatives. Supporting this hypothesis, we found enhanced performance on a later cued-recall test for previously nontested questions when their answers had previously appeared as competitive incorrect alternatives in the initial multiple-choice test, but not when they had previously appeared as noncompetitive alternatives. Importantly, however, competitive alternatives were not more likely than noncompetitive alternatives to be intruded as incorrect responses, indicating that a general increased accessibility for previously presented incorrect alternatives could not be the explanation for these results. The present findings, replicated across two experiments (one in which corrective feedback was provided during the initial multiple-choice testing, and one in which it was not), thus strongly suggest that competitive multiple-choice questions can trigger beneficial retrieval processes for both tested and related information, and the results have implications for the effective use of multiple-choice tests as tools for learning.

Application of dragonfly algorithm for optimal performance analysis of process parameters in turn-mill operations- A case study

NASA Astrophysics Data System (ADS)

Vikram, K. Arun; Ratnam, Ch; Lakshmi, VVK; Kumar, A. Sunny; Ramakanth, RT

2018-02-01

Meta-heuristic multi-response optimization methods are widely in use to solve multi-objective problems to obtain Pareto optimal solutions during optimization. This work focuses on optimal multi-response evaluation of process parameters in generating responses like surface roughness (Ra), surface hardness (H) and tool vibration displacement amplitude (Vib) while performing operations like tangential and orthogonal turn-mill processes on A-axis Computer Numerical Control vertical milling center. Process parameters like tool speed, feed rate and depth of cut are considered as process parameters machined over brass material under dry condition with high speed steel end milling cutters using Taguchi design of experiments (DOE). Meta-heuristic like Dragonfly algorithm is used to optimize the multi-objectives like ‘Ra’, ‘H’ and ‘Vib’ to identify the optimal multi-response process parameters combination. Later, the results thus obtained from multi-objective dragonfly algorithm (MODA) are compared with another multi-response optimization technique Viz. Grey relational analysis (GRA).

Prevention of Osmotic Injury to Human Umbilical Vein Endothelial Cells for Biopreservation: A First Step Toward Biobanking of Endothelial Cells for Vascular Tissue Engineering.

PubMed

Niu, Dan; Zhao, Gang; Liu, Xiaoli; Zhou, Ping; Cao, Yunxia

2016-03-01

High-survival-rate cryopreservation of endothelial cells plays a critical role in vascular tissue engineering, while optimization of osmotic injuries is the first step toward successful cryopreservation. We designed a low-cost, easy-to-use, microfluidics-based microperfusion chamber to investigate the osmotic responses of human umbilical vein endothelial cells (HUVECs) at different temperatures, and then optimized the protocols for using cryoprotective agents (CPAs) to minimize osmotic injuries and improve processes before freezing and after thawing. The fundamental cryobiological parameters were measured using the microperfusion chamber, and then, the optimized protocols using these parameters were confirmed by survival evaluation and cell proliferation experiments. It was revealed for the first time that HUVECs have an unusually small permeability coefficient for Me2SO. Even at the concentrations well established for slow freezing of cells (1.5 M), one-step removal of CPAs for HUVECs might result in inevitable osmotic injuries, indicating that multiple-step removal is essential. Further experiments revealed that multistep removal of 1.5 M Me2SO at 25°C was the best protocol investigated, in good agreement with theory. These results should prove invaluable for optimization of cryopreservation protocols of HUVECs.

Optimization of primaquine diphosphate tablet formulation for controlled drug release using the mixture experimental design.

PubMed

Duque, Marcelo Dutra; Kreidel, Rogério Nepomuceno; Taqueda, Maria Elena Santos; Baby, André Rolim; Kaneko, Telma Mary; Velasco, Maria Valéria Robles; Consiglieri, Vladi Olga

2013-01-01

A tablet formulation based on hydrophilic matrix with a controlled drug release was developed, and the effect of polymer concentrations on the release of primaquine diphosphate was evaluated. To achieve this purpose, a 20-run, four-factor with multiple constraints on the proportions of the components was employed to obtain tablet compositions. Drug release was determined by an in vitro dissolution study in phosphate buffer solution at pH 6.8. The polynomial fitted functions described the behavior of the mixture on simplex coordinate systems to study the effects of each factor (polymer) on tablet characteristics. Based on the response surface methodology, a tablet composition was optimized with the purpose of obtaining a primaquine diphosphate release closer to a zero order kinetic. This formulation released 85.22% of the drug for 8 h and its kinetic was studied regarding to Korsmeyer-Peppas model, (Adj-R(2) = 0.99295) which has confirmed that both diffusion and erosion were related to the mechanism of the drug release. The data from the optimized formulation were very close to the predictions from statistical analysis, demonstrating that mixture experimental design could be used to optimize primaquine diphosphate dissolution from hidroxypropylmethyl cellulose and polyethylene glycol matrix tablets.

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

NASA Astrophysics Data System (ADS)

Tang, Gao; Jiang, FanHuag; Li, JunFeng

2015-11-01

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

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

PubMed

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

2017-01-01

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

An approach to design controllers for MIMO fractional-order plants based on parameter optimization algorithm.

PubMed

Xue, Dingyü; Li, Tingxue

2017-04-27

The parameter optimization method for multivariable systems is extended to the controller design problems for multiple input multiple output (MIMO) square fractional-order plants. The algorithm can be applied to search for the optimal parameters of integer-order controllers for fractional-order plants with or without time delays. Two examples are given to present the controller design procedures for MIMO fractional-order systems. Simulation studies show that the integer-order controllers designed are robust to plant gain variations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Maximum margin multiple instance clustering with applications to image and text clustering.

PubMed

Zhang, Dan; Wang, Fei; Si, Luo; Li, Tao

2011-05-01

In multiple instance learning problems, patterns are often given as bags and each bag consists of some instances. Most of existing research in the area focuses on multiple instance classification and multiple instance regression, while very limited work has been conducted for multiple instance clustering (MIC). This paper formulates a novel framework, maximum margin multiple instance clustering (M(3)IC), for MIC. However, it is impractical to directly solve the optimization problem of M(3)IC. Therefore, M(3)IC is relaxed in this paper to enable an efficient optimization solution with a combination of the constrained concave-convex procedure and the cutting plane method. Furthermore, this paper presents some important properties of the proposed method and discusses the relationship between the proposed method and some other related ones. An extensive set of empirical results are shown to demonstrate the advantages of the proposed method against existing research for both effectiveness and efficiency.

Development of a fermented ice-cream as influenced by in situ exopolysaccharide production: Rheological, molecular, microstructural and sensory characterization.

PubMed

Dertli, Enes; Toker, Omer S; Durak, M Zeki; Yilmaz, Mustafa T; Tatlısu, Nevruz Berna; Sagdic, Osman; Cankurt, Hasan

2016-01-20

This study aimed to investigate the role of in situ exopolysaccharide (EPS) production by EPS(+)Streptococcus thermophilus strains on physicochemical, rheological, molecular, microstructural and sensory properties of ice cream in order to develop a fermented and consequently functional ice-cream in which no stabilizers would be required in ice-cream production. For this purpose, the effect of EPS producing strains (control, strain 1, strain 2 and mixture) and fermentation conditions (fermentation temperature; 32, 37 and 42 °C and time; 2, 3 and 4h) on pH, S. thermophilus count, EPS amount, consistency coefficient (K), and apparent viscosity (η50) were investigated and optimized using single and multiple response optimization tools of response surface methodology. Optimization analyses indicated that functional ice-cream should be fermented with strain 1 or strain mixture at 40-42 °C for 4h in order to produce the most viscous ice-cream with maximum EPS content. Optimization analysis results also revealed that strain specific conditions appeared to be more effective factor on in situ EPS production amount, K and η50 parameters than did fermentation temperature and time. The rheological analysis of the ice-cream produced by EPS(+) strains revealed its high viscous and pseudoplastic non-Newtonian fluid behavior, which demonstrates potential of S. thermophilus EPS as thickening and gelling agent in dairy industry. FTIR analysis proved that the EPS in ice-cream corresponded to a typical EPS, as revealed by the presence of carboxyl, hydroxyl and amide groups with additional α-glycosidic linkages. SEM studies demonstrated that it had a web-like compact microstructure with pores in ice-cream, revealing its application possibility in dairy products to improve their rheological properties. Copyright © 2015. Published by Elsevier Ltd.

Reliability Sensitivity Analysis and Design Optimization of Composite Structures Based on Response Surface Methodology

NASA Technical Reports Server (NTRS)

Rais-Rohani, Masoud

2003-01-01

This report discusses the development and application of two alternative strategies in the form of global and sequential local response surface (RS) techniques for the solution of reliability-based optimization (RBO) problems. The problem of a thin-walled composite circular cylinder under axial buckling instability is used as a demonstrative example. In this case, the global technique uses a single second-order RS model to estimate the axial buckling load over the entire feasible design space (FDS) whereas the local technique uses multiple first-order RS models with each applied to a small subregion of FDS. Alternative methods for the calculation of unknown coefficients in each RS model are explored prior to the solution of the optimization problem. The example RBO problem is formulated as a function of 23 uncorrelated random variables that include material properties, thickness and orientation angle of each ply, cylinder diameter and length, as well as the applied load. The mean values of the 8 ply thicknesses are treated as independent design variables. While the coefficients of variation of all random variables are held fixed, the standard deviations of ply thicknesses can vary during the optimization process as a result of changes in the design variables. The structural reliability analysis is based on the first-order reliability method with reliability index treated as the design constraint. In addition to the probabilistic sensitivity analysis of reliability index, the results of the RBO problem are presented for different combinations of cylinder length and diameter and laminate ply patterns. The two strategies are found to produce similar results in terms of accuracy with the sequential local RS technique having a considerably better computational efficiency.

