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Sample records for optimal tuner selection

  1. Optimized tuner selection for engine performance estimation

    NASA Technical Reports Server (NTRS)

    Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

    2013-01-01

    A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

  2. Application of an Optimal Tuner Selection Approach for On-Board Self-Tuning Engine Models

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Armstrong, Jeffrey B.; Garg, Sanjay

    2012-01-01

    An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specific-ally addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy.

  3. Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Garg, Sanjay

    2010-01-01

    A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

  4. Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Garg, Sanjay

    2011-01-01

    An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation

  5. Recurrent connections form a phase-locking neuronal tuner for frequency-dependent selective communication

    PubMed Central

    Shin, Dongkwan; Cho, Kwang-Hyun

    2013-01-01

    The brain requires task-dependent interregional coherence of information flow in the anatomically connected neural network. However, it is still unclear how a neuronal group can flexibly select its communication target. In this study, we revealed a hidden routing mechanism on the basis of recurrent connections. Our simulation results based on the spike response model show that recurrent connections between excitatory and inhibitory neurons modulate the resonant frequency of a local neuronal group, and that this modulation enables a neuronal group to receive selective information by filtering a preferred frequency component. We also found that the recurrent connection facilitates the successful routing of any necessary information flow between neuronal groups through frequency-dependent resonance of synchronized oscillations. Taken together, these results suggest that recurrent connections act as a phase-locking neuronal tuner which determines the resonant frequency of a local group and thereby controls the preferential routing of incoming signals. PMID:23981983

  6. Model-Based Control of an Aircraft Engine using an Optimal Tuner Approach

    NASA Technical Reports Server (NTRS)

    Connolly, Joseph W.; Chicatelli, Amy; Garg, Sanjay

    2012-01-01

    This paper covers the development of a model-based engine control (MBEC) method- ology applied to an aircraft turbofan engine. Here, a linear model extracted from the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) at a cruise operating point serves as the engine and the on-board model. The on-board model is up- dated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. MBEC provides the ability for a tighter control bound of thrust over the entire life cycle of the engine that is not achievable using traditional control feedback, which uses engine pressure ratio or fan speed. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC tighter thrust control. In addition, investigations of using the MBEC to provide a surge limit for the controller limit logic are presented that could provide benefits over a simple acceleration schedule that is currently used in engine control architectures.

  7. Fast ferrite tuner for the BNL synchrotron light source

    SciTech Connect

    Pivit, E. ); Hanna, S.M.; Keane, J. )

    1991-01-01

    A new type of ferrite tuner has been tested at the BNL. The ferrite tuner uses garnet slabs partially filling a stripline. One of the important features of the tuner is that the ferrite is perpendicularly biased for operation above FMR, thus reducing the magnetic losses. A unique design was adopted to achieve the efficient cooling. The principle of operation of the tuner as well as our preliminary results on tuning a 52 MHz cavity are reported. Optimized conditions under which we demonstrated linear tunability of 80 KHz are described. The tuner's losses and its effect on higher-order modes in the cavity are discussed. 2 refs., 8 figs.

  8. Model-Based Control of a Nonlinear Aircraft Engine Simulation using an Optimal Tuner Kalman Filter Approach

    NASA Technical Reports Server (NTRS)

    Connolly, Joseph W.; Csank, Jeffrey Thomas; Chicatelli, Amy; Kilver, Jacob

    2013-01-01

    This paper covers the development of a model-based engine control (MBEC) methodology featuring a self tuning on-board model applied to an aircraft turbofan engine simulation. Here, the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) serves as the MBEC application engine. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC over a wide range of operating points. The on-board model is a piece-wise linear model derived from CMAPSS40k and updated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. Investigations using the MBEC to provide a stall margin limit for the controller protection logic are presented that could provide benefits over a simple acceleration schedule that is currently used in traditional engine control architectures.

  9. Test of a coaxial blade tuner at HTS FNAL

    SciTech Connect

    Pischalnikov, Y.; Barbanotti, S.; Harms, E.; Hocker, A.; Khabiboulline, T.; Schappert, W.; Bosotti, A.; Pagani, C.; Paparella, R.; /LASA, Segrate

    2011-03-01

    A coaxial blade tuner has been selected for the 1.3GHz SRF cavities of the Fermilab SRF Accelerator Test Facility. Results from tuner cold tests in the Fermilab Horizontal Test Stand are presented. Fermilab is constructing the SRF Accelerator Test Facility, a facility for accelerator physics research and development. This facility will contain a total of six cryomodules, each containing eight 1.3 GHz nine-cell elliptical cavities. Each cavity will be equipped with a Slim Blade Tuner designed by INFN Milan. The blade tuner incorporates both a stepper motor and piezo actuators to allow for both slow and fast cavity tuning. The stepper motor allows the cavity frequency to be statically tuned over a range of 500 kHz with an accuracy of several Hz. The piezos provide up to 2 kHz of dynamic tuning for compensation of Lorentz force detuning and variations in the He bath pressure. The first eight blade tuners were built at INFN Milan, but the remainder are being manufactured commercially following the INFN design. To date, more than 40 of the commercial tuners have been delivered.

  10. Electromagnetic SCRF Cavity Tuner

    SciTech Connect

    Kashikhin, V.; Borissov, E.; Foster, G.W.; Makulski, A.; Pischalnikov, Y.; Khabiboulline, T.; /Fermilab

    2009-05-01

    A novel prototype of SCRF cavity tuner is being designed and tested at Fermilab. This is a superconducting C-type iron dominated magnet having a 10 mm gap, axial symmetry, and a 1 Tesla field. Inside the gap is mounted a superconducting coil capable of moving {+-} 1 mm and producing a longitudinal force up to {+-} 1.5 kN. The static force applied to the RF cavity flanges provides a long-term cavity geometry tuning to a nominal frequency. The same coil powered by fast AC current pulse delivers mechanical perturbation for fast cavity tuning. This fast mechanical perturbation could be used to compensate a dynamic RF cavity detuning caused by cavity Lorentz forces and microphonics. A special configuration of magnet system was designed and tested.

  11. Inductive tuners for microwave driven discharge lamps

    DOEpatents

    Simpson, James E.

    1999-01-01

    An RF powered electrodeless lamp utilizing an inductive tuner in the waveguide which couples the RF power to the lamp cavity, for reducing reflected RF power and causing the lamp to operate efficiently.

  12. Inductive tuners for microwave driven discharge lamps

    SciTech Connect

    Simpson, J.E.

    1999-11-02

    An RF powered electrodeless lamp utilizing an inductive tuner in the waveguide which couples the RF power to the lamp cavity, for reducing reflected RF power and causing the lamp to operate efficiently.

  13. ANT tuner retrofit for LEB cavity

    SciTech Connect

    Walling, L.; Goren, Y.; Kwiatkowski, S.

    1994-03-01

    This report describes a ferrite tuner design for the LEB cavity that utilizes techniques for bonding ferrite to metallic cooling plates that is utilized in the high-power rf and microwave industry. A test tuner was designed to fit into the existing LEB-built magnet and onto the Grimm LEB Cavity. It will require a new vacuum window in order to attain maximal tuning range and high voltage capability and a new center conductor of longer length and a different vacuum window connection than the Grimm center conductor. However, the new center conductor will be essentially identical to the Grimm center conductor in its basic construction and in the way it connects to the stand for support. The tuner is mechanically very similar to high-power stacked circulators built by ANT of Germany and was designed according to ANT`s established engineering and design criteria and SSC LEB tuning and power requirements. The tuner design incorporates thin tiles of ferrite glued using a high-radiation-resistance epoxy to copper-plated stainless steel cooling plates of thickness 6.5 mm with water cooling channels inside the plates. The cooling plates constitute 16 pie-shaped segments arranged in a disk. They are electrically isolated from each other to suppress eddy currents. Five of these disks are arranged in parallel with high-pressure rf contacts between the plates at the outer radius. The end walls are slotted copper-plated stainless steel of thickness 3 mm.

  14. Enhanced production of electron cyclotron resonance plasma by exciting selective microwave mode on a large-bore electron cyclotron resonance ion source with permanent magnet

    SciTech Connect

    Kimura, Daiju Kurisu, Yosuke; Nozaki, Dai; Yano, Keisuke; Imai, Youta; Kumakura, Sho; Sato, Fuminobu; Kato, Yushi; Iida, Toshiyuki

    2014-02-15

    We are constructing a tandem type ECRIS. The first stage is large-bore with cylindrically comb-shaped magnet. We optimize the ion beam current and ion saturation current by a mobile plate tuner. They change by the position of the plate tuner for 2.45 GHz, 11–13 GHz, and multi-frequencies. The peak positions of them are close to the position where the microwave mode forms standing wave between the plate tuner and the extractor. The absorbed powers are estimated for each mode. We show a new guiding principle, which the number of efficient microwave mode should be selected to fit to that of multipole of the comb-shaped magnets. We obtained the excitation of the selective modes using new mobile plate tuner to enhance ECR efficiency.

  15. Superconducting cavity tuner performance at CEBAF

    SciTech Connect

    Marshall, J.; Preble, J.; Schneider, W.

    1993-06-01

    At the Continuous Electron Beam Accelerator Facility (CEBAF), a 4 GeV, multipass CW electron beam is to be accelerated by 338 SRF, 5-cell niobium cavities operating at a resonant frequency of 1497 MHz. Eight cavities arranged as four pairs comprise a cyromodule, a croygenically isolated linac subdivision. The frequency is controlled by a mechanical tune attached to the first and fifth cell of the cavity which elastically deforms the cavity and thereby alters its resonant frequency. The tuner is driven by a stepper motor mounted external to the cryomodule that transfers torque through two rotary feedthroughs. A linear variable differential transducer (LVDT) mounted on the tuner monitors the displacement, and two limit switches interlock the movement beyond a 400 kHz bandwidth. Since the cavity has a loaded Q of 6.6 {center_dot} 10{sup 6}, the control system must maintain the frequency of the cavity to within {plus_minus} 50 Hz of the drive frequency for efficient coupling. This requirement is somewhat difficult to achieve since the difference in thermal contractions of the cavity and the tuner creates a frequency hystersis of approximately 10 kHz. The cavity is also subject to frequency shifts due to pressure fluctuations of the helium bath as well as radiation pressure. This requires that each cavity be characterized in terms of frequency change as a function of applied motor steps to allow proper tuning operations. This paper describes the electrical and mechanical performance of the cavity tuner during the commissioning and operation of the cryomodulus manufactured to date.

  16. Mechanical design upgrade of the APS storage ring rf cavity tuner

    SciTech Connect

    Jones, J.; Bromberek, D.; Kang, Y.

    1997-08-01

    The Advanced Photon Source (APS) storage ring (SR) rf system employs four banks of four spherical, single-cell resonant cavities. Each cavity is tuned by varying the cavity volume through insertion/retraction of a copper piston located at the circumference of the cavity and oriented perpendicular to the accelerator beam. During the commissioning of the APS SR, the tuners and cavity tuner ports were prone to extensive arcing and overheating. The existing tuners were modified to eliminate the problems, and two new, redesigned tuners were installed. In both cases marked improvements were obtained in the tuner mechanical performance. As measured by tuner piston and flange surface temperatures, tuner heating has been reduced by a factor of five in the new version. Redesign considerations discussed include tuner piston-to-housing alignment, tuner piston and housing materials and cooling configurations, and tuner piston sliding electrical contacts. The tuner redesign is also distinguished by a modular, more maintainable assembly.

  17. Dependence of ion beam current on position of mobile plate tuner in multi-frequencies microwaves electron cyclotron resonance ion source.

    PubMed

    Kurisu, Yosuke; Kiriyama, Ryutaro; Takenaka, Tomoya; Nozaki, Dai; Sato, Fuminobu; Kato, Yushi; Iida, Toshiyuki

    2012-02-01

    We are constructing a tandem-type electron cyclotron resonance ion source (ECRIS). The first stage of this can supply 2.45 GHz and 11-13 GHz microwaves to plasma chamber individually and simultaneously. We optimize the beam current I(FC) by the mobile plate tuner. The I(FC) is affected by the position of the mobile plate tuner in the chamber as like a circular cavity resonator. We aim to clarify the relation between the I(FC) and the ion saturation current in the ECRIS against the position of the mobile plate tuner. We obtained the result that the variation of the plasma density contributes largely to the variation of the I(FC) when we change the position of the mobile plate tuner.

  18. Dependence of ion beam current on position of mobile plate tuner in multi-frequencies microwaves electron cyclotron resonance ion source

    SciTech Connect

    Kurisu, Yosuke; Kiriyama, Ryutaro; Takenaka, Tomoya; Nozaki, Dai; Sato, Fuminobu; Kato, Yushi; Iida, Toshiyuki

    2012-02-15

    We are constructing a tandem-type electron cyclotron resonance ion source (ECRIS). The first stage of this can supply 2.45 GHz and 11-13 GHz microwaves to plasma chamber individually and simultaneously. We optimize the beam current I{sub FC} by the mobile plate tuner. The I{sub FC} is affected by the position of the mobile plate tuner in the chamber as like a circular cavity resonator. We aim to clarify the relation between the I{sub FC} and the ion saturation current in the ECRIS against the position of the mobile plate tuner. We obtained the result that the variation of the plasma density contributes largely to the variation of the I{sub FC} when we change the position of the mobile plate tuner.

  19. Methods to optimize selective hyperthermia

    NASA Astrophysics Data System (ADS)

    Cowan, Thomas M.; Bailey, Christopher A.; Liu, Hong; Chen, Wei R.

    2003-07-01

    Laser immunotherapy, a novel therapy for breast cancer, utilizes selective photothermal interaction to raise the temperature of tumor tissue above the cell damage threshold. Photothermal interaction is achieved with intratumoral injection of a laser absorbing dye followed by non-invasive laser irradiation. When tumor heating is used in combination with immunoadjuvant to stimulate an immune response, anti-tumor immunity can be achieved. In our study, gelatin phantom simulations were used to optimize therapy parameters such as laser power, laser beam radius, and dye concentration to achieve maximum heating of target tissue with the minimum heating of non-targeted tissue. An 805-nm diode laser and indocyanine green (ICG) were used to achieve selective photothermal interactions in a gelatin phantom. Spherical gelatin phantoms containing ICG were used to simulate the absorption-enhanced target tumors, which were embedded inside gelatin without ICG to simulate surrounding non-targeted tissue. Different laser powers and dye concentrations were used to treat the gelatin phantoms. The temperature distributions in the phantoms were measured, and the data were used to determine the optimal parameters used in selective hyperthermia (laser power and dye concentration for this case). The method involves an optimization coefficient, which is proportional to the difference between temperatures measured in targeted and non-targeted gel. The coefficient is also normalized by the difference between the most heated region of the target gel and the least heated region. A positive optimization coefficient signifies a greater temperature increase in targeted gelatin when compared to non-targeted gelatin, and therefore, greater selectivity. Comparisons were made between the optimization coefficients for varying laser powers in order to demonstrate the effectinvess of this method in finding an optimal parameter set. Our experimental results support the proposed use of an optimization

  20. Feedback controlled hybrid fast ferrite tuners

    SciTech Connect

    Remsen, D.B.; Phelps, D.A.; deGrassie, J.S.; Cary, W.P.; Pinsker, R.I.; Moeller, C.P.; Arnold, W.; Martin, S.; Pivit, E.

    1993-09-01

    A low power ANT-Bosch fast ferrite tuner (FFT) was successfully tested into (1) the lumped circuit equivalent of an antenna strap with dynamic plasma loading, and (2) a plasma loaded antenna strap in DIII-D. When the FFT accessible mismatch range was phase-shifted to encompass the plasma-induced variation in reflection coefficient, the 50 {Omega} source was matched (to within the desired 1.4 : 1 voltage standing wave ratio). The time required to achieve this match (i.e., the response time) was typically a few hundred milliseconds, mostly due to a relatively slow network analyzer-computer system. The response time for the active components of the FFT was 10 to 20 msec, or much faster than the present state-of-the-art for dynamic stub tuners. Future FFT tests are planned, that will utilize the DIII-D computer (capable of submillisecond feedback control), as well as several upgrades to the active control circuit, to produce a FFT feedback control system with a response time approaching 1 msec.

  1. Fast Tuner R&D for RIA

    SciTech Connect

    Rusnak, B; Shen, S

    2003-08-19

    The limited cavity beam loading conditions anticipated for the Rare Isotope Accelerator (RIA) create a situation where microphonic-induced cavity detuning dominates radio frequency (RF) coupling and RF system architecture choices in the linac design process. Where most superconducting electron and proton linacs have beam-loaded bandwidths that are comparable to or greater than typical microphonic detuning bandwidths on the cavities, the beam-loaded bandwidths for many heavy-ion species in the RIA driver linac can be as much as a factor of 10 less than the projected 80-150 Hz microphonic control window for the RF structures along the driver, making RF control problematic. System studies indicate that for the low-{beta} driver linac alone, running the cavities with no fast tuner may cost 50% or more than an RF system employing a voltage controlled reactance (VCX) or other type of fast tuner. An update of these system cost studies, along with the status of the VCX work being done at Lawrence Livermore National Lab is presented.

  2. Characterization of CNRS Fizeau wedge laser tuner

    NASA Astrophysics Data System (ADS)

    A fringe detection and measurement system was constructed for use with the CNRS Fizeau wedge laser tuner, consisting of three circuit boards. The first board is a standard Reticon RC-100 B motherboard which is used to provide the timing, video processing, and housekeeping functions required by the Reticon RL-512 G photodiode array used in the system. The sampled and held video signal from the motherboard is processed by a second, custom fabricated circuit board which contains a high speed fringe detection and locating circuit. This board includes a dc level discriminator type fringe detector, a counter circuit to determine fringe center, a pulsed laser triggering circuit, and a control circuit to operate the shutter for the He-Ne reference laser beam. The fringe center information is supplied to the third board, a commercial single board computer, which governs the data collection process and interprets the results.

  3. Characterization of CNRS Fizeau wedge laser tuner

    NASA Technical Reports Server (NTRS)

    1984-01-01

    A fringe detection and measurement system was constructed for use with the CNRS Fizeau wedge laser tuner, consisting of three circuit boards. The first board is a standard Reticon RC-100 B motherboard which is used to provide the timing, video processing, and housekeeping functions required by the Reticon RL-512 G photodiode array used in the system. The sampled and held video signal from the motherboard is processed by a second, custom fabricated circuit board which contains a high speed fringe detection and locating circuit. This board includes a dc level discriminator type fringe detector, a counter circuit to determine fringe center, a pulsed laser triggering circuit, and a control circuit to operate the shutter for the He-Ne reference laser beam. The fringe center information is supplied to the third board, a commercial single board computer, which governs the data collection process and interprets the results.

  4. Fast Ferroelectric L-Band Tuner for Superconducting Cavities

    SciTech Connect

    Jay L. Hirshfield

    2011-03-01

    Analysis and modeling is presented for a fast microwave tuner to operate at 700 MHz which incorporates ferroelectric elements whose dielectric permittivity can be rapidly altered by application of an external voltage. This tuner could be used to correct unavoidable fluctuations in the resonant frequency of superconducting cavities in accelerator structures, thereby greatly reducing the RF power needed to drive the cavities. A planar test version of the tuner has been tested at low levels of RF power, but at 1300 MHz to minimize the physical size of the test structure. This test version comprises one-third of the final version. The tests show performance in good agreement with simulations, but with losses in the ferroelectric elements that are too large for practical use, and with issues in bonding of ferroelectric elements to the metal walls of the tuner structure.

  5. Fast Ferroelectric L-Band Tuner for Superconducting Cavities

    SciTech Connect

    Jay L. Hirshfield

    2012-07-03

    Design, analysis, and low-power tests are described on a ferroelectric tuner concept that could be used for controlling external coupling to RF cavities for the superconducting Energy Recovery Linac (ERL) in the electron cooler of the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL). The tuner configuration utilizes several small donut-shaped ferroelectric assemblies, which allow the design to be simpler and more flexible, as compared to previous designs. Design parameters for 704 and 1300 MHz versions of the tuner are given. Simulation results point to efficient performance that could reduce by a factor-of-ten the RF power levels required for driving superconducting cavities in the BNL ERL.

  6. Fast Ferroelectric L-Band Tuner for ILC Cavities

    SciTech Connect

    Hirshfield, Jay L

    2010-03-15

    Design, analysis, and low-power tests are described on a 1.3 GHz ferroelectric tuner that could find application in the International Linear Collider or in Project X at Fermi National Accelerator Laboratory. The tuner configuration utilizes a three-deck sandwich imbedded in a WR-650 waveguide, in which ferroelectric bars are clamped between conducting plates that allow the tuning bias voltage to be applied. Use of a reduced one-third structure allowed tests of critical parameters of the configuration, including phase shift, loss, and switching speed. Issues that were revealed that require improvement include reducing loss tangent in the ferroelectric material, development of a reliable means of brazing ferroelectric elements to copper parts of the tuner, and simplification of the mechanical design of the configuration.

  7. Fast 704 MHz Ferroelectric Tuner for Superconducting Cavities

    SciTech Connect

    Jay L. Hirshfield

    2012-04-12

    The Omega-P SBIR project described in this Report has as its goal the development, test, and evaluation of a fast electrically-controlled L-band tuner for BNL Energy Recovery Linac (ERL) in the Electron Ion Collider (EIC) upgrade of the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL). The tuner, that employs an electrically-controlled ferroelectric component, is to allow fast compensation to cavity resonance changes. In ERLs, there are several factors which significantly affect the amount of power required from the wall-plug to provide the RF-power level necessary for the operation. When beam loading is small, the power requirements are determined by (i) ohmic losses in cavity walls, (ii) fluctuations in amplitude and/or phase for beam currents, and (iii) microphonics. These factors typically require a substantial change in the coupling between the cavity and the feeding line, which results in an intentional broadening of the cavity bandwidth, which in turn demands a significant amount of additional RF power. If beam loading is not small, there is a variety of beam-drive phase instabilities to be managed, and microphonics will still remain an issue, so there remain requirements for additional power. Moreover ERL performance is sensitive to changes in beam arrival time, since any such change is equivalent to phase instability with its vigorous demands for additional power. In this Report, we describe the new modular coaxial tuner, with specifications suitable for the 704 MHz ERL application. The device would allow changing the RF-coupling during the cavity filling process in order to effect significant RF power savings, and also will provide rapid compensation for beam imbalance and allow for fast stabilization against phase fluctuations caused by microphonics, beam-driven instabilities, etc. The tuner is predicted to allow a reduction of about ten times in the required power from the RF source, as compared to a compensation system

  8. Piezoelectric Tuner Compensation of Lorentz Detuning in Superconducting Cavities

    SciTech Connect

    Jean Delayen; G. Davis

    2003-09-01

    Pulsed operation of superconducting cavities can induce large variations of the resonant frequency through excitation of the mechanical modes by the radiation pressure. The phase and amplitude control system must be able to accommodate this frequency variation; this can be accomplished by increasing the capability of the rf power source. Alternatively, a piezo electric tuner can be activated at the same repetition rate as the rf to counteract the effect of the radiation pressure. We have demonstrated such a system on the prototype medium beta SNS cryomodule with a reduction of the dynamic Lorentz detuning during the rf pulse by a factor of 3. Piezo electric tuners can also be used to reduce the level of microphonics in low-current cw accelerators. We have measured the amplitude and phase of the transfer function of the piezo control system (from input voltage to cavity frequency) up to several kHz.

  9. Testing of the new tuner design for the CEBAF 12 GeV upgrade SRF cavities

    SciTech Connect

    Edward Daly; G. Davis; William Hicks

    2005-05-01

    The new tuner design for the 12 GeV Upgrade SRF cavities consists of a coarse mechanical tuner and a fine piezoelectric tuner. The mechanism provides a 30:1 mechanical advantage, is pre-loaded at room temperature and tunes the cavities in tension only. All of the components are located in the insulating vacuum space and attached to the helium vessel, including the motor, harmonic drive and piezoelectric actuators. The requirements and detailed design are presented. Measurements of range and resolution of the coarse tuner are presented and discussed.

  10. Self-extinction through optimizing selection.

    PubMed

    Parvinen, Kalle; Dieckmann, Ulf

    2013-09-21

    Evolutionary suicide is a process in which selection drives a viable population to extinction. So far, such selection-driven self-extinction has been demonstrated in models with frequency-dependent selection. This is not surprising, since frequency-dependent selection can disconnect individual-level and population-level interests through environmental feedback. Hence it can lead to situations akin to the tragedy of the commons, with adaptations that serve the selfish interests of individuals ultimately ruining a population. For frequency-dependent selection to play such a role, it must not be optimizing. Together, all published studies of evolutionary suicide have created the impression that evolutionary suicide is not possible with optimizing selection. Here we disprove this misconception by presenting and analyzing an example in which optimizing selection causes self-extinction. We then take this line of argument one step further by showing, in a further example, that selection-driven self-extinction can occur even under frequency-independent selection. PMID:23583808

  11. Self-extinction through optimizing selection.

    PubMed

    Parvinen, Kalle; Dieckmann, Ulf

    2013-09-21

    Evolutionary suicide is a process in which selection drives a viable population to extinction. So far, such selection-driven self-extinction has been demonstrated in models with frequency-dependent selection. This is not surprising, since frequency-dependent selection can disconnect individual-level and population-level interests through environmental feedback. Hence it can lead to situations akin to the tragedy of the commons, with adaptations that serve the selfish interests of individuals ultimately ruining a population. For frequency-dependent selection to play such a role, it must not be optimizing. Together, all published studies of evolutionary suicide have created the impression that evolutionary suicide is not possible with optimizing selection. Here we disprove this misconception by presenting and analyzing an example in which optimizing selection causes self-extinction. We then take this line of argument one step further by showing, in a further example, that selection-driven self-extinction can occur even under frequency-independent selection.

  12. Feature Selection via Chaotic Antlion Optimization

    PubMed Central

    Zawbaa, Hossam M.; Emary, E.; Grosan, Crina

    2016-01-01

    Background Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with performing a high-accuracy classification over the data can be a daunting task, particularly if the data are high dimensional. An often adopted approach is to formulate the feature selection problem as a biobjective optimization problem, with the aim of maximizing the performance of the data analysis model (the quality of the data training fitting) while minimizing the number of features used. Results We propose an optimization approach for the feature selection problem that considers a “chaotic” version of the antlion optimizer method, a nature-inspired algorithm that mimics the hunting mechanism of antlions in nature. The balance between exploration of the search space and exploitation of the best solutions is a challenge in multi-objective optimization. The exploration/exploitation rate is controlled by the parameter I that limits the random walk range of the ants/prey. This variable is increased iteratively in a quasi-linear manner to decrease the exploration rate as the optimization progresses. The quasi-linear decrease in the variable I may lead to immature convergence in some cases and trapping in local minima in other cases. The chaotic system proposed here attempts to improve the tradeoff between exploration and exploitation. The methodology is evaluated using different chaotic maps on a number of feature selection datasets. To ensure generality, we used ten biological datasets, but we also used other types of data from various sources. The results are compared with the particle swarm optimizer and with genetic algorithm variants for feature selection using a set of quality metrics. PMID:26963715

  13. DESIGN CONSIDERATIONS FOR THE MECHANICAL TUNER OF THE RHIC ELECTRON COOLER RF CAVITY.

    SciTech Connect

    RANK, J.; BEN-ZVI,I.; HAHN,G.; MCINTYRE,G.; DALY,E.; PREBLE,J.

    2005-05-16

    The ECX Project, Brookhaven Lab's predecessor to the RHIC e-Cooler, includes a prototype RF tuner mechanism capable of both coarse and fast tuning. This tuner concept, adapted originally from a DESY design, has longer stroke and significantly higher loads attributable to the very stiff ECX cavity shape. Structural design, kinematics, controls, thermal and RF issues are discussed and certain improvements are proposed.

  14. Selection of AN Optimal FORCE STATE Map

    NASA Astrophysics Data System (ADS)

    Duym, S. W. R.; Schoukens, J. F. M.

    1996-11-01

    The restoring force method and the equivalent force-state mapping technique have been used to characterise non-linear mechanical systems. Both acquire a number of samples and process them to produce a non-parametric representation of the non-linear force as a function of two state variables. Errors are primarily introduced by an incomplete model and by measurement noise. By establishing a trade-off between both error sources it is possible to attain an optimal model. In this paper it is shown how such an optimal model is obtained by selecting the number of grid elements and their respective distribution. The optimal grid selection method is illustrated for automotive shock absorbers.

  15. Reducing ferrite tuner power loss by bias field rotation

    SciTech Connect

    Smythe, W.R.

    1983-08-01

    It has been suggested that ferrite tuners for rf cavities with the magnetic bias field perpendicular to the rf magnetic field would have greatly reduced rf losses. Recent measurements at Los Alamos National Laboratory appear to confirm this effect. A simple model proposed here allows the calculation of tuning characteristics for a variety of bias schemes. The model shows that the perpendicular bias scheme mentioned above requires very much larger bias levels than does the parallel bias scheme in order to achieve the same tuning range with a particular ferrite tuner. However, further investigation with the model has led to the discovery that the use of perpendicular bias at low frequency and parallel bias at high frequency requires only a modest increase in the bias field. In effect, the ferrite is kept highly magnetized, reducing ferrite losses, and is tuned primarily by rotating the bias field direction with respect to the rf field direction. The resulting reduction in dissipation can significantly reduce the amount of ferrite required per cavity.

  16. Multi objective SNP selection using pareto optimality.

    PubMed

    Gumus, Ergun; Gormez, Zeliha; Kursun, Olcay

    2013-04-01

    Biomarker discovery is a challenging task of bioinformatics especially when targeting high dimensional problems such as SNP (single nucleotide polymorphism) datasets. Various types of feature selection methods can be applied to accomplish this task. Typically, using features versus class labels of samples in the training dataset, these methods aim at selecting feature subsets with maximal classification accuracies. Although finding such class-discriminative features is crucial, selection of relevant SNPs for maximizing other properties that exist in the nature of population genetics such as the correlation between genetic diversity and geographical distance of ethnic groups can also be equally important. In this work, a methodology using a multi objective optimization technique called Pareto Optimal is utilized for selecting SNP subsets offering both high classification accuracy and correlation between genomic and geographical distances. In this method, discriminatory power of an SNP is determined using mutual information and its contribution to the genomic-geographical correlation is estimated using its loadings on principal components. Combining these objectives, the proposed method identifies SNP subsets that can better discriminate ethnic groups than those obtained with sole mutual information and yield higher correlation than those obtained with sole principal components on the Human Genome Diversity Project (HGDP) SNP dataset.

  17. Optimal Sensor Selection for Health Monitoring Systems

    NASA Technical Reports Server (NTRS)

    Santi, L. Michael; Sowers, T. Shane; Aguilar, Robert B.

    2005-01-01

    Sensor data are the basis for performance and health assessment of most complex systems. Careful selection and implementation of sensors is critical to enable high fidelity system health assessment. A model-based procedure that systematically selects an optimal sensor suite for overall health assessment of a designated host system is described. This procedure, termed the Systematic Sensor Selection Strategy (S4), was developed at NASA John H. Glenn Research Center in order to enhance design phase planning and preparations for in-space propulsion health management systems (HMS). Information and capabilities required to utilize the S4 approach in support of design phase development of robust health diagnostics are outlined. A merit metric that quantifies diagnostic performance and overall risk reduction potential of individual sensor suites is introduced. The conceptual foundation for this merit metric is presented and the algorithmic organization of the S4 optimization process is described. Representative results from S4 analyses of a boost stage rocket engine previously under development as part of NASA's Next Generation Launch Technology (NGLT) program are presented.

  18. Optimal Portfolio Selection Under Concave Price Impact

    SciTech Connect

    Ma Jin; Song Qingshuo; Xu Jing; Zhang Jianfeng

    2013-06-15

    In this paper we study an optimal portfolio selection problem under instantaneous price impact. Based on some empirical analysis in the literature, we model such impact as a concave function of the trading size when the trading size is small. The price impact can be thought of as either a liquidity cost or a transaction cost, but the concavity nature of the cost leads to some fundamental difference from those in the existing literature. We show that the problem can be reduced to an impulse control problem, but without fixed cost, and that the value function is a viscosity solution to a special type of Quasi-Variational Inequality (QVI). We also prove directly (without using the solution to the QVI) that the optimal strategy exists and more importantly, despite the absence of a fixed cost, it is still in a 'piecewise constant' form, reflecting a more practical perspective.

  19. Separator profile selection for optimal battery performance

    NASA Astrophysics Data System (ADS)

    Whear, J. Kevin

    Battery performance, depending on the application, is normally defined by power delivery, electrical capacity, cycling regime and life in service. In order to meet the various performance goals, the Battery Design Engineer can vary things such as grid alloys, paste formulations, number of plates and methods of construction. Another design option available to optimize the battery performance is the separator profile. The goal of this paper is to demonstrate how separator profile selection can be utilized to optimize battery performance and manufacturing efficiencies. Also time will be given to explore novel separator profiles which may bring even greater benefits in the future. All major lead-acid application will be considered including automotive, motive power and stationary.

  20. Selected Isotopes for Optimized Fuel Assembly Tags

    SciTech Connect

    Gerlach, David C.; Mitchell, Mark R.; Reid, Bruce D.; Gesh, Christopher J.; Hurley, David E.

    2008-10-01

    In support of our ongoing signatures project we present information on 3 isotopes selected for possible application in optimized tags that could be applied to fuel assemblies to provide an objective measure of burnup. 1. Important factors for an optimized tag are compatibility with the reactor environment (corrosion resistance), low radioactive activation, at least 2 stable isotopes, moderate neutron absorption cross-section, which gives significant changes in isotope ratios over typical fuel assembly irradiation levels, and ease of measurement in the SIMS machine 2. From the candidate isotopes presented in the 3rd FY 08 Quarterly Report, the most promising appear to be Titanium, Hafnium, and Platinum. The other candidate isotopes (Iron, Tungsten, exhibited inadequate corrosion resistance and/or had neutron capture cross-sections either too high or too low for the burnup range of interest.

  1. Piezoelectric Tuner Compensation of Lorentz Detuning in Superconducting Cavities

    SciTech Connect

    G. Davis; Jean Delayen

    2003-05-12

    Pulsed operation of superconducting cavities can induce large variations of the resonant frequency through excitation of the mechanical modes by the radiation pressure. The phase and amplitude control system must be able to accommodate this frequency variation; this can be accomplished by increasing the capability of the rf power source. Alternatively, a piezo electric tuner can be activated at the same repetition rate as the rf to counteract the effect of the radiation pressure. We have demonstrated such a system on the prototype medium beta SNS cryomodule [1] with a reduction of the dynamic Lorentz detuning during the rf pulse by a factor of 3. We have also measured the amplitude and phase of the transfer function of the piezo control system (from input voltage to cavity frequency) up to several kHz [2].

  2. Tests of a tuner for a 325 MHz SRF spoke resonator

    SciTech Connect

    Pishchalnikov, Y.; Borissov, E.; Khabiboulline, T.; Madrak, R.; Pilipenko, R.; Ristori, L.; Schappert, W.; /Fermilab

    2011-03-01

    Fermilab is developing 325 MHz SRF spoke cavities for the proposed Project X. A compact fast/slow tuner has been developed for final tuning of the resonance frequency of the cavity after cooling down to operating temperature and to compensate microphonics and Lorentz force detuning [2]. The modified tuner design and results of 4.5K tests of the first prototype are presented. The performance of lever tuners for the SSR1 spoke resonator prototype has been measured during recent CW and pulsed tests in the Fermilab SCTF. The tuner met or exceeded all design goals and has been used to successfully: (1) Bring the cold cavity to the operating frequency; (2) Compensate for dynamic Lorentz force detuning; and (3) Compensate for frequency detuning of the cavity due to changes in the He bath pressure.

  3. Selectively-informed particle swarm optimization.

    PubMed

    Gao, Yang; Du, Wenbo; Yan, Gang

    2015-01-01

    Particle swarm optimization (PSO) is a nature-inspired algorithm that has shown outstanding performance in solving many realistic problems. In the original PSO and most of its variants all particles are treated equally, overlooking the impact of structural heterogeneity on individual behavior. Here we employ complex networks to represent the population structure of swarms and propose a selectively-informed PSO (SIPSO), in which the particles choose different learning strategies based on their connections: a densely-connected hub particle gets full information from all of its neighbors while a non-hub particle with few connections can only follow a single yet best-performed neighbor. Extensive numerical experiments on widely-used benchmark functions show that our SIPSO algorithm remarkably outperforms the PSO and its existing variants in success rate, solution quality, and convergence speed. We also explore the evolution process from a microscopic point of view, leading to the discovery of different roles that the particles play in optimization. The hub particles guide the optimization process towards correct directions while the non-hub particles maintain the necessary population diversity, resulting in the optimum overall performance of SIPSO. These findings deepen our understanding of swarm intelligence and may shed light on the underlying mechanism of information exchange in natural swarm and flocking behaviors. PMID:25787315

  4. Selectively-informed particle swarm optimization

    PubMed Central

    Gao, Yang; Du, Wenbo; Yan, Gang

    2015-01-01

    Particle swarm optimization (PSO) is a nature-inspired algorithm that has shown outstanding performance in solving many realistic problems. In the original PSO and most of its variants all particles are treated equally, overlooking the impact of structural heterogeneity on individual behavior. Here we employ complex networks to represent the population structure of swarms and propose a selectively-informed PSO (SIPSO), in which the particles choose different learning strategies based on their connections: a densely-connected hub particle gets full information from all of its neighbors while a non-hub particle with few connections can only follow a single yet best-performed neighbor. Extensive numerical experiments on widely-used benchmark functions show that our SIPSO algorithm remarkably outperforms the PSO and its existing variants in success rate, solution quality, and convergence speed. We also explore the evolution process from a microscopic point of view, leading to the discovery of different roles that the particles play in optimization. The hub particles guide the optimization process towards correct directions while the non-hub particles maintain the necessary population diversity, resulting in the optimum overall performance of SIPSO. These findings deepen our understanding of swarm intelligence and may shed light on the underlying mechanism of information exchange in natural swarm and flocking behaviors. PMID:25787315

  5. Selectively-informed particle swarm optimization

    NASA Astrophysics Data System (ADS)

    Gao, Yang; Du, Wenbo; Yan, Gang

    2015-03-01

    Particle swarm optimization (PSO) is a nature-inspired algorithm that has shown outstanding performance in solving many realistic problems. In the original PSO and most of its variants all particles are treated equally, overlooking the impact of structural heterogeneity on individual behavior. Here we employ complex networks to represent the population structure of swarms and propose a selectively-informed PSO (SIPSO), in which the particles choose different learning strategies based on their connections: a densely-connected hub particle gets full information from all of its neighbors while a non-hub particle with few connections can only follow a single yet best-performed neighbor. Extensive numerical experiments on widely-used benchmark functions show that our SIPSO algorithm remarkably outperforms the PSO and its existing variants in success rate, solution quality, and convergence speed. We also explore the evolution process from a microscopic point of view, leading to the discovery of different roles that the particles play in optimization. The hub particles guide the optimization process towards correct directions while the non-hub particles maintain the necessary population diversity, resulting in the optimum overall performance of SIPSO. These findings deepen our understanding of swarm intelligence and may shed light on the underlying mechanism of information exchange in natural swarm and flocking behaviors.

  6. Quantum dot laser optimization: selectively doped layers

    NASA Astrophysics Data System (ADS)

    Korenev, Vladimir V.; Konoplev, Sergey S.; Savelyev, Artem V.; Shernyakov, Yurii M.; Maximov, Mikhail V.; Zhukov, Alexey E.

    2016-08-01

    Edge emitting quantum dot (QD) lasers are discussed. It has been recently proposed to use modulation p-doping of the layers that are adjacent to QD layers in order to control QD's charge state. Experimentally it has been proven useful to enhance ground state lasing and suppress the onset of excited state lasing at high injection. These results have been also confirmed with numerical calculations involving solution of drift-diffusion equations. However, deep understanding of physical reasons for such behavior and laser optimization requires analytical approaches to the problem. In this paper, under a set of assumptions we provide an analytical model that explains major effects of selective p-doping. Capture rates of elections and holes can be calculated by solving Poisson equations for electrons and holes around the charged QD layer. The charge itself is ruled by capture rates and selective doping concentration. We analyzed this self-consistent set of equations and showed that it can be used to optimize QD laser performance and to explain underlying physics.

  7. Proof-of-principle Experiment of a Ferroelectric Tuner for the 1.3 GHz Cavity

    SciTech Connect

    Choi,E.M.; Hahn, H.; Shchelkunov, S. V.; Hirshfield, J.; Kazakov, S.

    2009-01-01

    A novel tuner has been developed by the Omega-P company to achieve fast control of the accelerator RF cavity frequency. The tuner is based on the ferroelectric property which has a variable dielectric constant as function of applied voltage. Tests using a Brookhaven National Laboratory (BNL) 1.3 GHz electron gun cavity have been carried out for a proof-of-principle experiment of the ferroelectric tuner. Two different methods were used to determine the frequency change achieved with the ferroelectric tuner (FT). The first method is based on a S11 measurement at the tuner port to find the reactive impedance change when the voltage is applied. The reactive impedance change then is used to estimate the cavity frequency shift. The second method is a direct S21 measurement of the frequency shift in the cavity with the tuner connected. The estimated frequency change from the reactive impedance measurement due to 5 kV is in the range between 3.2 kHz and 14 kHz, while 9 kHz is the result from the direct measurement. The two methods are in reasonable agreement. The detail description of the experiment and the analysis are discussed in the paper.

  8. OPTIMAL TIME-SERIES SELECTION OF QUASARS

    SciTech Connect

    Butler, Nathaniel R.; Bloom, Joshua S.

    2011-03-15

    We present a novel method for the optimal selection of quasars using time-series observations in a single photometric bandpass. Utilizing the damped random walk model of Kelly et al., we parameterize the ensemble quasar structure function in Sloan Stripe 82 as a function of observed brightness. The ensemble model fit can then be evaluated rigorously for and calibrated with individual light curves with no parameter fitting. This yields a classification in two statistics-one describing the fit confidence and the other describing the probability of a false alarm-which can be tuned, a priori, to achieve high quasar detection fractions (99% completeness with default cuts), given an acceptable rate of false alarms. We establish the typical rate of false alarms due to known variable stars as {approx}<3% (high purity). Applying the classification, we increase the sample of potential quasars relative to those known in Stripe 82 by as much as 29%, and by nearly a factor of two in the redshift range 2.5 < z < 3, where selection by color is extremely inefficient. This represents 1875 new quasars in a 290 deg{sup 2} field. The observed rates of both quasars and stars agree well with the model predictions, with >99% of quasars exhibiting the expected variability profile. We discuss the utility of the method at high redshift and in the regime of noisy and sparse data. Our time-series selection complements well-independent selection based on quasar colors and has strong potential for identifying high-redshift quasars for Baryon Acoustic Oscillations and other cosmology studies in the LSST era.

  9. Optimized wavelength selection for molecular absorption thermometry.

    PubMed

    An, Xinliang; Caswell, Andrew W; Lipor, John J; Sanders, Scott T

    2015-04-01

    A differential evolution (DE) algorithm is applied to a recently developed spectroscopic objective function to select wavelengths that optimize the temperature precision of water absorption thermometry. DE reliably finds optima even when many-wavelength sets are chosen from large populations of wavelengths (here 120 000 wavelengths from a spectrum with 0.002 cm(-1) resolution calculated by 16 856 transitions). Here, we study sets of fixed wavelengths in the 7280-7520 cm(-1) range. When optimizing the thermometer for performance within a narrow temperature range, the results confirm that the best temperature precision is obtained if all the available measurement time is split judiciously between the two most temperature-sensitive wavelengths. In the wide temperature range case (thermometer must perform throughout 280-2800 K), we find (1) the best four-wavelength set outperforms the best two-wavelength set by an average factor of 2, and (2) a complete spectrum (all 120 000 wavelengths from 16 856 transitions) is 4.3 times worse than the best two-wavelength set. Key implications for sensor designers include: (1) from the perspective of spectroscopic temperature sensitivity, it is usually sufficient to monitor two or three wavelengths, depending on the sensor's anticipated operating temperature range; and (2) although there is a temperature precision penalty to monitoring a complete spectrum, that penalty may be small enough, particularly at elevated pressure, to justify the complete-spectrum approach in many applications.

  10. MaNGA: Target selection and Optimization

    NASA Astrophysics Data System (ADS)

    Wake, David

    2016-01-01

    The 6-year SDSS-IV MaNGA survey will measure spatially resolved spectroscopy for 10,000 nearby galaxies using the Sloan 2.5m telescope and the BOSS spectrographs with a new fiber arrangement consisting of 17 individually deployable IFUs. We present the simultaneous design of the target selection and IFU size distribution to optimally meet our targeting requirements. The requirements for the main samples were to use simple cuts in redshift and magnitude to produce an approximately flat number density of targets as a function of stellar mass, ranging from 1x109 to 1x1011 M⊙, and radial coverage to either 1.5 (Primary sample) or 2.5 (Secondary sample) effective radii, while maximizing S/N and spatial resolution. In addition we constructed a "Color-Enhanced" sample where we required 25% of the targets to have an approximately flat number density in the color and mass plane. We show how these requirements are met using simple absolute magnitude (and color) dependent redshift cuts applied to an extended version of the NASA Sloan Atlas (NSA), how this determines the distribution of IFU sizes and the resulting properties of the MaNGA sample.

  11. MaNGA: Target selection and Optimization

    NASA Astrophysics Data System (ADS)

    Wake, David

    2015-01-01

    The 6-year SDSS-IV MaNGA survey will measure spatially resolved spectroscopy for 10,000 nearby galaxies using the Sloan 2.5m telescope and the BOSS spectrographs with a new fiber arrangement consisting of 17 individually deployable IFUs. We present the simultaneous design of the target selection and IFU size distribution to optimally meet our targeting requirements. The requirements for the main samples were to use simple cuts in redshift and magnitude to produce an approximately flat number density of targets as a function of stellar mass, ranging from 1x109 to 1x1011 M⊙, and radial coverage to either 1.5 (Primary sample) or 2.5 (Secondary sample) effective radii, while maximizing S/N and spatial resolution. In addition we constructed a 'Color-Enhanced' sample where we required 25% of the targets to have an approximately flat number density in the color and mass plane. We show how these requirements are met using simple absolute magnitude (and color) dependent redshift cuts applied to an extended version of the NASA Sloan Atlas (NSA), how this determines the distribution of IFU sizes and the resulting properties of the MaNGA sample.

  12. Perpendicularly Biased YIG Tuners for the Fermilab Recycler 52.809 MHz Cavities

    SciTech Connect

    Madrak, R.; Kashikhin, V.; Makarov, A.; Wildman, D.

    2013-09-13

    For NOvA and future experiments requiring high intensity proton beams, Fermilab is in the process of upgrading the existing accelerator complex for increased proton production. One such improvement is to reduce the Main Injector cycle time, by performing slip stacking, previously done in the Main Injector, in the now repurposed Recycler Ring. Recycler slip stacking requires new tuneable RF cavities, discussed separately in these proceedings. These are quarter wave cavities resonant at 52.809 MHz with a 10 kHz tuning range. The 10 kHz range is achieved by use of a tuner which has an electrical length of approximately one half wavelength at 52.809 MHz. The tuner is constructed from 31/8” diameter rigid coaxial line, with 5 inches of its length containing perpendicularly biased, Al doped Yttrium Iron Garnet (YIG). The tuner design, measurements, and high power test results are presented.

  13. Tuner control system of Spoke012 SRF cavity for C-ADS injector I

    NASA Astrophysics Data System (ADS)

    Liu, Na; Sun, Yi; Wang, Guang-Wei; Mi, Zheng-Hui; Lin, Hai-Ying; Wang, Qun-Yao; Liu, Rong; Ma, Xin-Peng

    2016-09-01

    A new tuner control system for spoke superconducting radio frequency (SRF) cavities has been developed and applied to cryomodule I of the C-ADS injector I at the Institute of High Energy Physics, Chinese Academy of Sciences. We have successfully implemented the tuner controller based on Programmable Logic Controller (PLC) for the first time and achieved a cavity tuning phase error of ±0.7° (about ±4 Hz peak to peak) in the presence of electromechanical coupled resonance. This paper presents preliminary experimental results based on the PLC tuner controller under proton beam commissioning. Supported by Proton linac accelerator I of China Accelerator Driven sub-critical System (Y12C32W129)

  14. Slug tuner effect on the field stabilization of the drift tube linac

    NASA Astrophysics Data System (ADS)

    Kim, Han-Sung

    2015-02-01

    In a drift tube linac (DTL), the accelerating field is stabilized against external perturbation, through resonant coupling between each cell by using post couplers. For proper field stabilization tuning, the frequency band between the post mode and the cavity mode should be closed. In addition, the field profile along the beam axis of the highest post mode should be similar to that of the TM011 cavity mode. As a conventional method to correct the resonance frequency and to make the accelerating field flat, slug tuners are incorporated. We observed that the similarity of field profiles between the highest post mode and the TM011 cavity mode disappeared when the slug tuners were inserted too much into the DTL tank. To achieve field stabilization tuning, we limited the slug tuner insertion and used a tuning ring around each post coupler to tune the resonant frequency of the DTL tank. The details of the effect of a slug tuner on the field stabilization tuning and the solution to the resonant frequency tuning problem caused by limited slug insertion will be presented in this paper.

  15. Development of a Movable Plunger Tuner for the High Power RF Cavity for the PEP II B Factory

    SciTech Connect

    Schwarz, H.D.; Fant, K.; Neubauer, Mark Stephen; Rimmer, R.A.; /LBL, Berkeley

    2011-08-26

    A 10 cm diameter by 5 cm travel plunger tuner was developed for the PEP-II RF copper cavity system. The single cell cavity including the tuner is designed to operate up to 150 kW of dissipated RF power. Spring finger contacts to protect the bellows from RF power are specially placed 8.5 cm away from the inside wall of the cavity to avoid fundamental and higher order mode resonances. The spring fingers are made of dispersion-strengthened copper to accommodate relatively high heating. The design, alignment, testing and performance of the tuner is described.

  16. On Optimal Input Design and Model Selection for Communication Channels

    SciTech Connect

    Li, Yanyan; Djouadi, Seddik M; Olama, Mohammed M

    2013-01-01

    In this paper, the optimal model (structure) selection and input design which minimize the worst case identification error for communication systems are provided. The problem is formulated using metric complexity theory in a Hilbert space setting. It is pointed out that model selection and input design can be handled independently. Kolmogorov n-width is used to characterize the representation error introduced by model selection, while Gel fand and Time n-widths are used to represent the inherent error introduced by input design. After the model is selected, an optimal input which minimizes the worst case identification error is shown to exist. In particular, it is proven that the optimal model for reducing the representation error is a Finite Impulse Response (FIR) model, and the optimal input is an impulse at the start of the observation interval. FIR models are widely popular in communication systems, such as, in Orthogonal Frequency Division Multiplexing (OFDM) systems.

  17. Optimization of ultrasonic transducers for selective guided wave actuation

    NASA Astrophysics Data System (ADS)

    Miszczynski, Mateusz; Packo, Pawel; Zbyrad, Paulina; Stepinski, Tadeusz; Uhl, Tadeusz; Lis, Jerzy; Wiatr, Kazimierz

    2016-04-01

    The application of guided waves using surface-bonded piezoceramic transducers for nondestructive testing (NDT) and Structural Health Monitoring (SHM) have shown great potential. However, due to difficulty in identification of individual wave modes resulting from their dispersive and multi-modal nature, selective mode excitement methods are highly desired. The presented work focuses on an optimization-based approach to design of a piezoelectric transducer for selective guided waves generation. The concept of the presented framework involves a Finite Element Method (FEM) model in the optimization process. The material of the transducer is optimized in topological sense with the aim of tuning piezoelectric properties for actuation of specific guided wave modes.