Ovarian response to 150 µg corifollitropin alfa in a GnRH-antagonist multiple-dose protocol: a prospective cohort study.

PubMed

Lerman, Tamara; Depenbusch, Marion; Schultze-Mosgau, Askan; von Otte, Soeren; Scheinhardt, Markus; Koenig, Inke; Kamischke, Axel; Macek, Milan; Schwennicke, Arne; Segerer, Sabine; Griesinger, Georg

2017-05-01

The incidence of low (<6 oocytes) and high (>18 oocytes) ovarian response to 150 µg corifollitropin alfa in relation to anti-Müllerian hormone (AMH) and other biomarkers was studied in a multi-centre (n = 5), multi-national, prospective, investigator-initiated, observational cohort study. Infertile women (n = 212), body weight >60 kg, underwent controlled ovarian stimulation in a gonadotrophin-releasing hormone-antagonist multiple-dose protocol. Demographic, sonographic and endocrine parameters were prospectively assessed on cycle day 2 or 3 of a spontaneous menstruation before the administration of 150 µg corifollitropin alfa. Serum AMH showed the best correlation with the number of oocytes obtained among all predictor variables. In receiver-operating characteristic analysis, AMH at a threshold of 0.91 ng/ml showed a sensitivity of 82.4%, specificity of 82.4%, positive predictive value 52.9%and negative predictive value 95.1% for predicting low response (area under the curve [AUC], 95% CI; P-value: 0.853, 0.769-0.936; <0.0001). For predicting high response, the optimal threshold for AMH was 2.58 ng/ml, relating to a sensitivity of 80.0%, specificity 82.1%, positive predictive value 42.5% and negative predictive value 96.1% (AUC, 95% CI; P-value: 0.871, 0.787-0.955; <0.0001). In conclusion, patients with serum AMH concentrations between approximately 0.9 and 2.6 ng/ml were unlikely to show extremes of response. Copyright © 2017. Published by Elsevier Ltd.

Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib

PubMed Central

Sobotta, Svantje; Raue, Andreas; Huang, Xiaoyun; Vanlier, Joep; Jünger, Anja; Bohl, Sebastian; Albrecht, Ute; Hahnel, Maximilian J.; Wolf, Stephanie; Mueller, Nikola S.; D'Alessandro, Lorenza A.; Mueller-Bohl, Stephanie; Boehm, Martin E.; Lucarelli, Philippe; Bonefas, Sandra; Damm, Georg; Seehofer, Daniel; Lehmann, Wolf D.; Rose-John, Stefan; van der Hoeven, Frank; Gretz, Norbert; Theis, Fabian J.; Ehlting, Christian; Bode, Johannes G.; Timmer, Jens; Schilling, Marcel; Klingmüller, Ursula

2017-01-01

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines. PMID:29062282

Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib.

PubMed

Sobotta, Svantje; Raue, Andreas; Huang, Xiaoyun; Vanlier, Joep; Jünger, Anja; Bohl, Sebastian; Albrecht, Ute; Hahnel, Maximilian J; Wolf, Stephanie; Mueller, Nikola S; D'Alessandro, Lorenza A; Mueller-Bohl, Stephanie; Boehm, Martin E; Lucarelli, Philippe; Bonefas, Sandra; Damm, Georg; Seehofer, Daniel; Lehmann, Wolf D; Rose-John, Stefan; van der Hoeven, Frank; Gretz, Norbert; Theis, Fabian J; Ehlting, Christian; Bode, Johannes G; Timmer, Jens; Schilling, Marcel; Klingmüller, Ursula

2017-01-01

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines.

Distributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor tasks.

PubMed

Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Ferrigno, Giancarlo; D'Angelo, Egidio; Pedrocchi, Alessandra

2015-01-01

The cerebellum plays a crucial role in motor learning and it acts as a predictive controller. Modeling it and embedding it into sensorimotor tasks allows us to create functional links between plasticity mechanisms, neural circuits and behavioral learning. Moreover, if applied to real-time control of a neurorobot, the cerebellar model has to deal with a real noisy and changing environment, thus showing its robustness and effectiveness in learning. A biologically inspired cerebellar model with distributed plasticity, both at cortical and nuclear sites, has been used. Two cerebellum-mediated paradigms have been designed: an associative Pavlovian task and a vestibulo-ocular reflex, with multiple sessions of acquisition and extinction and with different stimuli and perturbation patterns. The cerebellar controller succeeded to generate conditioned responses and finely tuned eye movement compensation, thus reproducing human-like behaviors. Through a productive plasticity transfer from cortical to nuclear sites, the distributed cerebellar controller showed in both tasks the capability to optimize learning on multiple time-scales, to store motor memory and to effectively adapt to dynamic ranges of stimuli.

Enhanced entrainability of genetic oscillators by period mismatch

PubMed Central

Hasegawa, Yoshihiko; Arita, Masanori

2013-01-01

Biological oscillators coordinate individual cellular components so that they function coherently and collectively. They are typically composed of multiple feedback loops, and period mismatch is unavoidable in biological implementations. We investigated the advantageous effect of this period mismatch in terms of a synchronization response to external stimuli. Specifically, we considered two fundamental models of genetic circuits: smooth and relaxation oscillators. Using phase reduction and Floquet multipliers, we numerically analysed their entrainability under different coupling strengths and period ratios. We found that a period mismatch induces better entrainment in both types of oscillator; the enhancement occurs in the vicinity of the bifurcation on their limit cycles. In the smooth oscillator, the optimal period ratio for the enhancement coincides with the experimentally observed ratio, which suggests biological exploitation of the period mismatch. Although the origin of multiple feedback loops is often explained as a passive mechanism to ensure robustness against perturbation, we study the active benefits of the period mismatch, which include increasing the efficiency of the genetic oscillators. Our findings show a qualitatively different perspective for both the inherent advantages of multiple loops and their essentiality. PMID:23389900

Multicomponent pre-stack seismic waveform inversion in transversely isotropic media using a non-dominated sorting genetic algorithm

NASA Astrophysics Data System (ADS)

Padhi, Amit; Mallick, Subhashis

2014-03-01

Inversion of band- and offset-limited single component (P wave) seismic data does not provide robust estimates of subsurface elastic parameters and density. Multicomponent seismic data can, in principle, circumvent this limitation but adds to the complexity of the inversion algorithm because it requires simultaneous optimization of multiple objective functions, one for each data component. In seismology, these multiple objectives are typically handled by constructing a single objective given as a weighted sum of the objectives of individual data components and sometimes with additional regularization terms reflecting their interdependence; which is then followed by a single objective optimization. Multi-objective problems, inclusive of the multicomponent seismic inversion are however non-linear. They have non-unique solutions, known as the Pareto-optimal solutions. Therefore, casting such problems as a single objective optimization provides one out of the entire set of the Pareto-optimal solutions, which in turn, may be biased by the choice of the weights. To handle multiple objectives, it is thus appropriate to treat the objective as a vector and simultaneously optimize each of its components so that the entire Pareto-optimal set of solutions could be estimated. This paper proposes such a novel multi-objective methodology using a non-dominated sorting genetic algorithm for waveform inversion of multicomponent seismic data. The applicability of the method is demonstrated using synthetic data generated from multilayer models based on a real well log. We document that the proposed method can reliably extract subsurface elastic parameters and density from multicomponent seismic data both when the subsurface is considered isotropic and transversely isotropic with a vertical symmetry axis. We also compute approximate uncertainty values in the derived parameters. Although we restrict our inversion applications to horizontally stratified models, we outline a practical procedure of extending the method to approximately include local dips for each source-receiver offset pair. Finally, the applicability of the proposed method is not just limited to seismic inversion but it could be used to invert different data types not only requiring multiple objectives but also multiple physics to describe them.

Pareto fronts for multiobjective optimization design on materials data

NASA Astrophysics Data System (ADS)

Gopakumar, Abhijith; Balachandran, Prasanna; Gubernatis, James E.; Lookman, Turab

Optimizing multiple properties simultaneously is vital in materials design. Here we apply infor- mation driven, statistical optimization strategies blended with machine learning methods, to address multi-objective optimization tasks on materials data. These strategies aim to find the Pareto front consisting of non-dominated data points from a set of candidate compounds with known character- istics. The objective is to find the pareto front in as few additional measurements or calculations as possible. We show how exploration of the data space to find the front is achieved by using uncer- tainties in predictions from regression models. We test our proposed design strategies on multiple, independent data sets including those from computations as well as experiments. These include data sets for Max phases, piezoelectrics and multicomponent alloys.

Achieving patient engagement in multiple sclerosis: A perspective from the multiple sclerosis in the 21st Century Steering Group.

PubMed

Rieckmann, Peter; Boyko, Alexey; Centonze, Diego; Elovaara, Irina; Giovannoni, Gavin; Havrdová, Eva; Hommes, Otto; Kesselring, Jurg; Kobelt, Gisela; Langdon, Dawn; LeLorier, Jacques; Morrow, Sarah A; Oreja-Guevara, Celia; Schippling, Sven; Thalheim, Christoph; Thompson, Heidi; Vermersch, Patrick

2015-05-01

While advances in medicine, technology and healthcare services offer promises of longevity and improved quality of life (QoL), there is also increasing reliance on a patient׳s skills and motivation to optimize all the benefits available. Patient engagement in their own healthcare has been described as the 'blockbuster drug of the century'. In multiple sclerosis (MS), patient engagement is vital if outcomes for the patient, society and healthcare systems are to be optimized. The MS in the 21st Century Steering Group devised a set of themes that require action with regard to patient engagement in MS, namely: 1) setting and facilitating engagement by education and confidence-building; 2) increasing the importance placed on QoL and patient concerns through patient-reported outcomes (PROs); 3) providing credible sources of accurate information; 4) encouraging treatment adherence through engagement; and 5) empowering through a sense of responsibility. Group members independently researched and contributed examples of patient engagement strategies from several countries and examined interventions that have worked well in areas of patient engagement in MS, and other chronic illnesses. The group presents their perspective on these programs, discusses the barriers to achieving patient engagement, and suggests practical strategies for overcoming these barriers. With an understanding of the issues that influence patient engagement in MS, we can start to investigate ways to enhance engagement and subsequent health outcomes. Engaging patients involves a broad, multidisciplinary approach. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Immuno-oncology Clinical Trial Design: Limitations, Challenges, and Opportunities

PubMed Central

Baik, Christina S.; Rubin, Eric H.; Forde, Patrick M.; Mehnert, Janice M.; Collyar, Deborah; Butler, Marcus O.; Dixon, Erica L.; Chow, Laura Q.M.

2017-01-01

Recent advances in immuno-oncology and regulatory approvals have been rapid and paradigm shifting in many difficult-to-treat malignancies. Despite immune checkpoint inhibitor therapy becoming the standard of care across multiple tumor types, there are many unanswered questions that need to be addressed before this therapeutic modality can be fully harnessed. Areas of limitations include treatment of patients not sufficiently represented in clinical trials, uncertainty of the optimal treatment dosing and duration, and lack of understanding regarding long-term immune related toxicities and atypical tumor responses. Patients such as those with autoimmune disease, chronic viral infections, limited performance status, and brain metastases were often excluded from initial trials due to concerns of safety. However, limited data suggest that some of these patients can benefit from therapy with manageable toxicities; thus, future studies should incorporate these patients to clearly define safety and efficacy. There are still controversies regarding the optimal dosing strategy that can vary from weight-based to flat dosing, with undefined treatment duration. Further elucidation of the optimal dosing approach and evaluation of predictive biomarkers should be incorporated in the design of future trials. Finally, there are long-term immune-mediated toxicities, atypical tumor responses such as pseudoprogression and endpoints unique to immuno-oncology that are not adequately captured by traditional trial designs; thus, novel study designs are needed. In this article, we discuss in detail the above challenges and propose needed areas of research for exploration and incorporation in the next generation of immuno-oncology clinical trials. PMID:28864727

A randomized controlled trial investigating the use of a predictive nomogram for the selection of the FSH starting dose in IVF/ICSI cycles.

PubMed

Allegra, Adolfo; Marino, Angelo; Volpes, Aldo; Coffaro, Francesco; Scaglione, Piero; Gullo, Salvatore; La Marca, Antonio

2017-04-01

The number of oocytes retrieved is a relevant intermediate outcome in women undergoing IVF/intracytoplasmic sperm injection (ICSI). This trial compared the efficiency of the selection of the FSH starting dose according to a nomogram based on multiple biomarkers (age, day 3 FSH, anti-Müllerian hormone) versus an age-based strategy. The primary outcome measure was the proportion of women with an optimal number of retrieved oocytes defined as 8-14. At their first IVF/ICSI cycle, 191 patients underwent a long gonadotrophin-releasing hormone agonist protocol and were randomized to receive a starting dose of recombinant (human) FSH, based on their age (150 IU if ≤35 years, 225 IU if >35 years) or based on the nomogram. Optimal response was observed in 58/92 patients (63%) in the nomogram group and in 42/99 (42%) in the control group (+21%, 95% CI = 0.07 to 0.35, P = 0.0037). No significant differences were found in the clinical pregnancy rate or the number of embryos cryopreserved per patient. The study showed that the FSH starting dose selected according to ovarian reserve is associated with an increase in the proportion of patients with an optimal response: large trials are recommended to investigate any possible effect on the live-birth rate. Copyright © 2017 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Small Changes: Using Assessment to Direct Instructional Practices in Large-Enrollment Biochemistry Courses

PubMed Central

Xu, Xiaoying; Lewis, Jennifer E.; Loertscher, Jennifer; Minderhout, Vicky; Tienson, Heather L.

2017-01-01

Multiple-choice assessments provide a straightforward way for instructors of large classes to collect data related to student understanding of key concepts at the beginning and end of a course. By tracking student performance over time, instructors receive formative feedback about their teaching and can assess the impact of instructional changes. The evidence of instructional effectiveness can in turn inform future instruction, and vice versa. In this study, we analyzed student responses on an optimized pretest and posttest administered during four different quarters in a large-enrollment biochemistry course. Student performance and the effect of instructional interventions related to three fundamental concepts—hydrogen bonding, bond energy, and pKa—were analyzed. After instructional interventions, a larger proportion of students demonstrated knowledge of these concepts compared with data collected before instructional interventions. Student responses trended from inconsistent to consistent and from incorrect to correct. The instructional effect was particularly remarkable for the later three quarters related to hydrogen bonding and bond energy. This study supports the use of multiple-choice instruments to assess the effectiveness of instructional interventions, especially in large classes, by providing instructors with quick and reliable feedback on student knowledge of each specific fundamental concept. PMID:28188280

Dynamic load mitigation using dissipative elastic metamaterials with multiple Maxwell-type oscillators

NASA Astrophysics Data System (ADS)

Alamri, Sagr; Li, Bing; Tan, K. T.

2018-03-01

Dissipative elastic metamaterials have attracted increased attention in recent times. This paper presents the development of a dissipative elastic metamaterial with multiple Maxwell-type resonators for stress wave attenuation. The mechanism of the dissipation effect on the vibration characteristics is systematically investigated by mass-spring-damper models with single and dual resonators. Based on the parameter optimization, it is revealed that a broadband wave attenuation region (stopping band) can be obtained by properly utilizing interactions from resonant motions and viscoelastic effects of the Maxwell-type oscillators. The relevant numerical verifications are conducted for various cases, and excellent agreement between the numerical and theoretical frequency response functions is shown. The design of this dissipative metamaterial system is further applied for dynamic load mitigation and blast wave attenuation. Moreover, the transient response in the continuum model is designed and analyzed for more robust design. By virtue of the bandgap merging effect induced by the Maxwell-type damper, the transient blast wave can be almost completely suppressed in the low frequency range. A significantly improved performance of the proposed dissipative metamaterials for stress wave mitigation is verified in both time and frequency domains.

Structural biology contributions to the discovery of drugs to treat chronic myelogenous leukaemia

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

Cowan-Jacob, Sandra W., E-mail: sandra.jacob@novartis.com; Fendrich, Gabriele; Floersheimer, Andreas

2007-01-01

A case study showing how the determination of multiple cocrystal structures of the protein tyrosine kinase c-Abl was used to support drug discovery, resulting in a compound effective in the treatment of chronic myelogenous leukaemia. Chronic myelogenous leukaemia (CML) results from the Bcr-Abl oncoprotein, which has a constitutively activated Abl tyrosine kinase domain. Although most chronic phase CML patients treated with imatinib as first-line therapy maintain excellent durable responses, patients who have progressed to advanced-stage CML frequently fail to respond or lose their response to therapy owing to the emergence of drug-resistant mutants of the protein. More than 40 suchmore » point mutations have been observed in imatinib-resistant patients. The crystal structures of wild-type and mutant Abl kinase in complex with imatinib and other small-molecule Abl inhibitors were determined, with the aim of understanding the molecular basis of resistance and to aid in the design and optimization of inhibitors active against the resistance mutants. These results are presented in a way which illustrates the approaches used to generate multiple structures, the type of information that can be gained and the way that this information is used to support drug discovery.« less

Dynamic fuzzy modeling of storm water infiltration in urban fractured aquifers

USGS Publications Warehouse

Hong, Y.-S.; Rosen, Michael R.; Reeves, R.R.

2002-01-01

In an urban fractured-rock aquifer in the Mt. Eden area of Auckland, New Zealand, disposal of storm water is via "soakholes" drilled directly into the top of the fractured basalt rock. The dynamic response of the groundwater level due to the storm water infiltration shows characteristics of a strongly time-varying system. A dynamic fuzzy modeling approach, which is based on multiple local models that are weighted using fuzzy membership functions, has been developed to identify and predict groundwater level fluctuations caused by storm water infiltration. The dynamic fuzzy model is initialized by the fuzzy clustering algorithm and optimized by the gradient-descent algorithm in order to effectively derive the multiple local models-each of which is associated with a locally valid model that represents the groundwater level state as a response to different intensities of rainfall events. The results have shown that even if the number of fuzzy local models derived is small, the fuzzy modeling approach developed provides good prediction results despite the highly time-varying nature of this urban fractured-rock aquifer system. Further, it allows interpretable representations of the dynamic behavior of the groundwater system due to storm water infiltration.