  18. Digital logic optimization using selection operators

    NASA Technical Reports Server (NTRS)

    Whitaker, Sterling R. (Inventor); Miles, Lowell H. (Inventor); Cameron, Eric G. (Inventor); Gambles, Jody W. (Inventor)

    2004-01-01

    According to the invention, a digital design method for manipulating a digital circuit netlist is disclosed. In one step, a first netlist is loaded. The first netlist is comprised of first basic cells that are comprised of first kernel cells. The first netlist is manipulated to create a second netlist. The second netlist is comprised of second basic cells that are comprised of second kernel cells. A percentage of the first and second kernel cells are selection circuits. There is less chip area consumed in the second basic cells than in the first basic cells. The second netlist is stored. In various embodiments, the percentage could be 2% or more, 5% or more, 10% or more, 20% or more, 30% or more, or 40% or more.

  19. Optimized Selective Coatings for Solar Collectors

    NASA Technical Reports Server (NTRS)

    Mcdonald, G.; Curtis, H. B.

    1967-01-01

    The spectral reflectance properties of black nickel electroplated over stainless steel and of black copper produced by oxidation of copper sheet were measured for various plating times of black nickel and for various lengths of time of oxidation of the copper sheet, and compared to black chrome over nickel and to converted zinc. It was determined that there was an optimum time for both plating of black nickel and for the oxidation of copper black. At this time the solar selective properties show high absorptance in the solar spectrum and low emittance in the infrared. The conditions are compared for production of optimum optical properties for black nickel, black copper, black chrome, and two black zinc conversions which at the same conditions had absorptances of 0.84, 0.90, 0.95, 0.84, and 0.92, respectively, and emittances of 0.18, 0.08, 0.09, 0.10, and 0.08, respectively.

  20. Neural network optimization, components, and design selection

    NASA Astrophysics Data System (ADS)

    Weller, Scott W.

    1990-07-01

    Neural Networks are part of a revived technology which has received a lot of hype in recent years. As is apt to happen in any hyped technology, jargon and predictions make its assimilation and application difficult. Nevertheless, Neural Networks have found use in a number of areas, working on non-trivial and noncontrived problems. For example, one net has been trained to "read", translating English text into phoneme sequences. Other applications of Neural Networks include data base manipulation and the solving of muting and classification types of optimization problems. Neural Networks are constructed from neurons, which in electronics or software attempt to model but are not constrained by the real thing, i.e., neurons in our gray matter. Neurons are simple processing units connected to many other neurons over pathways which modify the incoming signals. A single synthetic neuron typically sums its weighted inputs, runs this sum through a non-linear function, and produces an output. In the brain, neurons are connected in a complex topology: in hardware/software the topology is typically much simpler, with neurons lying side by side, forming layers of neurons which connect to the layer of neurons which receive their outputs. This simplistic model is much easier to construct than the real thing, and yet can solve real problems. The information in a network, or its "memory", is completely contained in the weights on the connections from one neuron to another. Establishing these weights is called "training" the network. Some networks are trained by design -- once constructed no further learning takes place. Other types of networks require iterative training once wired up, but are not trainable once taught Still other types of networks can continue to learn after initial construction. The main benefit to using Neural Networks is their ability to work with conflicting or incomplete ("fuzzy") data sets. This ability and its usefulness will become evident in the following

  1. Efficient Simulation Budget Allocation for Selecting an Optimal Subset

    NASA Technical Reports Server (NTRS)

    Chen, Chun-Hung; He, Donghai; Fu, Michael; Lee, Loo Hay

    2008-01-01

    We consider a class of the subset selection problem in ranking and selection. The objective is to identify the top m out of k designs based on simulated output. Traditional procedures are conservative and inefficient. Using the optimal computing budget allocation framework, we formulate the problem as that of maximizing the probability of correc tly selecting all of the top-m designs subject to a constraint on the total number of samples available. For an approximation of this corre ct selection probability, we derive an asymptotically optimal allocat ion and propose an easy-to-implement heuristic sequential allocation procedure. Numerical experiments indicate that the resulting allocatio ns are superior to other methods in the literature that we tested, and the relative efficiency increases for larger problems. In addition, preliminary numerical results indicate that the proposed new procedur e has the potential to enhance computational efficiency for simulation optimization.

  2. Opposing selection and environmental variation modify optimal timing of breeding.

    PubMed

    Tarwater, Corey E; Beissinger, Steven R

    2013-09-17

    Studies of evolution in wild populations often find that the heritable phenotypic traits of individuals producing the most offspring do not increase proportionally in the population. This paradox may arise when phenotypic traits influence both fecundity and viability and when there is a tradeoff between these fitness components, leading to opposing selection. Such tradeoffs are the foundation of life history theory, but they are rarely investigated in selection studies. Timing of breeding is a classic example of a heritable trait under directional selection that does not result in an evolutionary response. Using a 22-y study of a tropical parrot, we show that opposing viability and fecundity selection on the timing of breeding is common and affects optimal breeding date, defined by maximization of fitness. After accounting for sampling error, the directions of viability (positive) and fecundity (negative) selection were consistent, but the magnitude of selection fluctuated among years. Environmental conditions (rainfall and breeding density) primarily and breeding experience secondarily modified selection, shifting optimal timing among individuals and years. In contrast to other studies, viability selection was as strong as fecundity selection, late-born juveniles had greater survival than early-born juveniles, and breeding later in the year increased fitness under opposing selection. Our findings provide support for life history tradeoffs influencing selection on phenotypic traits, highlight the need to unify selection and life history theory, and illustrate the importance of monitoring survival as well as reproduction for understanding phenological responses to climate change.

  3. Opposing selection and environmental variation modify optimal timing of breeding.

    PubMed

    Tarwater, Corey E; Beissinger, Steven R

    2013-09-17

    Studies of evolution in wild populations often find that the heritable phenotypic traits of individuals producing the most offspring do not increase proportionally in the population. This paradox may arise when phenotypic traits influence both fecundity and viability and when there is a tradeoff between these fitness components, leading to opposing selection. Such tradeoffs are the foundation of life history theory, but they are rarely investigated in selection studies. Timing of breeding is a classic example of a heritable trait under directional selection that does not result in an evolutionary response. Using a 22-y study of a tropical parrot, we show that opposing viability and fecundity selection on the timing of breeding is common and affects optimal breeding date, defined by maximization of fitness. After accounting for sampling error, the directions of viability (positive) and fecundity (negative) selection were consistent, but the magnitude of selection fluctuated among years. Environmental conditions (rainfall and breeding density) primarily and breeding experience secondarily modified selection, shifting optimal timing among individuals and years. In contrast to other studies, viability selection was as strong as fecundity selection, late-born juveniles had greater survival than early-born juveniles, and breeding later in the year increased fitness under opposing selection. Our findings provide support for life history tradeoffs influencing selection on phenotypic traits, highlight the need to unify selection and life history theory, and illustrate the importance of monitoring survival as well as reproduction for understanding phenological responses to climate change. PMID:24003118

  4. Local and global strategies for optimal selective mass scaling

    NASA Astrophysics Data System (ADS)

    Tkachuk, Anton; Bischoff, Manfred

    2014-06-01

    The problem of optimal selective mass scaling for linearized elasto-dynamics is discussed. Optimal selective mass scaling should provide solutions for dynamical problems that are close to the ones obtained with a lumped mass matrix, but at much smaller computational costs. It should be equally applicable to all structurally relevant load cases. The three main optimality criteria, namely eigenmode preservation, small number of non-zero entries and good conditioning of the mass matrix are explicitly formulated in the article. An example of optimal mass scaling which relies on redistribution of mass on a global system level is constructed. Alternative local mass scaling strategies are proposed and compared with existing methods using one modal and two transient numerical examples.

  5. A technique for monitoring fast tuner piezoactuator preload forces for superconducting rf cavities

    SciTech Connect

    Pischalnikov, Y.; Branlard, J.; Carcagno, R.; Chase, B.; Edwards, H.; Orris, D.; Makulski, A.; McGee, M.; Nehring, R.; Poloubotko, V.; Sylvester, C.; /Fermilab

    2007-06-01

    The technology for mechanically compensating Lorentz Force detuning in superconducting RF cavities has already been developed at DESY. One technique is based on commercial piezoelectric actuators and was successfully demonstrated on TESLA cavities [1]. Piezo actuators for fast tuners can operate in a frequency range up to several kHz; however, it is very important to maintain a constant static force (preload) on the piezo actuator in the range of 10 to 50% of its specified blocking force. Determining the preload force during cool-down, warm-up, or re-tuning of the cavity is difficult without instrumentation, and exceeding the specified range can permanently damage the piezo stack. A technique based on strain gauge technology for superconducting magnets has been applied to fast tuners for monitoring the preload on the piezoelectric assembly. The design and testing of piezo actuator preload sensor technology is discussed. Results from measurements of preload sensors installed on the tuner of the Capture Cavity II (CCII)[2] tested at FNAL are presented. These results include measurements during cool-down, warmup, and cavity tuning along with dynamic Lorentz force compensation.

  6. Training set optimization under population structure in genomic selection

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The optimization of the training set (TRS) in genomic selection (GS) has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the Coefficient of D...

  7. Optimal Financial Aid Policies for a Selective University.

    ERIC Educational Resources Information Center

    Ehrenberg, Ronald G.; Sherman, Daniel R.

    1984-01-01

    This paper provides a model of optimal financial aid policies for a selective university. The model implies that the financial aid package to be offered to each category of admitted applicants depends on the elasticity of the fraction who accept offers of admission with respect to the financial aid package offered them. (Author/SSH)

  8. Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection

    ERIC Educational Resources Information Center

    Mulder, Joris; van der Linden, Wim J.

    2009-01-01

    Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the…

  9. Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

    NASA Technical Reports Server (NTRS)

    2004-01-01

    Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate

  10. Optimizing Ligand Efficiency of Selective Androgen Receptor Modulators (SARMs).

    PubMed

    Handlon, Anthony L; Schaller, Lee T; Leesnitzer, Lisa M; Merrihew, Raymond V; Poole, Chuck; Ulrich, John C; Wilson, Joseph W; Cadilla, Rodolfo; Turnbull, Philip

    2016-01-14

    A series of selective androgen receptor modulators (SARMs) containing the 1-(trifluoromethyl)benzyl alcohol core have been optimized for androgen receptor (AR) potency and drug-like properties. We have taken advantage of the lipophilic ligand efficiency (LLE) parameter as a guide to interpret the effect of structural changes on AR activity. Over the course of optimization efforts the LLE increased over 3 log units leading to a SARM 43 with nanomolar potency, good aqueous kinetic solubility (>700 μM), and high oral bioavailability in rats (83%).

  11. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

    PubMed Central

    Faltermeier, Rupert; Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander

    2015-01-01

    Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses. PMID:26693250

  12. Improved Clonal Selection Algorithm Combined with Ant Colony Optimization

    NASA Astrophysics Data System (ADS)

    Gao, Shangce; Wang, Wei; Dai, Hongwei; Li, Fangjia; Tang, Zheng

    Both the clonal selection algorithm (CSA) and the ant colony optimization (ACO) are inspired by natural phenomena and are effective tools for solving complex problems. CSA can exploit and explore the solution space parallely and effectively. However, it can not use enough environment feedback information and thus has to do a large redundancy repeat during search. On the other hand, ACO is based on the concept of indirect cooperative foraging process via secreting pheromones. Its positive feedback ability is nice but its convergence speed is slow because of the little initial pheromones. In this paper, we propose a pheromone-linker to combine these two algorithms. The proposed hybrid clonal selection and ant colony optimization (CSA-ACO) reasonably utilizes the superiorities of both algorithms and also overcomes their inherent disadvantages. Simulation results based on the traveling salesman problems have demonstrated the merit of the proposed algorithm over some traditional techniques.

  13. Monte Carlo optimization for site selection of new chemical plants.

    PubMed

    Cai, Tianxing; Wang, Sujing; Xu, Qiang

    2015-11-01

    Geographic distribution of chemical manufacturing sites has significant impact on the business sustainability of industrial development and regional environmental sustainability as well. The common site selection rules have included the evaluation of the air quality impact of a newly constructed chemical manufacturing site to surrounding communities. In order to achieve this target, the simultaneous consideration should cover the regional background air-quality information, the emissions of new manufacturing site, and statistical pattern of local meteorological conditions. According to the above information, the risk assessment can be conducted for the potential air-quality impacts from candidate locations of a new chemical manufacturing site, and thus the optimization of the final site selection can be achieved by minimizing its air-quality impacts. This paper has provided a systematic methodology for the above purpose. There are total two stages of modeling and optimization work: i) Monte Carlo simulation for the purpose to identify background pollutant concentration based on currently existing emission sources and regional statistical meteorological conditions; and ii) multi-objective (simultaneous minimization of both peak pollutant concentration and standard deviation of pollutant concentration spatial distribution at air-quality concern regions) Monte Carlo optimization for optimal location selection of new chemical manufacturing sites according to their design data of potential emission. This study can be helpful to both determination of the potential air-quality impact for geographic distribution of multiple chemical plants with respect to regional statistical meteorological conditions, and the identification of an optimal site for each new chemical manufacturing site with the minimal environment impact to surrounding communities. The efficacy of the developed methodology has been demonstrated through the case studies.

  14. Tuner and radiation shield for planar electron paramagnetic resonance microresonators

    SciTech Connect

    Narkowicz, Ryszard; Suter, Dieter

    2015-02-15

    Planar microresonators provide a large boost of sensitivity for small samples. They can be manufactured lithographically to a wide range of target parameters. The coupler between the resonator and the microwave feedline can be integrated into this design. To optimize the coupling and to compensate manufacturing tolerances, it is sometimes desirable to have a tuning element available that can be adjusted when the resonator is connected to the spectrometer. This paper presents a simple design that allows one to bring undercoupled resonators into the condition for critical coupling. In addition, it also reduces radiation losses and thereby increases the quality factor and the sensitivity of the resonator.

  15. Optimization of Parameter Selection for Partial Least Squares Model Development

    NASA Astrophysics Data System (ADS)

    Zhao, Na; Wu, Zhi-Sheng; Zhang, Qiao; Shi, Xin-Yuan; Ma, Qun; Qiao, Yan-Jiang

    2015-07-01

    In multivariate calibration using a spectral dataset, it is difficult to optimize nonsystematic parameters in a quantitative model, i.e., spectral pretreatment, latent factors and variable selection. In this study, we describe a novel and systematic approach that uses a processing trajectory to select three parameters including different spectral pretreatments, variable importance in the projection (VIP) for variable selection and latent factors in the Partial Least-Square (PLS) model. The root mean square errors of calibration (RMSEC), the root mean square errors of prediction (RMSEP), the ratio of standard error of prediction to standard deviation (RPD), and the determination coefficient of calibration (Rcal2) and validation (Rpre2) were simultaneously assessed to optimize the best modeling path. We used three different near-infrared (NIR) datasets, which illustrated that there was more than one modeling path to ensure good modeling. The PLS model optimizes modeling parameters step-by-step, but the robust model described here demonstrates better efficiency than other published papers.

  16. Hyperopt: a Python library for model selection and hyperparameter optimization

    NASA Astrophysics Data System (ADS)

    Bergstra, James; Komer, Brent; Eliasmith, Chris; Yamins, Dan; Cox, David D.

    2015-01-01

    Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization. This efficiency makes it appropriate for optimizing the hyperparameters of machine learning algorithms that are slow to train. The Hyperopt library provides algorithms and parallelization infrastructure for performing hyperparameter optimization (model selection) in Python. This paper presents an introductory tutorial on the usage of the Hyperopt library, including the description of search spaces, minimization (in serial and parallel), and the analysis of the results collected in the course of minimization. This paper also gives an overview of Hyperopt-Sklearn, a software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a single large hyperparameter optimization problem. We use Hyperopt to define a search space that encompasses many standard components (e.g. SVM, RF, KNN, PCA, TFIDF) and common patterns of composing them together. We demonstrate, using search algorithms in Hyperopt and standard benchmarking data sets (MNIST, 20-newsgroups, convex shapes), that searching this space is practical and effective. In particular, we improve on best-known scores for the model space for both MNIST and convex shapes. The paper closes with some discussion of ongoing and future work.

  17. 3D genome tuner: compare multiple circular genomes in a 3D context.

    PubMed

    Wang, Qi; Liang, Qun; Zhang, Xiuqing

    2009-09-01

    Circular genomes, being the largest proportion of sequenced genomes, play an important role in genome analysis. However, traditional 2D circular map only provides an overview and annotations of genome but does not offer feature-based comparison. For remedying these shortcomings, we developed 3D Genome Tuner, a hybrid of circular map and comparative map tools. Its capability of viewing comparisons between multiple circular maps in a 3D space offers great benefits to the study of comparative genomics. The program is freely available (under an LGPL licence) at http://sourceforge.net/projects/dgenometuner.

  18. State-Selective Excitation of Quantum Systems via Geometrical Optimization.

    PubMed

    Chang, Bo Y; Shin, Seokmin; Sola, Ignacio R

    2015-09-01

    We lay out the foundations of a general method of quantum control via geometrical optimization. We apply the method to state-selective population transfer using ultrashort transform-limited pulses between manifolds of levels that may represent, e.g., state-selective transitions in molecules. Assuming that certain states can be prepared, we develop three implementations: (i) preoptimization, which implies engineering the initial state within the ground manifold or electronic state before the pulse is applied; (ii) postoptimization, which implies engineering the final state within the excited manifold or target electronic state, after the pulse; and (iii) double-time optimization, which uses both types of time-ordered manipulations. We apply the schemes to two important dynamical problems: To prepare arbitrary vibrational superposition states on the target electronic state and to select weakly coupled vibrational states. Whereas full population inversion between the electronic states only requires control at initial time in all of the ground vibrational levels, only very specific superposition states can be prepared with high fidelity by either pre- or postoptimization mechanisms. Full state-selective population inversion requires manipulating the vibrational coherences in the ground electronic state before the optical pulse is applied and in the excited electronic state afterward, but not during all times.

  19. Field of view selection for optimal airborne imaging sensor performance

    NASA Astrophysics Data System (ADS)

    Goss, Tristan M.; Barnard, P. Werner; Fildis, Halidun; Erbudak, Mustafa; Senger, Tolga; Alpman, Mehmet E.

    2014-05-01

    The choice of the Field of View (FOV) of imaging sensors used in airborne targeting applications has major impact on the overall performance of the system. Conducting a market survey from published data on sensors used in stabilized airborne targeting systems shows a trend of ever narrowing FOVs housed in smaller and lighter volumes. This approach promotes the ever increasing geometric resolution provided by narrower FOVs, while it seemingly ignores the influences the FOV selection has on the sensor's sensitivity, the effects of diffraction, the influences of sight line jitter and collectively the overall system performance. This paper presents a trade-off methodology to select the optimal FOV for an imaging sensor that is limited in aperture diameter by mechanical constraints (such as space/volume available and window size) by balancing the influences FOV has on sensitivity and resolution and thereby optimizing the system's performance. The methodology may be applied to staring array based imaging sensors across all wavebands from visible/day cameras through to long wave infrared thermal imagers. Some examples of sensor analysis applying the trade-off methodology are given that highlights the performance advantages that can be gained by maximizing the aperture diameters and choosing the optimal FOV for an imaging sensor used in airborne targeting applications.

  20. Some useful upper bounds for the selection of optimal profiles

    NASA Astrophysics Data System (ADS)

    Daripa, Prabir

    2012-08-01

    In enhanced oil recovery by chemical flooding within tertiary oil recovery, it is often necessary to choose optimal viscous profiles of the injected displacing fluids that reduce growth rates of hydrodynamic instabilities the most thereby substantially reducing the well-known fingering problem and improving oil recovery. Within the three-layer Hele-Shaw model, we show in this paper that selection of the optimal monotonic viscous profile of the middle-layer fluid based on well known theoretical upper bound formula [P. Daripa, G. Pasa, A simple derivation of an upper bound in the presence of a viscosity gradient in three-layer Hele-Shaw flows, Journal of Statistical Mechanics (2006) 11. http://dx.doi.org/10.1088/1742-5468/2006/01/P01014] agrees very well with that based on the computation of maximum growth rate of instabilities from solving the linearized stability problem. Thus, this paper proposes a very simple, fast method for selection of the optimal monotonic viscous profiles of the displacing fluids in multi-layer flows.

  1. ICRF antenna matching system with ferrite tuners for the Alcator C-Mod tokamak

    NASA Astrophysics Data System (ADS)

    Lin, Y.; Binus, A.; Wukitch, S. J.; Koert, P.; Murray, R.; Pfeiffer, A.

    2015-12-01

    Real-time fast ferrite tuning (FFT) has been successfully implemented on the ICRF antennas on Alcator C-Mod. The former prototypical FFT system on the E-port 2-strap antenna has been upgraded using new ferrite tuners that have been designed specifically for the operational parameters of the Alcator C-Mod ICRF system (˜ 80 MHz). Another similar FFT system, with two ferrite tuners and one fixed-length stub, has been installed on the transmission line of the D-port 2-strap antenna. These two systems share a Linux-server-based real-time controller. These FFT systems are able to achieve and maintain the reflected power to the transmitters to less than 1% in real time during the plasma discharges under almost all plasma conditions, and help ensure reliable high power operation of the antennas. The innovative field-aligned (FA) 4-strap antenna on J-port has been found to have an interesting feature of loading insensitivity vs. plasma conditions. This feature allows us to significantly improve the matching for the FA J-port antenna by installing carefully designed stubs on the two transmission lines. The reduction of the RF voltages in the transmission lines has enabled the FA J-port antenna to deliver 3.7 MW RF power to plasmas out of the 4 MW source power in high performance I-mode plasmas.

  2. A proof-of-principle experiment of the ferroelectric tuner for the 1.3 GHz gun cavity

    SciTech Connect

    Hahn,H.; Choi, E.; Shchelkunov, S. V.; Hirshfield, J.; Kazakov, S.; Shschelkunov, S.

    2009-05-04

    A novel ferroelectric frequency tuner was developed by the Ornega-P company and was tested at the Brookhaven National Laboratory on a 1.3 GHz RF cavity at room temperature. The tuner is based on the ferroelectric property of having a permittivity variable with an applied electric field. The achievable frequency tuning range can be estimated from the reactive impedance change due to an applied voltage via a S{sub 11} measurement at the tuner port. The frequency shift can be measured directly with a S{sub 21} measurement across the gun cavity with the tuner connected and activated. The frequency change due to an applied 5 kV obtained from the two methods is in reasonable agreement. The reactive impedance measurement yields a value in the range between 3.2 kHz and 14 kHz, while 9 kHz is the result from the direct measurement. The detail description of the experiment and the analysis will be discussed in the paper.

  3. Optimizing Hammermill Performance Through Screen Selection and Hammer Design

    SciTech Connect

    Neal A. Yancey; Tyler L. Westover; Christopher T. Wright

    2013-01-01

    Background: Mechanical preprocessing, which includes particle size reduction and mechanical separation, is one of the primary operations in the feedstock supply system for a lignocellulosic biorefinery. It is the means by which raw biomass from the field or forest is mechanically transformed into an on-spec feedstock with characteristics better suited for the fuel conversion process. Results: This work provides a general overview of the objectives and methodologies of mechanical preprocessing and then presents experimental results illustrating (1) improved size reduction via optimization of hammer mill configuration, (2) improved size reduction via pneumatic-assisted hammer milling, and (3) improved control of particle size and particle size distribution through proper selection of grinder process parameters. Conclusion: Optimal grinder configuration for maximal process throughput and efficiency is strongly dependent on feedstock type and properties, such moisture content. Tests conducted using a HG200 hammer grinder indicate that increasing the tip speed, optimizing hammer geometry, and adding pneumatic assist can increase grinder throughput as much as 400%.

  4. Optimal Selection of Threshold Value 'r' for Refined Multiscale Entropy.

    PubMed

    Marwaha, Puneeta; Sunkaria, Ramesh Kumar

    2015-12-01

    Refined multiscale entropy (RMSE) technique was introduced to evaluate complexity of a time series over multiple scale factors 't'. Here threshold value 'r' is updated as 0.15 times SD of filtered scaled time series. The use of fixed threshold value 'r' in RMSE sometimes assigns very close resembling entropy values to certain time series at certain temporal scale factors and is unable to distinguish different time series optimally. The present study aims to evaluate RMSE technique by varying threshold value 'r' from 0.05 to 0.25 times SD of filtered scaled time series and finding optimal 'r' values for each scale factor at which different time series can be distinguished more effectively. The proposed RMSE was used to evaluate over HRV time series of normal sinus rhythm subjects, patients suffering from sudden cardiac death, congestive heart failure, healthy adult male, healthy adult female and mid-aged female groups as well as over synthetic simulated database for different datalengths 'N' of 3000, 3500 and 4000. The proposed RMSE results in improved discrimination among different time series. To enhance the computational capability, empirical mathematical equations have been formulated for optimal selection of threshold values 'r' as a function of SD of filtered scaled time series and datalength 'N' for each scale factor 't'.

  5. Optimal subinterval selection approach for power system transient stability simulation

    SciTech Connect

    Kim, Soobae; Overbye, Thomas J.

    2015-10-21

    Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modal analysis using a single machine infinite bus (SMIB) system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. As a result, the performance of the proposed method is demonstrated with the GSO 37-bus system.

  6. Optimal subinterval selection approach for power system transient stability simulation

    DOE PAGESBeta

    Kim, Soobae; Overbye, Thomas J.

    2015-10-21

    Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modalmore » analysis using a single machine infinite bus (SMIB) system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. As a result, the performance of the proposed method is demonstrated with the GSO 37-bus system.« less

  7. Optimal experiment design for model selection in biochemical networks

    PubMed Central

    2014-01-01

    Background Mathematical modeling is often used to formalize hypotheses on how a biochemical network operates by discriminating between competing models. Bayesian model selection offers a way to determine the amount of evidence that data provides to support one model over the other while favoring simple models. In practice, the amount of experimental data is often insufficient to make a clear distinction between competing models. Often one would like to perform a new experiment which would discriminate between competing hypotheses. Results We developed a novel method to perform Optimal Experiment Design to predict which experiments would most effectively allow model selection. A Bayesian approach is applied to infer model parameter distributions. These distributions are sampled and used to simulate from multivariate predictive densities. The method is based on a k-Nearest Neighbor estimate of the Jensen Shannon divergence between the multivariate predictive densities of competing models. Conclusions We show that the method successfully uses predictive differences to enable model selection by applying it to several test cases. Because the design criterion is based on predictive distributions, which can be computed for a wide range of model quantities, the approach is very flexible. The method reveals specific combinations of experiments which improve discriminability even in cases where data is scarce. The proposed approach can be used in conjunction with existing Bayesian methodologies where (approximate) posteriors have been determined, making use of relations that exist within the inferred posteriors. PMID:24555498

  8. Influenza B vaccine lineage selection--an optimized trivalent vaccine.

    PubMed

    Mosterín Höpping, Ana; Fonville, Judith M; Russell, Colin A; James, Sarah; Smith, Derek J

    2016-03-18

    Epidemics of seasonal influenza viruses cause considerable morbidity and mortality each year. Various types and subtypes of influenza circulate in humans and evolve continuously such that individuals at risk of serious complications need to be vaccinated annually to keep protection up to date with circulating viruses. The influenza vaccine in most parts of the world is a trivalent vaccine, including an antigenically representative virus of recently circulating influenza A/H3N2, A/H1N1, and influenza B viruses. However, since the 1970s influenza B has split into two antigenically distinct lineages, only one of which is represented in the annual trivalent vaccine at any time. We describe a lineage selection strategy that optimizes protection against influenza B using the standard trivalent vaccine as a potentially cost effective alternative to quadrivalent vaccines.

  9. Selective optimization of side activities: the SOSA approach.

    PubMed

    Wermuth, Camille G

    2006-02-01

    Selective optimization of side activities of drug molecules (the SOSA approach) is an intelligent and potentially more efficient strategy than HTS for the generation of new biological activities. Only a limited number of highly diverse drug molecules are screened, for which bioavailability and toxicity studies have already been performed and efficacy in humans has been confirmed. Once the screening has generated a hit it will be used as the starting point for a drug discovery program. Using traditional medicinal chemistry as well as parallel synthesis, the initial 'side activity' is transformed into the 'main activity' and, conversely, the initial 'main activity' is significantly reduced or abolished. This strategy has a high probability of yielding safe, bioavailable, original and patentable analogues. PMID:16533714

  10. A dual molecular analogue tuner for dissecting protein function in mammalian cells

    PubMed Central

    Brosh, Ran; Hrynyk, Iryna; Shen, Jessalyn; Waghray, Avinash; Zheng, Ning; Lemischka, Ihor R.

    2016-01-01

    Loss-of-function studies are fundamental for dissecting gene function. Yet, methods to rapidly and effectively perturb genes in mammalian cells, and particularly in stem cells, are scarce. Here we present a system for simultaneous conditional regulation of two different proteins in the same mammalian cell. This system harnesses the plant auxin and jasmonate hormone-induced degradation pathways, and is deliverable with only two lentiviral vectors. It combines RNAi-mediated silencing of two endogenous proteins with the expression of two exogenous proteins whose degradation is induced by external ligands in a rapid, reversible, titratable and independent manner. By engineering molecular tuners for NANOG, CHK1, p53 and NOTCH1 in mammalian stem cells, we have validated the applicability of the system and demonstrated its potential to unravel complex biological processes. PMID:27230261

  11. Optimal grid point selection for improved nonrigid medical image registration

    NASA Astrophysics Data System (ADS)

    Fookes, Clinton; Maeder, Anthony

    2004-05-01

    Non-rigid image registration is an essential tool required for overcoming the inherent local anatomical variations that exist between medical images acquired from different individuals or atlases, among others. This type of registration defines a deformation field that gives a translation or mapping for every pixel in the image. One popular local approach for estimating this deformation field, known as block matching, is where a grid of control points are defined on an image and are each taken as the centre of a small window. These windows are then translated in the second image to maximise a local similarity criterion. This generates two corresponding sets of control points for the two images, yielding a sparse deformation field. This sparse field can then be propagated to the entire image using well known methods such as the thin-plate spline warp or simple Gaussian convolution. Previous block matching procedures all utilise uniformly distributed grid points. This results in the generation of a sparse deformation field containing displacement estimates at uniformly spaced locations. This neglects to make use of the evidence that block matching results are dependent on the amount of local information content. That is, results are better in regions of high information when compared to regions of low information. Consequently, this paper presents a solution to this drawback by proposing the use of a Reversible Jump Markov Chain Monte Carlo (RJMCMC) statistical procedure to optimally select grid points of interest. These grid points have a greater concentration in regions of high information and a lower concentration in regions of small information. Results show that non-rigid registration can by improved by using optimally selected grid points of interest.

  12. Optimized bioregenerative space diet selection with crew choice.

    PubMed

    Vicens, Carrie; Wang, Carolyn; Olabi, Ammar; Jackson, Peter; Hunter, Jean

    2003-01-01

    Previous studies on optimization of crew diets have not accounted for choice. A diet selection model with crew choice was developed. Scenario analyses were conducted to assess the feasibility and cost of certain crew preferences, such as preferences for numerous-desserts, high-salt, and high-acceptability foods. For comparison purposes, a no-choice and a random-choice scenario were considered. The model was found to be feasible in terms of food variety and overall costs. The numerous-desserts, high-acceptability, and random-choice scenarios all resulted in feasible solutions costing between 13.2 and 17.3 kg ESM/person-day. Only the high-sodium scenario yielded an infeasible solution. This occurred when the foods highest in salt content were selected for the crew-choice portion of the diet. This infeasibility can be avoided by limiting the total sodium content in the crew-choice portion of the diet. Cost savings were found by reducing food variety in scenarios where the preference bias strongly affected nutritional content.

  13. Optimized bioregenerative space diet selection with crew choice

    NASA Technical Reports Server (NTRS)

    Vicens, Carrie; Wang, Carolyn; Olabi, Ammar; Jackson, Peter; Hunter, Jean

    2003-01-01

    Previous studies on optimization of crew diets have not accounted for choice. A diet selection model with crew choice was developed. Scenario analyses were conducted to assess the feasibility and cost of certain crew preferences, such as preferences for numerous-desserts, high-salt, and high-acceptability foods. For comparison purposes, a no-choice and a random-choice scenario were considered. The model was found to be feasible in terms of food variety and overall costs. The numerous-desserts, high-acceptability, and random-choice scenarios all resulted in feasible solutions costing between 13.2 and 17.3 kg ESM/person-day. Only the high-sodium scenario yielded an infeasible solution. This occurred when the foods highest in salt content were selected for the crew-choice portion of the diet. This infeasibility can be avoided by limiting the total sodium content in the crew-choice portion of the diet. Cost savings were found by reducing food variety in scenarios where the preference bias strongly affected nutritional content.

  14. Optimization of killer assays for yeast selection protocols.

    PubMed

    Lopes, C A; Sangorrín, M P

    2010-01-01

    A new optimized semiquantitative yeast killer assay is reported for the first time. The killer activity of 36 yeast isolates belonging to three species, namely, Metschnikowia pulcherrima, Wickerhamomyces anomala and Torulaspora delbrueckii, was tested with a view to potentially using these yeasts as biocontrol agents against the wine spoilage species Pichia guilliermondii and Pichia membranifaciens. The effectiveness of the classical streak-based (qualitative method) and the new semiquantitative techniques was compared. The percentage of yeasts showing killer activity was found to be higher by the semiquantitative technique (60%) than by the qualitative method (45%). In all cases, the addition of 1% NaCl into the medium allowed a better observation of the killer phenomenon. Important differences were observed in the killer capacity of different isolates belonging to a same killer species. The broadest spectrum of action was detected in isolates of W. anomala NPCC 1023 and 1025, and M. pulcherrima NPCC 1009 and 1013. We also brought experimental evidence supporting the importance of the adequate selection of the sensitive isolate to be used in killer evaluation. The new semiquantitative method proposed in this work enables to visualize the relationship between the number of yeasts tested and the growth of the inhibition halo (specific productivity). Hence, this experimental approach could become an interesting tool to be taken into account for killer yeast selection protocols.

  15. Power-Balance Control by Slug Tuner for the 175MHz Radio-Frequency Quadrupole (RFQ) Linac in IFMIF Project

    SciTech Connect

    Maebara, Sunao; Moriyama, Shinichi; Saigusa, Mikio; Sugimoto, Masayoshi; Imai, Tsuyoshi; Takeuchi, Hiroshi

    2005-05-15

    RF Power-balance control among the quadrants of IFMIF 4-vane radio-frequency quadrupole (RFQ) linac structure is a critical issue, because it may be affected by the fabrication error of the 12m-long RFQ and by the perturbation due to loop antenna installation. The power-balance controllability of slug tuners was measured by a low power test, and the distortion behavior of electric fields profiles at beam bore peripheral was calculated by an electromagnetic field simulation code. From the low power test, it was found that RF power-balance up to 80% can be controlled without overlap of modes. The calculation suggested that the design requirement of distortion limit of 1% can be attained by employing 1cm slug tuner with insertion depth of 1cm or less.

  16. Applications of Optimal Building Energy System Selection and Operation

    SciTech Connect

    Marnay, Chris; Stadler, Michael; Siddiqui, Afzal; DeForest, Nicholas; Donadee, Jon; Bhattacharya, Prajesh; Lai, Judy

    2011-04-01

    Berkeley Lab has been developing the Distributed Energy Resources Customer Adoption Model (DER-CAM) for several years. Given load curves for energy services requirements in a building microgrid (u grid), fuel costs and other economic inputs, and a menu of available technologies, DER-CAM finds the optimum equipment fleet and its optimum operating schedule using a mixed integer linear programming approach. This capability is being applied using a software as a service (SaaS) model. Optimisation problems are set up on a Berkeley Lab server and clients can execute their jobs as needed, typically daily. The evolution of this approach is demonstrated by description of three ongoing projects. The first is a public access web site focused on solar photovoltaic generation and battery viability at large commercial and industrial customer sites. The second is a building CO2 emissions reduction operations problem for a University of California, Davis student dining hall for which potential investments are also considered. And the third, is both a battery selection problem and a rolling operating schedule problem for a large County Jail. Together these examples show that optimization of building u grid design and operation can be effectively achieved using SaaS.

  17. Ultra-fast fluence optimization for beam angle selection algorithms

    NASA Astrophysics Data System (ADS)

    Bangert, M.; Ziegenhein, P.; Oelfke, U.

    2014-03-01

    Beam angle selection (BAS) including fluence optimization (FO) is among the most extensive computational tasks in radiotherapy. Precomputed dose influence data (DID) of all considered beam orientations (up to 100 GB for complex cases) has to be handled in the main memory and repeated FOs are required for different beam ensembles. In this paper, the authors describe concepts accelerating FO for BAS algorithms using off-the-shelf multiprocessor workstations. The FO runtime is not dominated by the arithmetic load of the CPUs but by the transportation of DID from the RAM to the CPUs. On multiprocessor workstations, however, the speed of data transportation from the main memory to the CPUs is non-uniform across the RAM; every CPU has a dedicated memory location (node) with minimum access time. We apply a thread node binding strategy to ensure that CPUs only access DID from their preferred node. Ideal load balancing for arbitrary beam ensembles is guaranteed by distributing the DID of every candidate beam equally to all nodes. Furthermore we use a custom sorting scheme of the DID to minimize the overall data transportation. The framework is implemented on an AMD Opteron workstation. One FO iteration comprising dose, objective function, and gradient calculation takes between 0.010 s (9 beams, skull, 0.23 GB DID) and 0.070 s (9 beams, abdomen, 1.50 GB DID). Our overall FO time is < 1 s for small cases, larger cases take ~ 4 s. BAS runs including FOs for 1000 different beam ensembles take ~ 15-70 min, depending on the treatment site. This enables an efficient clinical evaluation of different BAS algorithms.

  18. Mathematical modeling of 1D binary photonic tuner and realization of temperature sensor

    NASA Astrophysics Data System (ADS)

    Lahiri, A.; Chakraborty, M.

    2011-10-01

    In recent years photonic crystals have become a favored area of research due to their diversified applications. In this paper we propose a mathematical model for analyzing the photonic band gap of a 1D binary photonic crystal (GaAs and air) which allows us to use it effectively as a photonic tuner which is an integral part of any optical amplifier. As optical parameters like reflection and refraction follows similar pattern from each plane within a photonic crystal, we can take help of characteristic matrix for a single plane and multiply (m) times where the crystal consists of (m) periods. Using the fact that the characteristic matrix comes out to be unimodular and taking help of Cayley-Hamilton theorem and Chebyshev polynomials, we expand the matrix of the entire system to derive the location and width of photonic band gaps. Higher stop bands occur at lower frequency of incoming radiation and central bandgap wavelength decreases with increasing angle of incidence. The power transmitted by the tuning crystal decreases for radiations away from normal. Using a polarizer model, the attenuation is computed to be proportional to log|Cos2θ|, where θ is the angle of incidence. The mathematical modeling developed can also be extended for realization of n-array photonic crystal. We have also considered the refractive index modulation with respect to temperature for using it as a temperature sensor.

  19. A high-speed mixed-signal down-scaling circuit for DAB tuners

    NASA Astrophysics Data System (ADS)

    Lu, Tang; Zhigong, Wang; Jiahui, Xuan; Yang, Yang; Jian, Xu; Yong, Xu

    2012-07-01

    A high-speed mixed-signal down-scaling circuit with low power consumption and low phase noise for use in digital audio broadcasting tuners has been realized and characterized. Some new circuit techniques are adopted to improve its performance. A dual-modulus prescaler (DMP) with low phase noise is realized with a kind of improved source-coupled logic (SCL) D-flip-flop (DFF) in the synchronous divider and a kind of improved complementary metal oxide semiconductor master-slave (CMOS MS)-DFF in the asynchronous divider. A new more accurate wire-load model is used to realize the pulse-swallow counter (PS counter). Fabricated in a 0.18-μm CMOS process, the total chip size is 0.6 × 0.2 mm2. The DMP in the proposed down-scaling circuit exhibits a low phase noise of -118.2 dBc/Hz at 10 kHz off the carrier frequency. At a supply voltage of 1.8 V, the power consumption of the down-scaling circuit's core part is only 2.7 mW.

  20. Update on RF System Studies and VCX Fast Tuner Work for the RIA Drive Linac

    SciTech Connect

    Rusnak, B; Shen, S

    2003-05-06

    The limited cavity beam loading conditions anticipated for the Rare Isotope Accelerator (RIA) create a situation where microphonic-induced cavity detuning dominates radio frequency (RF) coupling and RF system architecture choices in the linac design process. Where most superconducting electron and proton linacs have beam-loaded bandwidths that are comparable to or greater than typical microphonic detuning bandwidths on the cavities, the beam-loaded bandwidths for many heavy-ion species in the RIA driver linac can be as much as a factor of 10 less than the projected 80-150 Hz microphonic control window for the RF structures along the driver, making RF control problematic. While simply overcoupling the coupler to the cavity can mitigate this problem to some degree, system studies indicate that for the low-{beta} driver linac alone, this approach may cost 50% or more than an RF system employing a voltage controlled reactance (VCX) fast tuner. An update of these system cost studies, along with the status of the VCX work being done at Lawrence Livermore National Lab is presented here.

  1. Comparison of Genetic Algorithm, Particle Swarm Optimization and Biogeography-based Optimization for Feature Selection to Classify Clusters of Microcalcifications

    NASA Astrophysics Data System (ADS)

    Khehra, Baljit Singh; Pharwaha, Amar Partap Singh

    2016-06-01

    Ductal carcinoma in situ (DCIS) is one type of breast cancer. Clusters of microcalcifications (MCCs) are symptoms of DCIS that are recognized by mammography. Selection of robust features vector is the process of selecting an optimal subset of features from a large number of available features in a given problem domain after the feature extraction and before any classification scheme. Feature selection reduces the feature space that improves the performance of classifier and decreases the computational burden imposed by using many features on classifier. Selection of an optimal subset of features from a large number of available features in a given problem domain is a difficult search problem. For n features, the total numbers of possible subsets of features are 2n. Thus, selection of an optimal subset of features problem belongs to the category of NP-hard problems. In this paper, an attempt is made to find the optimal subset of MCCs features from all possible subsets of features using genetic algorithm (GA), particle swarm optimization (PSO) and biogeography-based optimization (BBO). For simulation, a total of 380 benign and malignant MCCs samples have been selected from mammogram images of DDSM database. A total of 50 features extracted from benign and malignant MCCs samples are used in this study. In these algorithms, fitness function is correct classification rate of classifier. Support vector machine is used as a classifier. From experimental results, it is also observed that the performance of PSO-based and BBO-based algorithms to select an optimal subset of features for classifying MCCs as benign or malignant is better as compared to GA-based algorithm.

  2. To Eat or Not to Eat: An Easy Simulation of Optimal Diet Selection in the Classroom

    ERIC Educational Resources Information Center

    Ray, Darrell L.

    2010-01-01

    Optimal diet selection, a component of optimal foraging theory, suggests that animals should select a diet that either maximizes energy or nutrient consumption per unit time or minimizes the foraging time needed to attain required energy or nutrients. In this exercise, students simulate the behavior of foragers that either show no foraging…

  3. 75 FR 39437 - Optimizing the Security of Biological Select Agents and Toxins in the United States

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-08

    ..., 2010. [FR Doc. 2010-16864 Filed 7-7-10; 11:15 am] Billing code 3195-W0-P ... Executive Order 13546--Optimizing the Security of Biological Select Agents and Toxins in the United States... July 2, 2010 Optimizing the Security of Biological Select Agents and Toxins in the United States By...

  4. Polyhedral Interpolation for Optimal Reaction Control System Jet Selection

    NASA Technical Reports Server (NTRS)

    Gefert, Leon P.; Wright, Theodore

    2014-01-01

    An efficient algorithm is described for interpolating optimal values for spacecraft Reaction Control System jet firing duty cycles. The algorithm uses the symmetrical geometry of the optimal solution to reduce the number of calculations and data storage requirements to a level that enables implementation on the small real time flight control systems used in spacecraft. The process minimizes acceleration direction errors, maximizes control authority, and minimizes fuel consumption.

  5. Age-Related Differences in Goals: Testing Predictions from Selection, Optimization, and Compensation Theory and Socioemotional Selectivity Theory

    ERIC Educational Resources Information Center

    Penningroth, Suzanna L.; Scott, Walter D.

    2012-01-01

    Two prominent theories of lifespan development, socioemotional selectivity theory and selection, optimization, and compensation theory, make similar predictions for differences in the goal representations of younger and older adults. Our purpose was to test whether the goals of younger and older adults differed in ways predicted by these two…

  6. Optimal Bandwidth Selection in Observed-Score Kernel Equating

    ERIC Educational Resources Information Center

    Häggström, Jenny; Wiberg, Marie

    2014-01-01

    The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…

  7. An artificial system for selecting the optimal surgical team

    PubMed Central

    Saberi, Nahid; Mahvash, Mohsen; Zenati, Marco

    2016-01-01

    We introduce an intelligent system to optimize a team composition based on the team’s historical outcomes and apply this system to compose a surgical team. The system relies on a record of the procedures performed in the past. The optimal team composition is the one with the lowest probability of unfavorable outcome. We use the theory of probability and the inclusion exclusion principle to model the probability of team outcome for a given composition. A probability value is assigned to each person of database and the probability of a team composition is calculated from them. The model allows to determine the probability of all possible team compositions even if there is no recoded procedure for some team compositions. From an analytical perspective, assembling an optimal team is equivalent to minimizing the overlap of team members who have a recurring tendency to be involved with procedures of unfavorable results. A conceptual example shows the accuracy of the proposed system on obtaining the optimal team. PMID:26736239

  8. Self-Selection, Optimal Income Taxation, and Redistribution

    ERIC Educational Resources Information Center

    Amegashie, J. Atsu

    2009-01-01

    The author makes a pedagogical contribution to optimal income taxation. Using a very simple model adapted from George A. Akerlof (1978), he demonstrates a key result in the approach to public economics and welfare economics pioneered by Nobel laureate James Mirrlees. He shows how incomplete information, in addition to the need to preserve…

  9. Optimization of Swine Breeding Programs Using Genomic Selection with ZPLAN+

    PubMed Central

    Lopez, B. M.; Kang, H. S.; Kim, T. H.; Viterbo, V. S.; Kim, H. S.; Na, C. S.; Seo, K. S.

    2016-01-01

    The objective of this study was to evaluate the present conventional selection program of a swine nucleus farm and compare it with a new selection strategy employing genomic enhanced breeding value (GEBV) as the selection criteria. The ZPLAN+ software was employed to calculate and compare the genetic gain, total cost, return and profit of each selection strategy. The first strategy reflected the current conventional breeding program, which was a progeny test system (CS). The second strategy was a selection scheme based strictly on genomic information (GS1). The third scenario was the same as GS1, but the selection by GEBV was further supplemented by the performance test (GS2). The last scenario was a mixture of genomic information and progeny tests (GS3). The results showed that the accuracy of the selection index of young boars of GS1 was 26% higher than that of CS. On the other hand, both GS2 and GS3 gave 31% higher accuracy than CS for young boars. The annual monetary genetic gain of GS1, GS2 and GS3 was 10%, 12%, and 11% higher, respectively, than that of CS. As expected, the discounted costs of genomic selection strategies were higher than those of CS. The costs of GS1, GS2 and GS3 were 35%, 73%, and 89% higher than those of CS, respectively, assuming a genotyping cost of $120. As a result, the discounted profit per animal of GS1 and GS2 was 8% and 2% higher, respectively, than that of CS while GS3 was 6% lower. Comparison among genomic breeding scenarios revealed that GS1 was more profitable than GS2 and GS3. The genomic selection schemes, especially GS1 and GS2, were clearly superior to the conventional scheme in terms of monetary genetic gain and profit. PMID:26954222

  10. Optimal design and selection of magneto-rheological brake types based on braking torque and mass

    NASA Astrophysics Data System (ADS)

    Nguyen, Q. H.; Lang, V. T.; Choi, S. B.

    2015-06-01

    In developing magnetorheological brakes (MRBs), it is well known that the braking torque and the mass of the MRBs are important factors that should be considered in the product’s design. This research focuses on the optimal design of different types of MRBs, from which we identify an optimal selection of MRB types, considering braking torque and mass. In the optimization, common types of MRBs such as disc-type, drum-type, hybrid-type, and T-shape types are considered. The optimization problem is to find an optimal MRB structure that can produce the required braking torque while minimizing its mass. After a brief description of the configuration of the MRBs, the MRBs’ braking torque is derived based on the Herschel-Bulkley rheological model of the magnetorheological fluid. Then, the optimal designs of the MRBs are analyzed. The optimization objective is to minimize the mass of the brake while the braking torque is constrained to be greater than a required value. In addition, the power consumption of the MRBs is also considered as a reference parameter in the optimization. A finite element analysis integrated with an optimization tool is used to obtain optimal solutions for the MRBs. Optimal solutions of MRBs with different required braking torque values are obtained based on the proposed optimization procedure. From the results, we discuss the optimal selection of MRB types, considering braking torque and mass.

  11. Optimizing drilling performance using a selected drilling fluid

    DOEpatents

    Judzis, Arnis; Black, Alan D.; Green, Sidney J.; Robertson, Homer A.; Bland, Ronald G.; Curry, David Alexander; Ledgerwood, III, Leroy W.

    2011-04-19

    To improve drilling performance, a drilling fluid is selected based on one or more criteria and to have at least one target characteristic. Drilling equipment is used to drill a wellbore, and the selected drilling fluid is provided into the wellbore during drilling with the drilling equipment. The at least one target characteristic of the drilling fluid includes an ability of the drilling fluid to penetrate into formation cuttings during drilling to weaken the formation cuttings.

  12. Parameter selection for the SSC trade-offs and optimization

    SciTech Connect

    Edwards, D.A.; Syphers, M.J.

    1991-10-14

    In November of 1988, a site was selected in the state of Texas for the SSC. In January of 1989, the SSC Laboratory was established in Texas to adapt the design of the collider to the site and to manage the construction of the project. This paper describes the evolution of the SSC design since site selection, notes the increased concentration on the injector system, and addresses the rationale for choice of parameters.

  13. Material selection and corresponding optimal surface relief height for multilayer diffractive optical elements

    NASA Astrophysics Data System (ADS)

    Dun, Xiong; Jin, Weiqi; Wang, Xia

    2015-11-01

    We present a model based on refractive index difference analysis for optimization of material selection for multilayer diffractive optical elements (MLDOEs). From the proposed model, two important relationships are derived: the relationship between material selection and the maximum polychromatic integral diffraction efficiency of MLDOEs, and between material selection and the surface relief heights of MLDOEs. The new relationships are more comprehensive and reliable than those discussed in previous papers. A theoretical expression of the optimal surface relief heights of MLDOEs is also presented, and its correctness is demonstrated through a comparison with the results of enumeration optimization.

  14. Optimization of Metamaterial Selective Emitters for Use in Thermophotovoltaic Applications

    NASA Astrophysics Data System (ADS)

    Pfiester, Nicole A.

    The increasing costs of fossil fuels, both financial and environmental, has motivated many to look into sustainable energy sources. Thermophotovoltaics (TPVs), specialized photovoltaic cells focused on the infrared range, offer an opportunity to achieve both primary energy capture, similar to traditional photovoltaics, as well as secondary energy capture in the form of waste heat. However, to become a feasible energy source, TPV systems must become more efficient. One way to do this is through the development of selective emitters tailored to the bandgap of the TPV diode in question. This thesis proposes the use of metamaterial emitters as an engineerable, highly selective emitter that can withstand the temperatures required to collect waste heat. Metamaterial devices made of platinum and a dielectric such as alumina or silicon nitride were initially designed and tested as perfect absorbers. High temperature robustness testing demonstrates the device's ability to withstand the rigors of operating as a selective emitter.