Monitoring simultaneous photocatalytic-ozonation of mixture of pharmaceuticals in the presence of immobilized TiO2 nanoparticles using MCR-ALS: Identification of intermediates and multi-response optimization approach

NASA Astrophysics Data System (ADS)

Fathinia, Mehrangiz; Khataee, Alireza; Naseri, Abdolhosein; Aber, Soheil

2015-02-01

The present study has focused on the degradation of a mixture of three pharmaceuticals, i.e. methyldopa (MDP), nalidixic acid (NAD) and famotidine (FAM) which were quantified simultaneously during photocatalytic-ozonation process. The experiments were conducted in a semi-batch reactor where TiO2 nanoparticles (crystallites mean size 8 nm) were immobilized on ceramic plates irradiated by UV-A light in the proximity of oxygen and/or ozone. The surface morphology and roughness of the bare and TiO2-coated ceramic plates were analyzed using scanning electron microscopy (SEM) and atomic force microscopy (AFM). An analytical methodology was successfully developed based on both recording ultraviolet-visible (UV-Vis) spectra during the degradation process and a data analysis using multivariate curve resolution with alternating least squares (MCR-ALS). This methodology enabled the researchers to obtain the concentration and spectral profiles of the chemical compounds which were involved in the process. A central composite design was used to study the effect of several factors on multiple responses namely MDP removal (Y1), NAD removal (Y2) and FAM removal (Y3) in the simultaneous photocatalytic-ozonation of these pharmaceuticals. A multi-response optimization procedure based on global desirability of the factors was used to simultaneously maximize Y1, Y2 and Y3. The results of the global desirability revealed that 8 mg/L MAD, 8 mg/L NAD, 8 mg/L FAM, 6 L/h ozone flow rate and a 30 min-reaction time were the best conditions under which the optimized values of various responses were Y1 = 95.03%, Y2 = 84.93% and Y3 = 99.15%. Also, the intermediate products of pharmaceuticals generated in the photocatalytic-ozonation process were identified by gas chromatography coupled to mass spectrometry.

Perceived Parenting Styles on College Students' Optimism

ERIC Educational Resources Information Center

Baldwin, Debora R.; McIntyre, Anne; Hardaway, Elizabeth

2007-01-01

The purpose of this study was to examine the relationship between perceived parenting styles and levels of optimism in undergraduate college students. Sixty-three participants were administered surveys measuring dispositional optimism and perceived parental Authoritative and Authoritarian styles. Multiple regression analysis revealed that both…

Impact of treatment heterogeneity on drug resistance and supply chain costs☆

PubMed Central

Spiliotopoulou, Eirini; Boni, Maciej F.; Yadav, Prashant

2013-01-01

The efficacy of scarce drugs for many infectious diseases is threatened by the emergence and spread of resistance. Multiple studies show that available drugs should be used in a socially optimal way to contain drug resistance. This paper studies the tradeoff between risk of drug resistance and operational costs when using multiple drugs for a specific disease. Using a model for disease transmission and resistance spread, we show that treatment with multiple drugs, on a population level, results in better resistance-related health outcomes, but more interestingly, the marginal benefit decreases as the number of drugs used increases. We compare this benefit with the corresponding change in procurement and safety stock holding costs that result from higher drug variety in the supply chain. Using a large-scale simulation based on malaria transmission dynamics, we show that disease prevalence seems to be a less important factor when deciding the optimal width of drug assortment, compared to the duration of one episode of the disease and the price of the drug(s) used. Our analysis shows that under a wide variety of scenarios for disease prevalence and drug cost, it is optimal to simultaneously deploy multiple drugs in the population. If the drug price is high, large volume purchasing discounts are available, and disease prevalence is high, it may be optimal to use only one drug. Our model lends insights to policy makers into the socially optimal size of drug assortment for a given context. PMID:25843982

Impact of treatment heterogeneity on drug resistance and supply chain costs.

PubMed

Spiliotopoulou, Eirini; Boni, Maciej F; Yadav, Prashant

2013-09-01

The efficacy of scarce drugs for many infectious diseases is threatened by the emergence and spread of resistance. Multiple studies show that available drugs should be used in a socially optimal way to contain drug resistance. This paper studies the tradeoff between risk of drug resistance and operational costs when using multiple drugs for a specific disease. Using a model for disease transmission and resistance spread, we show that treatment with multiple drugs, on a population level, results in better resistance-related health outcomes, but more interestingly, the marginal benefit decreases as the number of drugs used increases. We compare this benefit with the corresponding change in procurement and safety stock holding costs that result from higher drug variety in the supply chain. Using a large-scale simulation based on malaria transmission dynamics, we show that disease prevalence seems to be a less important factor when deciding the optimal width of drug assortment, compared to the duration of one episode of the disease and the price of the drug(s) used. Our analysis shows that under a wide variety of scenarios for disease prevalence and drug cost, it is optimal to simultaneously deploy multiple drugs in the population. If the drug price is high, large volume purchasing discounts are available, and disease prevalence is high, it may be optimal to use only one drug. Our model lends insights to policy makers into the socially optimal size of drug assortment for a given context.

Swarm intelligence in bioinformatics: methods and implementations for discovering patterns of multiple sequences.

PubMed

Cui, Zhihua; Zhang, Yi

2014-02-01

As a promising and innovative research field, bioinformatics has attracted increasing attention recently. Beneath the enormous number of open problems in this field, one fundamental issue is about the accurate and efficient computational methodology that can deal with tremendous amounts of data. In this paper, we survey some applications of swarm intelligence to discover patterns of multiple sequences. To provide a deep insight, ant colony optimization, particle swarm optimization, artificial bee colony and artificial fish swarm algorithm are selected, and their applications to multiple sequence alignment and motif detecting problem are discussed.

Resolving the multiple sequence alignment problem using biogeography-based optimization with multiple populations.

PubMed

Zemali, El-Amine; Boukra, Abdelmadjid

2015-08-01

The multiple sequence alignment (MSA) is one of the most challenging problems in bioinformatics, it involves discovering similarity between a set of protein or DNA sequences. This paper introduces a new method for the MSA problem called biogeography-based optimization with multiple populations (BBOMP). It is based on a recent metaheuristic inspired from the mathematics of biogeography named biogeography-based optimization (BBO). To improve the exploration ability of BBO, we have introduced a new concept allowing better exploration of the search space. It consists of manipulating multiple populations having each one its own parameters. These parameters are used to build up progressive alignments allowing more diversity. At each iteration, the best found solution is injected in each population. Moreover, to improve solution quality, six operators are defined. These operators are selected with a dynamic probability which changes according to the operators efficiency. In order to test proposed approach performance, we have considered a set of datasets from Balibase 2.0 and compared it with many recent algorithms such as GAPAM, MSA-GA, QEAMSA and RBT-GA. The results show that the proposed approach achieves better average score than the previously cited methods.

Design of helicopter rotor blades for optimum dynamic characteristics

NASA Technical Reports Server (NTRS)

Peters, D. A.; Ko, T.; Korn, A.; Rossow, M. P.

1984-01-01

The optimal design of helicopter rotor blades is addressed. The forced response of an initial (i.e., non-optimized) blade to those of a final (optimized) blade are compared. Response of starting design and optimal designs for varying forcing frequencies, blade response to harmonics of rotor speed, and derivation of mass and stiffness matrices or functions of natural frequencies are discussed.

Sustained response to standard dose osimertinib in a patient with plasma T790M-positive leptomeningeal metastases from primary lung adenocarcinoma.

PubMed

Chan, Oscar Siu-Hong; Leung, Warren Kam-Wing; Yeung, Rebecca Mei-Wan

2017-12-01

A 44-year-old male, never smoker, suffers from stage IV adenocarcinoma of the right lung with epidermal growth factor receptor (EGFR) exon-21 L858R point mutation on initial presentation. After 23 months of treatment with gefitinib, intercalated with multiple courses of radiotherapy, leptomeningeal metastases (LMs) developed. Acquired T790M mutation was confirmed by the droplet digital polymerase chain reaction plasma EGFR test. After switching to osimertinib at the standard dose, his neurocognitive function improved clinically, coupled with sustained radiological improvement. As this clinical entity is underrepresented in clinical trials, the practicability of plasma EGFR testing and the optimal dose-response relationship of osimertinib in T790M-positive lung cancer complicated with LM deserves further exploration. © 2017 John Wiley & Sons Australia, Ltd.

Penalized nonparametric scalar-on-function regression via principal coordinates

PubMed Central

Reiss, Philip T.; Miller, David L.; Wu, Pei-Shien; Hua, Wen-Yu

2016-01-01

A number of classical approaches to nonparametric regression have recently been extended to the case of functional predictors. This paper introduces a new method of this type, which extends intermediate-rank penalized smoothing to scalar-on-function regression. In the proposed method, which we call principal coordinate ridge regression, one regresses the response on leading principal coordinates defined by a relevant distance among the functional predictors, while applying a ridge penalty. Our publicly available implementation, based on generalized additive modeling software, allows for fast optimal tuning parameter selection and for extensions to multiple functional predictors, exponential family-valued responses, and mixed-effects models. In an application to signature verification data, principal coordinate ridge regression, with dynamic time warping distance used to define the principal coordinates, is shown to outperform a functional generalized linear model. PMID:29217963

Cytokines and the immune-neuroendocrine network: What did we learn from infection and autoimmunity?

PubMed

Correa, Silvia G; Maccioni, Mariana; Rivero, Virginia E; Iribarren, Pablo; Sotomayor, Claudia E; Riera, Clelia M

2007-01-01

The initial view of the neuroendocrine-immune communication as the brake of immune activation is changing. Recent evidence suggests that the optimization of the body's overall response to infection could be actually the role of the immune-endocrine network. In gradually more complex organisms, the multiplicity of host-pathogen interfaces forced the development of efficient and protective responses. Molecules such as cytokines and Toll-like receptors (TLRs) are distributed both in the periphery and in the brain to participate in a coordinated adaptive function. When sustained release of inflammatory mediators occurs, as in autoimmune diseases, undesirable pathological consequences become evident with different manifestations and outcomes. Clearly, organisms are not well adapted to that disregulated condition yet, suggesting that additional partners within neuroendocrine-immune interactions might emerge from the evolutionary road.