  15. Selection of optimal sensors for predicting performance of polymer electrolyte membrane fuel cell

    NASA Astrophysics Data System (ADS)

    Mao, Lei; Jackson, Lisa

    2016-10-01

    In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches, including the largest gap method, and exhaustive brute force searching technique, are applied to find the optimal sensors providing reliable predictions. Based on the results, a sensor selection approach considering both sensor sensitivity and noise resistance is proposed to find the optimal sensor set with minimum size. Furthermore, the performance of the optimal sensor set is studied to predict fuel cell performance using test data from a PEM fuel cell system. Results demonstrate that with optimal sensors, the performance of PEM fuel cell can be predicted with good quality.

  16. Selection of optimal auxiliary soil nutrient variables for Cokriging interpolation.

    PubMed

    Song, Genxin; Zhang, Jing; Wang, Ke

    2014-01-01

    In order to explore the selection of the best auxiliary variables (BAVs) when using the Cokriging method for soil attribute interpolation, this paper investigated the selection of BAVs from terrain parameters, soil trace elements, and soil nutrient attributes when applying Cokriging interpolation to soil nutrients (organic matter, total N, available P, and available K). In total, 670 soil samples were collected in Fuyang, and the nutrient and trace element attributes of the soil samples were determined. Based on the spatial autocorrelation of soil attributes, the Digital Elevation Model (DEM) data for Fuyang was combined to explore the coordinate relationship among terrain parameters, trace elements, and soil nutrient attributes. Variables with a high correlation to soil nutrient attributes were selected as BAVs for Cokriging interpolation of soil nutrients, and variables with poor correlation were selected as poor auxiliary variables (PAVs). The results of Cokriging interpolations using BAVs and PAVs were then compared. The results indicated that Cokriging interpolation with BAVs yielded more accurate results than Cokriging interpolation with PAVs (the mean absolute error of BAV interpolation results for organic matter, total N, available P, and available K were 0.020, 0.002, 7.616, and 12.4702, respectively, and the mean absolute error of PAV interpolation results were 0.052, 0.037, 15.619, and 0.037, respectively). The results indicated that Cokriging interpolation with BAVs can significantly improve the accuracy of Cokriging interpolation for soil nutrient attributes. This study provides meaningful guidance and reference for the selection of auxiliary parameters for the application of Cokriging interpolation to soil nutrient attributes.

  17. Selection of Optimal Auxiliary Soil Nutrient Variables for Cokriging Interpolation

    PubMed Central

    Song, Genxin; Zhang, Jing; Wang, Ke

    2014-01-01

    In order to explore the selection of the best auxiliary variables (BAVs) when using the Cokriging method for soil attribute interpolation, this paper investigated the selection of BAVs from terrain parameters, soil trace elements, and soil nutrient attributes when applying Cokriging interpolation to soil nutrients (organic matter, total N, available P, and available K). In total, 670 soil samples were collected in Fuyang, and the nutrient and trace element attributes of the soil samples were determined. Based on the spatial autocorrelation of soil attributes, the Digital Elevation Model (DEM) data for Fuyang was combined to explore the coordinate relationship among terrain parameters, trace elements, and soil nutrient attributes. Variables with a high correlation to soil nutrient attributes were selected as BAVs for Cokriging interpolation of soil nutrients, and variables with poor correlation were selected as poor auxiliary variables (PAVs). The results of Cokriging interpolations using BAVs and PAVs were then compared. The results indicated that Cokriging interpolation with BAVs yielded more accurate results than Cokriging interpolation with PAVs (the mean absolute error of BAV interpolation results for organic matter, total N, available P, and available K were 0.020, 0.002, 7.616, and 12.4702, respectively, and the mean absolute error of PAV interpolation results were 0.052, 0.037, 15.619, and 0.037, respectively). The results indicated that Cokriging interpolation with BAVs can significantly improve the accuracy of Cokriging interpolation for soil nutrient attributes. This study provides meaningful guidance and reference for the selection of auxiliary parameters for the application of Cokriging interpolation to soil nutrient attributes. PMID:24927129

  18. Optimal selection of Orbital Replacement Unit on-orbit spares - A Space Station system availability model

    NASA Technical Reports Server (NTRS)

    Schwaab, Douglas G.

    1991-01-01

    A mathematical programing model is presented to optimize the selection of Orbital Replacement Unit on-orbit spares for the Space Station. The model maximizes system availability under the constraints of logistics resupply-cargo weight and volume allocations.

  19. Selection of Reserves for Woodland Caribou Using an Optimization Approach

    PubMed Central

    Schneider, Richard R.; Hauer, Grant; Dawe, Kimberly; Adamowicz, Wiktor; Boutin, Stan

    2012-01-01

    Habitat protection has been identified as an important strategy for the conservation of woodland caribou (Rangifer tarandus). However, because of the economic opportunity costs associated with protection it is unlikely that all caribou ranges can be protected in their entirety. We used an optimization approach to identify reserve designs for caribou in Alberta, Canada, across a range of potential protection targets. Our designs minimized costs as well as three demographic risk factors: current industrial footprint, presence of white-tailed deer (Odocoileus virginianus), and climate change. We found that, using optimization, 60% of current caribou range can be protected (including 17% in existing parks) while maintaining access to over 98% of the value of resources on public lands. The trade-off between minimizing cost and minimizing demographic risk factors was minimal because the spatial distributions of cost and risk were similar. The prospects for protection are much reduced if protection is directed towards the herds that are most at risk of near-term extirpation. PMID:22363702

  20. Optimizing selection of decentralized stormwater management strategies in urbanized regions

    NASA Astrophysics Data System (ADS)

    Yu, Z.; Montalto, F.

    2011-12-01

    A variety of decentralized stormwater options are available for implementation in urbanized regions. These strategies, which include bio-retention, porous pavement, green roof etc., vary in terms of cost, ability to reduce runoff, and site applicability. This paper explores the tradeoffs between different types of stormwater control meastures that could be applied in a typical urban study area. A nested optimization strategy first identifies the most cost-effective (e.g. runoff reduction / life cycle cost invested ) options for individual land parcel typologies, and then scales up the results with detailed attention paid to uncertainty in adoption rates, life cycle costs, and hydrologic performance. The study is performed with a custom built stochastic rainfall-runoff model (Monte Carlo techniques are used to quantify uncertainties associated with phased implementation of different strategies and different land parcel typologies under synthetic precipitation ensembles). The results are presented as a comparison of cost-effectiveness over the time span of 30 years, and state an optimized strategy on the cumulative cost-effectiveness over the period.

  1. Application’s Method of Quadratic Programming for Optimization of Portfolio Selection

    NASA Astrophysics Data System (ADS)

    Kawamoto, Shigeru; Takamoto, Masanori; Kobayashi, Yasuhiro

    Investors or fund-managers face with optimization of portfolio selection, which means that determine the kind and the quantity of investment among several brands. We have developed a method to obtain optimal stock’s portfolio more rapidly from twice to three times than conventional method with efficient universal optimization. The method is characterized by quadratic matrix of utility function and constrained matrices divided into several sub-matrices by focusing on structure of these matrices.

  2. Optimal band selection for dimensionality reduction of hyperspectral imagery

    NASA Technical Reports Server (NTRS)

    Stearns, Stephen D.; Wilson, Bruce E.; Peterson, James R.

    1993-01-01

    Hyperspectral images have many bands requiring significant computational power for machine interpretation. During image pre-processing, regions of interest that warrant full examination need to be identified quickly. One technique for speeding up the processing is to use only a small subset of bands to determine the 'interesting' regions. The problem addressed here is how to determine the fewest bands required to achieve a specified performance goal for pixel classification. The band selection problem has been addressed previously Chen et al., Ghassemian et al., Henderson et al., and Kim et al.. Some popular techniques for reducing the dimensionality of a feature space, such as principal components analysis, reduce dimensionality by computing new features that are linear combinations of the original features. However, such approaches require measuring and processing all the available bands before the dimensionality is reduced. Our approach, adapted from previous multidimensional signal analysis research, is simpler and achieves dimensionality reduction by selecting bands. Feature selection algorithms are used to determine which combination of bands has the lowest probability of pixel misclassification. Two elements required by this approach are a choice of objective function and a choice of search strategy.

  3. Sensor Selection and Optimization for Health Assessment of Aerospace Systems

    NASA Technical Reports Server (NTRS)

    Maul, William A.; Kopasakis, George; Santi, Louis M.; Sowers, Thomas S.; Chicatelli, Amy

    2008-01-01

    Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service these research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, defendable sensor suite to address system health assessment requirements.

  4. Sensor Selection and Optimization for Health Assessment of Aerospace Systems

    NASA Technical Reports Server (NTRS)

    Maul, William A.; Kopasakis, George; Santi, Louis M.; Sowers, Thomas S.; Chicatelli, Amy

    2007-01-01

    Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service. These research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, dependable sensor suite to address system health assessment requirements.

  5. Selection of optimal composition-control parameters for friable materials

    SciTech Connect

    Pak, Yu.N.; Vdovkin, A.V.

    1988-05-01

    A method for composition analysis of coal and minerals is proposed which uses scattered gamma radiation and does away with preliminary sample preparation to ensure homogeneous particle density, surface area, and size. Reduction of the error induced by material heterogeneity has previously been achieved by rotation of the control object during analysis. A further refinement is proposed which addresses the necessity that the contribution of the radiation scattered from each individual surface to the total intensity be the same. This is achieved by providing a constant linear rate of travel for the irradiated spot through back-and-forth motion of the sensor. An analytical expression is given for the laws of motion for the sensor and test tube which provides for uniform irradiated area movement along a path analogous to the Archimedes spiral. The relationships obtained permit optimization of measurement parameters in analyzing friable materials which are not uniform in grain size.

  6. Automated selection of appropriate pheromone representations in ant colony optimization.

    PubMed

    Montgomery, James; Randall, Marcus; Hendtlass, Tim

    2005-01-01

    Ant colony optimization (ACO) is a constructive metaheuristic that uses an analogue of ant trail pheromones to learn about good features of solutions. Critically, the pheromone representation for a particular problem is usually chosen intuitively rather than by following any systematic process. In some representations, distinct solutions appear multiple times, increasing the effective size of the search space and potentially misleading ants as to the true learned value of those solutions. In this article, we present a novel system for automatically generating appropriate pheromone representations, based on the characteristics of the problem model that ensures unique pheromone representation of solutions. This is the first stage in the development of a generalized ACO system that could be applied to a wide range of problems with little or no modification. However, the system we propose may be used in the development of any problem-specific ACO algorithm. PMID:16053571

  7. Discrepancies between selected Pareto optimal plans and final deliverable plans in radiotherapy multi-criteria optimization.

    PubMed

    Kyroudi, Archonteia; Petersson, Kristoffer; Ghandour, Sarah; Pachoud, Marc; Matzinger, Oscar; Ozsahin, Mahmut; Bourhis, Jean; Bochud, François; Moeckli, Raphaël

    2016-08-01

    Multi-criteria optimization provides decision makers with a range of clinical choices through Pareto plans that can be explored during real time navigation and then converted into deliverable plans. Our study shows that dosimetric differences can arise between the two steps, which could compromise the clinical choices made during navigation.

  8. Determination of an Optimal Recruiting-Selection Strategy to Fill a Specified Quota of Satisfactory Personnel.

    ERIC Educational Resources Information Center

    Sands, William A.

    Managers of military and civilian personnel systems justifiably demand an estimate of the payoff in dollars and cents, which can be expected to result from the implementation of a proposed selection program. The Cost of Attaining Personnel Requirements (CAPER) Model provides an optimal recruiting-selection strategy for personnel decisions which…

  9. Selection for optimal crew performance - Relative impact of selection and training

    NASA Technical Reports Server (NTRS)

    Chidester, Thomas R.

    1987-01-01

    An empirical study supporting Helmreich's (1986) theoretical work on the distinct manner in which training and selection impact crew coordination is presented. Training is capable of changing attitudes, while selection screens for stable personality characteristics. Training appears least effective for leadership, an area strongly influenced by personality. Selection is least effective for influencing attitudes about personal vulnerability to stress, which appear to be trained in resource management programs. Because personality correlates with attitudes before and after training, it is felt that selection may be necessary even with a leadership-oriented training cirriculum.

  10. Storage of human biospecimens: selection of the optimal storage temperature.

    PubMed

    Hubel, Allison; Spindler, Ralf; Skubitz, Amy P N

    2014-06-01

    Millions of biological samples are currently kept at low tempertures in cryobanks/biorepositories for long-term storage. The quality of the biospecimen when thawed, however, is not only determined by processing of the biospecimen but the storage conditions as well. The overall objective of this article is to describe the scientific basis for selecting a storage temperature for a biospecimen based on current scientific understanding. To that end, this article reviews some physical basics of the temperature, nucleation, and ice crystal growth present in biological samples stored at low temperatures (-20°C to -196°C), and our current understanding of the role of temperature on the activity of degradative molecules present in biospecimens. The scientific literature relevant to the stability of specific biomarkers in human fluid, cell, and tissue biospecimens is also summarized for the range of temperatures between -20°C to -196°C. These studies demonstrate the importance of storage temperature on the stability of critical biomarkers for fluid, cell, and tissue biospecimens.

  11. Optimizing landfill site selection by using land classification maps.

    PubMed

    Eskandari, M; Homaee, M; Mahmoodi, S; Pazira, E; Van Genuchten, M Th

    2015-05-01

    Municipal solid waste disposal is a major environmental concern throughout the world. Proper landfill siting involves many environmental, economic, technical, and sociocultural challenges. In this study, a new quantitative method for landfill siting that reduces the number of evaluation criteria, simplifies siting procedures, and enhances the utility of available land evaluation maps was proposed. The method is demonstrated by selecting a suitable landfill site near the city of Marvdasht in Iran. The approach involves two separate stages. First, necessary criteria for preliminary landfill siting using four constraints and eight factors were obtained from a land classification map initially prepared for irrigation purposes. Thereafter, the criteria were standardized using a rating approach and then weighted to obtain a suitability map for landfill siting, with ratings in a 0-1 domain and divided into five suitability classes. Results were almost identical to those obtained with a more traditional environmental landfill siting approach. Because of far fewer evaluation criteria, the proposed weighting method was much easier to implement while producing a more convincing database for landfill siting. The classification map also considered land productivity. In the second stage, the six best alternative sites were evaluated for final landfill siting using four additional criteria. Sensitivity analyses were furthermore conducted to assess the stability of the obtained ranking. Results indicate that the method provides a precise siting procedure that should convince all pertinent stakeholders.

  12. Biomass selection for optimal anaerobic treatment of olive mill wastewater.

    PubMed

    Sabbah, I; Yazbak, A; Haj, J; Saliba, A; Basheer, S

    2005-01-01

    This research was conducted to identify the most efficient biomass out of five different types of biomass sources for anaerobic treatment of Olive Mill Wastewater (OMW). This study was first focused on examining the selected biomass in anaerobic batch systems with sodium acetate solutions (control study). Then, the different types of biomass were tested with raw OMW (water-diluted) and with pretreated OMW by coagulation-flocculation using Poly Aluminum Chloride (PACl) combined with hydrated lime (Ca(OH)2). Two types of biomass from wastewater treatment systems of a citrus juice producing company "PriGat" and from a citric acid manufacturing factory "Gadot", were found to be the most efficient sources of microorganisms to anaerobically treat both sodium acetate solution and OMW. Both types of biomass were examined under different concentration ranges (1-40 g l(-1)) of OMW in order to detect the maximal COD tolerance for the microorganisms. The results show that 70-85% of COD removal was reached using Gadot biomass after 8-10 days when the initial concentration of OMW was up to 5 g l(-1), while a similar removal efficiency was achieved using OMW of initial COD concentration of 10 g l(-1) in 2-4 days of contact time with the PriGat biomass. The physico-chemical pretreatment of OMW was found to enhance the anaerobic activity for the treatment of OMW with initial concentration of 20 g l(-1) using PriGat biomass. This finding is attributed to reducing the concentrations of polyphenols and other toxicants originally present in OMW upon the applied pretreatment process. PMID:15747599

  13. Plastic scintillation dosimetry: Optimal selection of scintillating fibers and scintillators

    SciTech Connect

    Archambault, Louis; Arsenault, Jean; Gingras, Luc; Sam Beddar, A.; Roy, Rene; Beaulieu, Luc

    2005-07-15

    Scintillation dosimetry is a promising avenue for evaluating dose patterns delivered by intensity-modulated radiation therapy plans or for the small fields involved in stereotactic radiosurgery. However, the increase in signal has been the goal for many authors. In this paper, a comparison is made between plastic scintillating fibers and plastic scintillator. The collection of scintillation light was measured experimentally for four commercial models of scintillating fibers (BCF-12, BCF-60, SCSF-78, SCSF-3HF) and two models of plastic scintillators (BC-400, BC-408). The emission spectra of all six scintillators were obtained by using an optical spectrum analyzer and they were compared with theoretical behavior. For scintillation in the blue region, the signal intensity of a singly clad scintillating fiber (BCF-12) was 120% of that of the plastic scintillator (BC-400). For the multiclad fiber (SCSF-78), the signal reached 144% of that of the plastic scintillator. The intensity of the green scintillating fibers was lower than that of the plastic scintillator: 47% for the singly clad fiber (BCF-60) and 77% for the multiclad fiber (SCSF-3HF). The collected light was studied as a function of the scintillator length and radius for a cylindrical probe. We found that symmetric detectors with nearly the same spatial resolution in each direction (2 mm in diameter by 3 mm in length) could be made with a signal equivalent to those of the more commonly used asymmetric scintillators. With augmentation of the signal-to-noise ratio in consideration, this paper presents a series of comparisons that should provide insight into selection of a scintillator type and volume for development of a medical dosimeter.

  14. Biomass selection for optimal anaerobic treatment of olive mill wastewater.

    PubMed

    Sabbah, I; Yazbak, A; Haj, J; Saliba, A; Basheer, S

    2005-01-01

    This research was conducted to identify the most efficient biomass out of five different types of biomass sources for anaerobic treatment of Olive Mill Wastewater (OMW). This study was first focused on examining the selected biomass in anaerobic batch systems with sodium acetate solutions (control study). Then, the different types of biomass were tested with raw OMW (water-diluted) and with pretreated OMW by coagulation-flocculation using Poly Aluminum Chloride (PACl) combined with hydrated lime (Ca(OH)2). Two types of biomass from wastewater treatment systems of a citrus juice producing company "PriGat" and from a citric acid manufacturing factory "Gadot", were found to be the most efficient sources of microorganisms to anaerobically treat both sodium acetate solution and OMW. Both types of biomass were examined under different concentration ranges (1-40 g l(-1)) of OMW in order to detect the maximal COD tolerance for the microorganisms. The results show that 70-85% of COD removal was reached using Gadot biomass after 8-10 days when the initial concentration of OMW was up to 5 g l(-1), while a similar removal efficiency was achieved using OMW of initial COD concentration of 10 g l(-1) in 2-4 days of contact time with the PriGat biomass. The physico-chemical pretreatment of OMW was found to enhance the anaerobic activity for the treatment of OMW with initial concentration of 20 g l(-1) using PriGat biomass. This finding is attributed to reducing the concentrations of polyphenols and other toxicants originally present in OMW upon the applied pretreatment process.

  15. Plastic scintillation dosimetry: optimal selection of scintillating fibers and scintillators.

    PubMed

    Archambault, Louis; Arsenault, Jean; Gingras, Luc; Beddar, A Sam; Roy, René; Beaulieu, Luc

    2005-07-01

    Scintillation dosimetry is a promising avenue for evaluating dose patterns delivered by intensity-modulated radiation therapy plans or for the small fields involved in stereotactic radiosurgery. However, the increase in signal has been the goal for many authors. In this paper, a comparison is made between plastic scintillating fibers and plastic scintillator. The collection of scintillation light was measured experimentally for four commercial models of scintillating fibers (BCF-12, BCF-60, SCSF-78, SCSF-3HF) and two models of plastic scintillators (BC-400, BC-408). The emission spectra of all six scintillators were obtained by using an optical spectrum analyzer and they were compared with theoretical behavior. For scintillation in the blue region, the signal intensity of a singly clad scintillating fiber (BCF-12) was 120% of that of the plastic scintillator (BC-400). For the multiclad fiber (SCSF-78), the signal reached 144% of that of the plastic scintillator. The intensity of the green scintillating fibers was lower than that of the plastic scintillator: 47% for the singly clad fiber (BCF-60) and 77% for the multiclad fiber (SCSF-3HF). The collected light was studied as a function of the scintillator length and radius for a cylindrical probe. We found that symmetric detectors with nearly the same spatial resolution in each direction (2 mm in diameter by 3 mm in length) could be made with a signal equivalent to those of the more commonly used asymmetric scintillators. With augmentation of the signal-to-noise ratio in consideration, this paper presents a series of comparisons that should provide insight into selection of a scintillator type and volume for development of a medical dosimeter.

  16. Optimal neural network architecture selection: effects on computer-aided detection of mammographic microcalcifications

    NASA Astrophysics Data System (ADS)

    Gurcan, Metin N.; Chan, Heang-Ping; Sahiner, Berkman; Hadjiiski, Lubomir M.; Petrick, Nicholas; Helvie, Mark A.

    2002-05-01

    We evaluated the effectiveness of an optimal convolution neural network (CNN) architecture selected by simulated annealing for improving the performance of a computer-aided diagnosis (CAD) system designed for the detection of microcalcification clusters on digitized mammograms. The performances of the CAD programs with manually and optimally selected CNNs were compared using an independent test set. This set included 472 mammograms and contained 253 biopsy-proven malignant clusters. Free-response receiver operating characteristic (FROC) analysis was used for evaluation of the detection accuracy. At a false positive (FP) rate of 0.7 per image, the film-based sensitivity was 84.6% with the optimized CNN, in comparison with 77.2% with the manually selected CNN. If clusters having images in both craniocaudal and mediolateral oblique views were analyzed together and a cluster was considered to be detected when it was detected in one or both views, at 0.7 FPs/image, the sensitivity was 93.3% with the optimized CNN and 87.0% with the manually selected CNN. This study indicates that classification of true positive and FP signals is an important step of the CAD program and that the detection accuracy of the program can be considerably improved by optimizing this step with an automated optimization algorithm.

  17. Mode selective generation of guided waves by systematic optimization of the interfacial shear stress profile

    NASA Astrophysics Data System (ADS)

    Yazdanpanah Moghadam, Peyman; Quaegebeur, Nicolas; Masson, Patrice

    2015-01-01

    Piezoelectric transducers are commonly used in structural health monitoring systems to generate and measure ultrasonic guided waves (GWs) by applying interfacial shear and normal stresses to the host structure. In most cases, in order to perform damage detection, advanced signal processing techniques are required, since a minimum of two dispersive modes are propagating in the host structure. In this paper, a systematic approach for mode selection is proposed by optimizing the interfacial shear stress profile applied to the host structure, representing the first step of a global optimization of selective mode actuator design. This approach has the potential of reducing the complexity of signal processing tools as the number of propagating modes could be reduced. Using the superposition principle, an analytical method is first developed for GWs excitation by a finite number of uniform segments, each contributing with a given elementary shear stress profile. Based on this, cost functions are defined in order to minimize the undesired modes and amplify the selected mode and the optimization problem is solved with a parallel genetic algorithm optimization framework. Advantages of this method over more conventional transducers tuning approaches are that (1) the shear stress can be explicitly optimized to both excite one mode and suppress other undesired modes, (2) the size of the excitation area is not constrained and mode-selective excitation is still possible even if excitation width is smaller than all excited wavelengths, and (3) the selectivity is increased and the bandwidth extended. The complexity of the optimal shear stress profile obtained is shown considering two cost functions with various optimal excitation widths and number of segments. Results illustrate that the desired mode (A0 or S0) can be excited dominantly over other modes up to a wave power ratio of 1010 using an optimal shear stress profile.

  18. Analysis of double stub tuner control stability in a many element phased array antenna with strong cross-coupling

    SciTech Connect

    Wallace, G. M.; Fitzgerald, E.; Johnson, D. K.; Kanojia, A. D.; Koert, P.; Lin, Y.; Murray, R.; Shiraiwa, S.; Terry, D. R.; Wukitch, S. J.; Hillairet, J.

    2014-02-12

    Active stub tuning with a fast ferrite tuner (FFT) allows for the system to respond dynamically to changes in the plasma impedance such as during the L-H transition or edge localized modes (ELMs), and has greatly increased the effectiveness of fusion ion cyclotron range of frequency systems. A high power waveguide double-stub tuner is under development for use with the Alcator C-Mod lower hybrid current drive (LHCD) system. Exact impedance matching with a double-stub is possible for a single radiating element under most load conditions, with the reflection coefficient reduced from Γ to Γ{sup 2} in the “forbidden region.” The relative phase shift between adjacent columns of a LHCD antenna is critical for control of the launched n{sub ∥} spectrum. Adding a double-stub tuning network will perturb the phase of the forward wave particularly if the unmatched reflection coefficient is high. This effect can be compensated by adjusting the phase of the low power microwave drive for each klystron amplifier. Cross-coupling of the reflected power between columns of the launcher must also be considered. The problem is simulated by cascading a scattering matrix for the plasma provided by a linear coupling model with the measured launcher scattering matrix and that of the FFTs. The solution is advanced in an iterative manner similar to the time-dependent behavior of the real system. System performance is presented under a range of edge density conditions from under-dense to over-dense and a range of launched n{sub ∥}.

  19. Selective waste collection optimization in Romania and its impact to urban climate

    NASA Astrophysics Data System (ADS)

    Mihai, Šercǎianu; Iacoboaea, Cristina; Petrescu, Florian; Aldea, Mihaela; Luca, Oana; Gaman, Florian; Parlow, Eberhard

    2016-08-01

    According to European Directives, transposed in national legislation, the Member States should organize separate collection systems at least for paper, metal, plastic, and glass until 2015. In Romania, since 2011 only 12% of municipal collected waste was recovered, the rest being stored in landfills, although storage is considered the last option in the waste hierarchy. At the same time there was selectively collected only 4% of the municipal waste. Surveys have shown that the Romanian people do not have selective collection bins close to their residencies. The article aims to analyze the current situation in Romania in the field of waste collection and management and to make a proposal for selective collection containers layout, using geographic information systems tools, for a case study in Romania. Route optimization is used based on remote sensing technologies and network analyst protocols. Optimizing selective collection system the greenhouse gases, particles and dust emissions can be reduced.

  20. Direct-aperture optimization applied to selection of beam orientations in intensity-modulated radiation therapy

    NASA Astrophysics Data System (ADS)

    Bedford, J. L.; Webb, S.

    2007-01-01

    Direct-aperture optimization (DAO) was applied to iterative beam-orientation selection in intensity-modulated radiation therapy (IMRT), so as to ensure a realistic segmental treatment plan at each iteration. Nested optimization engines dealt separately with gantry angles, couch angles, collimator angles, segment shapes, segment weights and wedge angles. Each optimization engine performed a random search with successively narrowing step sizes. For optimization of segment shapes, the filtered backprojection (FBP) method was first used to determine desired fluence, the fluence map was segmented, and then constrained direct-aperture optimization was used thereafter. Segment shapes were fully optimized when a beam angle was perturbed, and minimally re-optimized otherwise. The algorithm was compared with a previously reported method using FBP alone at each orientation iteration. An example case consisting of a cylindrical phantom with a hemi-annular planning target volume (PTV) showed that for three-field plans, the method performed better than when using FBP alone, but for five or more fields, neither method provided much benefit over equally spaced beams. For a prostate case, improved bladder sparing was achieved through the use of the new algorithm. A plan for partial scalp treatment showed slightly improved PTV coverage and lower irradiated volume of brain with the new method compared to FBP alone. It is concluded that, although the method is computationally intensive and not suitable for searching large unconstrained regions of beam space, it can be used effectively in conjunction with prior class solutions to provide individually optimized IMRT treatment plans.

  1. Optimal band selection for high dimensional remote sensing data using genetic algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, Xianfeng; Sun, Quan; Li, Jonathan

    2009-06-01

    A 'fused' method may not be suitable for reducing the dimensionality of data and a band/feature selection method needs to be used for selecting an optimal subset of original data bands. This study examined the efficiency of GA in band selection for remote sensing classification. A GA-based algorithm for band selection was designed deliberately in which a Bhattacharyya distance index that indicates separability between classes of interest is used as fitness function. A binary string chromosome is designed in which each gene location has a value of 1 representing a feature being included or 0 representing a band being not included. The algorithm was implemented in MATLAB programming environment, and a band selection task for lithologic classification in the Chocolate Mountain area (California) was used to test the proposed algorithm. The proposed feature selection algorithm can be useful in multi-source remote sensing data preprocessing, especially in hyperspectral dimensionality reduction.

  2. Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

    PubMed Central

    Ozekes, Serhat; Gultekin, Selahattin; Tarhan, Nevzat

    2014-01-01

    Objective Many applications such as biomedical signals require selecting a subset of the input features in order to represent the whole set of features. A feature selection algorithm has recently been proposed as a new approach for feature subset selection. Methods Feature selection process using ant colony optimization (ACO) for 6 channel pre-treatment electroencephalogram (EEG) data from theta and delta frequency bands is combined with back propagation neural network (BPNN) classification method for 147 major depressive disorder (MDD) subjects. Results BPNN classified R subjects with 91.83% overall accuracy and 95.55% subjects detection sensitivity. Area under ROC curve (AUC) value after feature selection increased from 0.8531 to 0.911. The features selected by the optimization algorithm were Fp1, Fp2, F7, F8, F3 for theta frequency band and eliminated 7 features from 12 to 5 feature subset. Conclusion ACO feature selection algorithm improves the classification accuracy of BPNN. Using other feature selection algorithms or classifiers to compare the performance for each approach is important to underline the validity and versatility of the designed combination. PMID:25110496

  3. Quantum-behaved particle swarm optimization: analysis of individual particle behavior and parameter selection.

    PubMed

    Sun, Jun; Fang, Wei; Wu, Xiaojun; Palade, Vasile; Xu, Wenbo

    2012-01-01

    Quantum-behaved particle swarm optimization (QPSO), motivated by concepts from quantum mechanics and particle swarm optimization (PSO), is a probabilistic optimization algorithm belonging to the bare-bones PSO family. Although it has been shown to perform well in finding the optimal solutions for many optimization problems, there has so far been little analysis on how it works in detail. This paper presents a comprehensive analysis of the QPSO algorithm. In the theoretical analysis, we analyze the behavior of a single particle in QPSO in terms of probability measure. Since the particle's behavior is influenced by the contraction-expansion (CE) coefficient, which is the most important parameter of the algorithm, the goal of the theoretical analysis is to find out the upper bound of the CE coefficient, within which the value of the CE coefficient selected can guarantee the convergence or boundedness of the particle's position. In the experimental analysis, the theoretical results are first validated by stochastic simulations for the particle's behavior. Then, based on the derived upper bound of the CE coefficient, we perform empirical studies on a suite of well-known benchmark functions to show how to control and select the value of the CE coefficient, in order to obtain generally good algorithmic performance in real world applications. Finally, a further performance comparison between QPSO and other variants of PSO on the benchmarks is made to show the efficiency of the QPSO algorithm with the proposed parameter control and selection methods.

  4. [The Near Infrared Spectral Bands Optimal Selection in the Application of Liquor Fermented Grains Composition Analysis].

    PubMed

    Xiong, Ya-ting; Li, Zong-peng; Wang, Jian; Zhang, Ying; Wang, Shu-jun; Yin, Jian-jun; Song, Quan-hou

    2016-01-01

    In order to improve the technical level of the rapid detection of liquor fermented grains, in this paper, use near infrared spectroscopy technology to quantitative analysis moisture, starch, acidity and alcohol of liquor fermented grains. Using CARS, iPLS and no information variable elimination method (UVE), realize the characteristics of spectral band selection. And use the multiple scattering correction (MSC), derivative and standard normal variable transformation (SNV) pretreatment method to optimize the models. Establish models of quantitative analysis of fermented grains by PLS, and in order to select the best modeling method, using R2, RMSEP and optimal number of main factors to evaluate models. The results showed that the band selection is vital to optimize the model and CARS is the best optimization of the most significant effect. The calculation results showed that R2 of moisture, starch, acidity and alcohol were 0.885, 0.915, 0.951, 0.885 respectively and RMSEP of moisture, starch, acidity and alcohol were 0.630, 0.519, 0.228, 0.234 respectively. After optimization, the model prediction effect is good, the models can satisfy the requirement of the rapid detection of liquor fermented grains, which has certain reference value in the practical. PMID:27228746

  5. A new and fast image feature selection method for developing an optimal mammographic mass detection scheme

    PubMed Central

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-01-01

    Purpose: Selecting optimal features from a large image feature pool remains a major challenge in developing computer-aided detection (CAD) schemes of medical images. The objective of this study is to investigate a new approach to significantly improve efficacy of image feature selection and classifier optimization in developing a CAD scheme of mammographic masses. Methods: An image dataset including 1600 regions of interest (ROIs) in which 800 are positive (depicting malignant masses) and 800 are negative (depicting CAD-generated false positive regions) was used in this study. After segmentation of each suspicious lesion by a multilayer topographic region growth algorithm, 271 features were computed in different feature categories including shape, texture, contrast, isodensity, spiculation, local topological features, as well as the features related to the presence and location of fat and calcifications. Besides computing features from the original images, the authors also computed new texture features from the dilated lesion segments. In order to select optimal features from this initial feature pool and build a highly performing classifier, the authors examined and compared four feature selection methods to optimize an artificial neural network (ANN) based classifier, namely: (1) Phased Searching with NEAT in a Time-Scaled Framework, (2) A sequential floating forward selection (SFFS) method, (3) A genetic algorithm (GA), and (4) A sequential forward selection (SFS) method. Performances of the four approaches were assessed using a tenfold cross validation method. Results: Among these four methods, SFFS has highest efficacy, which takes 3%–5% of computational time as compared to GA approach, and yields the highest performance level with the area under a receiver operating characteristic curve (AUC) = 0.864 ± 0.034. The results also demonstrated that except using GA, including the new texture features computed from the dilated mass segments improved the AUC

  6. Subjective Career Success and Emotional Well-Being: Longitudinal Predictive Power of Selection, Optimization, and Compensation.

    ERIC Educational Resources Information Center

    Wiese, Bettina S.; Freund, Alexandra M.; Baltes, Paul B.

    2002-01-01

    A 3-year study of 82 young professionals found that work-related well-being was predicted by selection (commitment to personal goals), optimization (application of goal-related skills), and compensation (maintaining goals in the face of loss). The degree of compensation predicted emotional well-being and job satisfaction 3 years later. (Contains…

  7. Selection, Optimization, and Compensation: An Action-Related Approach to Work and Partnership.

    ERIC Educational Resources Information Center

    Wiese, Bettina S.; Baltes, Paul B.; Freund, Alexandra M.

    2000-01-01

    Data from German professionals (n=206) were used to test selective optimization with compensation (SOC)--goal setting in career and partnership domains and use of means to achieve goals. A positive relationship was found between SOC behaviors and successful life management; it was more predictive for the partnership domain. (Contains 82…

  8. Optimization of a series of potent and selective ketone histone deacetylase inhibitors.

    PubMed

    Pescatore, Giovanna; Kinzel, Olaf; Attenni, Barbara; Cecchetti, Ottavia; Fiore, Fabrizio; Fonsi, Massimiliano; Rowley, Michael; Schultz-Fademrecht, Carsten; Serafini, Sergio; Steinkühler, Christian; Jones, Philip

    2008-10-15

    Histone deacetylase (HDAC) inhibitors offer a promising strategy for cancer therapy and the first generation HDAC inhibitors are currently in the clinic. Herein we describe the optimization of a series of ketone small molecule HDAC inhibitors leading to potent and selective class I HDAC inhibitors with good dog PK.

  9. Self-Regulatory Strategies in Daily Life: Selection, Optimization, and Compensation and Everyday Memory Problems

    ERIC Educational Resources Information Center

    Robinson, Stephanie A.; Rickenbach, Elizabeth H.; Lachman, Margie E.

    2016-01-01

    The effective use of self-regulatory strategies, such as selection, optimization, and compensation (SOC) requires resources. However, it is theorized that SOC use is most advantageous for those experiencing losses and diminishing resources. The present study explored this seeming paradox within the context of limitations or constraints due to…

  10. Exploring the optimal performances of irreversible single resonance energy selective electron refrigerators

    NASA Astrophysics Data System (ADS)

    Zhou, Junle; Chen, Lingen; Ding, Zemin; Sun, Fengrui

    2016-05-01

    Applying finite-time thermodynamics (FTT) and electronic transport theory, the optimal performances of irreversible single resonance energy selective electron (ESE) refrigerator are analyzed. The effects of heat leakage between two electron reservoirs on optimal performances are discussed. The influences of system operating parameters on cooling load, coefficient of performance (COP), figure of merit and ecological function are demonstrated using numerical examples. Comparative performance analyses among different objective functions show that performance characteristics at maximum ecological function and maximum figure of merit are of great practical significance. Combining the two optimization objectives of maximum ecological function and maximum figure of merit together, more specific optimal ranges of cooling load and COP are obtained. The results can provide some advices to the design of practical electronic machine systems.

  11. Selection of Thermal Worst-Case Orbits via Modified Efficient Global Optimization

    NASA Technical Reports Server (NTRS)

    Moeller, Timothy M.; Wilhite, Alan W.; Liles, Kaitlin A.

    2014-01-01

    Efficient Global Optimization (EGO) was used to select orbits with worst-case hot and cold thermal environments for the Stratospheric Aerosol and Gas Experiment (SAGE) III. The SAGE III system thermal model changed substantially since the previous selection of worst-case orbits (which did not use the EGO method), so the selections were revised to ensure the worst cases are being captured. The EGO method consists of first conducting an initial set of parametric runs, generated with a space-filling Design of Experiments (DoE) method, then fitting a surrogate model to the data and searching for points of maximum Expected Improvement (EI) to conduct additional runs. The general EGO method was modified by using a multi-start optimizer to identify multiple new test points at each iteration. This modification facilitates parallel computing and decreases the burden of user interaction when the optimizer code is not integrated with the model. Thermal worst-case orbits for SAGE III were successfully identified and shown by direct comparison to be more severe than those identified in the previous selection. The EGO method is a useful tool for this application and can result in computational savings if the initial Design of Experiments (DoE) is selected appropriately.

  12. A general method to select representative models for decision making and optimization under uncertainty

    NASA Astrophysics Data System (ADS)

    Shirangi, Mehrdad G.; Durlofsky, Louis J.

    2016-11-01

    The optimization of subsurface flow processes under geological uncertainty technically requires flow simulation to be performed over a large set of geological realizations for each function evaluation at every iteration of the optimizer. Because flow simulation over many permeability realizations (only permeability is considered to be uncertain in this study) may entail excessive computation, simulations are often performed for only a subset of 'representative' realizations. It is however challenging to identify a representative subset that provides flow statistics in close agreement with those from the full set, especially when the decision parameters (e.g., time-varying well pressures, well locations) are unknown a priori, as they are in optimization problems. In this work, we introduce a general framework, based on clustering, for selecting a representative subset of realizations for use in simulations involving 'new' sets of decision parameters. Prior to clustering, each realization is represented by a low-dimensional feature vector that contains a combination of permeability-based and flow-based quantities. Calculation of flow-based features requires the specification of a (base) flow problem and simulation over the full set of realizations. Permeability information is captured concisely through use of principal component analysis. By computing the difference between the flow response for the subset and the full set, we quantify the performance of various realization-selection methods. The impact of different weightings for flow and permeability information in the cluster-based selection procedure is assessed for a range of examples involving different types of decision parameters. These decision parameters are generated either randomly, in a manner that is consistent with the solutions proposed in global stochastic optimization procedures such as GA and PSO, or through perturbation around a base case, consistent with the solutions considered in pattern search

  13. A Novel Method of Failure Sample Selection for Electrical Systems Using Ant Colony Optimization

    PubMed Central

    Tian, Shulin; Yang, Chenglin; Liu, Cheng

    2016-01-01

    The influence of failure propagation is ignored in failure sample selection based on traditional testability demonstration experiment method. Traditional failure sample selection generally causes the omission of some failures during the selection and this phenomenon could lead to some fearful risks of usage because these failures will lead to serious propagation failures. This paper proposes a new failure sample selection method to solve the problem. First, the method uses a directed graph and ant colony optimization (ACO) to obtain a subsequent failure propagation set (SFPS) based on failure propagation model and then we propose a new failure sample selection method on the basis of the number of SFPS. Compared with traditional sampling plan, this method is able to improve the coverage of testing failure samples, increase the capacity of diagnosis, and decrease the risk of using. PMID:27738424

  14. A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

    SciTech Connect

    Kim, Minsun Stewart, Robert D.; Phillips, Mark H.

    2015-11-15

    Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T{sub d}), and the size and location of tumor target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D{sub mean} ≤ 45 Gy), lungs (D{sub mean} ≤ 20 Gy), cord (D{sub max} ≤ 45 Gy), esophagus (D{sub max} ≤ 63 Gy), and unspecified tissues (D{sub 05} ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D{sub 95} of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T{sub d} (3–100 days), tumor lag-time (T{sub k} = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D{sub 95} were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T{sub d} and T{sub k} used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating

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

    PubMed

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

    2014-10-01

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

  16. Space debris selection and optimal guidance for removal in the SSO with low-thrust propulsion

    NASA Astrophysics Data System (ADS)

    Olympio, J. T.; Frouvelle, N.

    2014-06-01

    The current paper deals with the mission design of a generic active space debris removal spacecraft. Considered space debris are all on sun-synchronous orbits. A perturbed Lambert's problem, modelling the transfer between two space debris is devised to take into account J2 perturbation, and to quickly evaluate mission scenarios. A robust approach, using techniques of global optimisation, is followed to find the optimal space debris sequence and mission strategy. Low-thrust optimisation is then performed to turn bi-impulse transfers into optimal low-thrust transfers, and refine the selected scenarios.

  17. Optimal decision rule with class-selective rejection and performance constraints.

    PubMed

    Grall-Maës, Edith; Beauseroy, Pierre

    2009-11-01

    The problem of defining a decision rule which takes into account performance constraints and class-selective rejection is formalized in a general framework. In the proposed formulation, the problem is defined using three kinds of criteria. The first is the cost to be minimized, which defines the objective function, the second are the decision options, determined by the admissible assignment classes or subsets of classes, and the third are the performance constraints. The optimal decision rule within the statistical decision theory framework is obtained by solving the stated optimization problem. Two examples are provided to illustrate the formulation and the decision rule is obtained.

  18. Optimum selection of mechanism type for heavy manipulators based on particle swarm optimization method

    NASA Astrophysics Data System (ADS)

    Zhao, Yong; Chen, Genliang; Wang, Hao; Lin, Zhongqin

    2013-07-01

    The mechanism type plays a decisive role in the mechanical performance of robotic manipulators. Feasible mechanism types can be obtained by applying appropriate type synthesis theory, but there is still a lack of effective and efficient methods for the optimum selection among different types of mechanism candidates. This paper presents a new strategy for the purpose of optimum mechanism type selection based on the modified particle swarm optimization method. The concept of sub-swarm is introduced to represent the different mechanisms generated by the type synthesis, and a competitive mechanism is employed between the sub-swarms to reassign their population size according to the relative performances of the mechanism candidates to implement the optimization. Combining with a modular modeling approach for fast calculation of the performance index of the potential candidates, the proposed method is applied to determine the optimum mechanism type among the potential candidates for the desired manipulator. The effectiveness and efficiency of the proposed method is demonstrated through a case study on the optimum selection of mechanism type of a heavy manipulator where six feasible candidates are considered with force capability as the specific performance index. The optimization result shows that the fitness of the optimum mechanism type for the considered heavy manipulator can be up to 0.578 5. This research provides the instruction in optimum selection of mechanism types for robotic manipulators.

  19. An experimental and theoretical investigation of a fuel system tuner for the suppression of combustion driven oscillations

    NASA Astrophysics Data System (ADS)

    Scarborough, David E.

    Manufacturers of commercial, power-generating, gas turbine engines continue to develop combustors that produce lower emissions of nitrogen oxides (NO x) in order to meet the environmental standards of governments around the world. Lean, premixed combustion technology is one technique used to reduce NOx emissions in many current power and energy generating systems. However, lean, premixed combustors are susceptible to thermo-acoustic oscillations, which are pressure and heat-release fluctuations that occur because of a coupling between the combustion process and the natural acoustic modes of the system. These pressure oscillations lead to premature failure of system components, resulting in very costly maintenance and downtime. Therefore, a great deal of work has gone into developing methods to prevent or eliminate these combustion instabilities. This dissertation presents the results of a theoretical and experimental investigation of a novel Fuel System Tuner (FST) used to damp detrimental combustion oscillations in a gas turbine combustor by changing the fuel supply system impedance, which controls the amplitude and phase of the fuel flowrate. When the FST is properly tuned, the heat release oscillations resulting from the fuel-air ratio oscillations damp, rather than drive, the combustor acoustic pressure oscillations. A feasibility study was conducted to prove the validity of the basic idea and to develop some basic guidelines for designing the FST. Acoustic models for the subcomponents of the FST were developed, and these models were experimentally verified using a two-microphone impedance tube. Models useful for designing, analyzing, and predicting the performance of the FST were developed and used to demonstrate the effectiveness of the FST. Experimental tests showed that the FST reduced the acoustic pressure amplitude of an unstable, model, gas-turbine combustor over a wide range of operating conditions and combustor configurations. Finally, combustor

  20. An analysis of an optimal selection process for characteristics and technical performance of baseball pitchers.

    PubMed

    Lin, Wen-Bin; Tung, I-Wu; Chen, Mei-Jung; Chen, Mei-Yen

    2011-08-01

    Selection of a qualified pitcher has relied previously on qualitative indices; here, both quantitative and qualitative indices including pitching statistics, defense, mental skills, experience, and managers' recognition were collected, and an analytic hierarchy process was used to rank baseball pitchers. The participants were 8 experts who ranked characteristics and statistics of 15 baseball pitchers who comprised the first round of potential representatives for the Chinese Taipei National Baseball team. The results indicated a selection rate that was 91% consistent with the official national team roster, as 11 pitchers with the highest scores who were recommended as optimal choices to be official members of the Chinese Tai-pei National Baseball team actually participated in the 2009 Baseball World Cup. An analytic hierarchy can aid in selection of qualified pitchers, depending on situational and practical needs; the method could be extended to other sports and team-selection situations. PMID:21987928

  1. In Vitro Selection of Optimal DNA Substrates for Ligation by a Water-Soluble Carbodiimide

    NASA Technical Reports Server (NTRS)

    Harada, Kazuo; Orgel, Leslie E.

    1994-01-01

    We have used in vitro selection to investigate the sequence requirements for efficient template-directed ligation of oligonucleotides at 0 deg C using a water-soluble carbodiimide as condensing agent. We find that only 2 bp at each side of the ligation junction are needed. We also studied chemical ligation of substrate ensembles that we have previously selected as optimal by RNA ligase or by DNA ligase. As anticipated, we find that substrates selected with DNA ligase ligate efficiently with a chemical ligating agent, and vice versa. Substrates selected using RNA ligase are not ligated by the chemical condensing agent and vice versa. The implications of these results for prebiotic chemistry are discussed.

  2. An analysis of an optimal selection process for characteristics and technical performance of baseball pitchers.

    PubMed

    Lin, Wen-Bin; Tung, I-Wu; Chen, Mei-Jung; Chen, Mei-Yen

    2011-08-01

    Selection of a qualified pitcher has relied previously on qualitative indices; here, both quantitative and qualitative indices including pitching statistics, defense, mental skills, experience, and managers' recognition were collected, and an analytic hierarchy process was used to rank baseball pitchers. The participants were 8 experts who ranked characteristics and statistics of 15 baseball pitchers who comprised the first round of potential representatives for the Chinese Taipei National Baseball team. The results indicated a selection rate that was 91% consistent with the official national team roster, as 11 pitchers with the highest scores who were recommended as optimal choices to be official members of the Chinese Tai-pei National Baseball team actually participated in the 2009 Baseball World Cup. An analytic hierarchy can aid in selection of qualified pitchers, depending on situational and practical needs; the method could be extended to other sports and team-selection situations.

  3. Optoelectronic optimization of mode selective converter based on liquid crystal on silicon

    NASA Astrophysics Data System (ADS)

    Wang, Yongjiao; Liang, Lei; Yu, Dawei; Fu, Songnian

    2016-03-01

    We carry out comprehensive optoelectronic optimization of mode selective converter used for the mode division multiplexing, based on liquid crystal on silicon (LCOS) in binary mode. The conversion error of digital-to-analog (DAC) is investigated quantitatively for the purpose of driving the LCOS in the application of mode selective conversion. Results indicate the DAC must have a resolution of 8-bit, in order to achieve high mode extinction ratio (MER) of 28 dB. On the other hand, both the fast axis position error of half-wave-plate (HWP) and rotation angle error of Faraday rotator (FR) have negative influence on the performance of mode selective conversion. However, the commercial products provide enough angle error tolerance for the LCOS-based mode selective converter, taking both of insertion loss (IL) and MER into account.

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

    PubMed

    Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

    2015-01-01

    This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme. PMID:26690571

  5. On the non-stationarity of financial time series: impact on optimal portfolio selection

    NASA Astrophysics Data System (ADS)

    Livan, Giacomo; Inoue, Jun-ichi; Scalas, Enrico

    2012-07-01

    We investigate the possible drawbacks of employing the standard Pearson estimator to measure correlation coefficients between financial stocks in the presence of non-stationary behavior, and we provide empirical evidence against the well-established common knowledge that using longer price time series provides better, more accurate, correlation estimates. Then, we investigate the possible consequences of instabilities in empirical correlation coefficient measurements on optimal portfolio selection. We rely on previously published works which provide a framework allowing us to take into account possible risk underestimations due to the non-optimality of the portfolio weights being used in order to distinguish such non-optimality effects from risk underestimations genuinely due to non-stationarities. We interpret such results in terms of instabilities in some spectral properties of portfolio correlation matrices.

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

    PubMed Central

    Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

    2015-01-01

    This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme. PMID:26690571

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

    PubMed

    Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

    2015-01-01

    This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme.

  8. Gadolinium contrast agent selection and optimal use for body MR imaging.

    PubMed

    Guglielmo, Flavius F; Mitchell, Donald G; Gupta, Shiva

    2014-07-01

    Proper selection of a gadolinium-based contrast agent (GBCA) for body magnetic resonance imaging (MRI) cases requires understanding the indication for the MRI exam, the key features of the different GBCAs, and the effect that the GBCA has on the selected imaging protocol. The different categories of GBCAs require timing optimization on postcontrast sequences and adjusting imaging parameters to obtain the highest T1 contrast. Gadoxetate disodium has many advantages when evaluating liver lesions, although there are caveats and limitations that need to be understood. Gadobenate dimeglumine, a high-relaxivity GBCA, can be used for indications when stronger T1 relaxivity is needed.

  9. Optimal Sensor Selection for Classifying a Set of Ginsengs Using Metal-Oxide Sensors.

    PubMed

    Miao, Jiacheng; Zhang, Tinglin; Wang, You; Li, Guang

    2015-07-03

    The sensor selection problem was investigated for the application of classification of a set of ginsengs using a metal-oxide sensor-based homemade electronic nose with linear discriminant analysis. Samples (315) were measured for nine kinds of ginsengs using 12 sensors. We investigated the classification performances of combinations of 12 sensors for the overall discrimination of combinations of nine ginsengs. The minimum numbers of sensors for discriminating each sample set to obtain an optimal classification performance were defined. The relation of the minimum numbers of sensors with number of samples in the sample set was revealed. The results showed that as the number of samples increased, the average minimum number of sensors increased, while the increment decreased gradually and the average optimal classification rate decreased gradually. Moreover, a new approach of sensor selection was proposed to estimate and compare the effective information capacity of each sensor.