Axonal Conduction Delays, Brain State, and Corticogeniculate Communication

PubMed Central

2017-01-01

Thalamocortical conduction times are short, but layer 6 corticothalamic axons display an enormous range of conduction times, some exceeding 40–50 ms. Here, we investigate (1) how axonal conduction times of corticogeniculate (CG) neurons are related to the visual information conveyed to the thalamus, and (2) how alert versus nonalert awake brain states affect visual processing across the spectrum of CG conduction times. In awake female Dutch-Belted rabbits, we found 58% of CG neurons to be visually responsive, and 42% to be unresponsive. All responsive CG neurons had simple, orientation-selective receptive fields, and generated sustained responses to stationary stimuli. CG axonal conduction times were strongly related to modulated firing rates (F1 values) generated by drifting grating stimuli, and their associated interspike interval distributions, suggesting a continuum of visual responsiveness spanning the spectrum of axonal conduction times. CG conduction times were also significantly related to visual response latency, contrast sensitivity (C-50 values), directional selectivity, and optimal stimulus velocity. Increasing alertness did not cause visually unresponsive CG neurons to become responsive and did not change the response linearity (F1/F0 ratios) of visually responsive CG neurons. However, for visually responsive CG neurons, increased alertness nearly doubled the modulated response amplitude to optimal visual stimulation (F1 values), significantly shortened response latency, and dramatically increased response reliability. These effects of alertness were uniform across the broad spectrum of CG axonal conduction times. SIGNIFICANCE STATEMENT Corticothalamic neurons of layer 6 send a dense feedback projection to thalamic nuclei that provide input to sensory neocortex. While sensory information reaches the cortex after brief thalamocortical axonal delays, corticothalamic axons can exhibit conduction delays of <2 ms to 40–50 ms. Here, in the corticogeniculate visual system of awake rabbits, we investigate the functional significance of this axonal diversity, and the effects of shifting alert/nonalert brain states on corticogeniculate processing. We show that axonal conduction times are strongly related to multiple visual response properties, suggesting a continuum of visual responsiveness spanning the spectrum of corticogeniculate axonal conduction times. We also show that transitions between awake brain states powerfully affect corticogeniculate processing, in some ways more strongly than in layer 4. PMID:28559382

Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis.

PubMed

Haque, Shafiul; Khan, Saif; Wahid, Mohd; Dar, Sajad A; Soni, Nipunjot; Mandal, Raju K; Singh, Vineeta; Tiwari, Dileep; Lohani, Mohtashim; Areeshi, Mohammed Y; Govender, Thavendran; Kruger, Hendrik G; Jawed, Arshad

2016-01-01

For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD 600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD 600 nm ): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties.

Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis

PubMed Central

Haque, Shafiul; Khan, Saif; Wahid, Mohd; Dar, Sajad A.; Soni, Nipunjot; Mandal, Raju K.; Singh, Vineeta; Tiwari, Dileep; Lohani, Mohtashim; Areeshi, Mohammed Y.; Govender, Thavendran; Kruger, Hendrik G.; Jawed, Arshad

2016-01-01

For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD600 nm): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties. PMID:27920762

The Clustering of Lifestyle Behaviours in New Zealand and their Relationship with Optimal Wellbeing.

PubMed

Prendergast, Kate B; Mackay, Lisa M; Schofield, Grant M

2016-10-01

The purpose of this research was to determine (1) associations between multiple lifestyle behaviours and optimal wellbeing and (2) the extent to which five lifestyle behaviours-sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake-cluster in a national sample. A national sample of New Zealand adults participated in a web-based wellbeing survey. Five lifestyle behaviours-sleep, physical activity, sedentary behaviour, sugary drink consumption, and fruit and vegetable intake-were dichotomised into healthy (meets recommendations) and unhealthy (does not meet recommendations) categories. Optimal wellbeing was calculated using a multi-dimensional flourishing scale, and binary logistic regression analysis was used to calculate the relationship between multiple healthy behaviours and optimal wellbeing. Clustering was examined by comparing the observed and expected prevalence rates (O/E) of healthy and unhealthy two-, three-, four-, and five-behaviour combinations. Data from 9425 participants show those engaging in four to five healthy behaviours (23 %) were 4.7 (95 % confidence interval (CI) 3.8-5.7) times more likely to achieve optimal wellbeing compared to those engaging in zero to one healthy behaviour (21 %). Clustering was observed for healthy (5 %, O/E 2.0, 95 % CI 1.8-2.2) and unhealthy (5 %, O/E 2.1, 95 % CI 1.9-2.3) five-behaviour combinations and for four- and three-behaviour combinations. At the two-behaviour level, healthy fruit and vegetable intake clustered with all behaviours, except sleep which did not cluster with any behaviour. Multiple lifestyle behaviours were positively associated with optimal wellbeing. The results show lifestyle behaviours cluster, providing support for multiple behaviour lifestyle-based interventions for optimising wellbeing.

Application of response surface techniques to helicopter rotor blade optimization procedure

NASA Technical Reports Server (NTRS)

Henderson, Joseph Lynn; Walsh, Joanne L.; Young, Katherine C.

1995-01-01

In multidisciplinary optimization problems, response surface techniques can be used to replace the complex analyses that define the objective function and/or constraints with simple functions, typically polynomials. In this work a response surface is applied to the design optimization of a helicopter rotor blade. In previous work, this problem has been formulated with a multilevel approach. Here, the response surface takes advantage of this decomposition and is used to replace the lower level, a structural optimization of the blade. Problems that were encountered and important considerations in applying the response surface are discussed. Preliminary results are also presented that illustrate the benefits of using the response surface.

Enhanced Response Time of Electrowetting Lenses with Shaped Input Voltage Functions.

PubMed

Supekar, Omkar D; Zohrabi, Mo; Gopinath, Juliet T; Bright, Victor M

2017-05-16

Adaptive optical lenses based on the electrowetting principle are being rapidly implemented in many applications, such as microscopy, remote sensing, displays, and optical communication. To characterize the response of these electrowetting lenses, the dependence upon direct current (DC) driving voltage functions was investigated in a low-viscosity liquid system. Cylindrical lenses with inner diameters of 2.45 and 3.95 mm were used to characterize the dynamic behavior of the liquids under DC voltage electrowetting actuation. With the increase of the rise time of the input exponential driving voltage, the originally underdamped system response can be damped, enabling a smooth response from the lens. We experimentally determined the optimal rise times for the fastest response from the lenses. We have also performed numerical simulations of the lens actuation with input exponential driving voltage to understand the variation in the dynamics of the liquid-liquid interface with various input rise times. We further enhanced the response time of the devices by shaping the input voltage function with multiple exponential rise times. For the 3.95 mm inner diameter lens, we achieved a response time improvement of 29% when compared to the fastest response obtained using single-exponential driving voltage. The technique shows great promise for applications that require fast response times.

Effects of systemic glutamatergic manipulations on conditioned eyeblink responses and hyperarousal in a rabbit model of post-traumatic stress disorder.

PubMed

Burhans, Lauren B; Smith-Bell, Carrie A; Schreurs, Bernard G

2017-10-01

Glutamatergic dysfunction is implicated in many neuropsychiatric conditions, including post-traumatic stress disorder (PTSD). Glutamate antagonists have shown some utility in treating PTSD symptoms, whereas glutamate agonists may facilitate cognitive behavioral therapy outcomes. We have developed an animal model of PTSD, based on conditioning of the rabbit's eyeblink response, that addresses two key features: conditioned responses (CRs) to cues associated with an aversive event and a form of conditioned hyperarousal referred to as conditioning-specific reflex modification (CRM). The optimal treatment to reduce both CRs and CRM is unpaired extinction. The goals of the study were to examine whether treatment with the N-methyl-D-aspartate glutamate receptor antagonist ketamine could reduce CRs and CRM, and whether the N-methyl-D-aspartate agonist D-cycloserine combined with unpaired extinction treatment could enhance the extinction of both. Administration of a single dose of subanesthetic ketamine had no significant immediate or delayed effect on CRs or CRM. Combining D-cycloserine with a single day of unpaired extinction facilitated extinction of CRs in the short term while having no impact on CRM. These results caution that treatments may improve one aspect of the PTSD symptomology while having no significant effects on other symptoms, stressing the importance of a multiple-treatment approach to PTSD and of animal models that address multiple symptoms.

Optimal Sensor Allocation for Fault Detection and Isolation

NASA Technical Reports Server (NTRS)

Azam, Mohammad; Pattipati, Krishna; Patterson-Hine, Ann

2004-01-01

Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

MIDACO on MINLP space applications

NASA Astrophysics Data System (ADS)

Schlueter, Martin; Erb, Sven O.; Gerdts, Matthias; Kemble, Stephen; Rückmann, Jan-J.

2013-04-01

A numerical study on two challenging mixed-integer non-linear programming (MINLP) space applications and their optimization with MIDACO, a recently developed general purpose optimization software, is presented. These applications are the optimal control of the ascent of a multiple-stage space launch vehicle and the space mission trajectory design from Earth to Jupiter using multiple gravity assists. Additionally, an NLP aerospace application, the optimal control of an F8 aircraft manoeuvre, is discussed and solved. In order to enhance the optimization performance of MIDACO a hybridization technique, coupling MIDACO with an SQP algorithm, is presented for two of these three applications. The numerical results show, that the applications can be solved to their best known solution (or even new best solution) in a reasonable time by the considered approach. Since using the concept of MINLP is still a novelty in the field of (aero)space engineering, the demonstrated capabilities are seen as very promising.

Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming.