  10. Imaging multicellular specimens with real-time optimized tiling light-sheet selective plane illumination microscopy.

    PubMed

    Fu, Qinyi; Martin, Benjamin L; Matus, David Q; Gao, Liang

    2016-01-01

    Despite the progress made in selective plane illumination microscopy, high-resolution 3D live imaging of multicellular specimens remains challenging. Tiling light-sheet selective plane illumination microscopy (TLS-SPIM) with real-time light-sheet optimization was developed to respond to the challenge. It improves the 3D imaging ability of SPIM in resolving complex structures and optimizes SPIM live imaging performance by using a real-time adjustable tiling light sheet and creating a flexible compromise between spatial and temporal resolution. We demonstrate the 3D live imaging ability of TLS-SPIM by imaging cellular and subcellular behaviours in live C. elegans and zebrafish embryos, and show how TLS-SPIM can facilitate cell biology research in multicellular specimens by studying left-right symmetry breaking behaviour of C. elegans embryos. PMID:27004937

  11. Maximal area and conformal welding heuristics for optimal slice selection in splenic volume estimation

    NASA Astrophysics Data System (ADS)

    Gutenko, Ievgeniia; Peng, Hao; Gu, Xianfeng; Barish, Mathew; Kaufman, Arie

    2016-03-01

    Accurate estimation of splenic volume is crucial for the determination of disease progression and response to treatment for diseases that result in enlargement of the spleen. However, there is no consensus with respect to the use of single or multiple one-dimensional, or volumetric measurement. Existing methods for human reviewers focus on measurement of cross diameters on a representative axial slice and craniocaudal length of the organ. We propose two heuristics for the selection of the optimal axial plane for splenic volume estimation: the maximal area axial measurement heuristic and the novel conformal welding shape-based heuristic. We evaluate these heuristics on time-variant data derived from both healthy and sick subjects and contrast them to established heuristics. Under certain conditions our heuristics are superior to standard practice volumetric estimation methods. We conclude by providing guidance on selecting the optimal heuristic for splenic volume estimation.

  12. Techniques for optimal crop selection in a controlled ecological life support system

    NASA Technical Reports Server (NTRS)

    Mccormack, Ann; Finn, Cory; Dunsky, Betsy

    1993-01-01

    A Controlled Ecological Life Support System (CELSS) utilizes a plant's natural ability to regenerate air and water while being grown as a food source in a closed life support system. Current plant research is directed toward obtaining quantitative empirical data on the regenerative ability of each species of plant and the system volume and power requirements. Two techniques were adapted to optimize crop species selection while at the same time minimizing the system volume and power requirements. Each allows the level of life support supplied by the plants to be selected, as well as other system parameters. The first technique uses decision analysis in the form of a spreadsheet. The second method, which is used as a comparison with and validation of the first, utilizes standard design optimization techniques. Simple models of plant processes are used in the development of these methods.

  13. Techniques for optimal crop selection in a controlled ecological life support system

    NASA Technical Reports Server (NTRS)

    Mccormack, Ann; Finn, Cory; Dunsky, Betsy

    1992-01-01

    A Controlled Ecological Life Support System (CELSS) utilizes a plant's natural ability to regenerate air and water while being grown as a food source in a closed life support system. Current plant research is directed toward obtaining quantitative empirical data on the regenerative ability of each species of plant and the system volume and power requirements. Two techniques were adapted to optimize crop species selection while at the same time minimizing the system volume and power requirements. Each allows the level of life support supplied by the plants to be selected, as well as other system parameters. The first technique uses decision analysis in the form of a spreadsheet. The second method, which is used as a comparison with and validation of the first, utilizes standard design optimization techniques. Simple models of plant processes are used in the development of these methods.

  14. Imaging multicellular specimens with real-time optimized tiling light-sheet selective plane illumination microscopy

    PubMed Central

    Fu, Qinyi; Martin, Benjamin L.; Matus, David Q.; Gao, Liang

    2016-01-01

    Despite the progress made in selective plane illumination microscopy, high-resolution 3D live imaging of multicellular specimens remains challenging. Tiling light-sheet selective plane illumination microscopy (TLS-SPIM) with real-time light-sheet optimization was developed to respond to the challenge. It improves the 3D imaging ability of SPIM in resolving complex structures and optimizes SPIM live imaging performance by using a real-time adjustable tiling light sheet and creating a flexible compromise between spatial and temporal resolution. We demonstrate the 3D live imaging ability of TLS-SPIM by imaging cellular and subcellular behaviours in live C. elegans and zebrafish embryos, and show how TLS-SPIM can facilitate cell biology research in multicellular specimens by studying left-right symmetry breaking behaviour of C. elegans embryos. PMID:27004937

  15. Ant-cuckoo colony optimization for feature selection in digital mammogram.

    PubMed

    Jona, J B; Nagaveni, N

    2014-01-15

    Digital mammogram is the only effective screening method to detect the breast cancer. Gray Level Co-occurrence Matrix (GLCM) textural features are extracted from the mammogram. All the features are not essential to detect the mammogram. Therefore identifying the relevant feature is the aim of this work. Feature selection improves the classification rate and accuracy of any classifier. In this study, a new hybrid metaheuristic named Ant-Cuckoo Colony Optimization a hybrid of Ant Colony Optimization (ACO) and Cuckoo Search (CS) is proposed for feature selection in Digital Mammogram. ACO is a good metaheuristic optimization technique but the drawback of this algorithm is that the ant will walk through the path where the pheromone density is high which makes the whole process slow hence CS is employed to carry out the local search of ACO. Support Vector Machine (SVM) classifier with Radial Basis Kernal Function (RBF) is done along with the ACO to classify the normal mammogram from the abnormal mammogram. Experiments are conducted in miniMIAS database. The performance of the new hybrid algorithm is compared with the ACO and PSO algorithm. The results show that the hybrid Ant-Cuckoo Colony Optimization algorithm is more accurate than the other techniques. PMID:24783812

  16. Ant-cuckoo colony optimization for feature selection in digital mammogram.

    PubMed

    Jona, J B; Nagaveni, N

    2014-01-15

    Digital mammogram is the only effective screening method to detect the breast cancer. Gray Level Co-occurrence Matrix (GLCM) textural features are extracted from the mammogram. All the features are not essential to detect the mammogram. Therefore identifying the relevant feature is the aim of this work. Feature selection improves the classification rate and accuracy of any classifier. In this study, a new hybrid metaheuristic named Ant-Cuckoo Colony Optimization a hybrid of Ant Colony Optimization (ACO) and Cuckoo Search (CS) is proposed for feature selection in Digital Mammogram. ACO is a good metaheuristic optimization technique but the drawback of this algorithm is that the ant will walk through the path where the pheromone density is high which makes the whole process slow hence CS is employed to carry out the local search of ACO. Support Vector Machine (SVM) classifier with Radial Basis Kernal Function (RBF) is done along with the ACO to classify the normal mammogram from the abnormal mammogram. Experiments are conducted in miniMIAS database. The performance of the new hybrid algorithm is compared with the ACO and PSO algorithm. The results show that the hybrid Ant-Cuckoo Colony Optimization algorithm is more accurate than the other techniques.

  17. Selection of optimal threshold to construct recurrence plot for structural operational vibration measurements

    NASA Astrophysics Data System (ADS)

    Yang, Dong; Ren, Wei-Xin; Hu, Yi-Ding; Li, Dan

    2015-08-01

    The structural health monitoring (SHM) involves the sampled operational vibration measurements over time so that the structural features can be extracted accordingly. The recurrence plot (RP) and corresponding recurrence quantification analysis (RQA) have become a useful tool in various fields due to its efficiency. The threshold selection is one of key issues to make sure that the constructed recurrence plot contains enough recurrence points. Different signals have in nature different threshold values. This paper is aiming at presenting an approach to determine the optimal threshold for the operational vibration measurements of civil engineering structures. The surrogate technique and Taguchi loss function are proposed to generate reliable data and to achieve the optimal discrimination power point where the threshold is optimum. The impact of selecting recurrence thresholds on different signals is discussed. It is demonstrated that the proposed method to identify the optimal threshold is applicable to the operational vibration measurements. The proposed method provides a way to find the optimal threshold for the best RP construction of structural vibration measurements under operational conditions.

  18. Optimal band selection in hyperspectral remote sensing of aquatic benthic features: a wavelet filter window approach

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R., Jr.

    2006-09-01

    This paper describes a wavelet based approach to derivative spectroscopy. The approach is utilized to select, through optimization, optimal channels or bands to use as derivative based remote sensing algorithms. The approach is applied to airborne and modeled or synthetic reflectance signatures of environmental media and features or objects within such media, such as benthic submerged vegetation canopies. The technique can also applied to selected pixels identified within a hyperspectral image cube obtained from an board an airborne, ground based, or subsurface mobile imaging system. This wavelet based image processing technique is an extremely fast numerical method to conduct higher order derivative spectroscopy which includes nonlinear filter windows. Essentially, the wavelet filter scans a measured or synthetic signature in an automated sequential manner in order to develop a library of filtered spectra. The library is utilized in real time to select the optimal channels for direct algorithm application. The unique wavelet based derivative filtering technique makes us of a translating, and dilating derivative spectroscopy signal processing (TDDS-SP (R)) approach based upon remote sensing science and radiative transfer processes unlike other signal processing techniques applied to hyperspectral signatures.

  19. A multi-objective optimization tool for the selection and placement of BMPs for pesticide control

    NASA Astrophysics Data System (ADS)

    Maringanti, C.; Chaubey, I.; Arabi, M.; Engel, B.

    2008-07-01

    Pesticides (particularly atrazine used in corn fields) are the foremost source of water contamination in many of the water bodies in Midwestern corn belt, exceeding the 3 ppb MCL established by the U.S. EPA for drinking water. Best management practices (BMPs), such as buffer strips and land management practices, have been proven to effectively reduce the pesticide pollution loads from agricultural areas. However, selection and placement of BMPs in watersheds to achieve an ecologically effective and economically feasible solution is a daunting task. BMP placement decisions under such complex conditions require a multi-objective optimization algorithm that would search for the best possible solution that satisfies the given watershed management objectives. Genetic algorithms (GA) have been the most popular optimization algorithms for the BMP selection and placement problem. Most optimization models also had a dynamic linkage with the water quality model, which increased the computation time considerably thus restricting them to apply models on field scale or relatively smaller (11 or 14 digit HUC) watersheds. However, most previous works have considered the two objectives individually during the optimization process by introducing a constraint on the other objective, therefore decreasing the degree of freedom to find the solution. In this study, the optimization for atrazine reduction is performed by considering the two objectives simultaneously using a multi-objective genetic algorithm (NSGA-II). The limitation with the dynamic linkage with a distributed parameter watershed model was overcome through the utilization of a BMP tool, a database that stores the pollution reduction and cost information of different BMPs under consideration. The model was used for the selection and placement of BMPs in Wildcat Creek Watershed (located in Indiana, for atrazine reduction. The most ecologically effective solution from the model had an annual atrazine concentration reduction

  20. Near optimal energy selective x-ray imaging system performance with simple detectors

    SciTech Connect

    Alvarez, Robert E.

    2010-02-15

    Purpose: This article describes a method to achieve near optimal performance with low energy resolution detectors. Tapiovaara and Wagner [Phys. Med. Biol. 30, 519-529 (1985)] showed that an energy selective x-ray system using a broad spectrum source can produce images with a larger signal to noise ratio (SNR) than conventional systems using energy integrating or photon counting detectors. They showed that there is an upper limit to the SNR and that it can be achieved by measuring full spectrum information and then using an optimal energy dependent weighting. Methods: A performance measure is derived by applying statistical detection theory to an abstract vector space of the line integrals of the basis set coefficients of the two function approximation to the x-ray attenuation coefficient. The approach produces optimal results that utilize all the available energy dependent data. The method can be used with any energy selective detector and is applied not only to detectors using pulse height analysis (PHA) but also to a detector that simultaneously measures the total photon number and integrated energy, as discussed by Roessl et al. [Med. Phys. 34, 959-966 (2007)]. A generalization of this detector that improves the performance is introduced. A method is described to compute images with the optimal SNR using projections in a ''whitened'' vector space transformed so the noise is uncorrelated and has unit variance in both coordinates. Material canceled images with optimal SNR can also be computed by projections in this space. Results: The performance measure is validated by showing that it provides the Tapiovaara-Wagner optimal results for a detector with full energy information and also a conventional detector. The performance with different types of detectors is compared to the ideal SNR as a function of x-ray tube voltage and subject thickness. A detector that combines two bin PHA with a simultaneous measurement of integrated photon energy provides near ideal

  1. Optimal part and module selection for synthetic gene circuit design automation.

    PubMed

    Huynh, Linh; Tagkopoulos, Ilias

    2014-08-15

    An integral challenge in synthetic circuit design is the selection of optimal parts to populate a given circuit topology, so that the resulting circuit behavior best approximates the desired one. In some cases, it is also possible to reuse multipart constructs or modules that have been already built and experimentally characterized. Efficient part and module selection algorithms are essential to systematically search the solution space, and their significance will only increase in the following years due to the projected explosion in part libraries and circuit complexity. Here, we address this problem by introducing a structured abstraction methodology and a dynamic programming-based algorithm that guaranties optimal part selection. In addition, we provide three extensions that are based on symmetry check, information look-ahead and branch-and-bound techniques, to reduce the running time and space requirements. We have evaluated the proposed methodology with a benchmark of 11 circuits, a database of 73 parts and 304 experimentally constructed modules with encouraging results. This work represents a fundamental departure from traditional heuristic-based methods for part and module selection and is a step toward maximizing efficiency in synthetic circuit design and construction.

  2. Optimal part and module selection for synthetic gene circuit design automation.

    PubMed

    Huynh, Linh; Tagkopoulos, Ilias

    2014-08-15

    An integral challenge in synthetic circuit design is the selection of optimal parts to populate a given circuit topology, so that the resulting circuit behavior best approximates the desired one. In some cases, it is also possible to reuse multipart constructs or modules that have been already built and experimentally characterized. Efficient part and module selection algorithms are essential to systematically search the solution space, and their significance will only increase in the following years due to the projected explosion in part libraries and circuit complexity. Here, we address this problem by introducing a structured abstraction methodology and a dynamic programming-based algorithm that guaranties optimal part selection. In addition, we provide three extensions that are based on symmetry check, information look-ahead and branch-and-bound techniques, to reduce the running time and space requirements. We have evaluated the proposed methodology with a benchmark of 11 circuits, a database of 73 parts and 304 experimentally constructed modules with encouraging results. This work represents a fundamental departure from traditional heuristic-based methods for part and module selection and is a step toward maximizing efficiency in synthetic circuit design and construction. PMID:24933033

  3. Automatic selection of optimal segmentation scales for high-resolution remote sensing images

    NASA Astrophysics Data System (ADS)

    Yin, Ruijuan; Shi, Runhe; Gao, Wei

    2013-09-01

    To extract information from high resolution images is a challenge work.Compared tothe traditional pixel-based approach, the advantages of object-oriented classification methods are well documented. However, the appropriate scale parametersofthese methods are difficult to be determined, andthe choices of scale parametersareof high importance, whichwill havea strong effect on the segmentation effectiveness. Whereas the evaluations of the quality of a segmentation method are still mainly based onsubjective judgment, which is a complicated process and lacksstability and reliability. Thus, an objective and unsupervised method needs to beestablished for selecting suitable parameters for a multi-scale segmentation to ensure the bestresults. In this work, a novicemethod is introduced to choose the optimal parameter for themulti-scale segmentation. For large information in band itself and weak relationship among multispectral bands, valuable bands should be selected from original data and weighed by the degreeofcorrelation. Then thresholds of all 3 selected bands ranging from 20 to 200 (intervals of 10)are created in Definiens Professional 8.7. It considers that a segmentation has two desirable properties: each of the resulting segments should be internally homogeneous and should be distinguishable from its neighborhood. Therefore, the global intra-segment and inter-segment heterogeneity indexes are taken into account to identify the optimal segmentation scale. Finally, cubic spline interpolation is applied to select the optimalsegmentation scale. As a result, the measure combining a spatial autocorrelation indicator and a variance indicator shows that the method can improve the precision in global segmentation.

  4. Fuzzy Random λ-Mean SAD Portfolio Selection Problem: An Ant Colony Optimization Approach

    NASA Astrophysics Data System (ADS)

    Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mitra, Swapan Kumar

    2010-10-01

    To reach the investment goal, one has to select a combination of securities among different portfolios containing large number of securities. Only the past records of each security do not guarantee the future return. As there are many uncertain factors which directly or indirectly influence the stock market and there are also some newer stock markets which do not have enough historical data, experts' expectation and experience must be combined with the past records to generate an effective portfolio selection model. In this paper the return of security is assumed to be Fuzzy Random Variable Set (FRVS), where returns are set of random numbers which are in turn fuzzy numbers. A new λ-Mean Semi Absolute Deviation (λ-MSAD) portfolio selection model is developed. The subjective opinions of the investors to the rate of returns of each security are taken into consideration by introducing a pessimistic-optimistic parameter vector λ. λ-Mean Semi Absolute Deviation (λ-MSAD) model is preferred as it follows absolute deviation of the rate of returns of a portfolio instead of the variance as the measure of the risk. As this model can be reduced to Linear Programming Problem (LPP) it can be solved much faster than quadratic programming problems. Ant Colony Optimization (ACO) is used for solving the portfolio selection problem. ACO is a paradigm for designing meta-heuristic algorithms for combinatorial optimization problem. Data from BSE is used for illustration.

  5. New approach for automatic recognition of melanoma in profilometry: optimized feature selection using genetic algorithms

    NASA Astrophysics Data System (ADS)

    Handels, Heinz; Ross, Th; Kreusch, J.; Wolff, H. H.; Poeppl, S. J.

    1998-06-01

    A new approach to computer supported recognition of melanoma and naevocytic naevi based on high resolution skin surface profiles is presented. Profiles are generated by sampling an area of 4 X 4 mm2 at a resolution of 125 sample points per mm with a laser profilometer at a vertical resolution of 0.1 micrometers . With image analysis algorithms Haralick's texture parameters, Fourier features and features based on fractal analysis are extracted. In order to improve classification performance, a subsequent feature selection process is applied to determine the best possible subset of features. Genetic algorithms are optimized for the feature selection process, and results of different approaches are compared. As quality measure for feature subsets, the error rate of the nearest neighbor classifier estimated with the leaving-one-out method is used. In comparison to heuristic strategies and greedy algorithms, genetic algorithms show the best results for the feature selection problem. After feature selection, several architectures of feed forward neural networks with error back-propagation are evaluated. Classification performance of the neural classifier is optimized using different topologies, learning parameters and pruning algorithms. The best neural classifier achieved an error rate of 4.5% and was found after network pruning. The best result in all with an error rate of 2.3% was obtained with the nearest neighbor classifier.

  6. Rotating disk potentiometry for inner solution optimization of low-detection-limit ion-selective electrodes.

    PubMed

    Radu, Aleksandar; Telting-Diaz, Martin; Bakker, Eric

    2003-12-15

    The extent of optimization of the lower detection limit of ion-selective electrodes (ISEs) can be assessed with an elegant new method. At the detection limit (i.e., in the absence of primary ions in the sample), one can observe a reproducible change in the membrane potential upon alteration of the aqueous diffusion layer thickness. This stir effect is predicted to depend on the composition of the inner solution, which is known to influence the lower detection limit of the potentiometric sensor dramatically. For an optimized electrode, the stir effect is calculated to be exactly one-half the value of the case when substantial coextraction occurs at the inner membrane side. In contrast, there is no stir effect when substantial ion exchange occurs at the inner membrane side. Consequently, this experimental method can be used to determine how well the inner filling solution has been optimized. A rotating disk electrode was used in this study because it provides adequate control of the aqueous diffusion layer thickness. Various ion-selective membranes with a variety of inner solutions that gave different calculated concentrations of the complex at the inner membrane side were studied to evaluate this principle. They contained the well-examined silver ionophore O,O' '-bis[2-(methylthio)ethyl]-tert-butylcalix[4]arene, the potassium ionophore valinomycin, or the iodide carrier [9]mercuracarborand-3. Stir effects were determined in different background solutions and compared to theoretical expectations. Correlations were good, and the results encourage the use of such stir-effect measurements to optimize ISE compositions for real-world applications. The technique was also found to be useful in estimating the level of primary ion impurities in the sample. For an iodide-selective electrode measured in phosphoric acid, for example, apparent iodide impurity levels were calculated as 5 x 10(-10) M.

  7. Selection of optimal artificial boundary condition (ABC) frequencies for structural damage identification

    NASA Astrophysics Data System (ADS)

    Mao, Lei; Lu, Yong

    2016-07-01

    In this paper, the sensitivities of artificial boundary condition (ABC) frequencies to the damages are investigated, and the optimal sensors are selected to provide the reliable structural damage identification. The sensitivity expressions for one-pin and two-pin ABC frequencies, which are the natural frequencies from structures with one and two additional constraints to its original boundary condition, respectively, are proposed. Based on the expressions, the contributions of the underlying mode shapes in the ABC frequencies can be calculated and used to select more sensitive ABC frequencies. Selection criteria are then defined for different conditions, and their performance in structural damage identification is examined with numerical studies. From the findings, conclusions are given.

  8. Computer-aided image geometry analysis and subset selection for optimizing texture quality in photorealistic models

    NASA Astrophysics Data System (ADS)

    Sima, Aleksandra Anna; Bonaventura, Xavier; Feixas, Miquel; Sbert, Mateu; Howell, John Anthony; Viola, Ivan; Buckley, Simon John

    2013-03-01

    Photorealistic 3D models are used for visualization, interpretation and spatial measurement in many disciplines, such as cultural heritage, archaeology and geoscience. Using modern image- and laser-based 3D modelling techniques, it is normal to acquire more data than is finally used for 3D model texturing, as images may be acquired from multiple positions, with large overlap, or with different cameras and lenses. Such redundant image sets require sorting to restrict the number of images, increasing the processing efficiency and realism of models. However, selection of image subsets optimized for texturing purposes is an example of complex spatial analysis. Manual selection may be challenging and time-consuming, especially for models of rugose topography, where the user must account for occlusions and ensure coverage of all relevant model triangles. To address this, this paper presents a framework for computer-aided image geometry analysis and subset selection for optimizing texture quality in photorealistic models. The framework was created to offer algorithms for candidate image subset selection, whilst supporting refinement of subsets in an intuitive and visual manner. Automatic image sorting was implemented using algorithms originating in computer science and information theory, and variants of these were compared using multiple 3D models and covering image sets, collected for geological applications. The image subsets provided by the automatic procedures were compared to manually selected sets and their suitability for 3D model texturing was assessed. Results indicate that the automatic sorting algorithms are a promising alternative to manual methods. An algorithm based on a greedy solution to the weighted set-cover problem provided image sets closest to the quality and size of the manually selected sets. The improved automation and more reliable quality indicators make the photorealistic model creation workflow more accessible for application experts

  9. [The spectral characteristic wavelength selection and parameter optimization based on Tikhonov regularization].

    PubMed

    Zhao, An-Xin; Tang, Xiao-Jun; Zhang, Zhong-Hua; Liu, Jun-Hua

    2014-07-01

    In the multicomponent mixture hydrocarbon gases Fourier transform infrared (FTIR) quantitative analysis, especially for light alkane gases, it is not easy to establish the quantitative analysis model because their IR spectra absorption peaks are seriously overlapped. Aiming at this problem, the Tikhonov regularization algorithm was used to select the characteristic wavelengths for seven kinds of light alkane mixture gases FTIR which are composed with methane, ethane, propane, iso-butane, n-butane, iso-pentane and n-pentane. And then the wavelength selection was used to establish the quantitative analysis model. By comparing the analysis characteristics wavelength selection and TR parameters optimization of the mixed gases in the infrared all wave band, the first absorption peak band and the second peak band, the characteristic wavelength of 7 kinds of gases were selected by Tikhonov algorithm. The wavelength selection and Tikhonov regularization parameters were used to test the actual measured methane spectral data, and then we got that with other gas components the max cross sensitivity was 11.153 7%, the minimum cross sensitivity was 1.239 7%, and the root mean square prediction error was 0.004 8. The Tikhonov regularization algorithm effectively enhanced the accuracy in the light alkane mixed gas quantitative analysis. The feasibility of alkane gases mixture Fourier transform infrared spectrum wavelength selection was preliminarily verified by using the Tikhonov regularization algorithm. PMID:25269291

  10. [Selection of back-ground electrolyte in capillary zone electrophoresis by triangle and tetrahedron optimization methods].

    PubMed

    Sun, Guoxiang; Song, Wenjing; Lin, Ting

    2008-03-01

    The triangle and tetrahedron optimization methods were developed for the selection of back-ground electrolyte (BGE) in capillary zone electrophoresis (CZE). Chromatographic fingerprint index F and chromatographic fingerprint relative index F(r) were used as the objective functions for the evaluation, and the extract of Saussurea involucrate by water was used as the sample. The BGE was composed of borax, boric acid, dibasic sodium phosphate and sodium dihydrogen phosphate solution with different concentrations using triangle and tetrahedron optimization methods. Re-optimization was carried out by adding organic modifier to the BGE and adjusting the pH value. In triangle method, when 50 mmol/L borax-150 mmol/L sodium dihydrogen phosphate (containing 3% acetonitrile) (1 : 1, v/v) was used as BGE, the isolation was considered to be satisfactory. In tetrahedron method, the best BGE was 50 mmol/L borax-150 mmol/L sodium dihydrogen phosphate-200 mmol/L boric acid (1 : 1 : 2, v/v/v; adjusting the pH value to 8.55 by 0.1 mol/L sodium hydroxide). There were 28 peaks and 25 peaks under the different conditions respectively. The results showed that the methods could be applied to the selection of BGE in CZE of the extract of traditional Chinese medicine by water or ethanol.

  11. An integrated approach of topology optimized design and selective laser melting process for titanium implants materials.

    PubMed

    Xiao, Dongming; Yang, Yongqiang; Su, Xubin; Wang, Di; Sun, Jianfeng

    2013-01-01

    The load-bearing bone implants materials should have sufficient stiffness and large porosity, which are interacted since larger porosity causes lower mechanical properties. This paper is to seek the maximum stiffness architecture with the constraint of specific volume fraction by topology optimization approach, that is, maximum porosity can be achieved with predefine stiffness properties. The effective elastic modulus of conventional cubic and topology optimized scaffolds were calculated using finite element analysis (FEA) method; also, some specimens with different porosities of 41.1%, 50.3%, 60.2% and 70.7% respectively were fabricated by Selective Laser Melting (SLM) process and were tested by compression test. Results showed that the computational effective elastic modulus of optimized scaffolds was approximately 13% higher than cubic scaffolds, the experimental stiffness values were reduced by 76% than the computational ones. The combination of topology optimization approach and SLM process would be available for development of titanium implants materials in consideration of both porosity and mechanical stiffness.

  12. Achieving diverse and monoallelic olfactory receptor selection through dual-objective optimization design.

    PubMed

    Tian, Xiao-Jun; Zhang, Hang; Sannerud, Jens; Xing, Jianhua

    2016-05-24

    Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at the organism level, the types of expressed ORs need to be maximized. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and constructed a comprehensive model that has all its components based on physical interactions. Analyzing the model reveals an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic barrier crossing coupled to a negative feedback loop that mechanistically differs from previous theoretical proposals, and a previously unidentified enhancer competition step. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression, and has multiple predictions validated by existing experimental results. Through making an analogy to a physical system with thermally activated barrier crossing and comparative reverse engineering analyses, the study reveals that the olfactory receptor selection system is optimally designed, and particularly underscores cooperativity and synergy as a general design principle for multiobjective optimization in biology.

  13. Selection of optimal measures of growth and reproduction for the sublethal Leptocheirus plumulosus sediment bioassay

    SciTech Connect

    Gray, B.R.; Wright, R.B.; Duke, B.M.; Farrar, J.D.; Emery, V.L. Jr.; Brandon, D.L.; Moore, D.W.

    1998-11-01

    This article describes the selection process used to identify optimal measures of growth and reproduction for the proposed 28-d sublethal sediment bioassay with the estuarine amphipod Leptocheirus plumulosus. The authors used four criteria (relevance of each measure to its respective endpoint, signal-to-noise ratio, redundancy relative to other measures of the same endpoint, and cost) to evaluate nine growth and seven reproductive measures. Optimal endpoint measures were identified as those receiving relatively high scores for all or most criteria. Measures of growth scored similarly on all criteria, except for cost. The cost of the pooled (female plus male) growth measures was substantially lower than the cost of the female and male growth measures because the latter required more labor (by approx. 25 min per replicate). Pooled dry weight was identified as the optimal growth measure over pooled length because the latter required additional labor and nonstandard software and equipment. Embryo and neonate measures of reproduction exhibited wide differences in labor costs but yielded similar scores for other criteria. In contrast, brooding measures of reproduction scored relatively low on endpoint relevance, signal-to-noise ratio, and redundancy criteria. The authors recommend neonates/survivor as the optimal measure of L. plumulosus reproduction because it exhibited high endpoint relevance and signal-to-noise ratios, was redundant to other reproductive measures, and required minimal time.

  14. An integrated approach of topology optimized design and selective laser melting process for titanium implants materials.

    PubMed

    Xiao, Dongming; Yang, Yongqiang; Su, Xubin; Wang, Di; Sun, Jianfeng

    2013-01-01

    The load-bearing bone implants materials should have sufficient stiffness and large porosity, which are interacted since larger porosity causes lower mechanical properties. This paper is to seek the maximum stiffness architecture with the constraint of specific volume fraction by topology optimization approach, that is, maximum porosity can be achieved with predefine stiffness properties. The effective elastic modulus of conventional cubic and topology optimized scaffolds were calculated using finite element analysis (FEA) method; also, some specimens with different porosities of 41.1%, 50.3%, 60.2% and 70.7% respectively were fabricated by Selective Laser Melting (SLM) process and were tested by compression test. Results showed that the computational effective elastic modulus of optimized scaffolds was approximately 13% higher than cubic scaffolds, the experimental stiffness values were reduced by 76% than the computational ones. The combination of topology optimization approach and SLM process would be available for development of titanium implants materials in consideration of both porosity and mechanical stiffness. PMID:23988713

  15. Achieving diverse and monoallelic olfactory receptor selection through dual-objective optimization design.

    PubMed

    Tian, Xiao-Jun; Zhang, Hang; Sannerud, Jens; Xing, Jianhua

    2016-05-24

    Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at the organism level, the types of expressed ORs need to be maximized. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and constructed a comprehensive model that has all its components based on physical interactions. Analyzing the model reveals an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic barrier crossing coupled to a negative feedback loop that mechanistically differs from previous theoretical proposals, and a previously unidentified enhancer competition step. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression, and has multiple predictions validated by existing experimental results. Through making an analogy to a physical system with thermally activated barrier crossing and comparative reverse engineering analyses, the study reveals that the olfactory receptor selection system is optimally designed, and particularly underscores cooperativity and synergy as a general design principle for multiobjective optimization in biology. PMID:27162367

  16. SVM-RFE Based Feature Selection and Taguchi Parameters Optimization for Multiclass SVM Classifier

    PubMed Central

    Huang, Mei-Ling; Hung, Yung-Hsiang; Lee, W. M.; Li, R. K.; Jiang, Bo-Ru

    2014-01-01

    Recently, support vector machine (SVM) has excellent performance on classification and prediction and is widely used on disease diagnosis or medical assistance. However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification accuracy of multiclass problems for Dermatology and Zoo databases. Dermatology dataset contains 33 feature variables, 1 class variable, and 366 testing instances; and the Zoo dataset contains 16 feature variables, 1 class variable, and 101 testing instances. The feature variables in the two datasets were sorted in descending order by explanatory power, and different feature sets were selected by SVM-RFE to explore classification accuracy. Meanwhile, Taguchi method was jointly combined with SVM classifier in order to optimize parameters C and γ to increase classification accuracy for multiclass classification. The experimental results show that the classification accuracy can be more than 95% after SVM-RFE feature selection and Taguchi parameter optimization for Dermatology and Zoo databases. PMID:25295306

  17. Impact of cultivar selection and process optimization on ethanol yield from different varieties of sugarcane

    PubMed Central

    2014-01-01

    Background The development of ‘energycane’ varieties of sugarcane is underway, targeting the use of both sugar juice and bagasse for ethanol production. The current study evaluated a selection of such ‘energycane’ cultivars for the combined ethanol yields from juice and bagasse, by optimization of dilute acid pretreatment optimization of bagasse for sugar yields. Method A central composite design under response surface methodology was used to investigate the effects of dilute acid pretreatment parameters followed by enzymatic hydrolysis on the combined sugar yield of bagasse samples. The pressed slurry generated from optimum pretreatment conditions (maximum combined sugar yield) was used as the substrate during batch and fed-batch simultaneous saccharification and fermentation (SSF) processes at different solid loadings and enzyme dosages, aiming to reach an ethanol concentration of at least 40 g/L. Results Significant variations were observed in sugar yields (xylose, glucose and combined sugar yield) from pretreatment-hydrolysis of bagasse from different cultivars of sugarcane. Up to 33% difference in combined sugar yield between best performing varieties and industrial bagasse was observed at optimal pretreatment-hydrolysis conditions. Significant improvement in overall ethanol yield after SSF of the pretreated bagasse was also observed from the best performing varieties (84.5 to 85.6%) compared to industrial bagasse (74.5%). The ethanol concentration showed inverse correlation with lignin content and the ratio of xylose to arabinose, but it showed positive correlation with glucose yield from pretreatment-hydrolysis. The overall assessment of the cultivars showed greater improvement in the final ethanol concentration (26.9 to 33.9%) and combined ethanol yields per hectare (83 to 94%) for the best performing varieties with respect to industrial sugarcane. Conclusions These results suggest that the selection of sugarcane variety to optimize ethanol

  18. An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection

    PubMed Central

    Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

    2013-01-01

    One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This

  19. Optimal Spectral Domain Selection for Maximizing Archaeological Signatures: Italy Case Studies

    PubMed Central

    Cavalli, Rosa Maria; Pascucci, Simone; Pignatti, Stefano

    2009-01-01

    Different landscape elements, including archaeological remains, can be automatically classified when their spectral characteristics are different, but major difficulties occur when extracting and classifying archaeological spectral features, as archaeological remains do not have unique shape or spectral characteristics. The spectral anomaly characteristics due to buried remains depend strongly on vegetation cover and/or soil types, which can make feature extraction more complicated. For crop areas, such as the test sites selected for this study, soil and moisture changes within near-surface archaeological deposits can influence surface vegetation patterns creating spectral anomalies of various kinds. In this context, this paper analyzes the usefulness of hyperspectral imagery, in the 0.4 to 12.8 μm spectral region, to identify the optimal spectral range for archaeological prospection as a function of the dominant land cover. MIVIS airborne hyperspectral imagery acquired in five different archaeological areas located in Italy has been used. Within these archaeological areas, 97 test sites with homogenous land cover and characterized by a statistically significant number of pixels related to the buried remains have been selected. The archaeological detection potential for all MIVIS bands has been assessed by applying a Separability Index on each spectral anomaly-background system of the test sites. A scatterplot analysis of the SI values vs. the dominant land cover fractional abundances, as retrieved by spectral mixture analysis, was performed to derive the optimal spectral ranges maximizing the archaeological detection. This work demonstrates that whenever we know the dominant land cover fractional abundances in archaeological sites, we can a priori select the optimal spectral range to improve the efficiency of archaeological observations performed by remote sensing data. PMID:22573985

  20. Optimal selection of space transportation fleet to meet multi-mission space program needs

    NASA Technical Reports Server (NTRS)

    Morgenthaler, George W.; Montoya, Alex J.

    1989-01-01

    A space program that spans several decades will be comprised of a collection of missions such as low earth orbital space station, a polar platform, geosynchronous space station, lunar base, Mars astronaut mission, and Mars base. The optimal selection of a fleet of several recoverable and expendable launch vehicles, upper stages, and interplanetary spacecraft necessary to logistically establish and support these space missions can be examined by means of a linear integer programming optimization model. Such a selection must be made because the economies of scale which comes from producing large quantities of a few standard vehicle types, rather than many, will be needed to provide learning curve effects to reduce the overall cost of space transportation if these future missions are to be affordable. Optimization model inputs come from data and from vehicle designs. Each launch vehicle currently in existence has a launch history, giving rise to statistical estimates of launch reliability. For future, not-yet-developed launch vehicles, theoretical reliabilities corresponding to the maturity of the launch vehicles' technology and the degree of design redundancy must be estimated. Also, each such launch vehicle has a certain historical or estimated development cost, tooling cost, and a variable cost. The cost of a launch used in this paper includes the variable cost plus an amortized portion of the fixed and development costs. The integer linear programming model will have several constraint equations based on assumptions of mission mass requirements, volume requirements, and number of astronauts needed. The model will minimize launch vehicle logistic support cost and will select the most desirable launch vehicle fleet.

  1. Screening and selection of synthetic peptides for a novel and optimized endotoxin detection method.

    PubMed

    Mujika, M; Zuzuarregui, A; Sánchez-Gómez, S; Martínez de Tejada, G; Arana, S; Pérez-Lorenzo, E

    2014-09-30

    The current validated endotoxin detection methods, in spite of being highly sensitive, present several drawbacks in terms of reproducibility, handling and cost. Therefore novel approaches are being carried out in the scientific community to overcome these difficulties. Remarkable efforts are focused on the development of endotoxin-specific biosensors. The key feature of these solutions relies on the proper definition of the capture protocol, especially of the bio-receptor or ligand. The aim of the presented work is the screening and selection of a synthetic peptide specifically designed for LPS detection, as well as the optimization of a procedure for its immobilization onto gold substrates for further application to biosensors. PMID:25034430

  2. Optimal Intermittence in Search Strategies under Speed-Selective Target Detection

    NASA Astrophysics Data System (ADS)

    Campos, Daniel; Méndez, Vicenç; Bartumeus, Frederic

    2012-01-01

    Random search theory has been previously explored for both continuous and intermittent scanning modes with full target detection capacity. Here we present a new class of random search problems in which a single searcher performs flights of random velocities, the detection probability when it passes over a target location being conditioned to the searcher speed. As a result, target detection involves an N-passage process for which the mean search time is here analytically obtained through a renewal approximation. We apply the idea of speed-selective detection to random animal foraging since a fast movement is known to significantly degrade perception abilities in many animals. We show that speed-selective detection naturally introduces an optimal level of behavioral intermittence in order to solve the compromise between fast relocations and target detection capability.

  3. Analysis and selection of optimal function implementations in massively parallel computer

    DOEpatents

    Archer, Charles Jens; Peters, Amanda; Ratterman, Joseph D.

    2011-05-31

    An apparatus, program product and method optimize the operation of a parallel computer system by, in part, collecting performance data for a set of implementations of a function capable of being executed on the parallel computer system based upon the execution of the set of implementations under varying input parameters in a plurality of input dimensions. The collected performance data may be used to generate selection program code that is configured to call selected implementations of the function in response to a call to the function under varying input parameters. The collected performance data may be used to perform more detailed analysis to ascertain the comparative performance of the set of implementations of the function under the varying input parameters.

  4. Burnout and job performance: the moderating role of selection, optimization, and compensation strategies.

    PubMed

    Demerouti, Evangelia; Bakker, Arnold B; Leiter, Michael

    2014-01-01

    The present study aims to explain why research thus far has found only low to moderate associations between burnout and performance. We argue that employees use adaptive strategies that help them to maintain their performance (i.e., task performance, adaptivity to change) at acceptable levels despite experiencing burnout (i.e., exhaustion, disengagement). We focus on the strategies included in the selective optimization with compensation model. Using a sample of 294 employees and their supervisors, we found that compensation is the most successful strategy in buffering the negative associations of disengagement with supervisor-rated task performance and both disengagement and exhaustion with supervisor-rated adaptivity to change. In contrast, selection exacerbates the negative relationship of exhaustion with supervisor-rated adaptivity to change. In total, 42% of the hypothesized interactions proved to be significant. Our study uncovers successful and unsuccessful strategies that people use to deal with their burnout symptoms in order to achieve satisfactory job performance.

  5. Burnout and job performance: the moderating role of selection, optimization, and compensation strategies.

    PubMed

    Demerouti, Evangelia; Bakker, Arnold B; Leiter, Michael

    2014-01-01

    The present study aims to explain why research thus far has found only low to moderate associations between burnout and performance. We argue that employees use adaptive strategies that help them to maintain their performance (i.e., task performance, adaptivity to change) at acceptable levels despite experiencing burnout (i.e., exhaustion, disengagement). We focus on the strategies included in the selective optimization with compensation model. Using a sample of 294 employees and their supervisors, we found that compensation is the most successful strategy in buffering the negative associations of disengagement with supervisor-rated task performance and both disengagement and exhaustion with supervisor-rated adaptivity to change. In contrast, selection exacerbates the negative relationship of exhaustion with supervisor-rated adaptivity to change. In total, 42% of the hypothesized interactions proved to be significant. Our study uncovers successful and unsuccessful strategies that people use to deal with their burnout symptoms in order to achieve satisfactory job performance. PMID:24447224

  6. An Ant Colony Optimization Based Feature Selection for Web Page Classification

    PubMed Central

    2014-01-01

    The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods. PMID:25136678

  7. Properties of Neurons in External Globus Pallidus Can Support Optimal Action Selection

    PubMed Central

    Bogacz, Rafal; Martin Moraud, Eduardo; Abdi, Azzedine; Magill, Peter J.; Baufreton, Jérôme

    2016-01-01

    The external globus pallidus (GPe) is a key nucleus within basal ganglia circuits that are thought to be involved in action selection. A class of computational models assumes that, during action selection, the basal ganglia compute for all actions available in a given context the probabilities that they should be selected. These models suggest that a network of GPe and subthalamic nucleus (STN) neurons computes the normalization term in Bayes’ equation. In order to perform such computation, the GPe needs to send feedback to the STN equal to a particular function of the activity of STN neurons. However, the complex form of this function makes it unlikely that individual GPe neurons, or even a single GPe cell type, could compute it. Here, we demonstrate how this function could be computed within a network containing two types of GABAergic GPe projection neuron, so-called ‘prototypic’ and ‘arkypallidal’ neurons, that have different response properties in vivo and distinct connections. We compare our model predictions with the experimentally-reported connectivity and input-output functions (f-I curves) of the two populations of GPe neurons. We show that, together, these dichotomous cell types fulfil the requirements necessary to compute the function needed for optimal action selection. We conclude that, by virtue of their distinct response properties and connectivities, a network of arkypallidal and prototypic GPe neurons comprises a neural substrate capable of supporting the computation of the posterior probabilities of actions. PMID:27389780

  8. Small sample training and test selection method for optimized anomaly detection algorithms in hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Mindrup, Frank M.; Friend, Mark A.; Bauer, Kenneth W.

    2012-01-01

    There are numerous anomaly detection algorithms proposed for hyperspectral imagery. Robust parameter design (RPD) techniques provide an avenue to select robust settings capable of operating consistently across a large variety of image scenes. Many researchers in this area are faced with a paucity of data. Unfortunately, there are no data splitting methods for model validation of datasets with small sample sizes. Typically, training and test sets of hyperspectral images are chosen randomly. Previous research has developed a framework for optimizing anomaly detection in HSI by considering specific image characteristics as noise variables within the context of RPD; these characteristics include the Fisher's score, ratio of target pixels and number of clusters. We have developed method for selecting hyperspectral image training and test subsets that yields consistent RPD results based on these noise features. These subsets are not necessarily orthogonal, but still provide improvements over random training and test subset assignments by maximizing the volume and average distance between image noise characteristics. The small sample training and test selection method is contrasted with randomly selected training sets as well as training sets chosen from the CADEX and DUPLEX algorithms for the well known Reed-Xiaoli anomaly detector.

  9. Selective mapping: a strategy for optimizing the construction of high-density linkage maps.

    PubMed Central

    Vision, T J; Brown, D G; Shmoys, D B; Durrett, R T; Tanksley, S D

    2000-01-01

    Historically, linkage mapping populations have consisted of large, randomly selected samples of progeny from a given pedigree or cell lines from a panel of radiation hybrids. We demonstrate that, to construct a map with high genome-wide marker density, it is neither necessary nor desirable to genotype all markers in every individual of a large mapping population. Instead, a reduced sample of individuals bearing complementary recombinational or radiation-induced breakpoints may be selected for genotyping subsequent markers from a large, but sparsely genotyped, mapping population. Choosing such a sample can be reduced to a discrete stochastic optimization problem for which the goal is a sample with breakpoints spaced evenly throughout the genome. We have developed several different methods for selecting such samples and have evaluated their performance on simulated and actual mapping populations, including the Lister and Dean Arabidopsis thaliana recombinant inbred population and the GeneBridge 4 human radiation hybrid panel. Our methods quickly and consistently find much-reduced samples with map resolution approaching that of the larger populations from which they are derived. This approach, which we have termed selective mapping, can facilitate the production of high-quality, high-density genome-wide linkage maps. PMID:10790413

  10. An ant colony optimization based feature selection for web page classification.

    PubMed

    Saraç, Esra; Özel, Selma Ayşe

    2014-01-01

    The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

  11. Optimization of the Dutch Matrix Test by Random Selection of Sentences From a Preselected Subset

    PubMed Central

    Dreschler, Wouter A.

    2015-01-01

    Matrix tests are available for speech recognition testing in many languages. For an accurate measurement, a steep psychometric function of the speech materials is required. For existing tests, it would be beneficial if it were possible to further optimize the available materials by increasing the function’s steepness. The objective is to show if the steepness of the psychometric function of an existing matrix test can be increased by selecting a homogeneous subset of recordings with the steepest sentence-based psychometric functions. We took data from a previous multicenter evaluation of the Dutch matrix test (45 normal-hearing listeners). Based on half of the data set, first the sentences (140 out of 311) with a similar speech reception threshold and with the steepest psychometric function (≥9.7%/dB) were selected. Subsequently, the steepness of the psychometric function for this selection was calculated from the remaining (unused) second half of the data set. The calculation showed that the slope increased from 10.2%/dB to 13.7%/dB. The resulting subset did not allow the construction of enough balanced test lists. Therefore, the measurement procedure was changed to randomly select the sentences during testing. Random selection may interfere with a representative occurrence of phonemes. However, in our material, the median phonemic occurrence remained close to that of the original test. This finding indicates that phonemic occurrence is not a critical factor. The work highlights the possibility that existing speech tests might be improved by selecting sentences with a steep psychometric function. PMID:25964195

  12. Optimization of the Dutch matrix test by random selection of sentences from a preselected subset.

    PubMed

    Houben, Rolph; Dreschler, Wouter A

    2015-05-11

    Matrix tests are available for speech recognition testing in many languages. For an accurate measurement, a steep psychometric function of the speech materials is required. For existing tests, it would be beneficial if it were possible to further optimize the available materials by increasing the function's steepness. The objective is to show if the steepness of the psychometric function of an existing matrix test can be increased by selecting a homogeneous subset of recordings with the steepest sentence-based psychometric functions. We took data from a previous multicenter evaluation of the Dutch matrix test (45 normal-hearing listeners). Based on half of the data set, first the sentences (140 out of 311) with a similar speech reception threshold and with the steepest psychometric function (≥9.7%/dB) were selected. Subsequently, the steepness of the psychometric function for this selection was calculated from the remaining (unused) second half of the data set. The calculation showed that the slope increased from 10.2%/dB to 13.7%/dB. The resulting subset did not allow the construction of enough balanced test lists. Therefore, the measurement procedure was changed to randomly select the sentences during testing. Random selection may interfere with a representative occurrence of phonemes. However, in our material, the median phonemic occurrence remained close to that of the original test. This finding indicates that phonemic occurrence is not a critical factor. The work highlights the possibility that existing speech tests might be improved by selecting sentences with a steep psychometric function.

  13. Discovery of a potent class I selective ketone histone deacetylase inhibitor with antitumor activity in vivo and optimized pharmacokinetic properties.

    PubMed

    Kinzel, Olaf; Llauger-Bufi, Laura; Pescatore, Giovanna; Rowley, Michael; Schultz-Fademrecht, Carsten; Monteagudo, Edith; Fonsi, Massimiliano; Gonzalez Paz, Odalys; Fiore, Fabrizio; Steinkühler, Christian; Jones, Philip

    2009-06-11

    The optimization of a potent, class I selective ketone HDAC inhibitor is shown. It possesses optimized pharmacokinetic properties in preclinical species, has a clean off-target profile, and is negative in a microbial mutagenicity (Ames) test. In a mouse xenograft model it shows efficacy comparable to that of vorinostat at a 10-fold reduced dose.

  14. Optimizing the StackSlide setup and data selection for continuous-gravitational-wave searches in realistic detector data

    NASA Astrophysics Data System (ADS)

    Shaltev, M.

    2016-02-01

    The search for continuous gravitational waves in a wide parameter space at a fixed computing cost is most efficiently done with semicoherent methods, e.g., StackSlide, due to the prohibitive computing cost of the fully coherent search strategies. Prix and Shaltev [Phys. Rev. D 85, 084010 (2012)] have developed a semianalytic method for finding optimal StackSlide parameters at a fixed computing cost under ideal data conditions, i.e., gapless data and a constant noise floor. In this work, we consider more realistic conditions by allowing for gaps in the data and changes in the noise level. We show how the sensitivity optimization can be decoupled from the data selection problem. To find optimal semicoherent search parameters, we apply a numerical optimization using as an example the semicoherent StackSlide search. We also describe three different data selection algorithms. Thus, the outcome of the numerical optimization consists of the optimal search parameters and the selected data set. We first test the numerical optimization procedure under ideal conditions and show that we can reproduce the results of the analytical method. Then we gradually relax the conditions on the data and find that a compact data selection algorithm yields higher sensitivity compared to a greedy data selection procedure.

  15. Stochastic approach to reconstruction of dynamical systems: optimal model selection criterion

    NASA Astrophysics Data System (ADS)

    Gavrilov, A.; Mukhin, D.; Loskutov, E. M.; Feigin, A. M.

    2011-12-01

    Most of known observable systems are complex and high-dimensional that doesn't allow to make the exact long-term forecast of their behavior. The stochastic approach to reconstruction of such systems gives a hope to describe important qualitative features of their behavior in a low-dimensional way while all other dynamics is modelled as stochastic disturbance. This report is devoted to application of Bayesian evidence for optimal stochastic model selection when reconstructing the evolution operator of observable system. The idea of Bayesian evidence is to find compromise between the model predictiveness and quality of fitting the model into the data. We represent the evolution operator of investigated system in a form of random dynamic system including deterministic and stochastic parts, both parameterized by artificial neural network. Then we use Bayesian evidence criterion to estimate optimal complexity of the model, i.e. both number of parameters and dimension corresponding to most probable model given the data. We demonstrate on the number of model examples that the model with non-uniformly distributed stochastic part (which corresponds to non-Gaussian perturbations of evolution operator) is optimal in general case. Further, we show that simple stochastic model can be the most preferred for reconstruction of the evolution operator underlying complex observed dynamics even in a case of deterministic high-dimensional system. Workability of suggested approach for modeling and prognosis of real-measured geophysical dynamics is investigated.

  16. Design-Optimization and Material Selection for a Proximal Radius Fracture-Fixation Implant

    NASA Astrophysics Data System (ADS)

    Grujicic, M.; Xie, X.; Arakere, G.; Grujicic, A.; Wagner, D. W.; Vallejo, A.

    2010-11-01

    The problem of optimal size, shape, and placement of a proximal radius-fracture fixation-plate is addressed computationally using a combined finite-element/design-optimization procedure. To expand the set of physiological loading conditions experienced by the implant during normal everyday activities of the patient, beyond those typically covered by the pre-clinical implant-evaluation testing procedures, the case of a wheel-chair push exertion is considered. Toward that end, a musculoskeletal multi-body inverse-dynamics analysis is carried out of a human propelling a wheelchair. The results obtained are used as input to a finite-element structural analysis for evaluation of the maximum stress and fatigue life of the parametrically defined implant design. While optimizing the design of the radius-fracture fixation-plate, realistic functional requirements pertaining to the attainment of the required level of the devise safety factor and longevity/lifecycle were considered. It is argued that the type of analyses employed in the present work should be: (a) used to complement the standard experimental pre-clinical implant-evaluation tests (the tests which normally include a limited number of daily-living physiological loading conditions and which rely on single pass/fail outcomes/decisions with respect to a set of lower-bound implant-performance criteria) and (b) integrated early in the implant design and material/manufacturing-route selection process.