PubMed

Ren, Jingzheng; Dong, Liang; Sun, Lu; Goodsite, Michael Evan; Tan, Shiyu; Dong, Lichun

2015-01-01

The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties. Copyright © 2015 Elsevier Ltd. All rights reserved.

ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

PubMed Central

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

Optimization of Microwave-Assisted Extraction Conditions for Five Major Bioactive Compounds from Flos Sophorae Immaturus (Cultivars of Sophora japonica L.) Using Response Surface Methodology.

PubMed

Liu, Jin-Liang; Li, Long-Yun; He, Guang-Hua

2016-03-02

Microwave-assisted extraction was applied to extract rutin; quercetin; genistein; kaempferol; and isorhamnetin from Flos Sophorae Immaturus. Six independent variables; namely; solvent type; particle size; extraction frequency; liquid-to-solid ratio; microwave power; and extraction time were examined. Response surface methodology using a central composite design was employed to optimize experimental conditions (liquid-to-solid ratio; microwave power; and extraction time) based on the results of single factor tests to extract the five major components in Flos Sophorae Immaturus. Experimental data were fitted to a second-order polynomial equation using multiple regression analysis. Data were also analyzed using appropriate statistical methods. Optimal extraction conditions were as follows: extraction solvent; 100% methanol; particle size; 100 mesh; extraction frequency; 1; liquid-to-solid ratio; 50:1; microwave power; 287 W; and extraction time; 80 s. A rapid and sensitive ultra-high performance liquid chromatography method coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry (EIS-Q-TOF MS/MS) was developed and validated for the simultaneous determination of rutin; quercetin; genistein; kaempferol; and isorhamnetin in Flos Sophorae Immaturus. Chromatographic separation was accomplished on a Kinetex C18 column (100 mm × 2.1 mm; 2.6 μm) at 40 °C within 5 min. The mobile phase consisted of 0.1% aqueous formic acid and acetonitrile (71:29; v/v). Isocratic elution was carried out at a flow rate of 0.35 mL/min. The constituents of Flos Sophorae Immaturus were simultaneously identified by EIS-Q-TOF MS/MS in multiple reaction monitoring mode. During quantitative analysis; all of the calibration curves showed good linear relationships (R² > 0.999) within the tested ranges; and mean recoveries ranged from 96.0216% to 101.0601%. The precision determined through intra- and inter-day studies showed an RSD% of <2.833%. These results demonstrate that the developed method is accurate and effective and could be readily utilized for the comprehensive quality control of Flos Sophorae Immaturus.

Maximize, minimize or target - optimization for a fitted response from a designed experiment

DOE PAGES

Anderson-Cook, Christine Michaela; Cao, Yongtao; Lu, Lu

2016-04-01

One of the common goals of running and analyzing a designed experiment is to find a location in the design space that optimizes the response of interest. Depending on the goal of the experiment, we may seek to maximize or minimize the response, or set the process to hit a particular target value. After the designed experiment, a response model is fitted and the optimal settings of the input factors are obtained based on the estimated response model. Furthermore, the suggested optimal settings of the input factors are then used in the production environment.

Factors affecting synchronization and conception rate after the Ovsynch protocol in lactating Holstein cows.

PubMed

Galvão, K N; Santos, J E P

2010-06-01

Objectives were to evaluate risk factors affecting ovulatory responses and conception rate to the Ovsynch protocol. Holstein cows, 466, were submitted to the Ovsynch protocol [day 0, GnRH-1; day 7, prostaglandin (PG) F(2alpha); day 9, GnRH-2] and 103 cows were inseminated 12 h after GnRH-2. Information on parity, days in milk at GnRH-1, body condition, milk yield, exposure to heat stress, pre-synchronization with PGF(2alpha) and the use of progesterone insert from GnRH-1 to PGF(2alpha) was collected. Ovaries were scanned to determine responses to treatments. Overall, 54.7%, 10.6%, 2.2%, 81.1%, 9.0%, 91.5% and 36.9% of the cows ovulated to GnRH-1, multiple ovulated to GnRH-1, ovulated before GnRH-2, ovulated to GnRH-2, multiple ovulated to GnRH-2, experienced corpus luteum (CL) regression and conceived, respectively. Ovulation to GnRH-1 was greater in cows without a CL at GnRH-1, cows with follicles >19 mm and cows not pre-synchronized with PGF(2alpha) 14 days before GnRH-1. Multiple ovulations to GnRH-1 increased in cows without CL at GnRH-1 and cows with follicles < or =19 mm at GnRH-1. Ovulation before GnRH-2 was greater in cows without CL at PGF(2alpha). Ovulation to GnRH-2 increased in cows that received a progesterone insert, cows with a CL at GnRH-1, cows with follicles not regressing from the PGF(2alpha) to GnRH-2, cows with larger follicles at GnRH-2, cows that ovulated to GnRH-1 and cows not pre-synchronized. Multiple ovulations after GnRH-2 increased in cows with no CL at GnRH-1, multiparous cows and cows that multiple ovulated to GnRH-1. Conception rate at 42 days after AI increased in cows with body condition score > 2.75 and cows that ovulated to GnRH-2. Strategies that optimize ovulation to GnRH-2, such as increased ovulation to GnRH-1, should improve response to the Ovsynch protocol.

Structural optimization of framed structures using generalized optimality criteria

NASA Technical Reports Server (NTRS)

Kolonay, R. M.; Venkayya, Vipperla B.; Tischler, V. A.; Canfield, R. A.

1989-01-01

The application of a generalized optimality criteria to framed structures is presented. The optimality conditions, Lagrangian multipliers, resizing algorithm, and scaling procedures are all represented as a function of the objective and constraint functions along with their respective gradients. The optimization of two plane frames under multiple loading conditions subject to stress, displacement, generalized stiffness, and side constraints is presented. These results are compared to those found by optimizing the frames using a nonlinear mathematical programming technique.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

PubMed Central

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Plasticity of floral longevity and floral display in the self-compatible biennial Sabatia angularis (Gentianaceae): untangling the role of multiple components of pollination.

PubMed

Spigler, Rachel B

2017-01-01

Plasticity of floral traits in response to pollination can enable plants to maximize opportunities for pollen import and export under poor pollination conditions, while minimizing costs under favourable ones. Both floral longevity and display are key traits influencing pollination. While pollination-induced flower wilting is widely documented, we lack an understanding of the multifactorial complexity of this response, including the influence of other pollination components, costs of extended longevity and subsequent impacts on floral display. Plasticity of floral longevity was experimentally evaluated in Sabatia angularis in response to multiple pollination factors: pollen addition, removal, and source (self, single-donor outcross, multiple-donor outcross) and timing of pollination. Effects of pollen quantity were further evaluated by exploiting variation in autonomous self-pollen deposition. Delayed pollination costs were tested comparing seed set from early versus late pollinations. Finally, I compared floral display metrics (peak floral display, time to peak flower, flowering duration, mean flowering rate) between experimentally pollinated and control plants. Floral longevity was highly plastic in response to pollen addition and its timing, and the response was dose-dependent but insensitive to pollen source. Pollen removal tended to extend floral longevity, but only insofar as it precluded pollination-induced wilting via autonomous self-pollination. Under delayed pollination, the wilting response was faster and no cost was detected. Pollination further led to reduced peak floral displays and condensed flowering periods. Floral longevity and display plasticity could optimize fitness in S. angularis, a species prone to pollen limitation and high inbreeding depression. Under pollinator scarcity, extended floral longevities offer greater opportunities for pollen receipt and export at no cost to seed set, reproductive assurance via autonomous self-pollination and larger, more attractive floral displays. Under high pollinator availability, shortened longevities lead to smaller displays that should lower the risk of geitonogamy. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Optimization of Thick, Large Area YBCO Film Growth Through Response Surface Methods

NASA Astrophysics Data System (ADS)

Porzio, J.; Mahoney, C. H.; Sullivan, M. C.

2014-03-01

We present our work on the optimization of thick, large area YB2C3O7-δ (YBCO) film growth through response surface methods. Thick, large area films have commercial uses and have recently been used in dramatic demonstrations of levitation and suspension. Our films are grown via pulsed laser deposition and we have optimized growth parameters via response surface methods. Response surface methods is a statistical tool to optimize selected quantities with respect to a set of variables. We optimized our YBCO films' critical temperatures, thicknesses, and structures with respect to three PLD growth parameters: deposition temperature, laser energy, and deposition pressure. We will present an overview of YBCO growth via pulsed laser deposition, the statistical theory behind response surface methods, and the application of response surface methods to pulsed laser deposition growth of YBCO. Results from the experiment will be presented in a discussion of the optimized film quality. Supported by NFS grant DMR-1305637

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

NASA Astrophysics Data System (ADS)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis shows that terrestrial carbon and water cycle simulations in monsoon Asia were greatly improved, and the use of multiple satellite observations with this framework is an effective way for improving terrestrial biosphere models.

Limited-memory fast gradient descent method for graph regularized nonnegative matrix factorization.