  17. Optimizing mass spectrometric detection for ion chromatographic analysis. I. Common anions and selected organic acids.

    PubMed

    Wang, Jinyuan; Schnute, William C

    2009-11-01

    We describe a systematic method of optimizing mass spectrometric (MS) detection for ion chromatographic (IC) analysis of common anions and three selected organic acids using response surface methodology (RSM). RSM was utilized in this study because it minimized the number of experiments required to achieve the optimum MS response and included the interactions between individual parameters for multivariable optimization. Five MS parameters, including probe temperature, nebulizer gas, assistant makeup flow, needle voltage and cone voltage, were screened and systematically optimized by two steps. Central composite design (CCD) was used to design the experiment points and a quadratic model was applied to fit the experimental data. Analysis of variance (ANOVA) was carried out to evaluate the validity of the statistical model and to determine the most significant parameters for MS response. The optimum MS conditions for each analyte were summarized and the method optimum condition was achieved by applying desirability function. Our observation showed good agreements between statistically predicted optimum response and the responses collected at the predicted optimum condition. Operable range of each parameter (with normalized MS response greater than 0.8 for each analyte) was provided for general anionic IC/MS applications.

  18. Pareto archived dynamically dimensioned search with hypervolume-based selection for multi-objective optimization

    NASA Astrophysics Data System (ADS)

    Asadzadeh, Masoud; Tolson, Bryan

    2013-12-01

    Pareto archived dynamically dimensioned search (PA-DDS) is a parsimonious multi-objective optimization algorithm with only one parameter to diminish the user's effort for fine-tuning algorithm parameters. This study demonstrates that hypervolume contribution (HVC) is a very effective selection metric for PA-DDS and Monte Carlo sampling-based HVC is very effective for higher dimensional problems (five objectives in this study). PA-DDS with HVC performs comparably to algorithms commonly applied to water resources problems (ɛ-NSGAII and AMALGAM under recommended parameter values). Comparisons on the CEC09 competition show that with sufficient computational budget, PA-DDS with HVC performs comparably to 13 benchmark algorithms and shows improved relative performance as the number of objectives increases. Lastly, it is empirically demonstrated that the total optimization runtime of PA-DDS with HVC is dominated (90% or higher) by solution evaluation runtime whenever evaluation exceeds 10 seconds/solution. Therefore, optimization algorithm runtime associated with the unbounded archive of PA-DDS is negligible in solving computationally intensive problems.

  19. Optimality and stability of symmetric evolutionary games with applications in genetic selection.

    PubMed

    Huang, Yuanyuan; Hao, Yiping; Wang, Min; Zhou, Wen; Wu, Zhijun

    2015-06-01

    Symmetric evolutionary games, i.e., evolutionary games with symmetric fitness matrices, have important applications in population genetics, where they can be used to model for example the selection and evolution of the genotypes of a given population. In this paper, we review the theory for obtaining optimal and stable strategies for symmetric evolutionary games, and provide some new proofs and computational methods. In particular, we review the relationship between the symmetric evolutionary game and the generalized knapsack problem, and discuss the first and second order necessary and sufficient conditions that can be derived from this relationship for testing the optimality and stability of the strategies. Some of the conditions are given in different forms from those in previous work and can be verified more efficiently. We also derive more efficient computational methods for the evaluation of the conditions than conventional approaches. We demonstrate how these conditions can be applied to justifying the strategies and their stabilities for a special class of genetic selection games including some in the study of genetic disorders.

  20. Role of the development scientist in compound lead selection and optimization.

    PubMed

    Venkatesh, S; Lipper, R A

    2000-02-01

    The R&D process for bringing drugs from discovery laboratories to the marketplace is undergoing rapid change, as enabled by new technologies and as demanded by the global pharmaceutical business environment. One consequence of the accelerated R&D paradigm is a blurring of the traditional discovery-development interface, which in turn impacts the traditional roles of discovery and development scientists. R&D organizations must find ways to screen out rapidly compounds that have relatively poor probability of successful registration. Quality of development candidates can be favorably influenced by early consideration of "developability" criteria along with receptor-based potency and specificity. Computational approaches and/or high-throughput experimental determinations will be used increasingly to profile compound characteristics which influence "developability." If such criteria are considered at the time of lead selection and optimization, the compound attrition rate during later development should be decreased from the historical norm. This article discusses the emerging role of development scientists during small-molecule lead selection and optimization. The changing role of development scientists also has implications for graduate curricula in the pharmaceutical sciences. PMID:10688744

  1. Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

    PubMed Central

    Deng, Ning

    2014-01-01

    In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

  2. Efficient iris recognition based on optimal subfeature selection and weighted subregion fusion.

    PubMed

    Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; He, Fei; Wang, Hongye; Deng, Ning

    2014-01-01

    In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, and MMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

  3. Selective preparation of enantiomers by laser pulses: From optimal control to specific pump and dump transitions

    NASA Astrophysics Data System (ADS)

    González, L.; Hoki, K.; Kröner, D.; Leal, A. S.; Manz, J.; Ohtsuki, Y.

    2000-12-01

    Starting from optimal control, various series of infrared, ultrashort laser pulses with analytical shapes are designed in order to drive a preoriented molecule from its ground torsional state, which represents the coherent superposition of left and right atropisomers, towards a single enantiomer. Close analysis of the population dynamics, together with the underlying symmetry selection rules for the laser induced transitions, yields the mechanism. Namely, the molecule is driven from its ground vibrational state towards the coherent superposition of the lowest doublet of states via a doublet of excited torsional states with opposite symmetries. This pump-and-dump mechanism can be achieved by simpler series of analytical laser pulses. This decomposition of the optimal pulse into analytical subpulses allows us to design different scenarios for the selective preparation of left or right enantiomers. Exemplary this is demonstrated by quantum simulations of representative wave packets for the torsional motions of the model system, H2POSH, in the electronic ground state, based on the ab initio potential energy surface, and with ab initio dipole couplings.

  4. Analysis Methodology for Optimal Selection of Ground Station Site in Space Missions

    NASA Astrophysics Data System (ADS)

    Nieves-Chinchilla, J.; Farjas, M.; Martínez, R.

    2013-12-01

    Optimization of ground station sites is especially important in complex missions that include several small satellites (clusters or constellations) such as the QB50 project, where one ground station would be able to track several spatial vehicles, even simultaneously. In this regard the design of the communication system has to carefully take into account the ground station site and relevant signal phenomena, depending on the frequency band. To propose the optimal location of the ground station, these aspects become even more relevant to establish a trusted communication link due to the ground segment site in urban areas and/or selection of low orbits for the space segment. In addition, updated cartography with high resolution data of the location and its surroundings help to develop recommendations in the design of its location for spatial vehicles tracking and hence to improve effectiveness. The objectives of this analysis methodology are: completion of cartographic information, modelling the obstacles that hinder communication between the ground and space segment and representation in the generated 3D scene of the degree of impairment in the signal/noise of the phenomena that interferes with communication. The integration of new technologies of geographic data capture, such as 3D Laser Scan, determine that increased optimization of the antenna elevation mask, in its AOS and LOS azimuths along the horizon visible, maximizes visibility time with spatial vehicles. Furthermore, from the three-dimensional cloud of points captured, specific information is selected and, using 3D modeling techniques, the 3D scene of the antenna location site and surroundings is generated. The resulting 3D model evidences nearby obstacles related to the cartographic conditions such as mountain formations and buildings, and any additional obstacles that interfere with the operational quality of the antenna (other antennas and electronic devices that emit or receive in the same bandwidth

  5. Selection on synonymous codons in mammalian rhodopsins: a possible role in optimizing translational processes

    PubMed Central

    2014-01-01

    . Our results suggest that codon bias in mammalian rhodopsin arises from selection to optimally balance high overall translational speed, accuracy, and proper protein folding, especially in structurally complicated regions. Selection at synonymous sites may also be contributing to mRNA stability and splicing efficiency at exonic-splicing-enhancer (ESE) regions. Our results highlight the importance of investigating highly expressed genes in a broader phylogenetic context in order to better understand the evolution of synonymous substitutions. PMID:24884412

  6. Optimized diffusion of buck semen for saving genetic variability in selected dairy goat populations

    PubMed Central

    2011-01-01

    Background Current research on quantitative genetics has provided efficient guidelines for the sustainable management of selected populations: genetic gain is maximized while the loss of genetic diversity is maintained at a reasonable rate. However, actual selection schemes are complex, especially for large domestic species, and they have to take into account many operational constraints. This paper deals with the actual selection of dairy goats where the challenge is to optimize diffusion of buck semen on the field. Three objectives are considered simultaneously: i) natural service buck replacement (NSR); ii) goat replacement (GR); iii) semen distribution of young bucks to be progeny-tested. An appropriate optimization method is developed, which involves five analytical steps. Solutions are obtained by simulated annealing and the corresponding algorithms are presented in detail. Results The whole procedure was tested on two French goat populations (Alpine and Saanen breeds) and the results presented in the abstract were based on the average of the two breeds. The procedure induced an immediate acceleration of genetic gain in comparison with the current annual genetic gain (0.15 genetic standard deviation unit), as shown by two facts. First, the genetic level of replacement natural service (NS) bucks was predicted, 1.5 years ahead at the moment of reproduction, to be equivalent to that of the progeny-tested bucks in service, born from the current breeding scheme. Second, the genetic level of replacement goats was much higher than that of their dams (0.86 unit), which represented 6 years of selection, although dams were only 3 years older than their replacement daughters. This improved genetic gain could be achieved while decreasing inbreeding coefficients substantially. Inbreeding coefficients (%) of NS bucks was lower than that of the progeny-tested bucks (-0.17). Goats were also less inbred than their dams (-0.67). Conclusions It was possible to account for

  7. Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection

    PubMed Central

    Bailey, Jacqueline; Timmis, Jon; Chtanova, Tatyana

    2016-01-01

    The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks (CRWs) against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto fronts of optimal

  8. Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection.

    PubMed

    Read, Mark N; Bailey, Jacqueline; Timmis, Jon; Chtanova, Tatyana

    2016-09-01

    The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks (CRWs) against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto fronts of optimal

  9. Online stimulus optimization rapidly reveals multidimensional selectivity in auditory cortical neurons.

    PubMed

    Chambers, Anna R; Hancock, Kenneth E; Sen, Kamal; Polley, Daniel B

    2014-07-01

    Neurons in sensory brain regions shape our perception of the surrounding environment through two parallel operations: decomposition and integration. For example, auditory neurons decompose sounds by separately encoding their frequency, temporal modulation, intensity, and spatial location. Neurons also integrate across these various features to support a unified perceptual gestalt of an auditory object. At higher levels of a sensory pathway, neurons may select for a restricted region of feature space defined by the intersection of multiple, independent stimulus dimensions. To further characterize how auditory cortical neurons decompose and integrate multiple facets of an isolated sound, we developed an automated procedure that manipulated five fundamental acoustic properties in real time based on single-unit feedback in awake mice. Within several minutes, the online approach converged on regions of the multidimensional stimulus manifold that reliably drove neurons at significantly higher rates than predefined stimuli. Optimized stimuli were cross-validated against pure tone receptive fields and spectrotemporal receptive field estimates in the inferior colliculus and primary auditory cortex. We observed, from midbrain to cortex, increases in both level invariance and frequency selectivity, which may underlie equivalent sparseness of responses in the two areas. We found that onset and steady-state spike rates increased proportionately as the stimulus was tailored to the multidimensional receptive field. By separately evaluating the amount of leverage each sound feature exerted on the overall firing rate, these findings reveal interdependencies between stimulus features as well as hierarchical shifts in selectivity and invariance that may go unnoticed with traditional approaches. PMID:24990917

  10. Resonance Raman enhancement optimization in the visible range by selecting different excitation wavelengths

    NASA Astrophysics Data System (ADS)

    Wang, Zhong; Li, Yuee

    2015-09-01

    Resonance enhancement of Raman spectroscopy (RS) has been used to significantly improve the sensitivity and selectivity of detection for specific components in complicated environments. Resonance RS gives more insight into the biochemical structure and reactivity. In this field, selecting a proper excitation wavelength to achieve optimal resonance enhancement is vital for the study of an individual chemical/biological ingredient with a particular absorption characteristic. Raman spectra of three azo derivatives with absorption spectra in the visible range are studied under the same experimental conditions at 488, 532, and 633 nm excitations. Universal laws in the visible range have been concluded by analyzing resonance Raman (RR) spectra of samples. The long wavelength edge of the absorption spectrum is a better choice for intense enhancement and the integrity of a Raman signal. The obtained results are valuable for applying RR for the selective detection of biochemical constituents whose electronic transitions take place at energies corresponding to the visible spectra, which is much friendlier to biologial samples compared to ultraviolet.

  11. Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods.

    PubMed

    Maximov, Ivan I; Vinding, Mads S; Tse, Desmond H Y; Nielsen, Niels Chr; Shah, N Jon

    2015-05-01

    There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community.

  12. A strategy that iteratively retains informative variables for selecting optimal variable subset in multivariate calibration.

    PubMed

    Yun, Yong-Huan; Wang, Wei-Ting; Tan, Min-Li; Liang, Yi-Zeng; Li, Hong-Dong; Cao, Dong-Sheng; Lu, Hong-Mei; Xu, Qing-Song

    2014-01-01

    Nowadays, with a high dimensionality of dataset, it faces a great challenge in the creation of effective methods which can select an optimal variables subset. In this study, a strategy that considers the possible interaction effect among variables through random combinations was proposed, called iteratively retaining informative variables (IRIV). Moreover, the variables are classified into four categories as strongly informative, weakly informative, uninformative and interfering variables. On this basis, IRIV retains both the strongly and weakly informative variables in every iterative round until no uninformative and interfering variables exist. Three datasets were employed to investigate the performance of IRIV coupled with partial least squares (PLS). The results show that IRIV is a good alternative for variable selection strategy when compared with three outstanding and frequently used variable selection methods such as genetic algorithm-PLS, Monte Carlo uninformative variable elimination by PLS (MC-UVE-PLS) and competitive adaptive reweighted sampling (CARS). The MATLAB source code of IRIV can be freely downloaded for academy research at the website: http://code.google.com/p/multivariate-calibration/downloads/list. PMID:24356218

  13. Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods

    NASA Astrophysics Data System (ADS)

    Maximov, Ivan I.; Vinding, Mads S.; Tse, Desmond H. Y.; Nielsen, Niels Chr.; Shah, N. Jon

    2015-05-01

    There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community.

  14. Optimization methods for selecting founder individuals for captive breeding or reintroduction of endangered species.

    PubMed

    Miller, Webb; Wright, Stephen J; Zhang, Yu; Schuster, Stephan C; Hayes, Vanessa M

    2010-01-01

    Methods from genetics and genomics can be employed to help save endangered species. One potential use is to provide a rational strategy for selecting a population of founders for a captive breeding program. The hope is to capture most of the available genetic diversity that remains in the wild population, to provide a safe haven where representatives of the species can be bred, and eventually to release the progeny back into the wild. However, the founders are often selected based on a random-sampling strategy whose validity is based on unrealistic assumptions. Here we outline an approach that starts by using cutting-edge genome sequencing and genotyping technologies to objectively assess the available genetic diversity. We show how combinatorial optimization methods can be applied to these data to guide the selection of the founder population. In particular, we develop a mixed-integer linear programming technique that identifies a set of animals whose genetic profile is as close as possible to specified abundances of alleles (i.e., genetic variants), subject to constraints on the number of founders and their genders and ages. PMID:19908356

  15. Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods.

    PubMed

    Maximov, Ivan I; Vinding, Mads S; Tse, Desmond H Y; Nielsen, Niels Chr; Shah, N Jon

    2015-05-01

    There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community. PMID:25863895

  16. A strategy that iteratively retains informative variables for selecting optimal variable subset in multivariate calibration.

    PubMed

    Yun, Yong-Huan; Wang, Wei-Ting; Tan, Min-Li; Liang, Yi-Zeng; Li, Hong-Dong; Cao, Dong-Sheng; Lu, Hong-Mei; Xu, Qing-Song

    2014-01-01

    Nowadays, with a high dimensionality of dataset, it faces a great challenge in the creation of effective methods which can select an optimal variables subset. In this study, a strategy that considers the possible interaction effect among variables through random combinations was proposed, called iteratively retaining informative variables (IRIV). Moreover, the variables are classified into four categories as strongly informative, weakly informative, uninformative and interfering variables. On this basis, IRIV retains both the strongly and weakly informative variables in every iterative round until no uninformative and interfering variables exist. Three datasets were employed to investigate the performance of IRIV coupled with partial least squares (PLS). The results show that IRIV is a good alternative for variable selection strategy when compared with three outstanding and frequently used variable selection methods such as genetic algorithm-PLS, Monte Carlo uninformative variable elimination by PLS (MC-UVE-PLS) and competitive adaptive reweighted sampling (CARS). The MATLAB source code of IRIV can be freely downloaded for academy research at the website: http://code.google.com/p/multivariate-calibration/downloads/list.

  17. 3 CFR 13546 - Executive Order 13546 of July 2, 2010. Optimizing the Security of Biological Select Agents and...

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... the Security of Biological Select Agents and Toxins in the United States 13546 Order 13546 Presidential Documents Executive Orders Executive Order 13546 of July 2, 2010 EO 13546 Optimizing the Security... enterprise that utilizes biological select agents and toxins (BSAT) is essential to national security;...

  18. Evaluation of the selection methods used in the exIWO algorithm based on the optimization of multidimensional functions

    NASA Astrophysics Data System (ADS)

    Kostrzewa, Daniel; Josiński, Henryk

    2016-06-01

    The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version inspired by dynamic growth of weeds colony. The authors of the present paper have modified the exIWO algorithm introducing a set of both deterministic and non-deterministic strategies of individuals' selection. The goal of the project was to evaluate the modified exIWO by testing its usefulness for multidimensional numerical functions optimization. The optimized functions: Griewank, Rastrigin, and Rosenbrock are frequently used as benchmarks because of their characteristics.

  19. X-ray backscatter imaging for radiography by selective detection and snapshot: Evolution, development, and optimization

    NASA Astrophysics Data System (ADS)

    Shedlock, Daniel

    Compton backscatter imaging (CBI) is a single-sided imaging technique that uses the penetrating power of radiation and unique interaction properties of radiation with matter to image subsurface features. CBI has a variety of applications that include non-destructive interrogation, medical imaging, security and military applications. Radiography by selective detection (RSD), lateral migration radiography (LMR) and shadow aperture backscatter radiography (SABR) are different CBI techniques that are being optimized and developed. Radiography by selective detection (RSD) is a pencil beam Compton backscatter imaging technique that falls between highly collimated and uncollimated techniques. Radiography by selective detection uses a combination of single- and multiple-scatter photons from a projected area below a collimation plane to generate an image. As a result, the image has a combination of first- and multiple-scatter components. RSD techniques offer greater subsurface resolution than uncollimated techniques, at speeds at least an order of magnitude faster than highly collimated techniques. RSD scanning systems have evolved from a prototype into near market-ready scanning devices for use in a variety of single-sided imaging applications. The design has changed to incorporate state-of-the-art detectors and electronics optimized for backscatter imaging with an emphasis on versatility, efficiency and speed. The RSD system has become more stable, about 4 times faster, and 60% lighter while maintaining or improving image quality and contrast over the past 3 years. A new snapshot backscatter radiography (SBR) CBI technique, shadow aperture backscatter radiography (SABR), has been developed from concept and proof-of-principle to a functional laboratory prototype. SABR radiography uses digital detection media and shaded aperture configurations to generate near-surface Compton backscatter images without scanning, similar to how transmission radiographs are taken. Finally, a

  20. [Study on optimal selection of structure of vaneless centrifugal blood pump with constraints on blood perfusion and on blood damage indexes].

    PubMed

    Hu, Zhaoyan; Pan, Youlian; Chen, Zhenglong; Zhang, Tianyi; Lu, Lijun

    2012-12-01

    This paper is aimed to study the optimal selection of structure of vaneless centrifugal blood pump. The optimal objective is determined according to requirements of clinical use. Possible schemes are generally worked out based on structural feature of vaneless centrifugal blood pump. The optimal structure is selected from possible schemes with constraints on blood perfusion and blood damage indexes. Using an optimal selection method one can find the optimum structure scheme from possible schemes effectively. The results of numerical simulation of optimal blood pump showed that the method of constraints of blood perfusion and blood damage is competent for the requirements of selection of the optimal blood pumps.

  1. Optimization Of Mean-Semivariance-Skewness Portfolio Selection Model In Fuzzy Random Environment

    NASA Astrophysics Data System (ADS)

    Chatterjee, Amitava; Bhattacharyya, Rupak; Mukherjee, Supratim; Kar, Samarjit

    2010-10-01

    The purpose of the paper is to construct a mean-semivariance-skewness portfolio selection model in fuzzy random environment. The objective is to maximize the skewness with predefined maximum risk tolerance and minimum expected return. Here the security returns in the objectives and constraints are assumed to be fuzzy random variables in nature and then the vagueness of the fuzzy random variables in the objectives and constraints are transformed into fuzzy variables which are similar to trapezoidal numbers. The newly formed fuzzy model is then converted into a deterministic optimization model. The feasibility and effectiveness of the proposed method is verified by numerical example extracted from Bombay Stock Exchange (BSE). The exact parameters of fuzzy membership function and probability density function are obtained through fuzzy random simulating the past dates.

  2. Optimized multiple-quantum filter for robust selective excitation of metabolite signals

    NASA Astrophysics Data System (ADS)

    Holbach, Mirjam; Lambert, Jörg; Suter, Dieter

    2014-06-01

    The selective excitation of metabolite signals in vivo requires the use of specially adapted pulse techniques, in particular when the signals are weak and the resonances overlap with those of unwanted molecules. Several pulse sequences have been proposed for this spectral editing task. However, their performance is strongly degraded by unavoidable experimental imperfections. Here, we show that optimal control theory can be used to generate pulses and sequences that perform almost ideally over a range of rf field strengths and frequency offsets that can be chosen according to the specifics of the spectrometer or scanner being used. We demonstrate this scheme by applying it to lactate editing. In addition to the robust excitation, we also have designed the pulses to minimize the signal of unwanted molecular species.

  3. A Linked Simulation-Optimization (LSO) Model for Conjunctive Irrigation Management using Clonal Selection Algorithm

    NASA Astrophysics Data System (ADS)

    Islam, Sirajul; Talukdar, Bipul

    2016-08-01

    A Linked Simulation-Optimization (LSO) model based on a Clonal Selection Algorithm (CSA) was formulated for application in conjunctive irrigation management. A series of measures were considered for reducing the computational burden associated with the LSO approach. Certain modifications were incurred to the formulated CSA, so as to decrease the number of function evaluations. In addition, a simple problem specific code for a two dimensional groundwater flow simulation model was developed. The flow model was further simplified by a novel approach of area reduction, in order to save computational time in simulation. The LSO model was applied in the irrigation command of the Pagladiya Dam Project in Assam, India. With a view to evaluate the performance of the CSA, a Genetic Algorithm (GA) was used as a comparison base. The results from the CSA compared well with those from the GA. In fact, the CSA was found to consume less computational time than the GA while converging to the optimal solution, due to the modifications incurred in it.

  4. A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface.

    PubMed

    Zhou, Bangyan; Wu, Xiaopei; Lv, Zhao; Zhang, Lei; Guo, Xiaojin

    2016-01-01

    Independent component analysis (ICA) as a promising spatial filtering method can separate motor-related independent components (MRICs) from the multichannel electroencephalogram (EEG) signals. However, the unpredictable burst interferences may significantly degrade the performance of ICA-based brain-computer interface (BCI) system. In this study, we proposed a new algorithm frame to address this issue by combining the single-trial-based ICA filter with zero-training classifier. We developed a two-round data selection method to identify automatically the badly corrupted EEG trials in the training set. The "high quality" training trials were utilized to optimize the ICA filter. In addition, we proposed an accuracy-matrix method to locate the artifact data segments within a single trial and investigated which types of artifacts can influence the performance of the ICA-based MIBCIs. Twenty-six EEG datasets of three-class motor imagery were used to validate the proposed methods, and the classification accuracies were compared with that obtained by frequently used common spatial pattern (CSP) spatial filtering algorithm. The experimental results demonstrated that the proposed optimizing strategy could effectively improve the stability, practicality and classification performance of ICA-based MIBCI. The study revealed that rational use of ICA method may be crucial in building a practical ICA-based MIBCI system. PMID:27631789

  5. Bone Mineral Density and Fracture Risk Assessment to Optimize Prosthesis Selection in Total Hip Replacement

    PubMed Central

    Pétursson, Þröstur; Edmunds, Kyle Joseph; Gíslason, Magnús Kjartan; Magnússon, Benedikt; Magnúsdóttir, Gígja; Halldórsson, Grétar; Jónsson, Halldór; Gargiulo, Paolo

    2015-01-01

    The variability in patient outcome and propensity for surgical complications in total hip replacement (THR) necessitates the development of a comprehensive, quantitative methodology for prescribing the optimal type of prosthetic stem: cemented or cementless. The objective of the research presented herein was to describe a novel approach to this problem as a first step towards creating a patient-specific, presurgical application for determining the optimal prosthesis procedure. Finite element analysis (FEA) and bone mineral density (BMD) calculations were performed with ten voluntary primary THR patients to estimate the status of their operative femurs before surgery. A compilation model of the press-fitting procedure was generated to define a fracture risk index (FRI) from incurred forces on the periprosthetic femoral head. Comparing these values to patient age, sex, and gender elicited a high degree of variability between patients grouped by implant procedure, reinforcing the notion that age and gender alone are poor indicators for prescribing prosthesis type. Additionally, correlating FRI and BMD measurements indicated that at least two of the ten patients may have received nonideal implants. This investigation highlights the utility of our model as a foundation for presurgical software applications to assist orthopedic surgeons with selecting THR prostheses. PMID:26417376

  6. Catalyst optimization strategy: selective oxidation of o-xylene to phthalic anhydride.

    PubMed

    Wöelk, Hans-Jörg; Mestl, Gerhard

    2012-02-01

    The oxidation of o-xylene and/or naphthalene to phthalic anhydride is one of the important industrial processes based on catalytic selective oxidation reactions. Vanadia--titania catalysts have been used in the industrial phthalic anyhdride process for the last 50 years. The operation parameters like the temperature range of operation, reactor inlet pressures, contact times, o-xylene loadings, etc. were constantly improved during this period of continuous process optimization so as to optimize catalyst performance and increase its life time. However, a fundamental understanding of the mutual interaction of the rather complex reaction network and the catalyst formulation is still missing. Recently, a detailed study of by-product formation as function of process conditions allowed us to develop a novel, improved reaction scheme for the catalytic oxidation of o-xylene. Based on this understanding, a detailed investigation was conducted for the first time of the by-product formation under varying operation conditions and as a function of the active mass variation exploiting high-throughput, as well as bench scales reactors. This high-throughput testing allowed us to relate reaction kinetics to novel catalyst formulations.

  7. A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface

    PubMed Central

    Zhou, Bangyan; Wu, Xiaopei; Lv, Zhao; Zhang, Lei; Guo, Xiaojin

    2016-01-01

    Independent component analysis (ICA) as a promising spatial filtering method can separate motor-related independent components (MRICs) from the multichannel electroencephalogram (EEG) signals. However, the unpredictable burst interferences may significantly degrade the performance of ICA-based brain-computer interface (BCI) system. In this study, we proposed a new algorithm frame to address this issue by combining the single-trial-based ICA filter with zero-training classifier. We developed a two-round data selection method to identify automatically the badly corrupted EEG trials in the training set. The “high quality” training trials were utilized to optimize the ICA filter. In addition, we proposed an accuracy-matrix method to locate the artifact data segments within a single trial and investigated which types of artifacts can influence the performance of the ICA-based MIBCIs. Twenty-six EEG datasets of three-class motor imagery were used to validate the proposed methods, and the classification accuracies were compared with that obtained by frequently used common spatial pattern (CSP) spatial filtering algorithm. The experimental results demonstrated that the proposed optimizing strategy could effectively improve the stability, practicality and classification performance of ICA-based MIBCI. The study revealed that rational use of ICA method may be crucial in building a practical ICA-based MIBCI system. PMID:27631789

  8. A Linked Simulation-Optimization (LSO) Model for Conjunctive Irrigation Management using Clonal Selection Algorithm

    NASA Astrophysics Data System (ADS)

    Islam, Sirajul; Talukdar, Bipul

    2016-09-01

    A Linked Simulation-Optimization (LSO) model based on a Clonal Selection Algorithm (CSA) was formulated for application in conjunctive irrigation management. A series of measures were considered for reducing the computational burden associated with the LSO approach. Certain modifications were incurred to the formulated CSA, so as to decrease the number of function evaluations. In addition, a simple problem specific code for a two dimensional groundwater flow simulation model was developed. The flow model was further simplified by a novel approach of area reduction, in order to save computational time in simulation. The LSO model was applied in the irrigation command of the Pagladiya Dam Project in Assam, India. With a view to evaluate the performance of the CSA, a Genetic Algorithm (GA) was used as a comparison base. The results from the CSA compared well with those from the GA. In fact, the CSA was found to consume less computational time than the GA while converging to the optimal solution, due to the modifications incurred in it.

  9. Bone Mineral Density and Fracture Risk Assessment to Optimize Prosthesis Selection in Total Hip Replacement.

    PubMed

    Pétursson, Þröstur; Edmunds, Kyle Joseph; Gíslason, Magnús Kjartan; Magnússon, Benedikt; Magnúsdóttir, Gígja; Halldórsson, Grétar; Jónsson, Halldór; Gargiulo, Paolo

    2015-01-01

    The variability in patient outcome and propensity for surgical complications in total hip replacement (THR) necessitates the development of a comprehensive, quantitative methodology for prescribing the optimal type of prosthetic stem: cemented or cementless. The objective of the research presented herein was to describe a novel approach to this problem as a first step towards creating a patient-specific, presurgical application for determining the optimal prosthesis procedure. Finite element analysis (FEA) and bone mineral density (BMD) calculations were performed with ten voluntary primary THR patients to estimate the status of their operative femurs before surgery. A compilation model of the press-fitting procedure was generated to define a fracture risk index (FRI) from incurred forces on the periprosthetic femoral head. Comparing these values to patient age, sex, and gender elicited a high degree of variability between patients grouped by implant procedure, reinforcing the notion that age and gender alone are poor indicators for prescribing prosthesis type. Additionally, correlating FRI and BMD measurements indicated that at least two of the ten patients may have received nonideal implants. This investigation highlights the utility of our model as a foundation for presurgical software applications to assist orthopedic surgeons with selecting THR prostheses. PMID:26417376

  10. Closed-form solutions for linear regulator design of mechanical systems including optimal weighting matrix selection

    NASA Technical Reports Server (NTRS)

    Hanks, Brantley R.; Skelton, Robert E.

    1991-01-01

    Vibration in modern structural and mechanical systems can be reduced in amplitude by increasing stiffness, redistributing stiffness and mass, and/or adding damping if design techniques are available to do so. Linear Quadratic Regulator (LQR) theory in modern multivariable control design, attacks the general dissipative elastic system design problem in a global formulation. The optimal design, however, allows electronic connections and phase relations which are not physically practical or possible in passive structural-mechanical devices. The restriction of LQR solutions (to the Algebraic Riccati Equation) to design spaces which can be implemented as passive structural members and/or dampers is addressed. A general closed-form solution to the optimal free-decay control problem is presented which is tailored for structural-mechanical system. The solution includes, as subsets, special cases such as the Rayleigh Dissipation Function and total energy. Weighting matrix selection is a constrained choice among several parameters to obtain desired physical relationships. The closed-form solution is also applicable to active control design for systems where perfect, collocated actuator-sensor pairs exist.

  11. Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming

    NASA Astrophysics Data System (ADS)

    Sutrisno; Widowati; Solikhin

    2016-06-01

    In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well.

  12. Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

    NASA Astrophysics Data System (ADS)

    Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

    2016-06-01

    With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

  13. A Novel Hybrid Clonal Selection Algorithm with Combinatorial Recombination and Modified Hypermutation Operators for Global Optimization

    PubMed Central

    Lin, Jingjing; Jing, Honglei

    2016-01-01

    Artificial immune system is one of the most recently introduced intelligence methods which was inspired by biological immune system. Most immune system inspired algorithms are based on the clonal selection principle, known as clonal selection algorithms (CSAs). When coping with complex optimization problems with the characteristics of multimodality, high dimension, rotation, and composition, the traditional CSAs often suffer from the premature convergence and unsatisfied accuracy. To address these concerning issues, a recombination operator inspired by the biological combinatorial recombination is proposed at first. The recombination operator could generate the promising candidate solution to enhance search ability of the CSA by fusing the information from random chosen parents. Furthermore, a modified hypermutation operator is introduced to construct more promising and efficient candidate solutions. A set of 16 common used benchmark functions are adopted to test the effectiveness and efficiency of the recombination and hypermutation operators. The comparisons with classic CSA, CSA with recombination operator (RCSA), and CSA with recombination and modified hypermutation operator (RHCSA) demonstrate that the proposed algorithm significantly improves the performance of classic CSA. Moreover, comparison with the state-of-the-art algorithms shows that the proposed algorithm is quite competitive. PMID:27698662

  14. An Optimization Model for the Selection of Bus-Only Lanes in a City.

    PubMed

    Chen, Qun

    2015-01-01

    The planning of urban bus-only lane networks is an important measure to improve bus service and bus priority. To determine the effective arrangement of bus-only lanes, a bi-level programming model for urban bus lane layout is developed in this study that considers accessibility and budget constraints. The goal of the upper-level model is to minimize the total travel time, and the lower-level model is a capacity-constrained traffic assignment model that describes the passenger flow assignment on bus lines, in which the priority sequence of the transfer times is reflected in the passengers' route-choice behaviors. Using the proposed bi-level programming model, optimal bus lines are selected from a set of candidate bus lines; thus, the corresponding bus lane network on which the selected bus lines run is determined. The solution method using a genetic algorithm in the bi-level programming model is developed, and two numerical examples are investigated to demonstrate the efficacy of the proposed model.

  15. An Optimization Model for the Selection of Bus-Only Lanes in a City

    PubMed Central

    Chen, Qun

    2015-01-01

    The planning of urban bus-only lane networks is an important measure to improve bus service and bus priority. To determine the effective arrangement of bus-only lanes, a bi-level programming model for urban bus lane layout is developed in this study that considers accessibility and budget constraints. The goal of the upper-level model is to minimize the total travel time, and the lower-level model is a capacity-constrained traffic assignment model that describes the passenger flow assignment on bus lines, in which the priority sequence of the transfer times is reflected in the passengers’ route-choice behaviors. Using the proposed bi-level programming model, optimal bus lines are selected from a set of candidate bus lines; thus, the corresponding bus lane network on which the selected bus lines run is determined. The solution method using a genetic algorithm in the bi-level programming model is developed, and two numerical examples are investigated to demonstrate the efficacy of the proposed model. PMID:26214001

  16. A Novel Hybrid Clonal Selection Algorithm with Combinatorial Recombination and Modified Hypermutation Operators for Global Optimization

    PubMed Central

    Lin, Jingjing; Jing, Honglei

    2016-01-01

    Artificial immune system is one of the most recently introduced intelligence methods which was inspired by biological immune system. Most immune system inspired algorithms are based on the clonal selection principle, known as clonal selection algorithms (CSAs). When coping with complex optimization problems with the characteristics of multimodality, high dimension, rotation, and composition, the traditional CSAs often suffer from the premature convergence and unsatisfied accuracy. To address these concerning issues, a recombination operator inspired by the biological combinatorial recombination is proposed at first. The recombination operator could generate the promising candidate solution to enhance search ability of the CSA by fusing the information from random chosen parents. Furthermore, a modified hypermutation operator is introduced to construct more promising and efficient candidate solutions. A set of 16 common used benchmark functions are adopted to test the effectiveness and efficiency of the recombination and hypermutation operators. The comparisons with classic CSA, CSA with recombination operator (RCSA), and CSA with recombination and modified hypermutation operator (RHCSA) demonstrate that the proposed algorithm significantly improves the performance of classic CSA. Moreover, comparison with the state-of-the-art algorithms shows that the proposed algorithm is quite competitive.

  17. Optimization of Cu-Zn Massive Sulphide Flotation by Selective Reagents

    NASA Astrophysics Data System (ADS)

    Soltani, F.; Koleini, S. M. J.; Abdollahy, M.

    2014-10-01

    Selective floatation of base metal sulphide minerals can be achieved by using selective reagents. Sequential floatation of chalcopyrite-sphalerite from Taknar (Iran) massive sulphide ore with 3.5 % Zn and 1.26 % Cu was studied. D-optimal design of response surface methodology was used. Four mixed collector types (Aer238 + SIPX, Aero3477 + SIPX, TC1000 + SIPX and X231 + SIPX), two depressant systems (CuCN-ZnSO4 and dextrin-ZnSO4), pH and ZnSO4 dosage were considered as operational factors in the first stage of flotation. Different conditions of pH, CuSO4 dosage and SIPX dosage were studied for sphalerite flotation from first stage tailings. Aero238 + SIPX induced better selectivity for chalcopyrite against pyrite and sphalerite. Dextrin-ZnSO4 was as effective as CuCN-ZnSO4 in sphalerite-pyrite depression. Under optimum conditions, Cu recovery, Zn recovery and pyrite content in Cu concentrate were 88.99, 33.49 and 1.34 % by using Aero238 + SIPX as mixed collector, CuCN-ZnSO4 as depressant system, at ZnSO4 dosage of 200 g/t and pH 10.54. When CuCN was used at the first stage, CuSO4 consumption increased and Zn recovery decreased during the second stage. Maximum Zn recovery was 72.19 % by using 343.66 g/t of CuSO4, 22.22 g/t of SIPX and pH 9.99 at the second stage.

  18. Multi-Bandwidth Frequency Selective Surfaces for Near Infrared Filtering: Design and Optimization

    NASA Technical Reports Server (NTRS)

    Cwik, Tom; Fernandez, Salvador; Ksendzov, A.; LaBaw, Clayton C.; Maker, Paul D.; Muller, Richard E.

    1999-01-01

    Frequency selective surfaces are widely used in the microwave and millimeter wave regions of the spectrum for filtering signals. They are used in telecommunication systems for multi-frequency operation or in instrument detectors for spectroscopy. The frequency selective surface operation depends on a periodic array of elements resonating at prescribed wavelengths producing a filter response. The size of the elements is on the order of half the electrical wavelength, and the array period is typically less than a wavelength for efficient operation. When operating in the optical region, diffraction gratings are used for filtering. In this regime the period of the grating may be several wavelengths producing multiple orders of light in reflection or transmission. In regions between these bands (specifically in the infrared band) frequency selective filters consisting of patterned metal layers fabricated using electron beam lithography are beginning to be developed. The operation is completely analogous to surfaces made in the microwave and millimeter wave region except for the choice of materials used and the fabrication process. In addition, the lithography process allows an arbitrary distribution of patterns corresponding to resonances at various wavelengths to be produced. The design of sub-millimeter filters follows the design methods used in the microwave region. Exacting modal matching, integral equation or finite element methods can be used for design. A major difference though is the introduction of material parameters and thicknesses tha_ may not be important in longer wavelength designs. This paper describes the design of multi-bandwidth filters operating in the I-5 micrometer wavelength range. This work follows on previous design [1,2]. In this paper extensions based on further optimization and an examination of the specific shape of the element in the periodic cell will be reported. Results from the design, manufacture and test of linear wedge filters built

  19. Multi-Bandwidth Frequency Selective Surfaces for Near Infrared Filtering: Design and Optimization

    NASA Technical Reports Server (NTRS)

    Cwik, Tom; Fernandez, Salvador; Ksendzov, A.; LaBaw, Clayton C.; Maker, Paul D.; Muller, Richard E.

    1998-01-01

    Frequency selective surfaces are widely used in the microwave and millimeter wave regions of the spectrum for filtering signals. They are used in telecommunication systems for multi-frequency operation or in instrument detectors for spectroscopy. The frequency selective surface operation depends on a periodic array of elements resonating at prescribed wavelengths producing a filter response. The size of the elements is on the order of half the electrical wavelength, and the array period is typically less than a wavelength for efficient operation. When operating in the optical region, diffraction gratings are used for filtering. In this regime the period of the grating may be several wavelengths producing multiple orders of light in reflection or transmission. In regions between these bands (specifically in the infrared band) frequency selective filters consisting of patterned metal layers fabricated using electron beam lithography are beginning to be developed. The operation is completely analogous to surfaces made in the microwave and millimeter wave region except for the choice of materials used and the fabrication process. In addition, the lithography process allows an arbitrary distribution of patterns corresponding to resonances at various wavelengths to be produced. The design of sub-millimeter filters follows the design methods used in the microwave region. Exacting modal matching, integral equation or finite element methods can be used for design. A major difference though is the introduction of material parameters and thicknesses that may not be important in longer wavelength designs. This paper describes the design of multi- bandwidth filters operating in the 1-5 micrometer wavelength range. This work follows on a previous design. In this paper extensions based on further optimization and an examination of the specific shape of the element in the periodic cell will be reported. Results from the design, manufacture and test of linear wedge filters built

  20. Process optimization for lattice-selective wet etching of crystalline silicon structures

    NASA Astrophysics Data System (ADS)

    Dixson, Ronald G.; Guthrie, William F.; Allen, Richard A.; Orji, Ndubuisi G.; Cresswell, Michael W.; Murabito, Christine E.

    2016-01-01

    Lattice-selective etching of silicon is used in a number of applications, but it is particularly valuable in those for which the lattice-defined sidewall angle can be beneficial to the functional goals. A relatively small but important niche application is the fabrication of tip characterization standards for critical dimension atomic force microscopes (CD-AFMs). CD-AFMs are commonly used as reference tools for linewidth metrology in semiconductor manufacturing. Accurate linewidth metrology using CD-AFM, however, is critically dependent upon calibration of the tip width. Two national metrology institutes and at least two commercial vendors have explored the development of tip calibration standards using lattice-selective etching of crystalline silicon. The National Institute of Standards and Technology standard of this type is called the single crystal critical dimension reference material. These specimens, which are fabricated using a lattice-plane-selective etch on (110) silicon, exhibit near vertical sidewalls and high uniformity and can be used to calibrate CD-AFM tip width to a standard uncertainty of less than 1 nm. During the different generations of this project, we evaluated variations of the starting material and process conditions. Some of our starting materials required a large etch bias to achieve the desired linewidths. During the optimization experiment described in this paper, we found that for potassium hydroxide etching of the silicon features, it was possible to independently tune the target linewidth and minimize the linewidth nonuniformity. Consequently, this process is particularly well suited for small-batch fabrication of CD-AFM linewidth standards.

  1. Multi-objective selection and optimization of shaped materials and laminated composites

    NASA Astrophysics Data System (ADS)

    Singh, Jasveer

    Most of the current optimization techniques for the design of light-weight structures are unable to generate structural alternatives at the concept stage of design. This research tackles the challenge of developing methods for the early stage of design involving structures made up of conventional materials and composite laminates. For conventional materials, the recently introduced shape transformer approach is used. This work extends the method to deal with the case of torsional stiffness design, and generalizes it to single and multi-criteria selection of lightweight shafts subjected to a combination of bending, shear, and torsional load. The prominent feature of the work is the useful integration of shape and material to model and visualize multi-objective selection problems. The scheme is centered on concept selection in structural design, and hinges on measures that govern the shape properties of a cross-section regardless of its size. These measures, referred to as shape transformers, can classify shapes in a way similar to material classification. The procedure is demonstrated by considering torsional stiffness as a constraint. Performance charts are developed for both single and multi-criteria cases to let the reader visualize in a glance the whole range of cross-sectional shapes for each material. Each design chart is explained with a brief example. The above mentioned approach is also extended to incorporate orthotropic composite laminates. Design charts are obtained for the selection of five generic design variables: shape, size, material, layup, and number of plies. These charts also aid in comparing the performances of two commonly used laminates in bending and torsion - angle plies and cross plies. For a generic composite laminate, due to the number of variables involved, these kinds of design charts are very difficult. However, other tactics like using an analytical model for function evaluation can be used at conceptual stage of design. This is

  2. Optimal landmarks selection and fiducial marker placement for minimal target registration error in image-guided neurosurgery

    NASA Astrophysics Data System (ADS)

    Shamir, Reuben R.; Joskowicz, Leo; Shoshan, Yigal

    2009-02-01

    We describe a new framework and method for the optimal selection of anatomical landmarks and optimal placement of fiducial markers in image-guided neurosurgery. The method allows the surgeon to optimally plan the markers locations on routine diagnostic images before preoperative imaging and to intraoperatively select the fiducial markers and the anatomical landmarks that minimize the Target Registration Error (TRE). The optimal fiducial marker configuration selection is performed by the surgeon on the diagnostic image following the target selection based on a visual Estimated TRE (E-TRE) map. The E-TRE map is automatically updated when the surgeon interactively adds and deletes candidate markers and targets. The method takes the guesswork out of the registration process, provides a reliable localization uncertainty error for navigation, and can reduce the localization error without additional imaging and hardware. Our clinical experiments on five patients who underwent brain surgery with a navigation system show that optimizing one marker location and the anatomical landmarks configuration reduces the average TRE from 4.7mm to 3.2mm, with a maximum improvement of 4mm. The reduction of the target registration error has the potential to support safer and more accurate minimally invasive neurosurgical procedures.

  3. Optimization of Sample Site Selection Imaging for OSIRIS-REx Using Asteroid Surface Analog Images

    NASA Astrophysics Data System (ADS)

    Tanquary, Hannah E.; Sahr, Eric; Habib, Namrah; Hawley, Christopher; Weber, Nathan; Boynton, William V.; Kinney-Spano, Ellyne; Lauretta, Dante

    2014-11-01

    OSIRIS-REx will return a sample of regolith from the surface of asteroid 101955 Bennu. The mission will obtain high resolution images of the asteroid in order to create detailed maps which will satisfy multiple mission objectives. To select a site, we must (i) identify hazards to the spacecraft and (ii) characterize a number of candidate sites to determine the optimal location for sampling. To further characterize the site, a long-term science campaign will be undertaken to constrain the geologic properties. To satisfy these objectives, the distribution and size of blocks at the sample site and backup sample site must be determined. This will be accomplished through the creation of rock size frequency distribution maps. The primary goal of this study is to optimize the creation of these map products by assessing techniques for counting blocks on small bodies, and assessing the methods of analysis of the resulting data. We have produced a series of simulated surfaces of Bennu which have been imaged, and the images processed to simulate Polycam images during the Reconnaissance phase. These surface analog images allow us to explore a wide range of imaging conditions, both ideal and non-ideal. The images have been “degraded”, and are displayed as thumbnails representing the limits of Polycam resolution from an altitude of 225 meters. Specifically, this study addresses the mission requirement that the rock size frequency distribution of regolith grains < 2cm in longest dimension must be determined for the sample sites during Reconnaissance. To address this requirement, we focus on the range of available lighting angles. Varying illumination and phase angles in the simulated images, we can compare the size-frequency distributions calculated from the degraded images with the known size frequency distributions of the Bennu simulant material, and thus determine the optimum lighting conditions for satisfying the 2 cm requirement.

  4. Neural Network Cascade Optimizes MicroRNA Biomarker Selection for Nasopharyngeal Cancer Prognosis

    PubMed Central

    Zhu, Wenliang; Kan, Xuan

    2014-01-01

    MicroRNAs (miRNAs) have been shown to be promising biomarkers in predicting cancer prognosis. However, inappropriate or poorly optimized processing and modeling of miRNA expression data can negatively affect prediction performance. Here, we propose a holistic solution for miRNA biomarker selection and prediction model building. This work introduces the use of a neural network cascade, a cascaded constitution of small artificial neural network units, for evaluating miRNA expression and patient outcome. A miRNA microarray dataset of nasopharyngeal carcinoma was retrieved from Gene Expression Omnibus to illustrate the methodology. Results indicated a nonlinear relationship between miRNA expression and patient death risk, implying that direct comparison of expression values is inappropriate. However, this method performs transformation of miRNA expression values into a miRNA score, which linearly measures death risk. Spearman correlation was calculated between miRNA scores and survival status for each miRNA. Finally, a nine-miRNA signature was optimized to predict death risk after nasopharyngeal carcinoma by establishing a neural network cascade consisting of 13 artificial neural network units. Area under the ROC was 0.951 for the internal validation set and had a prediction accuracy of 83% for the external validation set. In particular, the established neural network cascade was found to have strong immunity against noise interference that disturbs miRNA expression values. This study provides an efficient and easy-to-use method that aims to maximize clinical application of miRNAs in prognostic risk assessment of patients with cancer. PMID:25310846

  5. Neural network cascade optimizes microRNA biomarker selection for nasopharyngeal cancer prognosis.

    PubMed

    Zhu, Wenliang; Kan, Xuan

    2014-01-01

    MicroRNAs (miRNAs) have been shown to be promising biomarkers in predicting cancer prognosis. However, inappropriate or poorly optimized processing and modeling of miRNA expression data can negatively affect prediction performance. Here, we propose a holistic solution for miRNA biomarker selection and prediction model building. This work introduces the use of a neural network cascade, a cascaded constitution of small artificial neural network units, for evaluating miRNA expression and patient outcome. A miRNA microarray dataset of nasopharyngeal carcinoma was retrieved from Gene Expression Omnibus to illustrate the methodology. Results indicated a nonlinear relationship between miRNA expression and patient death risk, implying that direct comparison of expression values is inappropriate. However, this method performs transformation of miRNA expression values into a miRNA score, which linearly measures death risk. Spearman correlation was calculated between miRNA scores and survival status for each miRNA. Finally, a nine-miRNA signature was optimized to predict death risk after nasopharyngeal carcinoma by establishing a neural network cascade consisting of 13 artificial neural network units. Area under the ROC was 0.951 for the internal validation set and had a prediction accuracy of 83% for the external validation set. In particular, the established neural network cascade was found to have strong immunity against noise interference that disturbs miRNA expression values. This study provides an efficient and easy-to-use method that aims to maximize clinical application of miRNAs in prognostic risk assessment of patients with cancer. PMID:25310846

  6. Experiments for practical education in process parameter optimization for selective laser sintering to increase workpiece quality

    NASA Astrophysics Data System (ADS)

    Reutterer, Bernd; Traxler, Lukas; Bayer, Natascha; Drauschke, Andreas

    2016-04-01

    Selective Laser Sintering (SLS) is considered as one of the most important additive manufacturing processes due to component stability and its broad range of usable materials. However the influence of the different process parameters on mechanical workpiece properties is still poorly studied, leading to the fact that further optimization is necessary to increase workpiece quality. In order to investigate the impact of various process parameters, laboratory experiments are implemented to improve the understanding of the SLS limitations and advantages on an educational level. Experiments are based on two different workstations, used to teach students the fundamentals of SLS. First of all a 50 W CO2 laser workstation is used to investigate the interaction of the laser beam with the used material in accordance with varied process parameters to analyze a single-layered test piece. Second of all the FORMIGA P110 laser sintering system from EOS is used to print different 3D test pieces in dependence on various process parameters. Finally quality attributes are tested including warpage, dimension accuracy or tensile strength. For dimension measurements and evaluation of the surface structure a telecentric lens in combination with a camera is used. A tensile test machine allows testing of the tensile strength and the interpreting of stress-strain curves. The developed laboratory experiments are suitable to teach students the influence of processing parameters. In this context they will be able to optimize the input parameters depending on the component which has to be manufactured and to increase the overall quality of the final workpiece.