PubMed

Guan, Naiyang; Wei, Lei; Luo, Zhigang; Tao, Dacheng

2013-01-01

Graph regularized nonnegative matrix factorization (GNMF) decomposes a nonnegative data matrix X[Symbol:see text]R(m x n) to the product of two lower-rank nonnegative factor matrices, i.e.,W[Symbol:see text]R(m x r) and H[Symbol:see text]R(r x n) (r < min {m,n}) and aims to preserve the local geometric structure of the dataset by minimizing squared Euclidean distance or Kullback-Leibler (KL) divergence between X and WH. The multiplicative update rule (MUR) is usually applied to optimize GNMF, but it suffers from the drawback of slow-convergence because it intrinsically advances one step along the rescaled negative gradient direction with a non-optimal step size. Recently, a multiple step-sizes fast gradient descent (MFGD) method has been proposed for optimizing NMF which accelerates MUR by searching the optimal step-size along the rescaled negative gradient direction with Newton's method. However, the computational cost of MFGD is high because 1) the high-dimensional Hessian matrix is dense and costs too much memory; and 2) the Hessian inverse operator and its multiplication with gradient cost too much time. To overcome these deficiencies of MFGD, we propose an efficient limited-memory FGD (L-FGD) method for optimizing GNMF. In particular, we apply the limited-memory BFGS (L-BFGS) method to directly approximate the multiplication of the inverse Hessian and the gradient for searching the optimal step size in MFGD. The preliminary results on real-world datasets show that L-FGD is more efficient than both MFGD and MUR. To evaluate the effectiveness of L-FGD, we validate its clustering performance for optimizing KL-divergence based GNMF on two popular face image datasets including ORL and PIE and two text corpora including Reuters and TDT2. The experimental results confirm the effectiveness of L-FGD by comparing it with the representative GNMF solvers.

Photoaffinity labeling in target- and binding-site identification

PubMed Central

Smith, Ewan; Collins, Ian

2015-01-01

Photoaffinity labeling (PAL) using a chemical probe to covalently bind its target in response to activation by light has become a frequently used tool in drug discovery for identifying new drug targets and molecular interactions, and for probing the location and structure of binding sites. Methods to identify the specific target proteins of hit molecules from phenotypic screens are highly valuable in early drug discovery. In this review, we summarize the principles of PAL including probe design and experimental techniques for in vitro and live cell investigations. We emphasize the need to optimize and validate probes and highlight examples of the successful application of PAL across multiple disease areas. PMID:25686004

Building a functional artery: issues from the perspective of mechanics.

PubMed

Gleason, Rudolph L; Hu, Jin-Jia; Humphrey, Jay D

2004-09-01

Despite the many successes of arterial tissue engineering, clinically viable implants may be a decade or more away. Fortunately, there is much more that we can learn from native vessels with regard to designing for optimal structure, function, and properties. Herein, we examine recent observations in vascular biology from the perspective of nonlinear mechanics. Moreover, we use a constrained mixture model to study potential contributions of individual wall constituents. In both cases, the unique biological and mechanical roles of elastin come to the forefront, especially its role in generating and modulating residual stress within the wall, which appears to be key to multiple growth and remodeling responses.

Quantum teleportation scheme by selecting one of multiple output ports

NASA Astrophysics Data System (ADS)

Ishizaka, Satoshi; Hiroshima, Tohya

2009-04-01

The scheme of quantum teleportation, where Bob has multiple (N) output ports and obtains the teleported state by simply selecting one of the N ports, is thoroughly studied. We consider both the deterministic version and probabilistic version of the teleportation scheme aiming to teleport an unknown state of a qubit. Moreover, we consider two cases for each version: (i) the state employed for the teleportation is fixed to a maximally entangled state and (ii) the state is also optimized as well as Alice’s measurement. We analytically determine the optimal protocols for all the four cases and show the corresponding optimal fidelity or optimal success probability. All these protocols can achieve the perfect teleportation in the asymptotic limit of N→∞ . The entanglement properties of the teleportation scheme are also discussed.

Design Method of Digital Optimal Control Scheme and Multiple Paralleled Bridge Type Current Amplifier for Generating Gradient Magnetic Fields in MRI Systems

NASA Astrophysics Data System (ADS)

Watanabe, Shuji; Takano, Hiroshi; Fukuda, Hiroya; Hiraki, Eiji; Nakaoka, Mutsuo

This paper deals with a digital control scheme of multiple paralleled high frequency switching current amplifier with four-quadrant chopper for generating gradient magnetic fields in MRI (Magnetic Resonance Imaging) systems. In order to track high precise current pattern in Gradient Coils (GC), the proposal current amplifier cancels the switching current ripples in GC with each other and designed optimum switching gate pulse patterns without influences of the large filter current ripple amplitude. The optimal control implementation and the linear control theory in GC current amplifiers have affinity to each other with excellent characteristics. The digital control system can be realized easily through the digital control implementation, DSPs or microprocessors. Multiple-parallel operational microprocessors realize two or higher paralleled GC current pattern tracking amplifier with optimal control design and excellent results are given for improving the image quality of MRI systems.

Scheduling optimization of design stream line for production research and development projects

NASA Astrophysics Data System (ADS)

Liu, Qinming; Geng, Xiuli; Dong, Ming; Lv, Wenyuan; Ye, Chunming

2017-05-01

In a development project, efficient design stream line scheduling is difficult and important owing to large design imprecision and the differences in the skills and skill levels of employees. The relative skill levels of employees are denoted as fuzzy numbers. Multiple execution modes are generated by scheduling different employees for design tasks. An optimization model of a design stream line scheduling problem is proposed with the constraints of multiple executive modes, multi-skilled employees and precedence. The model considers the parallel design of multiple projects, different skills of employees, flexible multi-skilled employees and resource constraints. The objective function is to minimize the duration and tardiness of the project. Moreover, a two-dimensional particle swarm algorithm is used to find the optimal solution. To illustrate the validity of the proposed method, a case is examined in this article, and the results support the feasibility and effectiveness of the proposed model and algorithm.

Using a derivative-free optimization method for multiple solutions of inverse transport problems

DOE PAGES

Armstrong, Jerawan C.; Favorite, Jeffrey A.

2016-01-14

Identifying unknown components of an object that emits radiation is an important problem for national and global security. Radiation signatures measured from an object of interest can be used to infer object parameter values that are not known. This problem is called an inverse transport problem. An inverse transport problem may have multiple solutions and the most widely used approach for its solution is an iterative optimization method. This paper proposes a stochastic derivative-free global optimization algorithm to find multiple solutions of inverse transport problems. The algorithm is an extension of a multilevel single linkage (MLSL) method where a meshmore » adaptive direct search (MADS) algorithm is incorporated into the local phase. Furthermore, numerical test cases using uncollided fluxes of discrete gamma-ray lines are presented to show the performance of this new algorithm.« less

Cholinergic and serotonergic modulation of visual information processing in monkey V1.

PubMed

Shimegi, Satoshi; Kimura, Akihiro; Sato, Akinori; Aoyama, Chisa; Mizuyama, Ryo; Tsunoda, Keisuke; Ueda, Fuyuki; Araki, Sera; Goya, Ryoma; Sato, Hiromichi

2016-09-01

The brain dynamically changes its input-output relationship depending on the behavioral state and context in order to optimize information processing. At the molecular level, cholinergic/monoaminergic transmitters have been extensively studied as key players for the state/context-dependent modulation of brain function. In this paper, we review how cortical visual information processing in the primary visual cortex (V1) of macaque monkey, which has a highly differentiated laminar structure, is optimized by serotonergic and cholinergic systems by examining anatomical and in vivo electrophysiological aspects to highlight their similarities and distinctions. We show that these two systems have a similar layer bias for axonal fiber innervation and receptor distribution. The common target sites are the geniculorecipient layers and geniculocortical fibers, where the appropriate gain control is established through a geniculocortical signal transformation. Both systems exert activity-dependent response gain control across layers, but in a manner consistent with the receptor subtype. The serotonergic receptors 5-HT1B and 5HT2A modulate the contrast-response curve in a manner consistent with bi-directional response gain control, where the sign (facilitation/suppression) is switched according to the firing rate and is complementary to the other. On the other hand, cholinergic nicotinic/muscarinic receptors exert mono-directional response gain control without a sign reversal. Nicotinic receptors increase the response magnitude in a multiplicative manner, while muscarinic receptors exert both suppressive and facilitative effects. We discuss the implications of the two neuromodulator systems in hierarchical visual signal processing in V1 on the basis of the developed laminar structure. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Unlocking Flexibility: Integrated Optimization and Control of Multienergy Systems

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

Dall'Anese, Emiliano; Mancarella, Pierluigi; Monti, Antonello

Electricity, natural gas, water, and dis trict heating/cooling systems are predominantly planned and operated independently. However, it is increasingly recognized that integrated optimization and control of such systems at multiple spatiotemporal scales can bring significant socioeconomic, operational efficiency, and environmental benefits. Accordingly, the concept of the multi-energy system is gaining considerable attention, with the overarching objectives of 1) uncovering fundamental gains (and potential drawbacks) that emerge from the integrated operation of multiple systems and 2) developing holistic yet computationally affordable optimization and control methods that maximize operational benefits, while 3) acknowledging intrinsic interdependencies and quality-of-service requirements for each provider.

Calculating and controlling the error of discrete representations of Pareto surfaces in convex multi-criteria optimization.

PubMed

Craft, David

2010-10-01

A discrete set of points and their convex combinations can serve as a sparse representation of the Pareto surface in multiple objective convex optimization. We develop a method to evaluate the quality of such a representation, and show by example that in multiple objective radiotherapy planning, the number of Pareto optimal solutions needed to represent Pareto surfaces of up to five dimensions grows at most linearly with the number of objectives. The method described is also applicable to the representation of convex sets. Copyright © 2009 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Precision analysis of the photomultiplier response to ultra low signals

NASA Astrophysics Data System (ADS)

Degtiarenko, Pavel

2017-11-01

A new computational model for the description of the photon detector response functions measured in conditions of low light is presented, together with examples of the observed photomultiplier signal amplitude distributions, successfully described using the parameterized model equation. In extension to the previously known approximations, the new model describes the underlying discrete statistical behavior of the photoelectron cascade multiplication processes in photon detectors with complex non-uniform gain structure of the first dynode. Important features of the model include the ability to represent the true single-photoelectron spectra from different photomultipliers with a variety of parameterized shapes, reflecting the variability in the design and in the individual parameters of the detectors. The new software tool is available for evaluation of the detectors' performance, response, and efficiency parameters that may be used in various applications including the ultra low background experiments such as the searches for Dark Matter and rare decays, underground neutrino studies, optimizing operations of the Cherenkov light detectors, help in the detector selection procedures, and in the experiment simulations.