  7. Optimizing Normal Tissue Sparing in Ion Therapy Using Calculated Isoeffective Dose for Ion Selection

    SciTech Connect

    Remmes, Nicholas B.; Herman, Michael G.; Kruse, Jon J.

    2012-06-01

    Purpose: To investigate how the selection of ion type affects the calculated isoeffective dose to the surrounding normal tissue as a function of both normal tissue and target tissue {alpha}/{beta} ratios. Methods and Materials: A microdosimetric biologic dose model was incorporated into a Geant4 simulation of parallel opposed beams of protons, helium, lithium, beryllium, carbon, and neon ions. The beams were constructed to give a homogeneous isoeffective dose to a volume in the center of a water phantom for target tissues covering a range of cobalt equivalent {alpha}/{beta} ratios of 1-20 Gy. Concomitant normal tissue isoeffective doses in the plateau of the ion beam were then compared for different ions across the range of normal tissue and target tissue radiosensitivities for a fixed isoeffective dose to the target tissue. Results: The ion type yielding the optimal normal tissue sparing was highly dependent on the {alpha}/{beta} ratio of both the normal and the target tissue. For carbon ions, the calculated isoeffective dose to normal tissue at a 5-cm depth varied by almost a factor of 5, depending on the {alpha}/{beta} ratios of the normal and target tissue. This ranges from a factor of 2 less than the isoeffective dose of a similar proton treatment to a factor of 2 greater. Conclusions: No single ion is optimal for all treatment scenarios. The heavier ions are superior in cases in which the {alpha}/{beta} ratio of the target tissue is low and the {alpha}/{beta} ratio of normal tissue is high, and protons are superior in the opposite circumstances. Lithium and beryllium appear to offer dose advantages similar to carbon, with a considerably lower normal tissue dose when the {alpha}/{beta} ratio in the target tissue is high and the {alpha}/{beta} ratio in the normal tissue is low.

  8. Feature selection for linear SVMs under uncertain data: robust optimization based on difference of convex functions algorithms.

    PubMed

    Le Thi, Hoai An; Vo, Xuan Thanh; Pham Dinh, Tao

    2014-11-01

    In this paper, we consider the problem of feature selection for linear SVMs on uncertain data that is inherently prevalent in almost all datasets. Using principles of Robust Optimization, we propose robust schemes to handle data with ellipsoidal model and box model of uncertainty. The difficulty in treating ℓ0-norm in feature selection problem is overcome by using appropriate approximations and Difference of Convex functions (DC) programming and DC Algorithms (DCA). The computational results show that the proposed robust optimization approaches are superior than a traditional approach in immunizing perturbation of the data.

  9. Selecting optimal screening items for delirium: an application of item response theory

    PubMed Central

    2013-01-01

    Background Delirium (acute confusion), is a common, morbid, and costly complication of acute illness in older adults. Yet, researchers and clinicians lack short, efficient, and sensitive case identification tools for delirium. Though the Confusion Assessment Method (CAM) is the most widely used algorithm for delirium, the existing assessments that operationalize the CAM algorithm may be too long or complicated for routine clinical use. Item response theory (IRT) models help facilitate the development of short screening tools for use in clinical applications or research studies. This study utilizes IRT to identify a reduced set of optimally performing screening indicators for the four CAM features of delirium. Methods Older adults were screened for enrollment in a large scale delirium study conducted in Boston-area post-acute facilities (n = 4,598). Trained interviewers conducted a structured delirium assessment that culminated in rating the presence or absence of four features of delirium based on the CAM. A pool of 135 indicators from established cognitive testing and delirium assessment tools were assigned by an expert panel into two indicator sets per CAM feature representing (a) direct interview questions, including cognitive testing, and (b) interviewer observations. We used IRT models to identify the best items to screen for each feature of delirium. Results We identified 10 dimensions and chose up to five indicators per dimension. Preference was given to items with peak psychometric information in the latent trait region relevant for screening for delirium. The final set of 48 indicators, derived from 39 items, maintains fidelity to clinical constructs of delirium and maximizes psychometric information relevant for screening. Conclusions We identified optimal indicators from a large item pool to screen for delirium. The selected indicators maintain fidelity to clinical constructs of delirium while maximizing psychometric information important for

  10. Selecting and optimizing eco-physiological parameters of Biome-BGC to reproduce observed woody and leaf biomass growth of Eucommia ulmoides plantation in China using Dakota optimizer

    NASA Astrophysics Data System (ADS)

    Miyauchi, T.; Machimura, T.

    2013-12-01

    In the simulation using an ecosystem process model, the adjustment of parameters is indispensable for improving the accuracy of prediction. This procedure, however, requires much time and effort for approaching the simulation results to the measurements on models consisting of various ecosystem processes. In this study, we tried to apply a general purpose optimization tool in the parameter optimization of an ecosystem model, and examined its validity by comparing the simulated and measured biomass growth of a woody plantation. A biometric survey of tree biomass growth was performed in 2009 in an 11-year old Eucommia ulmoides plantation in Henan Province, China. Climate of the site was dry temperate. Leaf, above- and below-ground woody biomass were measured from three cut trees and converted into carbon mass per area by measured carbon contents and stem density. Yearly woody biomass growth of the plantation was calculated according to allometric relationships determined by tree ring analysis of seven cut trees. We used Biome-BGC (Thornton, 2002) to reproduce biomass growth of the plantation. Air temperature and humidity from 1981 to 2010 was used as input climate condition. The plant functional type was deciduous broadleaf, and non-optimizing parameters were left default. 11-year long normal simulations were performed following a spin-up run. In order to select optimizing parameters, we analyzed the sensitivity of leaf, above- and below-ground woody biomass to eco-physiological parameters. Following the selection, optimization of parameters was performed by using the Dakota optimizer. Dakota is an optimizer developed by Sandia National Laboratories for providing a systematic and rapid means to obtain optimal designs using simulation based models. As the object function, we calculated the sum of relative errors between simulated and measured leaf, above- and below-ground woody carbon at each of eleven years. In an alternative run, errors at the last year (at the

  11. Parametric optimization of selective laser melting for forming Ti6Al4V samples by Taguchi method

    NASA Astrophysics Data System (ADS)

    Sun, Jianfeng; Yang, Yongqiang; Wang, Di

    2013-07-01

    In this study, a selective laser melting experiment was carried out with Ti6Al4V alloy powders. To produce samples with maximum density, selective laser melting parameters of laser power, scanning speed, powder thickness, hatching space and scanning strategy were carefully selected. As a statistical design of experimental technique, the Taguchi method was used to optimize the selected parameters. The results were analyzed using analyses of variance (ANOVA) and the signal-to-noise (S/N) ratios by design-expert software for the optimal parameters, and a regression model was established. The regression equation revealed a linear relationship among the density, laser power, scanning speed, powder thickness and scanning strategy. From the experiments, sample with density higher than 95% was obtained. The microstructure of obtained sample was mainly composed of acicular martensite, α phase and β phase. The micro-hardness was 492 HV0.2.

  12. A data driven model for optimal orthosis selection in children with cerebral palsy.

    PubMed

    Ries, Andrew J; Novacheck, Tom F; Schwartz, Michael H

    2014-09-01

    A statistical orthosis selection model was developed using the Random Forest Algorithm (RFA). The model's performance and potential clinical benefit was evaluated. The model predicts which of five orthosis designs - solid (SAFO), posterior leaf spring (PLS), hinged (HAFO), supra-malleolar (SMO), or foot orthosis (FO) - will provide the best gait outcome for individuals with diplegic cerebral palsy (CP). Gait outcome was defined as the change in Gait Deviation Index (GDI) between walking while wearing an orthosis compared to barefoot (ΔGDI=GDIOrthosis-GDIBarefoot). Model development was carried out using retrospective data from 476 individuals who wore one of the five orthosis designs bilaterally. Clinical benefit was estimated by predicting the optimal orthosis and ΔGDI for 1016 individuals (age: 12.6 (6.7) years), 540 of whom did not have an existing orthosis prescription. Among limbs with an orthosis, the model agreed with the prescription only 14% of the time. For 56% of limbs without an orthosis, the model agreed that no orthosis was expected to provide benefit. Using the current standard of care orthosis (i.e. existing orthosis prescriptions), ΔGDI is only +0.4 points on average. Using the orthosis prediction model, average ΔGDI for orthosis users was estimated to improve to +5.6 points. The results of this study suggest that an orthosis selection model derived from the RFA can significantly improve outcomes from orthosis use for the diplegic CP population. Further validation of the model is warranted using data from other centers and a prospective study.

  13. Optimism

    PubMed Central

    Carver, Charles S.; Scheier, Michael F.; Segerstrom, Suzanne C.

    2010-01-01

    Optimism is an individual difference variable that reflects the extent to which people hold generalized favorable expectancies for their future. Higher levels of optimism have been related prospectively to better subjective well-being in times of adversity or difficulty (i.e., controlling for previous well-being). Consistent with such findings, optimism has been linked to higher levels of engagement coping and lower levels of avoidance, or disengagement, coping. There is evidence that optimism is associated with taking proactive steps to protect one's health, whereas pessimism is associated with health-damaging behaviors. Consistent with such findings, optimism is also related to indicators of better physical health. The energetic, task-focused approach that optimists take to goals also relates to benefits in the socioeconomic world. Some evidence suggests that optimism relates to more persistence in educational efforts and to higher later income. Optimists also appear to fare better than pessimists in relationships. Although there are instances in which optimism fails to convey an advantage, and instances in which it may convey a disadvantage, those instances are relatively rare. In sum, the behavioral patterns of optimists appear to provide models of living for others to learn from. PMID:20170998

  14. Wind selection and drift compensation optimize migratory pathways in a high-flying moth.

    PubMed

    Chapman, Jason W; Reynolds, Don R; Mouritsen, Henrik; Hill, Jane K; Riley, Joe R; Sivell, Duncan; Smith, Alan D; Woiwod, Ian P

    2008-04-01

    Numerous insect species undertake regular seasonal migrations in order to exploit temporary breeding habitats [1]. These migrations are often achieved by high-altitude windborne movement at night [2-6], facilitating rapid long-distance transport, but seemingly at the cost of frequent displacement in highly disadvantageous directions (the so-called "pied piper" phenomenon [7]). This has lead to uncertainty about the mechanisms migrant insects use to control their migratory directions [8, 9]. Here we show that, far from being at the mercy of the wind, nocturnal moths have unexpectedly complex behavioral mechanisms that guide their migratory flight paths in seasonally-favorable directions. Using entomological radar, we demonstrate that free-flying individuals of the migratory noctuid moth Autographa gamma actively select fast, high-altitude airstreams moving in a direction that is highly beneficial for their autumn migration. They also exhibit common orientation close to the downwind direction, thus maximizing the rectilinear distance traveled. Most unexpectedly, we find that when winds are not closely aligned with the moth's preferred heading (toward the SSW), they compensate for cross-wind drift, thus increasing the probability of reaching their overwintering range. We conclude that nocturnally migrating moths use a compass and an inherited preferred direction to optimize their migratory track.

  15. Improving well-being at work: A randomized controlled intervention based on selection, optimization, and compensation.

    PubMed

    Müller, Andreas; Heiden, Barbara; Herbig, Britta; Poppe, Franziska; Angerer, Peter

    2016-04-01

    This study aimed to develop, implement, and evaluate an occupational health intervention that is based on the theoretical model of selection, optimization, and compensation (SOC). We conducted a stratified randomized controlled intervention with 70 nurses of a community hospital in Germany (94% women; mean age 43.7 years). Altogether, the training consisted of 6 sessions (16.5 hours) over a period of 9 months. The training took place in groups of 6-8 employees. Participants were familiarized with the SOC model and developed and implemented a personal project based on SOC to cope effectively with 1 important job demand or to activate a job resource. Consistent with our hypotheses, we observed a meaningful trend that the proposed SOC training enhanced mental well-being, particularly in employees with a strong commitment to the intervention. While highly committed training participants reported higher levels of job control at follow-up, the effects were not statistical significant. Additional analyses of moderation effects showed that the training is particularly effective to enhance mental well-being when job control is low. Contrary to our assumptions, perceived work ability was not improved by the training. Our study provides first indications that SOC training might be a promising approach to occupational health and stress prevention. Moreover, it identifies critical success factors of occupational interventions based on SOC. However, additional studies are needed to corroborate the effectiveness of SOC trainings in the occupational contexts. PMID:26322438

  16. Specific selection criteria and testing protocol optimize reservoir drill-in fluid design

    SciTech Connect

    Donovan, J.P.; Jones, T.A.

    1995-12-31

    Proper test and evaluation methodology for reservoir drill-in fluids is an important step in the construction design of a producing wellbore. Drill-in fluids are specifically designed to meet drilling and completion objectives, simplify reservoir cleanup and maximize production rates in open hole completions. New protocols developed by drilling fluid and completion laboratories have proven to be effective tools for evaluating fluid designs that optimize production. Drill-in fluid selection begins with an initial screening process taking into account qualifying issues such as environmental acceptability, reservoir temperature, physical limitations, and chemical compatibility between the fluid and the reservoir. The final fluid formulation should minimize formation damage, fluid leak-off rates, breakout pressures, and wellbore cleanup of drill-in and completion operations, thus maximizing the productivity of the well. Formation damage risks can be minimized if laboratory testing procedures parallel specific reservoir conditions. Case studies confirm that a methodology based on laboratory data that incorporates drilling fluid, completion, and workover operation protocols is effective in lowering completion costs and increasing production.

  17. a Geographic Analysis of Optimal Signage Location Selection in Scenic Area

    NASA Astrophysics Data System (ADS)

    Ruan, Ling; Long, Ying; Zhang, Ling; Wu, Xiao Ling

    2016-06-01

    As an important part of the scenic area infrastructure services, signage guiding system plays an indispensable role in guiding the way and improving the quality of tourism experience. This paper proposes an optimal method in signage location selection and direction content design in a scenic area based on geographic analysis. The object of the research is to provide a best solution to arrange limited guiding boards in a tourism area to show ways arriving at any scenic spot from any entrance. There are four steps to achieve the research object. First, the spatial distribution of the junction of the scenic road, the passageway and the scenic spots is analyzed. Then, the count of scenic roads intersection on the shortest path between all entrances and all scenic spots is calculated. Next, combing with the grade of the scenic road and scenic spots, the importance of each road intersection is estimated quantitatively. Finally, according to the importance of all road intersections, the most suitable layout locations of signage guiding boards can be provided. In addition, the method is applied in the Ming Tomb scenic area in China and the result is compared with the existing signage guiding space layout.

  18. Performance optimization of total momentum filtering double-resonance energy selective electron heat pump

    NASA Astrophysics Data System (ADS)

    Ding, Ze-Min; Chen, Lin-Gen; Ge, Yan-Lin; Sun, Feng-Rui

    2016-04-01

    A theoretical model for energy selective electron (ESE) heat pumps operating with two-dimensional electron reservoirs is established in this study. In this model, a double-resonance energy filter operating with a total momentum filtering mechanism is considered for the transmission of electrons. The optimal thermodynamic performance of the ESE heat pump devices is also investigated. Numerical calculations show that the heating load of the device with two resonances is larger, whereas the coefficient of performance (COP) is lower than the ESE heat pump when considering a single-resonance filter. The performance characteristics of the ESE heat pumps in the total momentum filtering condition are generally superior to those with a conventional filtering mechanism. In particular, the performance characteristics of the ESE heat pumps considering a conventional filtering mechanism are vastly different from those of a device with total momentum filtering, which is induced by extra electron momentum in addition to the horizontal direction. Parameters such as resonance width and energy spacing are found to be associated with the performance of the electron system.

  19. Burst-Modulated Waveforms Optimize Electrical Stimuli for Charge Efficiency and Fiber Selectivity.

    PubMed

    Qing, Kurt Y; Ward, Matthew P; Irazoqui, Pedro P

    2015-11-01

    We demonstrate an alternative method of designing electrical stimuli-termed burst modulation--for producing different patterns of nerve fiber recruitment. By delivering electrical charge in bursts of "pulsons"--miniature pulses-instead of as long continuous pulses, our method can optimize the waveform for stimulation efficiency and fiber selectivity. In our in vivo validation experiments, while maintaining C fibers of the rat vagus nerve at ∼ 50% activation with different waveforms, the burst-modulated waveform produced 11% less A fiber activation than the standard rectangular pulse waveform (rectangular: 50.8±1.5% of maximal A response, mean ± standard error of the mean; burst-modulated: 39.8 ±1.3%), which equates to a 20% reduction in A fiber response magnitude. In addition, the burst-modulated waveform required 45% less stimulus charge per phase to maintain 50% C fiber activation (rectangular: 20.7 ±0.86 μC; burst-modulated: 11.3 ±0.41 μC ). Burst-modulated waveforms produced consistent patterns of fiber recruitment within and across animals, which indicate that our methods of stimulus design and response analysis provide a reliable way to study neurostimulation and deliver therapy.

  20. Discrepancy among the synonymous codons with respect to their selection as optimal codon in bacteria

    PubMed Central

    Satapathy, Siddhartha Sankar; Powdel, Bhesh Raj; Buragohain, Alak Kumar; Ray, Suvendra Kumar

    2016-01-01

    The different triplets encoding the same amino acid, termed as synonymous codons, are not equally abundant in a genome. Factors such as G + C% and tRNA are known to influence their abundance in a genome. However, the order of the nucleotide in each codon per se might also be another factor impacting on its abundance values. Of the synonymous codons for specific amino acids, some are preferentially used in the high expression genes that are referred to as the ‘optimal codons’ (OCs). In this study, we compared OCs of the 18 amino acids in 221 species of bacteria. It is observed that there is amino acid specific influence for the selection of OCs. There is also influence of phylogeny in the choice of OCs for some amino acids such as Glu, Gln, Lys and Leu. The phenomenon of codon bias is also supported by the comparative studies of the abundance values of the synonymous codons with same G + C. It is likely that the order of the nucleotides in the triplet codon is also perhaps involved in the phenomenon of codon usage bias in organisms. PMID:27426467

  1. Wind selection and drift compensation optimize migratory pathways in a high-flying moth.

    PubMed

    Chapman, Jason W; Reynolds, Don R; Mouritsen, Henrik; Hill, Jane K; Riley, Joe R; Sivell, Duncan; Smith, Alan D; Woiwod, Ian P

    2008-04-01

    Numerous insect species undertake regular seasonal migrations in order to exploit temporary breeding habitats [1]. These migrations are often achieved by high-altitude windborne movement at night [2-6], facilitating rapid long-distance transport, but seemingly at the cost of frequent displacement in highly disadvantageous directions (the so-called "pied piper" phenomenon [7]). This has lead to uncertainty about the mechanisms migrant insects use to control their migratory directions [8, 9]. Here we show that, far from being at the mercy of the wind, nocturnal moths have unexpectedly complex behavioral mechanisms that guide their migratory flight paths in seasonally-favorable directions. Using entomological radar, we demonstrate that free-flying individuals of the migratory noctuid moth Autographa gamma actively select fast, high-altitude airstreams moving in a direction that is highly beneficial for their autumn migration. They also exhibit common orientation close to the downwind direction, thus maximizing the rectilinear distance traveled. Most unexpectedly, we find that when winds are not closely aligned with the moth's preferred heading (toward the SSW), they compensate for cross-wind drift, thus increasing the probability of reaching their overwintering range. We conclude that nocturnally migrating moths use a compass and an inherited preferred direction to optimize their migratory track. PMID:18394893

  2. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    PubMed Central

    Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms. PMID:27642363

  3. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    PubMed Central

    Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms.

  4. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine.

    PubMed

    Xi, Maolong; Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms. PMID:27642363

  5. A novel low-noise linear-in-dB intermediate frequency variable-gain amplifier for DRM/DAB tuners

    NASA Astrophysics Data System (ADS)

    Keping, Wang; Zhigong, Wang; Jianzheng, Zhou; Xuemei, Lei; Mingzhu, Zhou

    2009-03-01

    A broadband CMOS intermediate frequency (IF) variable-gain amplifier (VGA) for DRM/DAB tuners is presented. The VGA comprises two cascaded stages: one is for noise-canceling and another is for signal-summing. The chip is fabricated in a standard 0.18 μm 1P6M RF CMOS process of SMIC. Measured results show a good linear-in-dB gain characteristic in 28 dB dynamic gain range of -10 to 18 dB. It can operate in the frequency range of 30-700 MHz and consumes 27 mW at 1.8 V supply with the on-chip test buffer. The minimum noise figure is only 3.1 dB at maximum gain and the input-referred 1 dB gain compression point at the minimum gain is -3.9 dBm.

  6. Comparing the Selection and Placement of Best Management Practices in Improving Water Quality Using a Multiobjective Optimization and Targeting Method

    PubMed Central

    Chiang, Li-Chi; Chaubey, Indrajeet; Maringanti, Chetan; Huang, Tao

    2014-01-01

    Suites of Best Management Practices (BMPs) are usually selected to be economically and environmentally efficient in reducing nonpoint source (NPS) pollutants from agricultural areas in a watershed. The objective of this research was to compare the selection and placement of BMPs in a pasture-dominated watershed using multiobjective optimization and targeting methods. Two objective functions were used in the optimization process, which minimize pollutant losses and the BMP placement areas. The optimization tool was an integration of a multi-objective genetic algorithm (GA) and a watershed model (Soil and Water Assessment Tool—SWAT). For the targeting method, an optimum BMP option was implemented in critical areas in the watershed that contribute the greatest pollutant losses. A total of 171 BMP combinations, which consist of grazing management, vegetated filter strips (VFS), and poultry litter applications were considered. The results showed that the optimization is less effective when vegetated filter strips (VFS) are not considered, and it requires much longer computation times than the targeting method to search for optimum BMPs. Although the targeting method is effective in selecting and placing an optimum BMP, larger areas are needed for BMP implementation to achieve the same pollutant reductions as the optimization method. PMID:24619160

  7. Discovery and Optimization of Selective Nav1.8 Modulator Series That Demonstrate Efficacy in Preclinical Models of Pain.

    PubMed

    Bagal, Sharan K; Bungay, Peter J; Denton, Stephen M; Gibson, Karl R; Glossop, Melanie S; Hay, Tanya L; Kemp, Mark I; Lane, Charlotte A L; Lewis, Mark L; Maw, Graham N; Million, William A; Payne, C Elizabeth; Poinsard, Cedric; Rawson, David J; Stammen, Blanda L; Stevens, Edward B; Thompson, Lisa R

    2015-06-11

    Voltage-gated sodium channels, in particular Nav1.8, can be targeted for the treatment of neuropathic and inflammatory pain. Herein, we described the optimization of Nav1.8 modulator series to deliver subtype selective, state, and use-dependent chemical matter that is efficacious in preclinical models of neuropathic and inflammatory pain. PMID:26101568

  8. Discovery and Optimization of Selective Nav1.8 Modulator Series That Demonstrate Efficacy in Preclinical Models of Pain

    PubMed Central

    2015-01-01

    Voltage-gated sodium channels, in particular Nav1.8, can be targeted for the treatment of neuropathic and inflammatory pain. Herein, we described the optimization of Nav1.8 modulator series to deliver subtype selective, state, and use-dependent chemical matter that is efficacious in preclinical models of neuropathic and inflammatory pain. PMID:26101568

  9. The D-Optimality Item Selection Criterion in the Early Stage of CAT: A Study with the Graded Response Model

    ERIC Educational Resources Information Center

    Passos, Valeria Lima; Berger, Martijn P. F.; Tan, Frans E. S.

    2008-01-01

    During the early stage of computerized adaptive testing (CAT), item selection criteria based on Fisher"s information often produce less stable latent trait estimates than the Kullback-Leibler global information criterion. Robustness against early stage instability has been reported for the D-optimality criterion in a polytomous CAT with the…

  10. Insights into the Experiences of Older Workers and Change: Through the Lens of Selection, Optimization, and Compensation

    ERIC Educational Resources Information Center

    Unson, Christine; Richardson, Margaret

    2013-01-01

    Purpose: The study examined the barriers faced, the goals selected, and the optimization and compensation strategies of older workers in relation to career change. Method: Thirty open-ended interviews, 12 in the United States and 18 in New Zealand, were conducted, recorded, transcribed verbatim, and analyzed for themes. Results: Barriers to…

  11. Optimization of an indazole series of selective estrogen receptor degraders: Tumor regression in a tamoxifen-resistant breast cancer xenograft.

    PubMed

    Govek, Steven P; Nagasawa, Johnny Y; Douglas, Karensa L; Lai, Andiliy G; Kahraman, Mehmet; Bonnefous, Celine; Aparicio, Anna M; Darimont, Beatrice D; Grillot, Katherine L; Joseph, James D; Kaufman, Joshua A; Lee, Kyoung-Jin; Lu, Nhin; Moon, Michael J; Prudente, Rene Y; Sensintaffar, John; Rix, Peter J; Hager, Jeffrey H; Smith, Nicholas D

    2015-11-15

    Selective estrogen receptor degraders (SERDs) have shown promise for the treatment of ER+ breast cancer. Disclosed herein is the continued optimization of our indazole series of SERDs. Exploration of ER degradation and antagonism in vitro followed by in vivo antagonism and oral exposure culminated in the discovery of indazoles 47 and 56, which induce tumor regression in a tamoxifen-resistant breast cancer xenograft.

  12. Effect of Selection of Design Parameters on the Optimization of a Horizontal Axis Wind Turbine via Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Alpman, Emre

    2014-06-01

    The effect of selecting the twist angle and chord length distributions on the wind turbine blade design was investigated by performing aerodynamic optimization of a two-bladed stall regulated horizontal axis wind turbine. Twist angle and chord length distributions were defined using Bezier curve using 3, 5, 7 and 9 control points uniformly distributed along the span. Optimizations performed using a micro-genetic algorithm with populations composed of 5, 10, 15, 20 individuals showed that, the number of control points clearly affected the outcome of the process; however the effects were different for different population sizes. The results also showed the superiority of micro-genetic algorithm over a standard genetic algorithm, for the selected population sizes. Optimizations were also performed using a macroevolutionary algorithm and the resulting best blade design was compared with that yielded by micro-genetic algorithm.

  13. Automatised selection of load paths to construct reduced-order models in computational damage micromechanics: from dissipation-driven random selection to Bayesian optimization

    NASA Astrophysics Data System (ADS)

    Goury, Olivier; Amsallem, David; Bordas, Stéphane Pierre Alain; Liu, Wing Kam; Kerfriden, Pierre

    2016-08-01

    In this paper, we present new reliable model order reduction strategies for computational micromechanics. The difficulties rely mainly upon the high dimensionality of the parameter space represented by any load path applied onto the representative volume element. We take special care of the challenge of selecting an exhaustive snapshot set. This is treated by first using a random sampling of energy dissipating load paths and then in a more advanced way using Bayesian optimization associated with an interlocked division of the parameter space. Results show that we can insure the selection of an exhaustive snapshot set from which a reliable reduced-order model can be built.

  14. Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery.

    PubMed

    Ghose, Arup K; Herbertz, Torsten; Hudkins, Robert L; Dorsey, Bruce D; Mallamo, John P

    2012-01-18

    The central nervous system (CNS) is the major area that is affected by aging. Alzheimer's disease (AD), Parkinson's disease (PD), brain cancer, and stroke are the CNS diseases that will cost trillions of dollars for their treatment. Achievement of appropriate blood-brain barrier (BBB) penetration is often considered a significant hurdle in the CNS drug discovery process. On the other hand, BBB penetration may be a liability for many of the non-CNS drug targets, and a clear understanding of the physicochemical and structural differences between CNS and non-CNS drugs may assist both research areas. Because of the numerous and challenging issues in CNS drug discovery and the low success rates, pharmaceutical companies are beginning to deprioritize their drug discovery efforts in the CNS arena. Prompted by these challenges and to aid in the design of high-quality, efficacious CNS compounds, we analyzed the physicochemical property and the chemical structural profiles of 317 CNS and 626 non-CNS oral drugs. The conclusions derived provide an ideal property profile for lead selection and the property modification strategy during the lead optimization process. A list of substructural units that may be useful for CNS drug design was also provided here. A classification tree was also developed to differentiate between CNS drugs and non-CNS oral drugs. The combined analysis provided the following guidelines for designing high-quality CNS drugs: (i) topological molecular polar surface area of <76 Å(2) (25-60 Å(2)), (ii) at least one (one or two, including one aliphatic amine) nitrogen, (iii) fewer than seven (two to four) linear chains outside of rings, (iv) fewer than three (zero or one) polar hydrogen atoms, (v) volume of 740-970 Å(3), (vi) solvent accessible surface area of 460-580 Å(2), and (vii) positive QikProp parameter CNS. The ranges within parentheses may be used during lead optimization. One violation to this proposed profile may be acceptable. The

  15. Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery.

    PubMed

    Ghose, Arup K; Herbertz, Torsten; Hudkins, Robert L; Dorsey, Bruce D; Mallamo, John P

    2012-01-18

    The central nervous system (CNS) is the major area that is affected by aging. Alzheimer's disease (AD), Parkinson's disease (PD), brain cancer, and stroke are the CNS diseases that will cost trillions of dollars for their treatment. Achievement of appropriate blood-brain barrier (BBB) penetration is often considered a significant hurdle in the CNS drug discovery process. On the other hand, BBB penetration may be a liability for many of the non-CNS drug targets, and a clear understanding of the physicochemical and structural differences between CNS and non-CNS drugs may assist both research areas. Because of the numerous and challenging issues in CNS drug discovery and the low success rates, pharmaceutical companies are beginning to deprioritize their drug discovery efforts in the CNS arena. Prompted by these challenges and to aid in the design of high-quality, efficacious CNS compounds, we analyzed the physicochemical property and the chemical structural profiles of 317 CNS and 626 non-CNS oral drugs. The conclusions derived provide an ideal property profile for lead selection and the property modification strategy during the lead optimization process. A list of substructural units that may be useful for CNS drug design was also provided here. A classification tree was also developed to differentiate between CNS drugs and non-CNS oral drugs. The combined analysis provided the following guidelines for designing high-quality CNS drugs: (i) topological molecular polar surface area of <76 Å(2) (25-60 Å(2)), (ii) at least one (one or two, including one aliphatic amine) nitrogen, (iii) fewer than seven (two to four) linear chains outside of rings, (iv) fewer than three (zero or one) polar hydrogen atoms, (v) volume of 740-970 Å(3), (vi) solvent accessible surface area of 460-580 Å(2), and (vii) positive QikProp parameter CNS. The ranges within parentheses may be used during lead optimization. One violation to this proposed profile may be acceptable. The

  16. Knowledge-Based, Central Nervous System (CNS) Lead Selection and Lead Optimization for CNS Drug Discovery

    PubMed Central

    2011-01-01

    The central nervous system (CNS) is the major area that is affected by aging. Alzheimer’s disease (AD), Parkinson’s disease (PD), brain cancer, and stroke are the CNS diseases that will cost trillions of dollars for their treatment. Achievement of appropriate blood–brain barrier (BBB) penetration is often considered a significant hurdle in the CNS drug discovery process. On the other hand, BBB penetration may be a liability for many of the non-CNS drug targets, and a clear understanding of the physicochemical and structural differences between CNS and non-CNS drugs may assist both research areas. Because of the numerous and challenging issues in CNS drug discovery and the low success rates, pharmaceutical companies are beginning to deprioritize their drug discovery efforts in the CNS arena. Prompted by these challenges and to aid in the design of high-quality, efficacious CNS compounds, we analyzed the physicochemical property and the chemical structural profiles of 317 CNS and 626 non-CNS oral drugs. The conclusions derived provide an ideal property profile for lead selection and the property modification strategy during the lead optimization process. A list of substructural units that may be useful for CNS drug design was also provided here. A classification tree was also developed to differentiate between CNS drugs and non-CNS oral drugs. The combined analysis provided the following guidelines for designing high-quality CNS drugs: (i) topological molecular polar surface area of <76 Å2 (25–60 Å2), (ii) at least one (one or two, including one aliphatic amine) nitrogen, (iii) fewer than seven (two to four) linear chains outside of rings, (iv) fewer than three (zero or one) polar hydrogen atoms, (v) volume of 740–970 Å3, (vi) solvent accessible surface area of 460–580 Å2, and (vii) positive QikProp parameter CNS. The ranges within parentheses may be used during lead optimization. One violation to this proposed profile may be acceptable. The

  17. On selection of the optimal data time interval for real-time hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Liu, J.; Han, D.

    2013-09-01

    With the advancement in modern telemetry and communication technologies, hydrological data can be collected with an increasingly higher sampling rate. An important issue deserving attention from the hydrological community is which suitable time interval of the model input data should be chosen in hydrological forecasting. Such a problem has long been recognised in the control engineering community but is a largely ignored topic in operational applications of hydrological forecasting. In this study, the intrinsic properties of rainfall-runoff data with different time intervals are first investigated from the perspectives of the sampling theorem and the information loss using the discrete wavelet transform tool. It is found that rainfall signals with very high sampling rates may not always improve the accuracy of rainfall-runoff modelling due to the catchment low-pass-filtering effect. To further investigate the impact of a data time interval in real-time forecasting, a real-time forecasting system is constructed by incorporating the probability distributed model (PDM) with a real-time updating scheme, the autoregressive moving-average (ARMA) model. Case studies are then carried out on four UK catchments with different concentration times for real-time flow forecasting using data with different time intervals of 15, 30, 45, 60, 90 and 120 min. A positive relation is found between the forecast lead time and the optimal choice of the data time interval, which is also highly dependent on the catchment concentration time. Finally, based on the conclusions from the case studies, a hypothetical pattern is proposed in three-dimensional coordinates to describe the general impact of the data time interval and to provide implications of the selection of the optimal time interval in real-time hydrological forecasting. Although nowadays most operational hydrological systems still have low data sampling rates (daily or hourly), the future is that higher sampling rates will become

  18. On selection of the optimal data time interval for real-time hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Liu, J.; Han, D.

    2012-09-01

    With the advancement in modern telemetry and communication technologies, hydrological data can be collected with an increasingly higher sampling rate. An important issue deserving attention from the hydrological community is what suitable time interval of the model input data should be chosen in hydrological forecasting. Such a problem has long been recognised in the control engineering community but is a largely ignored topic in operational applications of hydrological forecasting. In this study, the intrinsic properties of rainfall-runoff data with different time intervals are first investigated from the perspectives of the sampling theorem and the information loss using the discrete wavelet decomposition tool. It is found that rainfall signals with very high sampling rates may not always improve the accuracy of rainfall-runoff modelling due to the catchment low-pass filtering effect. To further investigate the impact of data time interval in real-time forecasting, a real-time forecasting system is constructed by incorporating the Probability Distributed Model (PDM) with a real-time updating scheme, the autoregressive-moving average (ARMA) model. Case studies are then carried out on four UK catchments with different concentration times for real-time flow forecasting using data with different time intervals of 15 min, 30 min, 45 min, 60 min, 90 min and 120 min. A positive relation is found between the forecast lead time and the optimal choice of the data time interval, which is also highly dependent on the catchment concentration time. Finally, based on the conclusions from the case studies, a hypothetical pattern is proposed in three-dimensional coordinates to describe the general impact of the data time interval and to provide implications on the selection of the optimal time interval in real-time hydrological forecasting. Although nowadays most operational hydrological systems still have low data sampling rates (daily or hourly), the trend in the future is that

  19. Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

    PubMed

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-07-30

    In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

  20. Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

    PubMed

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-01-01

    In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

  1. Synthesis and purification of iodoaziridines involving quantitative selection of the optimal stationary phase for chromatography.

    PubMed

    Boultwood, Tom; Affron, Dominic P; Bull, James A

    2014-05-16

    The highly diastereoselective preparation of cis-N-Ts-iodoaziridines through reaction of diiodomethyllithium with N-Ts aldimines is described. Diiodomethyllithium is prepared by the deprotonation of diiodomethane with LiHMDS, in a THF/diethyl ether mixture, at -78 °C in the dark. These conditions are essential for the stability of the LiCHI2 reagent generated. The subsequent dropwise addition of N-Ts aldimines to the preformed diiodomethyllithium solution affords an amino-diiodide intermediate, which is not isolated. Rapid warming of the reaction mixture to 0 °C promotes cyclization to afford iodoaziridines with exclusive cis-diastereoselectivity. The addition and cyclization stages of the reaction are mediated in one reaction flask by careful temperature control. Due to the sensitivity of the iodoaziridines to purification, assessment of suitable methods of purification is required. A protocol to assess the stability of sensitive compounds to stationary phases for column chromatography is described. This method is suitable to apply to new iodoaziridines, or other potentially sensitive novel compounds. Consequently this method may find application in range of synthetic projects. The procedure involves firstly the assessment of the reaction yield, prior to purification, by (1)H NMR spectroscopy with comparison to an internal standard. Portions of impure product mixture are then exposed to slurries of various stationary phases appropriate for chromatography, in a solvent system suitable as the eluent in flash chromatography. After stirring for 30 min to mimic chromatography, followed by filtering, the samples are analyzed by (1)H NMR spectroscopy. Calculated yields for each stationary phase are then compared to that initially obtained from the crude reaction mixture. The results obtained provide a quantitative assessment of the stability of the compound to the different stationary phases; hence the optimal can be selected. The choice of basic alumina, modified to

  2. Optimal selection of on-site generation with combined heat andpower applications

    SciTech Connect

    Siddiqui, Afzal S.; Marnay, Chris; Bailey, Owen; HamachiLaCommare, Kristina

    2004-11-30

    While demand for electricity continues to grow, expansion of the traditional electricity supply system, or macrogrid, is constrained and is unlikely to keep pace with the growing thirst western economies have for electricity. Furthermore, no compelling case has been made that perpetual improvement in the overall power quality and reliability (PQR)delivered is technically possible or economically desirable. An alternative path to providing high PQR for sensitive loads would generate close to them in microgrids, such as the Consortium for Electricity Reliability Technology Solutions (CERTS) Microgrid. Distributed generation would alleviate the pressure for endless improvement in macrogrid PQR and might allow the establishment of a sounder economically based level of universal grid service. Energy conversion from available fuels to electricity close to loads can also provide combined heat and power (CHP) opportunities that can significantly improve the economics of small-scale on-site power generation, especially in hot climates when the waste heat serves absorption cycle cooling equipment that displaces expensive on-peak electricity. An optimization model, the Distributed Energy Resources Customer Adoption Model (DER-CAM), developed at Berkeley Lab identifies the energy bill minimizing combination of on-site generation and heat recovery equipment for sites, given their electricity and heat requirements, the tariffs they face, and a menu of available equipment. DER-CAM is used to conduct a systemic energy analysis of a southern California naval base building and demonstrates atypical current economic on-site power opportunity. Results achieve cost reductions of about 15 percent with DER, depending on the tariff.Furthermore, almost all of the energy is provided on-site, indicating that modest cost savings can be achieved when the microgrid is free to select distributed generation and heat recovery equipment in order to minimize its over all costs.

  3. Optimal Wavelength Selection on Hyperspectral Data with Fused Lasso for Biomass Estimation of Tropical Rain Forest

    NASA Astrophysics Data System (ADS)

    Takayama, T.; Iwasaki, A.

    2016-06-01

    Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE) of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.

  4. G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies.

    PubMed

    Wang, Miaoyan; Jakobsdottir, Johanna; Smith, Albert V; McPeek, Mary Sara

    2016-09-01

    In a large-scale genetic association study, the number of phenotyped individuals available for sequencing may, in some cases, be greater than the study's sequencing budget will allow. In that case, it can be important to prioritize individuals for sequencing in a way that optimizes power for association with the trait. Suppose a cohort of phenotyped individuals is available, with some subset of them possibly already sequenced, and one wants to choose an additional fixed-size subset of individuals to sequence in such a way that the power to detect association is maximized. When the phenotyped sample includes related individuals, power for association can be gained by including partial information, such as phenotype data of ungenotyped relatives, in the analysis, and this should be taken into account when assessing whom to sequence. We propose G-STRATEGY, which uses simulated annealing to choose a subset of individuals for sequencing that maximizes the expected power for association. In simulations, G-STRATEGY performs extremely well for a range of complex disease models and outperforms other strategies with, in many cases, relative power increases of 20-40% over the next best strategy, while maintaining correct type 1 error. G-STRATEGY is computationally feasible even for large datasets and complex pedigrees. We apply G-STRATEGY to data on high-density lipoprotein and low-density lipoprotein from the AGES-Reykjavik and REFINE-Reykjavik studies, in which G-STRATEGY is able to closely approximate the power of sequencing the full sample by selecting for sequencing a only small subset of the individuals.

  5. In vitro selection of optimal DNA substrates for T4 RNA ligase

    NASA Technical Reports Server (NTRS)

    Harada, Kazuo; Orgel, Leslie E.

    1993-01-01

    We have used in vitro selection techniques to characterize DNA sequences that are ligated efficiently by T4 RNA ligase. We find that the ensemble of selected sequences ligated about 10 times as efficiently as the random mixture of sequences used as the input for selection. Surprisingly, the majority of the selected sequences approximated a well-defined consensus sequence.

  6. Optimizing candidate selection--a vision in business limited conference. 1-2 December 1998, Basel, Switzerland.

    PubMed

    Audus, K L

    1999-02-01

    The pharmaceutical industry is faced with filtering hundreds of thousands of compounds to identify successful drug candidates. Given these numbers, how does the pharmaceutical industry identify optimal therapeutic agents rapidly, efficiently, economically and successfully, with the ultimate result of the patient receiving the best drug? The conference summarized the present and future requirements for evaluating emerging technologies, integrating that technology into a filter for large and growing numbers of compounds, building and linking diverse knowledge bases, and establishing predictive foundations that will optimize and accelerate drug discovery and development. Specific conference topics focused on organizational and management approaches as well as some of the major technologies and emerging techniques for supporting drug candidate selection and optimization. It is predicted that the pharmaceutical industry will be synthesizing and screening a million or more compounds for multiple therapeutic targets in the near future. Pulling together the resources of current and emerging technology, knowledge, and multidisciplinary teamwork, so that discovery and selection of successful drug candidates from this large pool of compounds can take place rapidly, is a significant challenge. This conference focused on the organizational issues and experimental tools that can provide for a shortening of discovery time, identification of current and future selection techniques and criteria, the linking of technologies and business strategies to reduce risk, and novel processes for optimizing candidates more quickly and efficiently. The conference was directed at industrial scientists involved in all stages along the drug discovery and development interface. This conference was well-attended, with approximately 100 participants.

  7. Optimal contribution selection applied to the Norwegian and the North-Swedish cold-blooded trotter - a feasibility study.

    PubMed

    Olsen, H F; Meuwissen, T; Klemetsdal, G

    2013-06-01

    The aim of this study was to examine how to apply optimal contribution selection (OCS) in the Norwegian and the North-Swedish cold-blooded trotter and give practical recommendations for the future. OCS was implemented using the software Gencont with overlapping generations and selected a few, but young sires, as these turn over the generations faster and thus is less related to the mare candidates. In addition, a number of Swedish sires were selected as they were less related to the selection candidates. We concluded that implementing OCS is feasible to select sires (there is no selection on mares), and we recommend the number of available sire candidates to be continuously updated because of amongst others deaths and geldings. In addition, only considering sire candidates with phenotype above average within a year class would allow selection candidates from many year classes to be included and circumvent current limitation on number of selection candidates in Gencont (approx. 3000). The results showed that mare candidates can well be those being mated the previous year. OCS will, dynamically, recruit young stallions and manage the culling or renewal of annual breeding permits for stallions that had been previously approved. For the annual mating proportion per sire, a constraint in accordance with the maximum that a sire can mate naturally is recommended. PMID:23679942

  8. Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

    PubMed

    Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

    2015-10-01

    In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

  9. Selection of appropriate training and validation set chemicals for modelling dermal permeability by U-optimal design.

    PubMed

    Xu, G; Hughes-Oliver, J M; Brooks, J D; Yeatts, J L; Baynes, R E

    2013-01-01

    Quantitative structure-activity relationship (QSAR) models are being used increasingly in skin permeation studies. The main idea of QSAR modelling is to quantify the relationship between biological activities and chemical properties, and thus to predict the activity of chemical solutes. As a key step, the selection of a representative and structurally diverse training set is critical to the prediction power of a QSAR model. Early QSAR models selected training sets in a subjective way and solutes in the training set were relatively homogenous. More recently, statistical methods such as D-optimal design or space-filling design have been applied but such methods are not always ideal. This paper describes a comprehensive procedure to select training sets from a large candidate set of 4534 solutes. A newly proposed 'Baynes' rule', which is a modification of Lipinski's 'rule of five', was used to screen out solutes that were not qualified for the study. U-optimality was used as the selection criterion. A principal component analysis showed that the selected training set was representative of the chemical space. Gas chromatograph amenability was verified. A model built using the training set was shown to have greater predictive power than a model built using a previous dataset [1].

  10. Discovery of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1: optimization of kinase selectivity and pharmacokinetics.

    PubMed

    Hornberger, Keith R; Chen, Xin; Crew, Andrew P; Kleinberg, Andrew; Ma, Lifu; Mulvihill, Mark J; Wang, Jing; Wilde, Victoria L; Albertella, Mark; Bittner, Mark; Cooke, Andrew; Kadhim, Salam; Kahler, Jennifer; Maresca, Paul; May, Earl; Meyn, Peter; Romashko, Darlene; Tokar, Brianna; Turton, Roy

    2013-08-15

    The kinase selectivity and pharmacokinetic optimization of a series of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1 is described. The intersection of insights from molecular modeling, computational prediction of metabolic sites, and in vitro metabolite identification studies resulted in a simple and unique solution to both of these problems. These efforts culminated in the discovery of compound 13a, a potent, relatively selective inhibitor of TAK1 with good pharmacokinetic properties in mice, which was active in an in vivo model of ovarian cancer. PMID:23856049

  11. Discovery of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1: optimization of kinase selectivity and pharmacokinetics.

    PubMed

    Hornberger, Keith R; Chen, Xin; Crew, Andrew P; Kleinberg, Andrew; Ma, Lifu; Mulvihill, Mark J; Wang, Jing; Wilde, Victoria L; Albertella, Mark; Bittner, Mark; Cooke, Andrew; Kadhim, Salam; Kahler, Jennifer; Maresca, Paul; May, Earl; Meyn, Peter; Romashko, Darlene; Tokar, Brianna; Turton, Roy

    2013-08-15

    The kinase selectivity and pharmacokinetic optimization of a series of 7-aminofuro[2,3-c]pyridine inhibitors of TAK1 is described. The intersection of insights from molecular modeling, computational prediction of metabolic sites, and in vitro metabolite identification studies resulted in a simple and unique solution to both of these problems. These efforts culminated in the discovery of compound 13a, a potent, relatively selective inhibitor of TAK1 with good pharmacokinetic properties in mice, which was active in an in vivo model of ovarian cancer.

  12. High-Efficiency Nonfullerene Polymer Solar Cell Enabling by Integration of Film-Morphology Optimization, Donor Selection, and Interfacial Engineering.

    PubMed

    Zhang, Xin; Li, Weiping; Yao, Jiannian; Zhan, Chuanlang

    2016-06-22

    Carrier mobility is a vital factor determining the electrical performance of organic solar cells. In this paper we report that a high-efficiency nonfullerene organic solar cell (NF-OSC) with a power conversion efficiency of 6.94 ± 0.27% was obtained by optimizing the hole and electron transportations via following judicious selection of polymer donor and engineering of film-morphology and cathode interlayers: (1) a combination of solvent annealing and solvent vapor annealing optimizes the film morphology and hence both hole and electron mobilities, leading to a trade-off of fill factor and short-circuit current density (Jsc); (2) the judicious selection of polymer donor affords a higher hole and electron mobility, giving a higher Jsc; and (3) engineering the cathode interlayer affords a higher electron mobility, which leads to a significant increase in electrical current generation and ultimately the power conversion efficiency (PCE). PMID:27246160

  13. High-Efficiency Nonfullerene Polymer Solar Cell Enabling by Integration of Film-Morphology Optimization, Donor Selection, and Interfacial Engineering.

    PubMed

    Zhang, Xin; Li, Weiping; Yao, Jiannian; Zhan, Chuanlang

    2016-06-22

    Carrier mobility is a vital factor determining the electrical performance of organic solar cells. In this paper we report that a high-efficiency nonfullerene organic solar cell (NF-OSC) with a power conversion efficiency of 6.94 ± 0.27% was obtained by optimizing the hole and electron transportations via following judicious selection of polymer donor and engineering of film-morphology and cathode interlayers: (1) a combination of solvent annealing and solvent vapor annealing optimizes the film morphology and hence both hole and electron mobilities, leading to a trade-off of fill factor and short-circuit current density (Jsc); (2) the judicious selection of polymer donor affords a higher hole and electron mobility, giving a higher Jsc; and (3) engineering the cathode interlayer affords a higher electron mobility, which leads to a significant increase in electrical current generation and ultimately the power conversion efficiency (PCE).

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

    PubMed

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

    2010-07-01

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

  15. Growth Optimal Portfolio Selection Under Proportional Transaction Costs with Obligatory Diversification

    SciTech Connect

    Duncan, T. Pasik Duncan, B.; Stettner, L.

    2011-02-15

    A continuous time long run growth optimal or optimal logarithmic utility portfolio with proportional transaction costs consisting of a fixed proportional cost and a cost proportional to the volume of transaction is considered. The asset prices are modeled as exponent of diffusion with jumps whose parameters depend on a finite state Markov process of economic factors. An obligatory portfolio diversification is introduced, accordingly to which it is required to invest at least a fixed small portion of our wealth in each asset.

  16. The Why of Waiting: How mathematical Best-Choice Models demonstrate optimality of a Refractory Period in Habitat Selection

    NASA Astrophysics Data System (ADS)

    Brugger, M. F.; Waymire, E. C.; Betts, M. G.

    2010-12-01

    When brush mice, fruit flies, and other animals disperse from their natal site, they are immediately tasked with selecting new habitat, and must do so in such a way as to optimize their chances of surviving and breeding. Habitat selection connects the fields of behavioral ecology and landscape ecology by describing the role the physical quality of habitat plays in the selection process. Interestingly, observations indicate a strategy that occurs with a certain prescribed statistical regularity. It has been demonstrated (Stamps, Davis, Blozis, Boundy-Mills, Anim. Behav., 2007) that brush mice and fruit flies employ a refractory period: a period wherein a disperser, after leaving its natal site, will not accept highly-preferred natural habitats. Assuming this behavior has adaptive benefit, the apparent optimality of this strategy is mirrored in mathematical models of Stochastic Optimization. In one such model, the Classical Best Choice Problem, a selector views some permutation of the numbers {1, ..., n} one-by-one, seeing only their relative ranks and then either selecting that element or discarding it. The goal is to choose the ``n" element. The optimal strategy is to wait for the ⌈ n/e ⌉ th element and then pick an element if it is better than all those already seen; this might demonstrate why refractory periods have adaptive benefit. We present three extensions to the Best Choice Problem: a partial ordering on the set of elements (Kubicki & Morayne, SIAM J. Discrete Math., 2005), a new goal of minimizing the expected rank (Chow, Moriguti, Robbins, Samuels, Israel J. Math., 1964), and a general utility function (Gusein-Zade, Theory of Prob. and Applications, 1966), allowing the top r sites to be equally desirable. These extensions relate to ecological phenomena not represented by the Classical Problem. In each, we discuss the effect on the duration or existence of the Refractory Period.

  17. Algorithms for selecting breakpoint locations to optimize diversity in protein engineering by site-directed protein recombination.

    PubMed

    Zheng, Wei; Ye, Xiaoduan; Friedman, Alan M; Bailey-Kellogg, Chris

    2007-01-01

    Protein engineering by site-directed recombination seeks to develop proteins with new or improved function, by accumulating multiple mutations from a set of homologous parent proteins. A library of hybrid proteins is created by recombining the parent proteins at specified breakpoint locations; subsequent screening/selection identifies hybrids with desirable functional characteristics. In order to improve the frequency of generating novel hybrids, this paper develops the first approach to explicitly plan for diversity in site-directed recombination, including metrics for characterizing the diversity of a planned hybrid library and efficient algorithms for optimizing experiments accordingly. The goal is to choose breakpoint locations to sample sequence space as uniformly as possible (which we argue maximizes diversity), under the constraints imposed by the recombination process and the given set of parents. A dynamic programming approach selects optimal breakpoint locations in polynomial time. Application of our method to optimizing breakpoints for an example biosynthetic enzyme, purE, demonstrates the significance of diversity optimization and the effectiveness of our algorithms.

  18. Quantitative and qualitative optimization of allergen extraction from peanut and selected tree nuts. Part 1. Screening of optimal extraction conditions using a D-optimal experimental design.

    PubMed

    L'Hocine, Lamia; Pitre, Mélanie

    2016-03-01

    A D-optimal design was constructed to optimize allergen extraction efficiency simultaneously from roasted, non-roasted, defatted, and non-defatted almond, hazelnut, peanut, and pistachio flours using three non-denaturing aqueous (phosphate, borate, and carbonate) buffers at various conditions of ionic strength, buffer-to-protein ratio, extraction temperature, and extraction duration. Statistical analysis showed that roasting and non-defatting significantly lowered protein recovery for all nuts. Increasing the temperature and the buffer-to-protein ratio during extraction significantly increased protein recovery, whereas increasing the extraction time had no significant impact. The impact of the three buffers on protein recovery varied significantly among the nuts. Depending on the extraction conditions, protein recovery varied from 19% to 95% for peanut, 31% to 73% for almond, 17% to 64% for pistachio, and 27% to 88% for hazelnut. A modulation by the buffer type and ionic strength of protein and immunoglobuline E binding profiles of extracts was evidenced, where high protein recovery levels did not always correlate with high immunoreactivity.

  19. Quantitative and qualitative optimization of allergen extraction from peanut and selected tree nuts. Part 1. Screening of optimal extraction conditions using a D-optimal experimental design.

    PubMed

    L'Hocine, Lamia; Pitre, Mélanie

    2016-03-01

    A D-optimal design was constructed to optimize allergen extraction efficiency simultaneously from roasted, non-roasted, defatted, and non-defatted almond, hazelnut, peanut, and pistachio flours using three non-denaturing aqueous (phosphate, borate, and carbonate) buffers at various conditions of ionic strength, buffer-to-protein ratio, extraction temperature, and extraction duration. Statistical analysis showed that roasting and non-defatting significantly lowered protein recovery for all nuts. Increasing the temperature and the buffer-to-protein ratio during extraction significantly increased protein recovery, whereas increasing the extraction time had no significant impact. The impact of the three buffers on protein recovery varied significantly among the nuts. Depending on the extraction conditions, protein recovery varied from 19% to 95% for peanut, 31% to 73% for almond, 17% to 64% for pistachio, and 27% to 88% for hazelnut. A modulation by the buffer type and ionic strength of protein and immunoglobuline E binding profiles of extracts was evidenced, where high protein recovery levels did not always correlate with high immunoreactivity. PMID:26471618

  20. Optimization of 2-phenylcyclopropylmethylamines as selective serotonin 2C receptor agonists and their evaluation as potential antipsychotic agents.

    PubMed

    Cheng, Jianjun; Giguère, Patrick M; Onajole, Oluseye K; Lv, Wei; Gaisin, Arsen; Gunosewoyo, Hendra; Schmerberg, Claire M; Pogorelov, Vladimir M; Rodriguiz, Ramona M; Vistoli, Giulio; Wetsel, William C; Roth, Bryan L; Kozikowski, Alan P

    2015-02-26

    The discovery of a new series of compounds that are potent, selective 5-HT2C receptor agonists is described herein as we continue our efforts to optimize the 2-phenylcyclopropylmethylamine scaffold. Modifications focused on the alkoxyl substituent present on the aromatic ring led to the identification of improved ligands with better potency at the 5-HT2C receptor and excellent selectivity against the 5-HT2A and 5-HT2B receptors. ADMET studies coupled with a behavioral test using the amphetamine-induced hyperactivity model identified four compounds possessing drug-like profiles and having antipsychotic properties. Compound (+)-16b, which displayed an EC50 of 4.2 nM at 5-HT2C, no activity at 5-HT2B, and an 89-fold selectivity against 5-HT2A, is one of the most potent and selective 5-HT2C agonists reported to date. The likely binding mode of this series of compounds to the 5-HT2C receptor was also investigated in a modeling study, using optimized models incorporating the structures of β2-adrenergic receptor and 5-HT2B receptor. PMID:25633969

  1. Design and optimization of a multi-element piezoelectric transducer for mode-selective generation of guided waves

    NASA Astrophysics Data System (ADS)

    Yazdanpanah Moghadam, Peyman; Quaegebeur, Nicolas; Masson, Patrice

    2016-07-01

    A novel multi-element piezoelectric transducers (MEPT) is designed, optimized, machined and experimentally tested to improve structural health monitoring systems for mode-selective generation of guided waves (GW) in an isotropic structure. GW generation using typical piezoceramics makes the signal processing and consequently damage detection very complicated because at any driving frequency at least two fundamental symmetric (S 0) and antisymmetric (A 0) modes are generated. To prevent this, mode selective transducer design is proposed based on MEPT. A numerical method is first developed to extract the interfacial stress between a single piezoceramic element and a host structure and then used as the input of an analytical model to predict the GW propagation through the thickness of an isotropic plate. Two novel objective functions are proposed to optimize the interfacial shear stress for both suppressing unwanted mode(s) and maximizing the desired mode. Simplicity and low manufacturing cost are two main targets driving the design of the MEPT. A prototype MEPT is then manufactured using laser micro-machining. An experimental procedure is presented to validate the performances of the MEPT as a new solution for mode-selective GW generation. Experimental tests illustrate the high capability of the MEPT for mode-selective GW generation, as unwanted mode is suppressed by a factor up to 170 times compared with the results obtained with a single piezoceramic.

  2. Improvement of olfactometric measurement accuracy and repeatability by optimization of panel selection procedures.

    PubMed

    Capelli, L; Sironi, S; Del Rosso, R; Céntola, P; Bonati, S

    2010-01-01

    The EN 13725:2003, which standardizes the determination of odour concentration by dynamic olfactometry, fixes the limits for panel selection in terms of individual threshold towards a reference gas (n-butanol in nitrogen) and of standard deviation of the responses. Nonetheless, laboratories have some degrees of freedom in developing their own procedures for panel selection and evaluation. Most Italian olfactometric laboratories use a similar procedure for panel selection, based on the repeated analysis of samples of n-butanol at a concentration of 60 ppm. The first part of this study demonstrates that this procedure may originate a sort of "smartening" of the assessors, which means that they become able to guess the right answers in order to maintain their qualification as panel members, independently from their real olfactory perception. For this reason, the panel selection procedure has been revised with the aim of making it less repetitive, therefore preventing the possibility for panel members to be able to guess the best answers in order to comply with the selection criteria. The selection of new panel members and the screening of the active ones according to this revised procedure proved this new procedure to be more selective than the "standard" one. Finally, the results of the tests with n-butanol conducted after the introduction of the revised procedure for panel selection and regular verification showed an effective improvement of the laboratory measurement performances in terms of accuracy and precision.

  3. Improvement of olfactometric measurement accuracy and repeatability by optimization of panel selection procedures.

    PubMed

    Capelli, L; Sironi, S; Del Rosso, R; Céntola, P; Bonati, S

    2010-01-01

    The EN 13725:2003, which standardizes the determination of odour concentration by dynamic olfactometry, fixes the limits for panel selection in terms of individual threshold towards a reference gas (n-butanol in nitrogen) and of standard deviation of the responses. Nonetheless, laboratories have some degrees of freedom in developing their own procedures for panel selection and evaluation. Most Italian olfactometric laboratories use a similar procedure for panel selection, based on the repeated analysis of samples of n-butanol at a concentration of 60 ppm. The first part of this study demonstrates that this procedure may originate a sort of "smartening" of the assessors, which means that they become able to guess the right answers in order to maintain their qualification as panel members, independently from their real olfactory perception. For this reason, the panel selection procedure has been revised with the aim of making it less repetitive, therefore preventing the possibility for panel members to be able to guess the best answers in order to comply with the selection criteria. The selection of new panel members and the screening of the active ones according to this revised procedure proved this new procedure to be more selective than the "standard" one. Finally, the results of the tests with n-butanol conducted after the introduction of the revised procedure for panel selection and regular verification showed an effective improvement of the laboratory measurement performances in terms of accuracy and precision. PMID:20220249

  4. Optimization of breast mass classification using sequential forward floating selection (SFFS) and a support vector machine (SVM) model

    PubMed Central

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-01-01

    Purpose: Improving radiologists’ performance in classification between malignant and benign breast lesions is important to increase cancer detection sensitivity and reduce false-positive recalls. For this purpose, developing computer-aided diagnosis (CAD) schemes has been attracting research interest in recent years. In this study, we investigated a new feature selection method for the task of breast mass classification. Methods: We initially computed 181 image features based on mass shape, spiculation, contrast, presence of fat or calcifications, texture, isodensity, and other morphological features. From this large image feature pool, we used a sequential forward floating selection (SFFS)-based feature selection method to select relevant features, and analyzed their performance using a support vector machine (SVM) model trained for the classification task. On a database of 600 benign and 600 malignant mass regions of interest (ROIs), we performed the study using a ten-fold cross-validation method. Feature selection and optimization of the SVM parameters were conducted on the training subsets only. Results: The area under the receiver operating characteristic curve (AUC) = 0.805±0.012 was obtained for the classification task. The results also showed that the most frequently-selected features by the SFFS-based algorithm in 10-fold iterations were those related to mass shape, isodensity and presence of fat, which are consistent with the image features frequently used by radiologists in the clinical environment for mass classification. The study also indicated that accurately computing mass spiculation features from the projection mammograms was difficult, and failed to perform well for the mass classification task due to tissue overlap within the benign mass regions. Conclusions: In conclusion, this comprehensive feature analysis study provided new and valuable information for optimizing computerized mass classification schemes that may have potential to be

  5. A Conceptual Framework for Procurement Decision Making Model to Optimize Supplier Selection: The Case of Malaysian Construction Industry

    NASA Astrophysics Data System (ADS)

    Chuan, Ngam Min; Thiruchelvam, Sivadass; Nasharuddin Mustapha, Kamal; Che Muda, Zakaria; Mat Husin, Norhayati; Yong, Lee Choon; Ghazali, Azrul; Ezanee Rusli, Mohd; Itam, Zarina Binti; Beddu, Salmia; Liyana Mohd Kamal, Nur

    2016-03-01

    This paper intends to fathom the current state of procurement system in Malaysia specifically in the construction industry in the aspect of supplier selection. This paper propose a comprehensive study on the supplier selection metrics for infrastructure building, weight the importance of each metrics assigned and to find the relationship between the metrics among initiators, decision makers, buyers and users. With the metrics hierarchy of criteria importance, a supplier selection process can be defined, repeated and audited with lesser complications or difficulties. This will help the field of procurement to improve as this research is able to develop and redefine policies and procedures that have been set in supplier selection. Developing this systematic process will enable optimization of supplier selection and thus increasing the value for every stakeholders as the process of selection is greatly simplified. With a new redefined policy and procedure, it does not only increase the company’s effectiveness and profit, but also make it available for the company to reach greater heights in the advancement of procurement in Malaysia.

  6. Optimization of fermentation parameters to study the behavior of selected lactic cultures on soy solid state fermentation.

    PubMed

    Rodríguez de Olmos, A; Bru, E; Garro, M S

    2015-03-01

    The use of solid fermentation substrate (SSF) has been appreciated by the demand for natural and healthy products. Lactic acid bacteria and bifidobacteria play a leading role in the production of novel functional foods and their behavior is practically unknown in these systems. Soy is an excellent substrate for the production of functional foods for their low cost and nutritional value. The aim of this work was to optimize different parameters involved in solid state fermentation (SSF) using selected lactic cultures to improve soybean substrate as a possible strategy for the elaboration of new soy food with enhanced functional and nutritional properties. Soy flour and selected lactic cultures were used under different conditions to optimize the soy SSF. The measured responses were bacterial growth, free amino acids and β-glucosidase activity, which were analyzed by applying response surface methodology. Based on the proposed statistical model, different fermentation conditions were raised by varying the moisture content (50-80%) of the soy substrate and temperature of incubation (31-43°C). The effect of inoculum amount was also investigated. These studies demonstrated the ability of selected strains (Lactobacillus paracasei subsp. paracasei and Bifidobacterium longum) to grow with strain-dependent behavior on the SSF system. β-Glucosidase activity was evident in both strains and L. paracasei subsp. paracasei was able to increase the free amino acids at the end of fermentation under assayed conditions. The used statistical model has allowed the optimization of fermentation parameters on soy SSF by selected lactic strains. Besides, the possibility to work with lower initial bacterial amounts to obtain results with significant technological impact was demonstrated.

  7. Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

    PubMed

    Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

    2015-12-01

    The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also for calcification CAD systems which are currently deployed for clinical use. This paper tackles two problems related to reducing the number of false positives in the detection of all lesions and masses, respectively. Firstly, textural patterns of breast tissue have been analyzed using several multi-scale textural descriptors based on wavelet and gray level co-occurrence matrix. The second problem addressed in this paper is the parameter selection and performance optimization. For this, we adopt a model selection procedure based on Particle Swarm Optimization (PSO) for selecting the most discriminative textural features and for strengthening the generalization capacity of the supervised learning stage based on a Support Vector Machine (SVM) classifier. For evaluating the proposed methods, two sets of suspicious mammogram regions have been used. The first one, obtained from Digital Database for Screening Mammography (DDSM), contains 1494 regions (1000 normal and 494 abnormal samples). The second set of suspicious regions was obtained from database of Mammographic Image Analysis Society (mini-MIAS) and contains 315 (207 normal and 108 abnormal) samples. Results from both datasets demonstrate the efficiency of using PSO based model selection for optimizing both classifier hyper-parameters and parameters, respectively. Furthermore, the obtained results indicate the promising performance of the proposed textural features and more specifically, those based on co-occurrence matrix of wavelet image representation technique. PMID:25795630

  8. Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

    PubMed

    Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

    2015-12-01

    The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also for calcification CAD systems which are currently deployed for clinical use. This paper tackles two problems related to reducing the number of false positives in the detection of all lesions and masses, respectively. Firstly, textural patterns of breast tissue have been analyzed using several multi-scale textural descriptors based on wavelet and gray level co-occurrence matrix. The second problem addressed in this paper is the parameter selection and performance optimization. For this, we adopt a model selection procedure based on Particle Swarm Optimization (PSO) for selecting the most discriminative textural features and for strengthening the generalization capacity of the supervised learning stage based on a Support Vector Machine (SVM) classifier. For evaluating the proposed methods, two sets of suspicious mammogram regions have been used. The first one, obtained from Digital Database for Screening Mammography (DDSM), contains 1494 regions (1000 normal and 494 abnormal samples). The second set of suspicious regions was obtained from database of Mammographic Image Analysis Society (mini-MIAS) and contains 315 (207 normal and 108 abnormal) samples. Results from both datasets demonstrate the efficiency of using PSO based model selection for optimizing both classifier hyper-parameters and parameters, respectively. Furthermore, the obtained results indicate the promising performance of the proposed textural features and more specifically, those based on co-occurrence matrix of wavelet image representation technique.

  9. Optimization of fermentation parameters to study the behavior of selected lactic cultures on soy solid state fermentation.

    PubMed

    Rodríguez de Olmos, A; Bru, E; Garro, M S

    2015-03-01

    The use of solid fermentation substrate (SSF) has been appreciated by the demand for natural and healthy products. Lactic acid bacteria and bifidobacteria play a leading role in the production of novel functional foods and their behavior is practically unknown in these systems. Soy is an excellent substrate for the production of functional foods for their low cost and nutritional value. The aim of this work was to optimize different parameters involved in solid state fermentation (SSF) using selected lactic cultures to improve soybean substrate as a possible strategy for the elaboration of new soy food with enhanced functional and nutritional properties. Soy flour and selected lactic cultures were used under different conditions to optimize the soy SSF. The measured responses were bacterial growth, free amino acids and β-glucosidase activity, which were analyzed by applying response surface methodology. Based on the proposed statistical model, different fermentation conditions were raised by varying the moisture content (50-80%) of the soy substrate and temperature of incubation (31-43°C). The effect of inoculum amount was also investigated. These studies demonstrated the ability of selected strains (Lactobacillus paracasei subsp. paracasei and Bifidobacterium longum) to grow with strain-dependent behavior on the SSF system. β-Glucosidase activity was evident in both strains and L. paracasei subsp. paracasei was able to increase the free amino acids at the end of fermentation under assayed conditions. The used statistical model has allowed the optimization of fermentation parameters on soy SSF by selected lactic strains. Besides, the possibility to work with lower initial bacterial amounts to obtain results with significant technological impact was demonstrated. PMID:25498472

  10. Selecting Segmental Errors in Non-Native Dutch for Optimal Pronunciation Training

    ERIC Educational Resources Information Center

    Neri, Ambra; Cucchiarini, Catia; Strik, Helmer

    2006-01-01

    The current emphasis in second language teaching lies in the achievement of communicative effectiveness. In line with this approach, pronunciation training is nowadays geared towards helping learners avoid serious pronunciation errors, rather than eradicating the finest traces of foreign accent. However, to devise optimal pronunciation training…

  11. Item Selection for the Development of Short Forms of Scales Using an Ant Colony Optimization Algorithm

    ERIC Educational Resources Information Center

    Leite, Walter L.; Huang, I-Chan; Marcoulides, George A.

    2008-01-01

    This article presents the use of an ant colony optimization (ACO) algorithm for the development of short forms of scales. An example 22-item short form is developed for the Diabetes-39 scale, a quality-of-life scale for diabetes patients, using a sample of 265 diabetes patients. A simulation study comparing the performance of the ACO algorithm and…

  12. A Preliminary Evaluation of an Optimizing Technique for Use in Selecting New School Locations.

    ERIC Educational Resources Information Center

    Hall, Fred L.

    During the past two decades, mathematical programing techniques have been widely utilized in the private sector for optimization studies in locating industrial plants, scheduling commodity flows, determining product mix, etc. However, their use in the public sector has been less extensive, partly because of the absence of a clear-cut profit motive…

  13. Optimal sensor selection for noisy binary detection in stochastic pooling networks

    NASA Astrophysics Data System (ADS)

    McDonnell, Mark D.; Li, Feng; Amblard, P.-O.; Grant, Alex J.

    2013-08-01

    Stochastic Pooling Networks (SPNs) are a useful model for understanding and explaining how naturally occurring encoding of stochastic processes can occur in sensor systems ranging from macroscopic social networks to neuron populations and nanoscale electronics. Due to the interaction of nonlinearity, random noise, and redundancy, SPNs support various unexpected emergent features, such as suprathreshold stochastic resonance, but most existing mathematical results are restricted to the simplest case where all sensors in a network are identical. Nevertheless, numerical results on information transmission have shown that in the presence of independent noise, the optimal configuration of a SPN is such that there should be partial heterogeneity in sensor parameters, such that the optimal solution includes clusters of identical sensors, where each cluster has different parameter values. In this paper, we consider a SPN model of a binary hypothesis detection task and show mathematically that the optimal solution for a specific bound on detection performance is also given by clustered heterogeneity, such that measurements made by sensors with identical parameters either should all be excluded from the detection decision or all included. We also derive an algorithm for numerically finding the optimal solution and illustrate its utility with several examples, including a model of parallel sensory neurons with Poisson firing characteristics.

  14. Wind data for wind driven plant. [site selection for optimal performance

    NASA Technical Reports Server (NTRS)

    Stodhart, A. H.

    1973-01-01

    Simple, averaged wind velocity data provide information on energy availability, facilitate generator site selection and enable appropriate operating ranges to be established for windpowered plants. They also provide a basis for the prediction of extreme wind speeds.

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

    USGS Publications Warehouse

    Stohlgren, Thomas J.; Kumar, Sunil; Barnett, David T.; Evangelista, Paul H.

    2011-01-01

    Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

  16. Optimizing the selection process of yeast starter cultures by preselecting strains dominating spontaneous fermentations.

    PubMed

    Pulvirenti, Andrea; Rainieri, Sandra; Boveri, Silvio; Giudici, Paolo

    2009-03-01

    We propose an efficient and time-saving strategy for starter culture selection. Our approach is based on the accomplishment of 3 phases: (i) the selection of yeast strains dominating spontaneous fermentations, (ii) the selection among the dominant strains of those showing the best technological characteristics, and (iii) the final selection among good technological strains of those showing the desired qualitative traits. We applied this approach to wine fermentations, even though the same strategy has the potential to be employed for the selection of any type of starter culture. We isolated and identified yeast strains at the mid- and final stages of 6 spontaneous fermentations carried out in 3 different Spanish wineries. We identified all strains as Saccharomyces cerevisiae by restriction fragment length polymorphism of the ribosomal DNA internal transcribed spacer region, and subsequently distinguished each strain by analyzing the polymorphism of the inter-delta regions. Strains that were detected both at the mid- and final stages of the fermentation were considered dominant. Four dominant strains were finally selected and tested in pilot-scale fermentation, and their performance was compared with that of a commercial wine strain. All dominant strains showed good fitness and resulted suitable to be employed as starter cultures. One of the dominant strains isolated in this study is currently commercialized.

  17. A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.

    PubMed

    Tsai, Jason S-H; Hsu, Wen-Teng; Lin, Long-Guei; Guo, Shu-Mei; Tann, Joseph W

    2014-01-01

    A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input-output direct transmission term, which also has measurement and system noises and inaccessible system states. Besides, an effective state space self-turner with fault tolerance scheme is presented for the unknown multivariable stochastic system. A quantitative criterion is suggested by comparing the innovation process error estimated by the Kalman filter estimation algorithm, so that a weighting matrix resetting technique by adjusting and resetting the covariance matrices of parameter estimate obtained by the Kalman filter estimation algorithm is utilized to achieve the parameter estimation for faulty system recovery. Consequently, the proposed method can effectively cope with partially abrupt and/or gradual system faults and input failures by the fault detection.

  18. Optimizing the science of drug development: opportunities for better candidate selection and accelerated evaluation in humans.

    PubMed

    Lesko, L J; Rowland, M; Peck, C C; Blaschke, T F

    2000-08-01

    Two international meetings were convened in 1998 to review the current science of drug development and the potential opportunities to optimize the evaluation of new drugs in humans. This report represents a synopsis of these meetings, and focuses on the current state of knowledge pertaining to drug development, future scientific and technical needs, and the relative merits of various strategies intended to accelerate the clinical development of drugs. PMID:10934664

  19. Responding to home maintenance challenge scenarios: the role of selection, optimization, and compensation in aging-in-place.

    PubMed

    Kelly, Andrew John; Fausset, Cara Bailey; Rogers, Wendy; Fisk, Arthur D

    2014-12-01

    This study examined potential issues faced by older adults in managing their homes and their proposed solutions for overcoming hypothetical difficulties. Forty-four diverse, independently living older adults (66-85) participated in structured group interviews in which they discussed potential solutions to manage difficulties presented in four scenarios: perceptual, mobility, physical, and cognitive difficulties. The proposed solutions were classified using the Selection, Optimization, and Compensation (SOC) model. Participants indicated they would continue performing most tasks and reported a range of strategies to manage home maintenance challenges. Most participants reported that they would manage home maintenance challenges using compensation; the most frequently mentioned compensation strategy was using tools and technologies. There were also differences across the scenarios: Optimization was discussed most frequently with perceptual and cognitive difficulty scenarios. These results provide insights into supporting older adults' potential needs for aging-in-place and provide evidence of the value of the SOC model in applied research.

  20. Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains

    USGS Publications Warehouse

    Gu, Y.; Howard, D.M.; Wylie, B.K.; Zhang, L.

    2012-01-01

    Flux tower networks (e. g., AmeriFlux, Agriflux) provide continuous observations of ecosystem exchanges of carbon (e. g., net ecosystem exchange), water vapor (e. g., evapotranspiration), and energy between terrestrial ecosystems and the atmosphere. The long-term time series of flux tower data are essential for studying and understanding terrestrial carbon cycles, ecosystem services, and climate changes. Currently, there are 13 flux towers located within the Great Plains (GP). The towers are sparsely distributed and do not adequately represent the varieties of vegetation cover types, climate conditions, and geophysical and biophysical conditions in the GP. This study assessed how well the available flux towers represent the environmental conditions or "ecological envelopes" across the GP and identified optimal locations for future flux towers in the GP. Regression-based remote sensing and weather-driven net ecosystem production (NEP) models derived from different extrapolation ranges (10 and 50%) were used to identify areas where ecological conditions were poorly represented by the flux tower sites and years previously used for mapping grassland fluxes. The optimal lands suitable for future flux towers within the GP were mapped. Results from this study provide information to optimize the usefulness of future flux towers in the GP and serve as a proxy for the uncertainty of the NEP map.

  1. Radar Tracking Waveform Design in Continuous Space and Optimization Selection Using Differential Evolution

    NASA Astrophysics Data System (ADS)

    Paul, Bryan

    Waveform design that allows for a wide variety of frequency-modulation (FM) has proven benefits. However, dictionary based optimization is limited and gradient search methods are often intractable. A new method is proposed using differential evolution to design waveforms with instantaneous frequencies (IFs) with cubic FM functions whose coefficients are constrained to the surface of the three dimensional unit sphere. Cubic IF functions subsume well-known IF functions such as linear, quadratic monomial, and cubic monomial IF functions. In addition, all nonlinear IF functions sufficiently approximated by a third order Taylor series over the unit time sequence can be represented in this space. Analog methods for generating polynomial IF waveforms are well established allowing for practical implementation in real world systems. By sufficiently constraining the search space to these waveforms of interest, alternative optimization methods such as differential evolution can be used to optimize tracking performance in a variety of radar environments. While simplified tracking models and finite waveform dictionaries have information theoretic results, continuous waveform design in high SNR, narrowband, cluttered environments is explored.

  2. Selecting Observation Platforms for Optimized Anomaly Detectability under Unreliable Partial Observations

    SciTech Connect

    Wen-Chiao Lin; Humberto E. Garcia; Tae-Sic Yoo

    2011-06-01

    Diagnosers for keeping track on the occurrences of special events in the framework of unreliable partially observed discrete-event dynamical systems were developed in previous work. This paper considers observation platforms consisting of sensors that provide partial and unreliable observations and of diagnosers that analyze them. Diagnosers in observation platforms typically perform better as sensors providing the observations become more costly or increase in number. This paper proposes a methodology for finding an observation platform that achieves an optimal balance between cost and performance, while satisfying given observability requirements and constraints. Since this problem is generally computational hard in the framework considered, an observation platform optimization algorithm is utilized that uses two greedy heuristics, one myopic and another based on projected performances. These heuristics are sequentially executed in order to find best observation platforms. The developed algorithm is then applied to an observation platform optimization problem for a multi-unit-operation system. Results show that improved observation platforms can be found that may significantly reduce the observation platform cost but still yield acceptable performance for correctly inferring the occurrences of special events.

  3. Determine the optimal carrier selection for a logistics network based on multi-commodity reliability criterion

    NASA Astrophysics Data System (ADS)

    Lin, Yi-Kuei; Yeh, Cheng-Ta

    2013-05-01

    From the perspective of supply chain management, the selected carrier plays an important role in freight delivery. This article proposes a new criterion of multi-commodity reliability and optimises the carrier selection based on such a criterion for logistics networks with routes and nodes, over which multiple commodities are delivered. Carrier selection concerns the selection of exactly one carrier to deliver freight on each route. The capacity of each carrier has several available values associated with a probability distribution, since some of a carrier's capacity may be reserved for various orders. Therefore, the logistics network, given any carrier selection, is a multi-commodity multi-state logistics network. Multi-commodity reliability is defined as a probability that the logistics network can satisfy a customer's demand for various commodities, and is a performance indicator for freight delivery. To solve this problem, this study proposes an optimisation algorithm that integrates genetic algorithm, minimal paths and Recursive Sum of Disjoint Products. A practical example in which multi-sized LCD monitors are delivered from China to Germany is considered to illustrate the solution procedure.

  4. Web-GIS oriented systems viability for municipal solid waste selective collection optimization in developed and transient economies

    SciTech Connect

    Rada, E.C.; Ragazzi, M.; Fedrizzi, P.

    2013-04-15

    Highlights: ► As an appropriate solution for MSW management in developed and transient countries. ► As an option to increase the efficiency of MSW selective collection. ► As an opportunity to integrate MSW management needs and services inventories. ► As a tool to develop Urban Mining actions. - Abstract: Municipal solid waste management is a multidisciplinary activity that includes generation, source separation, storage, collection, transfer and transport, processing and recovery, and, last but not least, disposal. The optimization of waste collection, through source separation, is compulsory where a landfill based management must be overcome. In this paper, a few aspects related to the implementation of a Web-GIS based system are analyzed. This approach is critically analyzed referring to the experience of two Italian case studies and two additional extra-European case studies. The first case is one of the best examples of selective collection optimization in Italy. The obtained efficiency is very high: 80% of waste is source separated for recycling purposes. In the second reference case, the local administration is going to be faced with the optimization of waste collection through Web-GIS oriented technologies for the first time. The starting scenario is far from an optimized management of municipal solid waste. The last two case studies concern pilot experiences in China and Malaysia. Each step of the Web-GIS oriented strategy is comparatively discussed referring to typical scenarios of developed and transient economies. The main result is that transient economies are ready to move toward Web oriented tools for MSW management, but this opportunity is not yet well exploited in the sector.

  5. Spacecraft flight control with the new phase space control law and optimal linear jet select

    NASA Technical Reports Server (NTRS)

    Bergmann, E. V.; Croopnick, S. R.; Turkovich, J. J.; Work, C. C.

    1977-01-01

    An autopilot designed for rotation and translation control of a rigid spacecraft is described. The autopilot uses reaction control jets as control effectors and incorporates a six-dimensional phase space control law as well as a linear programming algorithm for jet selection. The interaction of the control law and jet selection was investigated and a recommended configuration proposed. By means of a simulation procedure the new autopilot was compared with an existing system and was found to be superior in terms of core memory, central processing unit time, firings, and propellant consumption. But it is thought that the cycle time required to perform the jet selection computations might render the new autopilot unsuitable for existing flight computer applications, without modifications. The new autopilot is capable of maintaining attitude control in the presence of a large number of jet failures.

  6. A methodology for selecting an optimal experimental design for the computer analysis of a complex system

    SciTech Connect

    RUTHERFORD,BRIAN M.

    2000-02-03

    Investigation and evaluation of a complex system is often accomplished through the use of performance measures based on system response models. The response models are constructed using computer-generated responses supported where possible by physical test results. The general problem considered is one where resources and system complexity together restrict the number of simulations that can be performed. The levels of input variables used in defining environmental scenarios, initial and boundary conditions and for setting system parameters must be selected in an efficient way. This report describes an algorithmic approach for performing this selection.

  7. Methodology of research for qualitative composition of municipal solid waste to select an optimal method of recycling

    NASA Astrophysics Data System (ADS)

    Kravtsova, M. V.; Volkov, D. A.

    2015-09-01

    The article offers research methodology for qualitative composition of municipal solid waste to select an optimal method of recycling. The resource potential of waste directly depends on its composition and determines effectiveness of using various techniques, including separation and separate collection of refuge. The decision on re-equipment of waste-separating enterprise, which decreases the supply of waste to the burial site and provides economy of nonrenewable energy sources, is well-grounded, because it allows to diminish an anthropogenic load on environment.

  8. Selection, optimization, and compensation: strategies to maintain, maximize, and generate resources in later life in the face of chronic illnesses.

    PubMed

    Rozario, Philip A; Kidahashi, Miwako; DeRienzis, Daniel R

    2011-02-01

    This qualitative study of 45 older adults examines how they allocate their resources in the face of chronic health conditions. Participants were recruited from 2 senior centers and interviewed about their repertoire of activities, any changes in those activities in later life, and meanings they ascribed to those changes. The Selection, Optimization, and Compensation model guided our analysis and interpretation of participants' responses. The findings demonstrate the complexity of participants' responses to age-related changes, particularly in how they adapted and negotiated both their perception and life goals when faced with changing social landscapes. We discuss some implications and nuances of our findings.

  9. Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches.

    PubMed

    Stellacci, A M; Castrignanò, A; Troccoli, A; Basso, B; Buttafuoco, G

    2016-03-01

    Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325-1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R(2) (LL R(2)) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.

  10. Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches.

    PubMed

    Stellacci, A M; Castrignanò, A; Troccoli, A; Basso, B; Buttafuoco, G

    2016-03-01

    Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325-1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R(2) (LL R(2)) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design. PMID:26922749

  11. Encapsulation of a Decision-Making Model to Optimize Supplier Selection via Structural Equation Modeling (SEM)

    NASA Astrophysics Data System (ADS)

    Sahul Hameed, Ruzanna; Thiruchelvam, Sivadass; Nasharuddin Mustapha, Kamal; Che Muda, Zakaria; Mat Husin, Norhayati; Ezanee Rusli, Mohd; Yong, Lee Choon; Ghazali, Azrul; Itam, Zarina; Hakimie, Hazlinda; Beddu, Salmia; Liyana Mohd Kamal, Nur

    2016-03-01

    This paper proposes a conceptual framework to compare criteria/factor that influence the supplier selection. A mixed methods approach comprising qualitative and quantitative survey will be used. The study intend to identify and define the metrics that key stakeholders at Public Works Department (PWD) believed should be used for supplier. The outcomes would foresee the possible initiatives to bring procurement in PWD to a strategic level. The results will provide a deeper understanding of drivers for supplier’s selection in the construction industry. The obtained output will benefit many parties involved in the supplier selection decision-making. The findings provides useful information and greater understanding of the perceptions that PWD executives hold regarding supplier selection and the extent to which these perceptions are consistent with findings from prior studies. The findings from this paper can be utilized as input for policy makers to outline any changes in the current procurement code of practice in order to enhance the degree of transparency and integrity in decision-making.

  12. Use of optimization to predict the effect of selected parameters on commuter aircraft performance

    NASA Technical Reports Server (NTRS)

    Wells, V. L.; Shevell, R. S.

    1982-01-01

    An optimizing computer program determined the turboprop aircraft with lowest direct operating cost for various sets of cruise speed and field length constraints. External variables included wing area, wing aspect ratio and engine sea level static horsepower; tail sizes, climb speed and cruise altitude were varied within the function evaluation program. Direct operating cost was minimized for a 150 n.mi typical mission. Generally, DOC increased with increasing speed and decreasing field length but not by a large amount. Ride roughness, however, increased considerably as speed became higher and field length became shorter.

  13. Surface stability and the selection rules of substrate orientation for optimal growth of epitaxial II-VI semiconductors

    SciTech Connect

    Yin, Wan-Jian; Yang, Ji-Hui; Zaunbrecher, Katherine; Gessert, Tim; Barnes, Teresa; Wei, Su-Huai; Yan, Yanfa

    2015-10-05

    The surface structures of ionic zinc-blende CdTe (001), (110), (111), and (211) surfaces are systematically studied by first-principles density functional calculations. Based on the surface structures and surface energies, we identify the detrimental twinning appearing in molecular beam epitaxy (MBE) growth of II-VI compounds as the (111) lamellar twin boundaries. To avoid the appearance of twinning in MBE growth, we propose the following selection rules for choosing optimal substrate orientations: (1) the surface should be nonpolar so that there is no large surface reconstructions that could act as a nucleation center and promote the formation of twins; (2) the surface structure should have low symmetry so that there are no multiple equivalent directions for growth. These straightforward rules, in consistent with experimental observations, provide guidelines for selecting proper substrates for high-quality MBE growth of II-VI compounds.

  14. Surface stability and the selection rules of substrate orientation for optimal growth of epitaxial II-VI semiconductors

    NASA Astrophysics Data System (ADS)

    Yin, Wan-Jian; Yang, Ji-Hui; Zaunbrecher, Katherine; Gessert, Tim; Barnes, Teresa; Yan, Yanfa; Wei, Su-Huai

    2015-10-01

    The surface structures of ionic zinc-blende CdTe (001), (110), (111), and (211) surfaces are systematically studied by first-principles density functional calculations. Based on the surface structures and surface energies, we identify the detrimental twinning appearing in molecular beam epitaxy (MBE) growth of II-VI compounds as the (111) lamellar twin boundaries. To avoid the appearance of twinning in MBE growth, we propose the following selection rules for choosing optimal substrate orientations: (1) the surface should be nonpolar so that there is no large surface reconstructions that could act as a nucleation center and promote the formation of twins; (2) the surface structure should have low symmetry so that there are no multiple equivalent directions for growth. These straightforward rules, in consistent with experimental observations, provide guidelines for selecting proper substrates for high-quality MBE growth of II-VI compounds.

  15. Topology optimization design of a lightweight ultra-broadband wide-angle resistance frequency selective surface absorber

    NASA Astrophysics Data System (ADS)

    Sui, Sai; Ma, Hua; Wang, Jiafu; Pang, Yongqiang; Qu, Shaobo

    2015-06-01

    In this paper, the topology design of a lightweight ultra-broadband polarization-independent frequency selective surface absorber is proposed. The absorption over a wide frequency range of 6.68-26.08 GHz with reflection below -10 dB can be achieved by optimizing the topology and dimensions of the resistive frequency selective surface by virtue of genetic algorithm. This ultra-broadband absorption can be kept when the incident angle is less than 55 degrees and is independent of the incident wave polarization. The experimental results agree well with the numerical simulations. The density of our ultra-broadband absorber is only 0.35 g cm  -  3 and thus may find potential applications in microwave engineering, such as electromagnetic interference and stealth technology.

  16. Leveraging information storage to select forecast-optimal parameters for delay-coordinate reconstructions.

    PubMed

    Garland, Joshua; James, Ryan G; Bradley, Elizabeth

    2016-02-01

    Delay-coordinate reconstruction is a proven modeling strategy for building effective forecasts of nonlinear time series. The first step in this process is the estimation of good values for two parameters, the time delay and the embedding dimension. Many heuristics and strategies have been proposed in the literature for estimating these values. Few, if any, of these methods were developed with forecasting in mind, however, and their results are not optimal for that purpose. Even so, these heuristics-intended for other applications-are routinely used when building delay coordinate reconstruction-based forecast models. In this paper, we propose an alternate strategy for choosing optimal parameter values for forecast methods that are based on delay-coordinate reconstructions. The basic calculation involves maximizing the shared information between each delay vector and the future state of the system. We illustrate the effectiveness of this method on several synthetic and experimental systems, showing that this metric can be calculated quickly and reliably from a relatively short time series, and that it provides a direct indication of how well a near-neighbor based forecasting method will work on a given delay reconstruction of that time series. This allows a practitioner to choose reconstruction parameters that avoid any pathologies, regardless of the underlying mechanism, and maximize the predictive information contained in the reconstruction. PMID:26986345

  17. Selection of optimal oligonucleotide probes for microarrays usingmultiple criteria, global alignment and parameter estimation.

    SciTech Connect

    Li, Xingyuan; He, Zhili; Zhou, Jizhong

    2005-10-30

    The oligonucleotide specificity for microarray hybridizationcan be predicted by its sequence identity to non-targets, continuousstretch to non-targets, and/or binding free energy to non-targets. Mostcurrently available programs only use one or two of these criteria, whichmay choose 'false' specific oligonucleotides or miss 'true' optimalprobes in a considerable proportion. We have developed a software tool,called CommOligo using new algorithms and all three criteria forselection of optimal oligonucleotide probes. A series of filters,including sequence identity, free energy, continuous stretch, GC content,self-annealing, distance to the 3'-untranslated region (3'-UTR) andmelting temperature (Tm), are used to check each possibleoligonucleotide. A sequence identity is calculated based on gapped globalalignments. A traversal algorithm is used to generate alignments for freeenergy calculation. The optimal Tm interval is determined based on probecandidates that have passed all other filters. Final probes are pickedusing a combination of user-configurable piece-wise linear functions andan iterative process. The thresholds for identity, stretch and freeenergy filters are automatically determined from experimental data by anaccessory software tool, CommOligo_PE (CommOligo Parameter Estimator).The program was used to design probes for both whole-genome and highlyhomologous sequence data. CommOligo and CommOligo_PE are freely availableto academic users upon request.

  18. On Optimization of Surface Roughness of Selective Laser Melted Stainless Steel Parts: A Statistical Study

    NASA Astrophysics Data System (ADS)

    Alrbaey, K.; Wimpenny, D.; Tosi, R.; Manning, W.; Moroz, A.

    2014-06-01

    In this work, the effects of re-melting parameters for postprocessing the surface texture of Additively Manufactured parts using a statistical approach are investigated. This paper focuses on improving the final surface texture of stainless steel (316L) parts, built using a Renishaw SLM 125 machine. This machine employs a fiber laser to fuse fine powder on a layer-by-layer basis to generate three-dimensional parts. The samples were produced using varying angles of inclination in order to generate range of surface roughness between 8 and 20 µm. Laser re-melting (LR) as post-processing was performed in order to investigate surface roughness through optimization of parameters. The re-melting process was carried out using a custom-made hybrid laser re-cladding machine, which uses a 200 W fiber laser. Optimized processing parameters were based on statistical analysis within a Design of Experiment framework, from which a model was then constructed. The results indicate that the best obtainable final surface roughness is about 1.4 µm ± 10%. This figure was obtained when laser power of about 180 W was used, to give energy density between 2200 and 2700 J/cm2 for the re-melting process. Overall, the obtained results indicate LR as a post-build process has the capacity to improve surface finishing of SLM components up to 80%, compared with the initial manufactured surface.

  19. Optimal selection of sib pairs from random samples for linkage analysis of a QTL using the EDAC test.

    PubMed

    Dolan, C V; Boomsma, D I

    1998-05-01

    Percentages of extremely concordant and extremely discordant sib pairs are calculated that maximize the power to detect a quantitative trait locus (QTL) under a variety of circumstances using the EDAC test. We assume a large fixed number of randomly sampled sib pairs, such as one would hope to find in the large twin registries, and limited resources to genotype a certain number of selected sib pairs. Our aim is to investigate whether optimal selection can be achieved when prior knowledge concerning the QTL gene action, QTL allele frequency, QTL effect size, and background (residual) sib correlation is limited or absent. To this end we calculate the best selection percentages for a large number of models, which differ in QTL gene action allele frequency, background correlation, and QTL effect size. By averaging these percentages over gene action, over allele frequency, over gene action, and over allele frequencies, we arrive at general recommendations concerning selection percentages. The soundness of these recommendations is subsequently in a number of test cases. PMID:9670595

  20. Identification and optimization of anthranilic sulfonamides as novel, selective cholecystokinin-2 receptor antagonists.

    PubMed

    Allison, Brett D; Phuong, Victor K; McAtee, Laura C; Rosen, Mark; Morton, Magda; Prendergast, Clodagh; Barrett, Terry; Lagaud, Guy; Freedman, Jamie; Li, Lina; Wu, Xiaodong; Venkatesan, Hariharan; Pippel, Marna; Woods, Craig; Rizzolio, Michèle C; Hack, Michael; Hoey, Kenway; Deng, Xiaohu; King, Christopher; Shankley, Nigel P; Rabinowitz, Michael H

    2006-10-19

    A high throughput screening approach to the identification of selective cholecystokinin-2 receptor (CCK-2R) ligands resulted in the discovery of a novel series of antagonists, represented by 1-[2-[(2,1,3-benzothiadiazol-4-ylsulfonyl)amino]-5-chlorobenzoyl]-piperidine (1; CCK-2R, pK(I) = 6.4). Preliminary exploration of the structure-activity relationships around the anthranilic ring and the amide and sulfonamide moieties led to a nearly 50-fold improvement of receptor affinity and showed a greater than 1000-fold selectivity over the related cholecystokinin-1 receptor. Pharmacokinetic evaluation led to the identification of 4-[4-iodo-2-[(5-quinoxalinylsulfonyl)amino]benzoyl]-morpholine, 26d, a compound that demonstrates promising pharmacokinetic properties in the rat and dog with respect to plasma clearance and oral bioavailability and is a potent inhibitor in vivo of pentagastrin-stimulated acid secretion in the rat when dosed orally.

  1. Optimization of biguanide derivatives as selective antitumor agents blocking adaptive stress responses in the tumor microenvironment.

    PubMed

    Narise, Kosuke; Okuda, Kensuke; Enomoto, Yukihiro; Hirayama, Tasuku; Nagasawa, Hideko

    2014-01-01

    Adaptive cellular responses resulting from multiple microenvironmental stresses, such as hypoxia and nutrient deprivation, are potential novel drug targets for cancer treatment. Accordingly, we focused on developing anticancer agents targeting the tumor microenvironment (TME). In this study, to search for selective antitumor agents blocking adaptive responses in the TME, thirteen new compounds, designed and synthesized on the basis of the arylmethylbiguanide scaffold of phenformin, were used in structure activity relationship studies of inhibition of hypoxia inducible factor (HIF)-1 and unfolded protein response (UPR) activation and of selective cytotoxicity under glucose-deprived stress conditions, using HT29 cells. We conducted luciferase reporter assays using stable cell lines expressing either an HIF-1-responsive reporter gene or a glucose-regulated protein 78 promoter-reporter gene, which were induced by hypoxia and glucose deprivation stress, respectively, to screen for TME-targeting antitumor drugs. The guanidine analog (compound 2), obtained by bioisosteric replacement of the biguanide group, had activities comparable with those of phenformin (compound 1). Introduction of various substituents on the phenyl ring significantly affected the activities. In particular, the o-methylphenyl analog compound 7 and the o-chlorophenyl analog compound 12 showed considerably more potent inhibitory effects on HIF-1 and UPR activation than did phenformin, and excellent selective cytotoxicity under glucose deprivation. These compounds, therefore, represent an improvement over phenformin. They also suppressed HIF-1- and UPR-related protein expression and secretion of vascular endothelial growth factor-A. Moreover, these compounds exhibited significant antiangiogenic effects in the chick chorioallantoic membrane assay. Our structural development studies of biguanide derivatives provided promising candidates for a novel anticancer agent targeting the TME for selective cancer

  2. Optimal site selection for a high-resolution ice core record in East Antarctica

    NASA Astrophysics Data System (ADS)

    Vance, Tessa R.; Roberts, Jason L.; Moy, Andrew D.; Curran, Mark A. J.; Tozer, Carly R.; Gallant, Ailie J. E.; Abram, Nerilie J.; van Ommen, Tas D.; Young, Duncan A.; Grima, Cyril; Blankenship, Don D.; Siegert, Martin J.

    2016-03-01

    Ice cores provide some of the best-dated and most comprehensive proxy records, as they yield a vast and growing array of proxy indicators. Selecting a site for ice core drilling is nonetheless challenging, as the assessment of potential new sites needs to consider a variety of factors. Here, we demonstrate a systematic approach to site selection for a new East Antarctic high-resolution ice core record. Specifically, seven criteria are considered: (1) 2000-year-old ice at 300 m depth; (2) above 1000 m elevation; (3) a minimum accumulation rate of 250 mm years-1 IE (ice equivalent); (4) minimal surface reworking to preserve the deposited climate signal; (5) a site with minimal displacement or elevation change in ice at 300 m depth; (6) a strong teleconnection to midlatitude climate; and (7) an appropriately complementary relationship to the existing Law Dome record (a high-resolution record in East Antarctica). Once assessment of these physical characteristics identified promising regions, logistical considerations (for site access and ice core retrieval) were briefly considered. We use Antarctic surface mass balance syntheses, along with ground-truthing of satellite data by airborne radar surveys to produce all-of-Antarctica maps of surface roughness, age at specified depth, elevation and displacement change, and surface air temperature correlations to pinpoint promising locations. We also use the European Centre for Medium-Range Weather Forecast ERA 20th Century reanalysis (ERA-20C) to ensure that a site complementary to the Law Dome record is selected. We find three promising sites in the Indian Ocean sector of East Antarctica in the coastal zone from Enderby Land to the Ingrid Christensen Coast (50-100° E). Although we focus on East Antarctica for a new ice core site, the methodology is more generally applicable, and we include key parameters for all of Antarctica which may be useful for ice core site selection elsewhere and/or for other purposes.

  3. Optimal site selection for a high resolution ice core record in East Antarctica

    NASA Astrophysics Data System (ADS)

    Vance, T.; Roberts, J.; Moy, A.; Curran, M.; Tozer, C.; Gallant, A.; Abram, N.; van Ommen, T.; Young, D.; Grima, C.; Blankenship, D.; Siegert, M.

    2015-11-01

    Ice cores provide some of the best dated and most comprehensive proxy records, as they yield a vast and growing array of proxy indicators. Selecting a site for ice core drilling is nonetheless challenging, as the assessment of potential new sites needs to consider a variety of factors. Here, we demonstrate a systematic approach to site selection for a new East Antarctic high resolution ice core record. Specifically, seven criteria are considered: (1) 2000 year old ice at 300 m depth, (2) above 1000 m elevation, (3) a minimum accumulation rate of 250 mm yr-1 IE, (4) minimal surface re-working to preserve the deposited climate signal, (5) a site with minimal displacement or elevation change of ice at 300 m depth, (6) a strong teleconnection to mid-latitude climate and (7) an appropriately complementary relationship to the existing Law Dome record (a high resolution record in East Antarctica). Once assessment of these physical characteristics identified promising regions, logistical considerations (for site access and ice core retrieval) were briefly considered. We use Antarctic surface mass balance syntheses, along with ground-truthing of satellite data by airborne radar surveys to produce all-of-Antarctica maps of surface roughness, age at specified depth, elevation and displacement change and surface air temperature correlations to pinpoint promising locations. We also use the European Centre for Medium-Range Weather Forecast ERA 20th Century reanalysis (ERA-20C) to ensure a site complementary to the Law Dome record is selected. We find three promising sites in the Indian Ocean sector of East Antarctica in the coastal zone from Enderby Land to the Ingrid Christensen Coast (50-100° E). Although we focus on East Antarctica for a new ice core site, the methodology is more generally applicable and we include key parameters for all of Antarctica which may be useful for ice core site selection elsewhere and/or for other purposes.

  4. Design, synthesis, and optimization of novel epoxide incorporating peptidomimetics as selective calpain inhibitors.

    PubMed

    Schiefer, Isaac T; Tapadar, Subhasish; Litosh, Vladislav; Siklos, Marton; Scism, Rob; Wijewickrama, Gihani T; Chandrasena, Esala P; Sinha, Vaishali; Tavassoli, Ehsan; Brunsteiner, Michael; Fa', Mauro; Arancio, Ottavio; Petukhov, Pavel; Thatcher, Gregory R J

    2013-08-01

    Hyperactivation of the calcium-dependent cysteine protease calpain 1 (Cal1) is implicated as a primary or secondary pathological event in a wide range of illnesses and in neurodegenerative states, including Alzheimer's disease (AD). E-64 is an epoxide-containing natural product identified as a potent nonselective, calpain inhibitor, with demonstrated efficacy in animal models of AD. By use of E-64 as a lead, three successive generations of calpain inhibitors were developed using computationally assisted design to increase selectivity for Cal1. First generation analogues were potent inhibitors, effecting covalent modification of recombinant Cal1 catalytic domain (Cal1cat), demonstrated using LC-MS/MS. Refinement yielded second generation inhibitors with improved selectivity. Further library expansion and ligand refinement gave three Cal1 inhibitors, one of which was designed as an activity-based protein profiling probe. These were determined to be irreversible and selective inhibitors by kinetics studies comparing full length Cal1 with the general cysteine protease papain.