3 Echo: concept of operations for early care and evacuation of victims of mass violence.

PubMed

Autrey, Allen W; Hick, John L; Bramer, Kurtis; Berndt, Jeremy; Bundt, Jonathan

2014-08-01

This report describes the successful use of a simple 3-phase approach that guides the initial 30 minutes of a response to blast and active shooter events with casualties: Enter, Evaluate, and Evacuate (3 Echo) in a mass-shooting event occurring in Minneapolis, Minnesota USA, on September 27, 2012. Early coordination between law enforcement (LE) and rescue was emphasized, including establishment of unified command, a common operating picture, determination of evacuation corridors, swift victim evaluation, basic treatment, and rapid evacuation utilizing an approach developed collaboratively over the four years prior to the event. Field implementation of 3 Echo requires multi-disciplinary (Emergency Medical Services (EMS), fire and LE) training to optimize performance. This report details the mass-shooting event, the framework created to support the response, and also describes important aspects of the concepts of operation and curriculum evolved through years of collaboration between multiple disciplines to arrive at unprecedented EMS transport times in response to the event.

Effect of cytokinins on in vitro multiplication of Sophora tonkinensis

PubMed Central

Jana, Sonali; Sivanesan, Iyyakkannu; Jeong, Byoung Ryong

2013-01-01

Objective To determine the effects of different cytokinins at various concentrations on in vitro shoot multiplication of an important medicinal plant. Methods Nodal explants (1.5-2.0 cm) of Sophora tonkinensis were used. Multiple shoots were induced from nodal explants cultured on the Murashige and Skoog (MS) medium supplemented with 0.0, 0.5, 1.0, 2.0, 4.0, 8.0, or 16.0 µmol 2-isopentyladenine (2iP), N6 benzyladenine, kinetin or thiadiazuron. Results Among the four investigated cytokinins, 2iP showed the best response for shoot multiplication. Maximum shoot induction (75%) was achieved on the MS medium supplemented with 2.0 µmol 2iP, with a mean number of 5.0 shoots per explant. In comparison to other cytokinins tried, 2iP showed the highest shoot elongation with a mean shoot length of 4.8 cm. Root initiation was observed within 15 d within the transfer of shoots onto the MS basal medium, and the rooting percentage was 100% with a mean number of 5.4 roots per shoot and root length of 6.2 cm over a period of 4 weeks. The healthy plants, hardened and transferred to a greenhouse for proper acclimatization, exhibited 100% survival. Conclusions It can be summarized that 2iP is the optimal plant growth regulator for Sophora multiplication. PMID:23836310

Sparse matrix multiplications for linear scaling electronic structure calculations in an atom-centered basis set using multiatom blocks.

PubMed

Saravanan, Chandra; Shao, Yihan; Baer, Roi; Ross, Philip N; Head-Gordon, Martin

2003-04-15

A sparse matrix multiplication scheme with multiatom blocks is reported, a tool that can be very useful for developing linear-scaling methods with atom-centered basis functions. Compared to conventional element-by-element sparse matrix multiplication schemes, efficiency is gained by the use of the highly optimized basic linear algebra subroutines (BLAS). However, some sparsity is lost in the multiatom blocking scheme because these matrix blocks will in general contain negligible elements. As a result, an optimal block size that minimizes the CPU time by balancing these two effects is recovered. In calculations on linear alkanes, polyglycines, estane polymers, and water clusters the optimal block size is found to be between 40 and 100 basis functions, where about 55-75% of the machine peak performance was achieved on an IBM RS6000 workstation. In these calculations, the blocked sparse matrix multiplications can be 10 times faster than a standard element-by-element sparse matrix package. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 618-622, 2003

Dynamic optimization of ISR sensors using a risk-based reward function applied to ground and space surveillance scenarios

NASA Astrophysics Data System (ADS)

DeSena, J. T.; Martin, S. R.; Clarke, J. C.; Dutrow, D. A.; Newman, A. J.

2012-06-01

As the number and diversity of sensing assets available for intelligence, surveillance and reconnaissance (ISR) operations continues to expand, the limited ability of human operators to effectively manage, control and exploit the ISR ensemble is exceeded, leading to reduced operational effectiveness. Automated support both in the processing of voluminous sensor data and sensor asset control can relieve the burden of human operators to support operation of larger ISR ensembles. In dynamic environments it is essential to react quickly to current information to avoid stale, sub-optimal plans. Our approach is to apply the principles of feedback control to ISR operations, "closing the loop" from the sensor collections through automated processing to ISR asset control. Previous work by the authors demonstrated non-myopic multiple platform trajectory control using a receding horizon controller in a closed feedback loop with a multiple hypothesis tracker applied to multi-target search and track simulation scenarios in the ground and space domains. This paper presents extensions in both size and scope of the previous work, demonstrating closed-loop control, involving both platform routing and sensor pointing, of a multisensor, multi-platform ISR ensemble tasked with providing situational awareness and performing search, track and classification of multiple moving ground targets in irregular warfare scenarios. The closed-loop ISR system is fullyrealized using distributed, asynchronous components that communicate over a network. The closed-loop ISR system has been exercised via a networked simulation test bed against a scenario in the Afghanistan theater implemented using high-fidelity terrain and imagery data. In addition, the system has been applied to space surveillance scenarios requiring tracking of space objects where current deliberative, manually intensive processes for managing sensor assets are insufficiently responsive. Simulation experiment results are presented. The algorithm to jointly optimize sensor schedules against search, track, and classify is based on recent work by Papageorgiou and Raykin on risk-based sensor management. It uses a risk-based objective function and attempts to minimize and balance the risks of misclassifying and losing track on an object. It supports the requirement to generate tasking for metric and feature data concurrently and synergistically, and account for both tracking accuracy and object characterization, jointly, in computing reward and cost for optimizing tasking decisions.

A liquid metal-based structurally embedded vascular antenna: II. Multiobjective and parameterized design exploration

NASA Astrophysics Data System (ADS)

Hartl, D. J.; Frank, G. J.; Malak, R. J.; Baur, J. W.

2017-02-01

Research on the structurally embedded vascular antenna concept leverages past efforts on liquid metal (LM) reconfigurable electronics, microvascular composites, and structurally integrated and reconfigurable antennas. Such a concept has potential for reducing system weight or volume while simultaneously allowing in situ adjustment of resonant frequencies and/or changes in antenna directivity. This work considers a microvascular pattern embedded in a laminated composite and filled with LM. The conductive liquid provides radio frequency (RF) functionality while also allowing self-cooling. Models describing RF propagation and heat transfer, in addition to the structural effects of both the inclusion of channels and changes in temperature, were described in part 1 of this two-part work. In this part 2, the engineering models developed and demonstrated in part 1 toward the initial exploration of design trends are implemented into multiple optimization frameworks for more detailed design studies, one of which being novel and particularly applicable to this class of problem. The computational expense associated with the coupled multiphysical analysis of the structurally embedded LM transmitting antenna motivates the consideration of surrogate-based optimization methods. Both static and adaptive approaches are explored; it is shown that iteratively correcting the surrogate leads to more accurate optimized design predictions. The expected strong dependence of antenna performance on thermal environment motivates the consideration of a novel ‘parameterized’ optimization approach that simultaneously calculates whole families of optimal designs based on changes in design or operational variables generally beyond the control of the designer. The change in Pareto-optimal response with evolution in operating conditions is clearly demonstrated.

Enhanced Ungual Permeation of Terbinafine HCl Delivered Through Liposome-Loaded Nail Lacquer Formulation Optimized by QbD Approach.

PubMed

Shah, Viral H; Jobanputra, Amee

2018-01-01

The present investigation focused on developing, optimizing, and evaluating a novel liposome-loaded nail lacquer formulation for increasing the transungual permeation flux of terbinafine HCl for efficient treatment of onychomycosis. A three-factor, three-level, Box-Behnken design was employed for optimizing process and formulation parameters of liposomal formulation. Liposomes were formulated by thin film hydration technique followed by sonication. Drug to lipid ratio, sonication amplitude, and sonication time were screened as independent variables while particle size, PDI, entrapment efficiency, and zeta potential were selected as quality attributes for liposomal formulation. Multiple regression analysis was employed to construct a second-order quadratic polynomial equation and contour plots. Design space (overlay plot) was generated to optimize a liposomal system, with software-suggested levels of independent variables that could be transformed to desired responses. The optimized liposome formulation was characterized and dispersed in nail lacquer which was further evaluated for different parameters. Results depicted that the optimized terbinafine HCl-loaded liposome formulation exhibited particle size of 182 nm, PDI of 0.175, zeta potential of -26.8 mV, and entrapment efficiency of 80%. Transungual permeability flux of terbinafine HCl through liposome-dispersed nail lacquer formulation was observed to be significantly higher in comparison to nail lacquer with a permeation enhancer. The developed formulation was also observed to be as efficient as pure drug dispersion in its antifungal activity. Thus, it was concluded that the developed formulation can serve as an efficient tool for enhancing the permeability of terbinafine HCl across human nail plate thereby improving its therapeutic efficiency.