  5. Cluster resolution: a metric for automated, objective and optimized feature selection in chemometric modeling.

    PubMed

    Sinkov, Nikolai A; Harynuk, James J

    2011-01-30

    A novel metric termed cluster resolution is presented. This metric compares the separation of clusters of data points while simultaneously considering the shapes of the clusters and their relative orientations. Using cluster resolution in conjunction with an objective variable ranking metric allows for fully automated feature selection for the construction of chemometric models. The metric is based upon considering the maximum size of confidence ellipses around clusters of points representing different classes of objects that can be constructed without any overlap of the ellipses. For demonstration purposes we utilized PCA to classify samples of gasoline based upon their octane rating. The entire GC-MS chromatogram of each sample comprising over 2 × 10(6) variables was considered. As an example, automated ranking by ANOVA was applied followed by a forward selection approach to choose variables for inclusion. This approach can be generally applied to feature selection for a variety of applications and represents a significant step towards the development of fully automated, objective construction of chemometric models.

  6. Metal-organic framework with optimally selective xenon adsorption and separation.

    PubMed

    Banerjee, Debasis; Simon, Cory M; Plonka, Anna M; Motkuri, Radha K; Liu, Jian; Chen, Xianyin; Smit, Berend; Parise, John B; Haranczyk, Maciej; Thallapally, Praveen K

    2016-01-01

    Nuclear energy is among the most viable alternatives to our current fossil fuel-based energy economy. The mass deployment of nuclear energy as a low-emissions source requires the reprocessing of used nuclear fuel to recover fissile materials and mitigate radioactive waste. A major concern with reprocessing used nuclear fuel is the release of volatile radionuclides such as xenon and krypton that evolve into reprocessing facility off-gas in parts per million concentrations. The existing technology to remove these radioactive noble gases is a costly cryogenic distillation; alternatively, porous materials such as metal-organic frameworks have demonstrated the ability to selectively adsorb xenon and krypton at ambient conditions. Here we carry out a high-throughput computational screening of large databases of metal-organic frameworks and identify SBMOF-1 as the most selective for xenon. We affirm this prediction and report that SBMOF-1 exhibits by far the highest reported xenon adsorption capacity and a remarkable Xe/Kr selectivity under conditions pertinent to nuclear fuel reprocessing. PMID:27291101

  7. Metal–organic framework with optimally selective xenon adsorption and separation

    PubMed Central

    Banerjee, Debasis; Simon, Cory M.; Plonka, Anna M.; Motkuri, Radha K.; Liu, Jian; Chen, Xianyin; Smit, Berend; Parise, John B.; Haranczyk, Maciej; Thallapally, Praveen K.

    2016-01-01

    Nuclear energy is among the most viable alternatives to our current fossil fuel-based energy economy. The mass deployment of nuclear energy as a low-emissions source requires the reprocessing of used nuclear fuel to recover fissile materials and mitigate radioactive waste. A major concern with reprocessing used nuclear fuel is the release of volatile radionuclides such as xenon and krypton that evolve into reprocessing facility off-gas in parts per million concentrations. The existing technology to remove these radioactive noble gases is a costly cryogenic distillation; alternatively, porous materials such as metal–organic frameworks have demonstrated the ability to selectively adsorb xenon and krypton at ambient conditions. Here we carry out a high-throughput computational screening of large databases of metal–organic frameworks and identify SBMOF-1 as the most selective for xenon. We affirm this prediction and report that SBMOF-1 exhibits by far the highest reported xenon adsorption capacity and a remarkable Xe/Kr selectivity under conditions pertinent to nuclear fuel reprocessing. PMID:27291101

  8. Saving Lives and Money: A Multi-Objective Optimization Approach to the Selection of Structural Retrofits

    NASA Astrophysics Data System (ADS)

    Franco, G.; Deodatis, G.; Smyth, A.

    2005-12-01

    The existence of large numbers of poorly constructed buildings in earthquake-prone areas has made large scale retrofitting campaigns a desirable strategy for reducing the risk of loss of life and infrastructure. Since the retrofitting operation must be, therefore, carried out for numerous buildings, it has become a necessity to find the most attractive retrofitting solution for a given type of buildings that significantly reduces the risk of loss of life while remaining as economic as possible. Each retrofit solution for an existing building carries a set of potential costs and benefits over a given period of time. Some of these costs and benefits can be taken into account in terms of monetary values, whereas others cannot. The value of lives spared or lives lost that may potentially occur over the lifespan of a building as a consequence of choosing a particular retrofit cannot be easily measured in terms of money. In the absence of better methods to incorporate the value of life into economic analyses, a somewhat arbitrary monetary quantity based on personal insurance or personal productivity is often chosen as a proxy to quantify it. These quantities, however, not only fail to capture the otherwise incalculable cost of life, but are also strongly dependent on the economy under study. In this work, the monetary costs of construction and structural damage are clearly differentiated from the loss of life, which is simply measured as the number of potential casualties in a certain earthquake scenario. Finding the best retrofit then becomes a multi-objective optimization problem, whose purpose is to find the cheapest solution that saves most lives. The conflicting nature of the objectives causes the appearance of not only one optimal solution but of a set of most convenient solutions that capture the different levels of trade-off between costs and lives saved. A large number of possible structural retrofits must be considered in order to find the set of best solutions

  9. On optimization of a composite bone plate using the selective stress shielding approach.

    PubMed

    Samiezadeh, Saeid; Tavakkoli Avval, Pouria; Fawaz, Zouheir; Bougherara, Habiba

    2015-02-01

    Bone fracture plates are used to stabilize fractures while allowing for adequate compressive force on the fracture ends. Yet the high stiffness of conventional bone plates significantly reduces compression at the fracture site, and can lead to subsequent bone loss upon healing. Fibre-reinforced composite bone plates have been introduced to address this drawback. However, no studies have optimized their configurations to fulfill the requirements of proper healing. In the present study, classical laminate theory and the finite element method were employed for optimization of a composite bone plate. A hybrid composite made of carbon fibre/epoxy with a flax/epoxy core, which was introduced previously, was optimized by varying the laminate stacking sequence and the contribution of each material, in order to minimize the axial stiffness and maximize the torsional stiffness for a given range of bending stiffness. The initial 14×4(14) possible configurations were reduced to 13 after applying various design criteria. A comprehensive finite element model, validated against a previous experimental study, was used to evaluate the mechanical performance of each composite configuration in terms of its fracture stability, load sharing, and strength in transverse and oblique Vancouver B1 fracture configurations at immediately post-operative, post-operative, and healed bone stages. It was found that a carbon fibre/epoxy plate with an axial stiffness of 4.6 MN, and bending and torsional stiffness of 13 and 14 N·m(2), respectively, showed an overall superiority compared with other laminate configurations. It increased the compressive force at the fracture site up to 14% when compared to a conventional metallic plate, and maintained fracture stability by ensuring the fracture fragments' relative motions were comparable to those found during metallic plate fixation. The healed stage results revealed that implantation of the titanium plate caused a 40.3% reduction in bone stiffness

  10. On optimization of a composite bone plate using the selective stress shielding approach.

    PubMed

    Samiezadeh, Saeid; Tavakkoli Avval, Pouria; Fawaz, Zouheir; Bougherara, Habiba

    2015-02-01

    Bone fracture plates are used to stabilize fractures while allowing for adequate compressive force on the fracture ends. Yet the high stiffness of conventional bone plates significantly reduces compression at the fracture site, and can lead to subsequent bone loss upon healing. Fibre-reinforced composite bone plates have been introduced to address this drawback. However, no studies have optimized their configurations to fulfill the requirements of proper healing. In the present study, classical laminate theory and the finite element method were employed for optimization of a composite bone plate. A hybrid composite made of carbon fibre/epoxy with a flax/epoxy core, which was introduced previously, was optimized by varying the laminate stacking sequence and the contribution of each material, in order to minimize the axial stiffness and maximize the torsional stiffness for a given range of bending stiffness. The initial 14×4(14) possible configurations were reduced to 13 after applying various design criteria. A comprehensive finite element model, validated against a previous experimental study, was used to evaluate the mechanical performance of each composite configuration in terms of its fracture stability, load sharing, and strength in transverse and oblique Vancouver B1 fracture configurations at immediately post-operative, post-operative, and healed bone stages. It was found that a carbon fibre/epoxy plate with an axial stiffness of 4.6 MN, and bending and torsional stiffness of 13 and 14 N·m(2), respectively, showed an overall superiority compared with other laminate configurations. It increased the compressive force at the fracture site up to 14% when compared to a conventional metallic plate, and maintained fracture stability by ensuring the fracture fragments' relative motions were comparable to those found during metallic plate fixation. The healed stage results revealed that implantation of the titanium plate caused a 40.3% reduction in bone stiffness

  11. Comparative evaluation of five Beauveria isolates for housefly (Musca domestica L.) control and growth optimization of selected strain.

    PubMed

    Mishra, Sapna; Malik, Anushree

    2012-11-01

    Pathogenic potential of five native Beauveria isolates was assessed against housefly adult and larvae in laboratory bioassays. Beauveria isolate Beauveria bassiana HQ917687 showed highest virulence with 72.3 and 100 % mortality of larvae and adults of Musca domestica, respectively. Other Beauveria isolates caused 36-52 % housefly larval mortality while the adult mortalities varied between 72 and 82 %. B. bassiana HQ917687 also showed the fastest killing activity with LT(50) of 4 days (for larvae) and 3 days (for adults). This isolate showing highest virulence was selected for its growth optimization in terms of biomass and spore production using response surface methodology. The optimum value of temperature, yeast extract, and pH for maximum biomass and spore production was predicted as 27 °C, 5.00 g/l, and 6.75, respectively. Temperature was found to be the most critical factor influencing biomass and spore yield of the fungus and even nullified the effects of other factors at sufficiently higher value. The results obtained in this study depict the significance of appropriate strain selection and process parameter optimization in order to facilitate mass production of biocontrol agents.

  12. Optimal Technology Selection and Operation of Microgrids inCommercial Buildings

    SciTech Connect

    Marnay, Chris; Venkataramanan, Giri; Stadler, Michael; Siddiqui,Afzal; Firestone, Ryan; Chandran, Bala

    2007-01-15

    The deployment of small (<1-2 MW) clusters of generators,heat and electrical storage, efficiency investments, and combined heatand power (CHP) applications (particularly involving heat activatedcooling) in commercial buildings promises significant benefits but posesmany technical and financial challenges, both in system choice and itsoperation; if successful, such systems may be precursors to widespreadmicrogrid deployment. The presented optimization approach to choosingsuch systems and their operating schedules uses Berkeley Lab'sDistributed Energy Resources Customer Adoption Model [DER-CAM], extendedto incorporate electrical storage options. DER-CAM chooses annual energybill minimizing systems in a fully technology-neutral manner. Anillustrative example for a San Francisco hotel is reported. The chosensystem includes two engines and an absorption chiller, providing anestimated 11 percent cost savings and 10 percent carbon emissionreductions, under idealized circumstances.

  13. Use of optimization to predict the effect of selected parameters on commuter aircraft performance

    NASA Technical Reports Server (NTRS)

    Wells, V. L.; Shevell, R. S.

    1982-01-01

    The relationships between field length and cruise speed and aircraft direct operating cost were determined. A gradient optimizing computer program was developed to minimize direct operating cost (DOC) as a function of airplane geometry. In this way, the best airplane operating under one set of constraints can be compared with the best operating under another. A constant 30-passenger fuselage and rubberized engines based on the General Electric CT-7 were used as a baseline. All aircraft had to have a 600 nautical mile maximum range and were designed to FAR part 25 structural integrity and climb gradient regulations. Direct operating cost was minimized for a typical design mission of 150 nautical miles. For purposes of C sub L sub max calculation, all aircraft had double-slotted flaps but with no Fowler action.

  14. High Performance Vanadium Redox Flow Batteries with Optimized Electrode Configuration and Membrane Selection

    SciTech Connect

    Liu, Q. H.; Grim, G. M.; Papandrew, A; Turhan, A.; Zawodzinski, Thomas A; Mench, Matthew M

    2012-01-01

    The performance of a vanadium flow battery with no-gap architecture was significantly improved via several techniques. Specifically, gains arising from variation of the overall electrode thickness, membrane thickness, and electrode thermal treatment were studied. There is a trade-off between apparent kinetic losses, mass transfer losses, and ionic resistance as the electrode thickness is varied at the anode and cathode. Oxidative thermal pretreatment of the carbon paper electrode increased the peak power density by 16%. Results of the pretreatment in air showed greater improvement in peak power density compared to that obtained with pretreatment in an argon environment. The highest peak power density in a VRB yet published to the author s knowledge was achieved at a value of 767 mW cm 2 with optimized membrane and electrode engineering. 2012 The Electrochemical Society. [DOI: 10.1149/2.051208jes] All rights reserved.

  15. Using information Theory in Optimal Test Point Selection for Health Management in NASA's Exploration Vehicles

    NASA Technical Reports Server (NTRS)

    Mehr, Ali Farhang; Tumer, Irem

    2005-01-01

    In this paper, we will present a new methodology that measures the "worth" of deploying an additional testing instrument (sensor) in terms of the amount of information that can be retrieved from such measurement. This quantity is obtained using a probabilistic model of RLV's that has been partially developed in the NASA Ames Research Center. A number of correlated attributes are identified and used to obtain the worth of deploying a sensor in a given test point from an information-theoretic viewpoint. Once the information-theoretic worth of sensors is formulated and incorporated into our general model for IHM performance, the problem can be formulated as a constrained optimization problem where reliability and operational safety of the system as a whole is considered. Although this research is conducted specifically for RLV's, the proposed methodology in its generic form can be easily extended to other domains of systems health monitoring.

  16. Optimizing anaerobic digestion by selection of the immobilizing surface for enhanced methane production.

    PubMed

    Adu-Gyamfi, Nicholas; Ravella, Sreenivas Rao; Hobbs, Phil J

    2012-09-01

    Maximizing methane production while maintaining an appreciable level of process stability is a crucial challenge in the anaerobic digestion industry. In this study, the role of six parameters: the type of immobilizing supports, loading rate, inoculum levels, C:N ratio, trace nutrients concentrations and mixing rate, on methane production were investigated under thermophilic conditions (55 ± 1°C) with synthetic substrate medium. The immobilizing supports were Silica gel, Sand, Molecular Sieve and Dowex Marathon beads. A Taguchi Design of Experiment (DOE) methodology was employed to determine the effects of different parameters using an L(16) orthogonal array. Overall, immobilizing supports influenced methane production substantially (contributing 61.3% of the observed variation in methane yield) followed by loading rate and inoculum which had comparable influence (17.9% and 17.7% respectively). Optimization improved methane production by 153% (from 183 to 463 ml CH(4)l(-1)d(-1)).

  17. Selection of optimal river water quality improvement programs using QUAL2K: a case study of Taihu Lake Basin, China.

    PubMed

    Zhang, Ruibin; Qian, Xin; Li, Huiming; Yuan, Xingcheng; Ye, Rui

    2012-08-01

    In recent years, water quality degradation associated with rapid socio-economic development in the Taihu Lake Basin, China, has attracted increasing attention from both the public and the Chinese government. The primary sources of pollution in Taihu Lake are its inflow rivers and their tributaries. Effective water quality improvement programs need to be implemented in these rivers to improve the water quality of Taihu Lake, and to ensure sustainable development in the region. To ensure effectiveness and efficiency, it is important that the optimal water quality improvement program for a specific situation be selected. The aim of this study was to facilitate the selection of this optimal program. The QUAL2K model for river and stream water quality was used to simulate the effects of a range of water quality improvement scenarios in the Hongqi River, which is a polluted tributary in the Taihu Lake Basin. These scenarios consisted of a series of three water treatment technologies in different configurations, from upstream to downstream. The results showed that the optimal scenario comprised a bio-contact oxidation system upstream, followed by an ecological floating bed, and a vertical moveable eco-bed downstream. The reduction rates achieved by this scenario for biochemical oxygen demand (BOD), ammonia nitrogen (NH(3)-N), total nitrogen (TN), and total phosphorus (TP) were 49.50%, 32.81%, 35.94%, and 45.27%, respectively. The QUAL2K model proved to be an effective tool in the comparative evaluation of potential water quality improvement programs. The method applied in this study can prevent the implementation of water quality improvement programs that would not achieve the desired goals.

  18. Optimal artificial neural network architecture selection for performance prediction of compact heat exchanger with the EBaLM-OTR technique

    SciTech Connect

    Dumidu Wijayasekara; Milos Manic; Piyush Sabharwall; Vivek Utgikar

    2011-07-01

    Artificial Neural Networks (ANN) have been used in the past to predict the performance of printed circuit heat exchangers (PCHE) with satisfactory accuracy. Typically published literature has focused on optimizing ANN using a training dataset to train the network and a testing dataset to evaluate it. Although this may produce outputs that agree with experimental results, there is a risk of over-training or overlearning the network rather than generalizing it, which should be the ultimate goal. An over-trained network is able to produce good results with the training dataset but fails when new datasets with subtle changes are introduced. In this paper we present EBaLM-OTR (error back propagation and Levenberg-Marquardt algorithms for over training resilience) technique, which is based on a previously discussed method of selecting neural network architecture that uses a separate validation set to evaluate different network architectures based on mean square error (MSE), and standard deviation of MSE. The method uses k-fold cross validation. Therefore in order to select the optimal architecture for the problem, the dataset is divided into three parts which are used to train, validate and test each network architecture. Then each architecture is evaluated according to their generalization capability and capability to conform to original data. The method proved to be a comprehensive tool in identifying the weaknesses and advantages of different network architectures. The method also highlighted the fact that the architecture with the lowest training error is not always the most generalized and therefore not the optimal. Using the method the testing error achieved was in the order of magnitude of within 10{sup -5} - 10{sup -3}. It was also show that the absolute error achieved by EBaLM-OTR was an order of magnitude better than the lowest error achieved by EBaLM-THP.

  19. Sensor selection and chemo-sensory optimization: toward an adaptable chemo-sensory system.

    PubMed

    Vergara, Alexander; Llobet, Eduard

    2011-01-01

    Over the past two decades, despite the tremendous research on chemical sensors and machine olfaction to develop micro-sensory systems that will accomplish the growing existent needs in personal health (implantable sensors), environment monitoring (widely distributed sensor networks), and security/threat detection (chemo/bio warfare agents), simple, low-cost molecular sensing platforms capable of long-term autonomous operation remain beyond the current state-of-the-art of chemical sensing. A fundamental issue within this context is that most of the chemical sensors depend on interactions between the targeted species and the surfaces functionalized with receptors that bind the target species selectively, and that these binding events are coupled with transduction processes that begin to change when they are exposed to the messy world of real samples. With the advent of fundamental breakthroughs at the intersection of materials science, micro- and nano-technology, and signal processing, hybrid chemo-sensory systems have incorporated tunable, optimizable operating parameters, through which changes in the response characteristics can be modeled and compensated as the environmental conditions or application needs change. The objective of this article, in this context, is to bring together the key advances at the device, data processing, and system levels that enable chemo-sensory systems to "adapt" in response to their environments. Accordingly, in this review we will feature the research effort made by selected experts on chemical sensing and information theory, whose work has been devoted to develop strategies that provide tunability and adaptability to single sensor devices or sensory array systems. Particularly, we consider sensor-array selection, modulation of internal sensing parameters, and active sensing. The article ends with some conclusions drawn from the results presented and a visionary look toward the future in terms of how the field may evolve. PMID

  20. Optimizing energy yields in black locust through genetic selection: final report

    SciTech Connect

    Bongarten, B.C.; Merkle, S.A.

    1996-10-01

    The purpose of this work was to assess the magnitude of improvement in biomass yield of black locust possible through breeding, and to determine methods for efficiently capturing the yield improvement achievable from selective breeding. To meet this overall objective, six tasks were undertaken to determine: (1) the amount and geographic pattern of natural genetic variation, (2) the mating system of the species, (3) quantitative genetic parameters of relevant traits, (4) the relationship between nitrogen fixation and growth in black locust, (5) the viability of mass vegetative propagation, and (6) the feasibility of improvement through genetic transformation.

  1. Optimization of process configuration and strain selection for microalgae-based biodiesel production.

    PubMed

    Yu, Nan; Dieu, Linus Tao Jie; Harvey, Simon; Lee, Dong-Yup

    2015-10-01

    A mathematical model was developed for the design of microalgae-based biodiesel production system by systematically integrating all the production stages and strain properties. Through the hypothetical case study, the model suggested the most economical system configuration for the selected microalgae strains from the available processes at each stage, thus resulting in the cheapest biodiesel production cost, S$2.66/kg, which is still higher than the current diesel price (S$1.05/kg). Interestingly, the microalgae strain properties, such as lipid content, effective diameter and productivity, were found to be one of the major factors that significantly affect the production cost as well as system configuration.

  2. Computer-aided method for automated selection of optimal imaging plane for measurement of total cerebral blood flow by MRI

    NASA Astrophysics Data System (ADS)

    Teng, Pang-yu; Bagci, Ahmet Murat; Alperin, Noam

    2009-02-01

    A computer-aided method for finding an optimal imaging plane for simultaneous measurement of the arterial blood inflow through the 4 vessels leading blood to the brain by phase contrast magnetic resonance imaging is presented. The method performance is compared with manual selection by two observers. The skeletons of the 4 vessels for which centerlines are generated are first extracted. Then, a global direction of the relatively less curved internal carotid arteries is calculated to determine the main flow direction. This is then used as a reference direction to identify segments of the vertebral arteries that strongly deviates from the main flow direction. These segments are then used to identify anatomical landmarks for improved consistency of the imaging plane selection. An optimal imaging plane is then identified by finding a plane with the smallest error value, which is defined as the sum of the angles between the plane's normal and the vessel centerline's direction at the location of the intersections. Error values obtained using the automated and the manual methods were then compared using 9 magnetic resonance angiography (MRA) data sets. The automated method considerably outperformed the manual selection. The mean error value with the automated method was significantly lower than the manual method, 0.09+/-0.07 vs. 0.53+/-0.45, respectively (p<.0001, Student's t-test). Reproducibility of repeated measurements was analyzed using Bland and Altman's test, the mean 95% limits of agreements for the automated and manual method were 0.01~0.02 and 0.43~0.55 respectively.

  3. Selection of Steady-State Process Simulation Software to Optimize Treatment of Radioactive and Hazardous Waste

    SciTech Connect

    Nichols, T. T.; Barnes, C. M.; Lauerhass, L.; Taylor, D. D.

    2001-06-01

    The process used for selecting a steady-state process simulator under conditions of high uncertainty and limited time is described. Multiple waste forms, treatment ambiguity, and the uniqueness of both the waste chemistries and alternative treatment technologies result in a large set of potential technical requirements that no commercial simulator can totally satisfy. The aim of the selection process was two-fold. First, determine the steady-state simulation software that best, albeit not completely, satisfies the requirements envelope. And second, determine if the best is good enough to justify the cost. Twelve simulators were investigated with varying degrees of scrutiny. The candidate list was narrowed to three final contenders: ASPEN Plus 10.2, PRO/II 5.11, and CHEMCAD 5.1.0. It was concluded from ''road tests'' that ASPEN Plus appears to satisfy the project's technical requirements the best and is worth acquiring. The final software decisions provide flexibility: they involve annual rather than multi-year licensing, and they include periodic re-assessment.

  4. Selection of Steady-State Process Simulation Software to Optimize Treatment of Radioactive and Hazardous Waste

    SciTech Connect

    Nichols, Todd Travis; Barnes, Charles Marshall; Lauerhass, Lance; Taylor, Dean Dalton

    2001-06-01

    The process used for selecting a steady-state process simulator under conditions of high uncertainty and limited time is described. Multiple waste forms, treatment ambiguity, and the uniqueness of both the waste chemistries and alternative treatment technologies result in a large set of potential technical requirements that no commercial simulator can totally satisfy. The aim of the selection process was two-fold. First, determine the steady-state simulation software that best, albeit not completely, satisfies the requirements envelope. And second, determine if the best is good enough to justify the cost. Twelve simulators were investigated with varying degrees of scrutiny. The candidate list was narrowed to three final contenders: ASPEN Plus 10.2, PRO/II 5.11, and CHEMCAD 5.1.0. It was concluded from "road tests" that ASPEN Plus appears to satisfy the project's technical requirements the best and is worth acquiring. The final software decisions provide flexibility: they involve annual rather than multi-year licensing, and they include periodic re-assessment.

  5. NESP: Nonlinear enhancement and selection of plane for optimal segmentation and recognition of scene word images

    NASA Astrophysics Data System (ADS)

    Kumar, Deepak; Anil Prasad, M. N.; Ramakrishnan, A. G.

    2013-01-01

    In this paper, we report a breakthrough result on the difficult task of segmentation and recognition of coloured text from the word image dataset of ICDAR robust reading competition challenge 2: reading text in scene images. We split the word image into individual colour, gray and lightness planes and enhance the contrast of each of these planes independently by a power-law transform. The discrimination factor of each plane is computed as the maximum between-class variance used in Otsu thresholding. The plane that has maximum discrimination factor is selected for segmentation. The trial version of Omnipage OCR is then used on the binarized words for recognition. Our recognition results on ICDAR 2011 and ICDAR 2003 word datasets are compared with those reported in the literature. As baseline, the images binarized by simple global and local thresholding techniques were also recognized. The word recognition rate obtained by our non-linear enhancement and selection of plance method is 72.8% and 66.2% for ICDAR 2011 and 2003 word datasets, respectively. We have created ground-truth for each image at the pixel level to benchmark these datasets using a toolkit developed by us. The recognition rate of benchmarked images is 86.7% and 83.9% for ICDAR 2011 and 2003 datasets, respectively.

  6. Optimized hyperspectral band selection using hybrid genetic algorithm and gravitational search algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

    2015-12-01

    The serious information redundancy in hyperspectral images (HIs) cannot contribute to the data analysis accuracy, instead it require expensive computational resources. Consequently, to identify the most useful and valuable information from the HIs, thereby improve the accuracy of data analysis, this paper proposed a novel hyperspectral band selection method using the hybrid genetic algorithm and gravitational search algorithm (GA-GSA). In the proposed method, the GA-GSA is mapped to the binary space at first. Then, the accuracy of the support vector machine (SVM) classifier and the number of selected spectral bands are utilized to measure the discriminative capability of the band subset. Finally, the band subset with the smallest number of spectral bands as well as covers the most useful and valuable information is obtained. To verify the effectiveness of the proposed method, studies conducted on an AVIRIS image against two recently proposed state-of-the-art GSA variants are presented. The experimental results revealed the superiority of the proposed method and indicated that the method can indeed considerably reduce data storage costs and efficiently identify the band subset with stable and high classification precision.

  7. The challenge of selecting protein kinase assays for lead discovery optimization

    PubMed Central

    Ma, Haiching; Deacon, Sean; Horiuchi, Kurumi

    2009-01-01

    Background Protein kinases represent one of the most promising groups of drug targets owing to their involvement in such pathological conditions as cancer, inflammatory diseases, neural disorders, and metabolism problems. In the last few years, numerous pharmaceutical and biotech companies have established kinase high-throughput screening (HTS) programs, and the reagent and service industries for kinase assay platforms, kits, and profiling services have begun to thrive. Objective The plethora of different assay formats available today poses a great challenge to scientists who want to select a technology that will be cost efficient, convenient to use, and have low false positive and false negative rates. Methods In the current review, we summarize the most commonly used kinase assay methods in the drug discovery process, present the advantages and disadvantages of each of these methods, and discuss the challenges of discovering kinase inhibitors by using these technologies. Conclusions The decision of selecting the assay formats for HTS or service platform for profiling should take into account not only the final goals of the screens but also the limitation of resources. PMID:19662101

  8. Design and optimization for variable rate selective excitation using an analytic RF scaling function.

    PubMed

    Gai, Neville D; Zur, Yuval

    2007-11-01

    At higher B(0) fields, specific absorption rate (SAR) deposition increases. Due to maximum SAR limitation, slice coverage decreases and/or scan time increases. Conventional selective RF pulses are played out in conjunction with a time independent field gradient. Variable rate selective excitation (VERSE) is a technique that modifies the original RF and gradient waveforms such that slice profile is unchanged. The drawback is that the slice profile for off-resonance spins is distorted. A new VERSE algorithm based on modeling the scaled waveforms as a Fermi function is introduced. It ensures that system related constraints of maximum gradient amplitude and slew rate are not exceeded. The algorithm can be used to preserve the original RF pulse duration while minimizing SAR and peak b1 or to minimize the RF pulse duration. The design is general and can be applied to any symmetrical or asymmetrical RF waveform. The algorithm is demonstrated by using it to (a) minimize the SAR of a linear phase RF pulse, (b) minimize SAR of a hyperbolic secant RF pulse, and (c) minimize the duration of a linear phase RF pulse. Images with a T1-FLAIR (T1 FLuid Attenuated Inversion Recovery) sequence using a conventional and VERSE adiabatic inversion RF pulse are presented. Comparison of images and scan parameters for different anatomies and coils shows increased scan coverage and decreased SAR with the VERSE inversion RF pulse, while image quality is preserved.

  9. On the selection of optimal feature region set for robust digital image watermarking.

    PubMed

    Tsai, Jen-Sheng; Huang, Win-Bin; Kuo, Yau-Hwang

    2011-03-01

    A novel feature region selection method for robust digital image watermarking is proposed in this paper. This method aims to select a nonoverlapping feature region set, which has the greatest robustness against various attacks and can preserve image quality as much as possible after watermarked. It first performs a simulated attacking procedure using some predefined attacks to evaluate the robustness of every candidate feature region. According to the evaluation results, it then adopts a track-with-pruning procedure to search a minimal primary feature set which can resist the most predefined attacks. In order to enhance its resistance to undefined attacks under the constraint of preserving image quality, the primary feature set is then extended by adding into some auxiliary feature regions. This work is formulated as a multidimensional knapsack problem and solved by a genetic algorithm based approach. The experimental results for StirMark attacks on some benchmark images support our expectation that the primary feature set can resist all the predefined attacks and its extension can enhance the robustness against undefined attacks. Comparing with some well-known feature-based methods, the proposed method exhibits better performance in robust digital watermarking.

  10. Optimal stapler cartridge selection according to the thickness of the pancreas in distal pancreatectomy.

    PubMed

    Kim, Hongbeom; Jang, Jin-Young; Son, Donghee; Lee, Seungyeoun; Han, Youngmin; Shin, Yong Chan; Kim, Jae Ri; Kwon, Wooil; Kim, Sun-Whe

    2016-08-01

    Stapling is a popular method for stump closure in distal pancreatectomy (DP). However, research on which cartridges are suitable for different pancreatic thickness is lacking. To identify the optimal stapler cartridge choice in DP according to pancreatic thickness.From November 2011 to April 2015, data were prospectively collected from 217 consecutive patients who underwent DP with 3-layer endoscopic staple closure in Seoul National University Hospital, Korea. Postoperative pancreatic fistula (POPF) was graded according to International Study Group on Pancreatic Fistula definitions. Staplers were grouped based on closed length (CL) (Group I: CL ≤ 1.5 mm, II: 1.5 mm < CL < 2 mm, III: CL ≥ 2 mm). Compression ratio (CR) was defined as pancreas thickness/CL. Distribution of pancreatic thickness was used to find the cut-off point of thickness which predicts POPF according to stapler groups.POPF developed in 130 (59.9%) patients (Grade A; n = 86 [66.1%], B; n = 44 [33.8%]). The numbers in each stapler group were 46, 101, and 70, respectively. Mean thickness was higher in POPF cases (15.2 mm vs 13.5 mm, P = 0.002). High body mass index (P = 0.003), thick pancreas (P = 0.011), and high CR (P = 0.024) were independent risk factors for POPF in multivariate analysis. Pancreatic thickness was grouped into <12 mm, 12 to 17 mm, and >17 mm. With pancreatic thickness <12 mm, the POPF rate was lowest with Group II (I: 50%, II: 27.6%, III: 69.2%, P = 0.035).The optimal stapler cartridges with pancreatic thickness <12 mm were those in Group II (Gold, CL: 1.8 mm). There was no suitable cartridge for thicker pancreases. Further studies are necessary to reduce POPF in thick pancreases. PMID:27583852

  11. Optimal stapler cartridge selection according to the thickness of the pancreas in distal pancreatectomy

    PubMed Central

    Kim, Hongbeom; Jang, Jin-Young; Son, Donghee; Lee, Seungyeoun; Han, Youngmin; Shin, Yong Chan; Kim, Jae Ri; Kwon, Wooil; Kim, Sun-Whe

    2016-01-01

    Abstract Stapling is a popular method for stump closure in distal pancreatectomy (DP). However, research on which cartridges are suitable for different pancreatic thickness is lacking. To identify the optimal stapler cartridge choice in DP according to pancreatic thickness. From November 2011 to April 2015, data were prospectively collected from 217 consecutive patients who underwent DP with 3-layer endoscopic staple closure in Seoul National University Hospital, Korea. Postoperative pancreatic fistula (POPF) was graded according to International Study Group on Pancreatic Fistula definitions. Staplers were grouped based on closed length (CL) (Group I: CL ≤ 1.5 mm, II: 1.5 mm < CL < 2 mm, III: CL ≥ 2 mm). Compression ratio (CR) was defined as pancreas thickness/CL. Distribution of pancreatic thickness was used to find the cut-off point of thickness which predicts POPF according to stapler groups. POPF developed in 130 (59.9%) patients (Grade A; n = 86 [66.1%], B; n = 44 [33.8%]). The numbers in each stapler group were 46, 101, and 70, respectively. Mean thickness was higher in POPF cases (15.2 mm vs 13.5 mm, P = 0.002). High body mass index (P = 0.003), thick pancreas (P = 0.011), and high CR (P = 0.024) were independent risk factors for POPF in multivariate analysis. Pancreatic thickness was grouped into <12 mm, 12 to 17 mm, and >17 mm. With pancreatic thickness <12 mm, the POPF rate was lowest with Group II (I: 50%, II: 27.6%, III: 69.2%, P = 0.035). The optimal stapler cartridges with pancreatic thickness <12 mm were those in Group II (Gold, CL: 1.8 mm). There was no suitable cartridge for thicker pancreases. Further studies are necessary to reduce POPF in thick pancreases. PMID:27583852

  12. Binary particle swarm optimization for frequency band selection in motor imagery based brain-computer interfaces.

    PubMed

    Wei, Qingguo; Wei, Zhonghai

    2015-01-01

    A brain-computer interface (BCI) enables people suffering from affective neurological diseases to communicate with the external world. Common spatial pattern (CSP) is an effective algorithm for feature extraction in motor imagery based BCI systems. However, many studies have proved that the performance of CSP depends heavily on the frequency band of EEG signals used for the construction of covariance matrices. The use of different frequency bands to extract signal features may lead to different classification performances, which are determined by the discriminative and complementary information they contain. In this study, the broad frequency band (8-30 Hz) is divided into 10 sub-bands of band width 4 Hz and overlapping 2 Hz. Binary particle swarm optimization (BPSO) is used to find the best sub-band set to improve the performance of CSP and subsequent classification. Experimental results demonstrate that the proposed method achieved an average improvement of 6.91% in cross-validation accuracy when compared to broad band CSP.

  13. Optimization of selective emitter fabrication method for solar cells using a laser grooving.

    PubMed

    Jung, W W; Kim, S C; Jung, S W; Moon, I Y; Kumar, K; Lee, Y W; Kim, S Y; Ju, M K; Han, S K; Yi, J

    2011-05-01

    In this paper, screen-printing laser grooved buried contact (LGBC) method was applied, which is compatible with the existing screen-printed solar cell equipment and facilities. Experiments were performed in order to optimize short circuit current (I(sc)), open circuit voltage (V(oc)) and fill factor of high efficiency solar cells. To enhance I(sc), V(oc) and efficiency, heavy doping was performed at low sheet resistance in the laser grooved region of the cell. In contrast, light doping was carried out at a high sheet resistance in the non-laser grooved region. To increase fill factor, porous silicon found on the wafer after dipping in an HF solution to remove SiN(x), was cleared. The fabricated screen-printing LGBC solar cell using a 125 mm x 125 mm single crystalline silicon wafer exhibited an efficiency of 17.2%. The results show that screen-printing LGBC method can be applied for high efficiency solar cells.

  14. 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.

  15. Selection of energy optimized pump concepts for multi core and multi mode erbium doped fiber amplifiers.

    PubMed

    Krummrich, Peter M; Akhtari, Simon

    2014-12-01

    The selection of an appropriate pump concept has a major impact on amplifier cost and power consumption. The energy efficiency of different pump concepts is compared for multi core and multi mode active fibers. In preamplifier stages, pump power density requirements derived from full C-band low noise WDM operation result in superior energy efficiency of direct pumping of individual cores in a multi core fiber with single mode pump lasers compared to cladding pumping with uncooled multi mode lasers. Even better energy efficiency is achieved by direct pumping of the core in multi mode active fibers. Complexity of pump signal combiners for direct pumping of multi core fibers can be reduced by deploying integrated components.

  16. Optimizing selection of large animals for antibody production by screening immune response to standard vaccines.

    PubMed

    Thompson, Mary K; Fridy, Peter C; Keegan, Sarah; Chait, Brian T; Fenyö, David; Rout, Michael P

    2016-03-01

    Antibodies made in large animals are integral to many biomedical research endeavors. Domesticated herd animals like goats, sheep, donkeys, horses and camelids all offer distinct advantages in antibody production. However, their cost of use is often prohibitive, especially where poor antigen response is commonplace; choosing a non-responsive animal can set a research program back or even prevent experiments from moving forward entirely. Over the course of production of antibodies from llamas, we found that some animals consistently produced a higher humoral antibody response than others, even to highly divergent antigens, as well as to their standard vaccines. Based on our initial data, we propose that these "high level responders" could be pre-selected by checking antibody titers against common vaccines given to domestic farm animals. Thus, time and money can be saved by reducing the chances of getting poor responding animals and minimizing the use of superfluous animals.

  17. Discovery and Optimization of Potent, Selective, and in Vivo Efficacious 2-Aryl Benzimidazole BCATm Inhibitors.

    PubMed

    Deng, Hongfeng; Zhou, Jingye; Sundersingh, Flora; Messer, Jeffrey A; Somers, Donald O; Ajakane, Myriam; Arico-Muendel, Christopher C; Beljean, Arthur; Belyanskaya, Svetlana L; Bingham, Ryan; Blazensky, Emily; Boullay, Anne-Benedicte; Boursier, Eric; Chai, Jing; Carter, Paul; Chung, Chun-Wa; Daugan, Alain; Ding, Yun; Herry, Kenny; Hobbs, Clare; Humphries, Eric; Kollmann, Christopher; Nguyen, Van Loc; Nicodeme, Edwige; Smith, Sarah E; Dodic, Nerina; Ancellin, Nicolas

    2016-04-14

    To identify BCATm inhibitors suitable for in vivo study, Encoded Library Technology (ELT) was used to affinity screen a 117 million member benzimidazole based DNA encoded library, which identified an inhibitor series with both biochemical and cellular activities. Subsequent SAR studies led to the discovery of a highly potent and selective compound, 1-(3-(5-bromothiophene-2-carboxamido)cyclohexyl)-N-methyl-2-(pyridin-2-yl)-1H-benzo[d]imidazole-5-carboxamide (8b) with much improved PK properties. X-ray structure revealed that 8b binds to the active site of BACTm in a unique mode via multiple H-bond and van der Waals interactions. After oral administration, 8b raised mouse blood levels of all three branched chain amino acids as a consequence of BCATm inhibition. PMID:27096045

  18. Precursor Selection for Property Optimization in Biomorphic SiC Ceramics

    NASA Technical Reports Server (NTRS)

    Varela-Feria, F. M.; Lopez-Robledo, M. J.; Martinez-Fernandez, J.; deArellano-Lopez, A. R.; Singh, M.; Gray, Hugh R. (Technical Monitor)

    2002-01-01

    Biomorphic SiC ceramics have been fabricated using different wood precursors. The evolution of volume, density and microstructure of the woods, carbon performs, and final SiC products are systematically studied in order to establish experimental guidelines that allow materials selection. The wood density is a critical characteristic, which results in a particular final SiC density, and the level of anisotropy in mechanical properties in directions parallel (axial) and perpendicular (radial) to the growth of the wood. The purpose of this work is to explore experimental laws that can help choose a type of wood as precursor for a final SiC product, with a given microstructure, density and level of anisotropy. Preliminary studies of physical properties suggest that not only mechanical properties are strongly anisotropic, but also electrical conductivity and gas permeability, which have great technological importance.

  19. Optimizing selection of large animals for antibody production by screening immune response to standard vaccines.

    PubMed

    Thompson, Mary K; Fridy, Peter C; Keegan, Sarah; Chait, Brian T; Fenyö, David; Rout, Michael P

    2016-03-01

    Antibodies made in large animals are integral to many biomedical research endeavors. Domesticated herd animals like goats, sheep, donkeys, horses and camelids all offer distinct advantages in antibody production. However, their cost of use is often prohibitive, especially where poor antigen response is commonplace; choosing a non-responsive animal can set a research program back or even prevent experiments from moving forward entirely. Over the course of production of antibodies from llamas, we found that some animals consistently produced a higher humoral antibody response than others, even to highly divergent antigens, as well as to their standard vaccines. Based on our initial data, we propose that these "high level responders" could be pre-selected by checking antibody titers against common vaccines given to domestic farm animals. Thus, time and money can be saved by reducing the chances of getting poor responding animals and minimizing the use of superfluous animals. PMID:26775851

  20. A new method for wavelength interval selection that intelligently optimizes the locations, widths and combinations of the intervals.

    PubMed

    Deng, Bai-Chuan; Yun, Yong-Huan; Ma, Pan; Lin, Chen-Chen; Ren, Da-Bing; Liang, Yi-Zeng

    2015-03-21

    In this study, a new algorithm for wavelength interval selection, known as interval variable iterative space shrinkage approach (iVISSA), is proposed based on the VISSA algorithm. It combines global and local searches to iteratively and intelligently optimize the locations, widths and combinations of the spectral intervals. In the global search procedure, it inherits the merit of soft shrinkage from VISSA to search the locations and combinations of informative wavelengths, whereas in the local search procedure, it utilizes the information of continuity in spectroscopic data to determine the widths of wavelength intervals. The global and local search procedures are carried out alternatively to realize wavelength interval selection. This method was tested using three near infrared (NIR) datasets. Some high-performing wavelength selection methods, such as synergy interval partial least squares (siPLS), moving window partial least squares (MW-PLS), competitive adaptive reweighted sampling (CARS), genetic algorithm PLS (GA-PLS) and interval random frog (iRF), were used for comparison. The results show that the proposed method is very promising with good results both on prediction capability and stability. The MATLAB codes for implementing iVISSA are freely available on the website: .

  1. Optimization of immobilized gallium (III) ion affinity chromatography for selective binding and recovery of phosphopeptides from protein digests.

    PubMed

    Aryal, Uma K; Olson, Douglas J H; Ross, Andrew R S

    2008-12-01

    Although widely used in proteomics research for the selective enrichment of phosphopeptides from protein digests, immobilized metal-ion affinity chromatography (IMAC) often suffers from low specificity and differential recovery of peptides carrying different numbers of phosphate groups. By systematically evaluating and optimizing different loading, washing, and elution conditions, we have developed an efficient and highly selective procedure for the enrichment of phosphopeptides using a commercially available gallium(III)-IMAC column (PhosphoProfile, Sigma). Phosphopeptide enrichment using the reagents supplied with the column is incomplete and biased toward the recovery and/or detection of smaller, singly phosphorylated peptides. In contrast, elution with base (0.4 M ammonium hydroxide) gives efficient and balanced recovery of both singly and multiply phosphorylated peptides, while loading peptides in a strong acidic solution (1% trifluoracetic acid) further increases selectivity toward phosphopeptides, with minimal carryover of nonphosphorylated peptides. 2,5-Dihydroxybenzoic acid, a matrix commonly used when analyzing phosphopeptides by matrix-assisted laser desorption/ionization mass spectrometry was also evaluated as an additive in loading and eluting solvents. Elution with 50% acetonitrile containing 20 mg/mL dihydroxybenzoic acid and 1% phosphoric acid gave results similar to those obtained using ammonium hydroxide as the eluent, although the latter showed the highest specificity for phosphorylated peptides. PMID:19183793

  2. Optimizing Training Population Data and Validation of Genomic Selection for Economic Traits in Soft Winter Wheat

    PubMed Central

    Hoffstetter, Amber; Cabrera, Antonio; Huang, Mao; Sneller, Clay

    2016-01-01

    Genomic selection (GS) is a breeding tool that estimates breeding values (GEBVs) of individuals based solely on marker data by using a model built using phenotypic and marker data from a training population (TP). The effectiveness of GS increases as the correlation of GEBVs and phenotypes (accuracy) increases. Using phenotypic and genotypic data from a TP of 470 soft winter wheat lines, we assessed the accuracy of GS for grain yield, Fusarium Head Blight (FHB) resistance, softness equivalence (SE), and flour yield (FY). Four TP data sampling schemes were tested: (1) use all TP data, (2) use subsets of TP lines with low genotype-by-environment interaction, (3) use subsets of markers significantly associated with quantitative trait loci (QTL), and (4) a combination of 2 and 3. We also correlated the phenotypes of relatives of the TP to their GEBVs calculated from TP data. The GS accuracy within the TP using all TP data ranged from 0.35 (FHB) to 0.62 (FY). On average, the accuracy of GS from using subsets of data increased by 54% relative to using all TP data. Using subsets of markers selected for significant association with the target trait had the greatest impact on GS accuracy. Between-environment prediction accuracy was also increased by using data subsets. The accuracy of GS when predicting the phenotypes of TP relatives ranged from 0.00 to 0.85. These results suggest that GS could be useful for these traits and GS accuracy can be greatly improved by using subsets of TP data. PMID:27440921

  3. Optimizing Training Population Data and Validation of Genomic Selection for Economic Traits in Soft Winter Wheat.

    PubMed

    Hoffstetter, Amber; Cabrera, Antonio; Huang, Mao; Sneller, Clay

    2016-01-01

    Genomic selection (GS) is a breeding tool that estimates breeding values (GEBVs) of individuals based solely on marker data by using a model built using phenotypic and marker data from a training population (TP). The effectiveness of GS increases as the correlation of GEBVs and phenotypes (accuracy) increases. Using phenotypic and genotypic data from a TP of 470 soft winter wheat lines, we assessed the accuracy of GS for grain yield, Fusarium Head Blight (FHB) resistance, softness equivalence (SE), and flour yield (FY). Four TP data sampling schemes were tested: (1) use all TP data, (2) use subsets of TP lines with low genotype-by-environment interaction, (3) use subsets of markers significantly associated with quantitative trait loci (QTL), and (4) a combination of 2 and 3. We also correlated the phenotypes of relatives of the TP to their GEBVs calculated from TP data. The GS accuracy within the TP using all TP data ranged from 0.35 (FHB) to 0.62 (FY). On average, the accuracy of GS from using subsets of data increased by 54% relative to using all TP data. Using subsets of markers selected for significant association with the target trait had the greatest impact on GS accuracy. Between-environment prediction accuracy was also increased by using data subsets. The accuracy of GS when predicting the phenotypes of TP relatives ranged from 0.00 to 0.85. These results suggest that GS could be useful for these traits and GS accuracy can be greatly improved by using subsets of TP data. PMID:27440921

  4. Optimizing Training Population Data and Validation of Genomic Selection for Economic Traits in Soft Winter Wheat.

    PubMed

    Hoffstetter, Amber; Cabrera, Antonio; Huang, Mao; Sneller, Clay

    2016-09-08

    Genomic selection (GS) is a breeding tool that estimates breeding values (GEBVs) of individuals based solely on marker data by using a model built using phenotypic and marker data from a training population (TP). The effectiveness of GS increases as the correlation of GEBVs and phenotypes (accuracy) increases. Using phenotypic and genotypic data from a TP of 470 soft winter wheat lines, we assessed the accuracy of GS for grain yield, Fusarium Head Blight (FHB) resistance, softness equivalence (SE), and flour yield (FY). Four TP data sampling schemes were tested: (1) use all TP data, (2) use subsets of TP lines with low genotype-by-environment interaction, (3) use subsets of markers significantly associated with quantitative trait loci (QTL), and (4) a combination of 2 and 3. We also correlated the phenotypes of relatives of the TP to their GEBVs calculated from TP data. The GS accuracy within the TP using all TP data ranged from 0.35 (FHB) to 0.62 (FY). On average, the accuracy of GS from using subsets of data increased by 54% relative to using all TP data. Using subsets of markers selected for significant association with the target trait had the greatest impact on GS accuracy. Between-environment prediction accuracy was also increased by using data subsets. The accuracy of GS when predicting the phenotypes of TP relatives ranged from 0.00 to 0.85. These results suggest that GS could be useful for these traits and GS accuracy can be greatly improved by using subsets of TP data.

  5. Optimizing nest survival and female survival: Consequences of nest site selection for Canada Geese

    USGS Publications Warehouse

    Miller, David A.; Grand, J.B.; Fondell, T.F.; Anthony, R.M.

    2007-01-01

    We examined the relationship between attributes of nest sites used by Canada Geese (Branta canadensis) in the Copper River Delta, Alaska, and patterns in nest and female survival. We aimed to determine whether nest site attributes related to nest and female survival differed and whether nest site attributes related to nest survival changed within and among years. Nest site attributes that we examined included vegetation at and surrounding the nest, as well as associations with other nesting birds. Optimal nest site characteristics were different depending on whether nest survival or female survival was examined. Prior to 25 May, the odds of daily survival for nests in tall shrubs and on islands were 2.92 and 2.26 times greater, respectively, than for nests in short shrub sites. Bald Eagles (Halieaeetus leucocephalus) are the major predator during the early breeding season and their behavior was likely important in determining this pattern. After 25 May, when eagle predation is limited due to the availability of alternative prey, no differences in nest survival among the nest site types were found. In addition, nest survival was positively related to the density of other Canada Goose nests near the nest site. Although the number of detected mortalities for females was relatively low, a clear pattern was found, with mortality three times more likely at nest sites dominated by high shrub density within 50 m than at open sites dominated by low shrub density. The negative relationship of nest concealment and adult survival is consistent with that found in other studies of ground-nesting birds. Physical barriers that limited access to nest sites by predators and sites that allowed for early detection of predators were important characteristics of nest site quality for Canada Geese and nest site quality shifted within seasons, likely as a result of shifting predator-prey interactions.

  6. Optimal Site Characterization and Selection Criteria for Oyster Restoration using Multicolinear Factorial Water Quality Approach

    NASA Astrophysics Data System (ADS)

    Yoon, J.

    2015-12-01

    Elevated levels of nutrient loadings have enriched the Chesapeake Bay estuaries and coastal waters via point and nonpoint sources and the atmosphere. Restoring oyster beds is considered a Best Management Practice (BMP) to improve the water quality as well as provide physical aquatic habitat and a healthier estuarine system. Efforts include declaring sanctuaries for brood-stocks, supplementing hard substrate on the bottom and aiding natural populations with the addition of hatchery-reared and disease-resistant stocks. An economic assessment suggests that restoring the ecological functions will improve water quality, stabilize shorelines, and establish a habitat for breeding grounds that outweighs the value of harvestable oyster production. Parametric factorial models were developed to investigate multicolinearities among in situ water quality and oyster restoration activities to evaluate posterior success rates upon multiple substrates, and physical, chemical, hydrological and biological site characteristics to systematically identify significant factors. Findings were then further utilized to identify the optimal sites for successful oyster restoration augmentable with Total Maximum Daily Loads (TMDLs) and BMPs. Factorial models evaluate the relationship among the dependent variable, oyster biomass, and treatments of temperature, salinity, total suspended solids, E. coli/Enterococci counts, depth, dissolved oxygen, chlorophyll a, nitrogen and phosphorus, and blocks consist of alternative substrates (oyster shells versus riprap, granite, cement, cinder blocks, limestone marl or combinations). Factorial model results were then compared to identify which combination of variables produces the highest posterior biomass of oysters. Developed Factorial model can facilitate maximizing the likelihood of successful oyster reef restoration in an effort to establish a healthier ecosystem and to improve overall estuarine water quality in the Chesapeake Bay estuaries.

  7. Quantitative and qualitative optimization of allergen extraction from peanut and selected tree nuts. Part 2. Optimization of buffer and ionic strength using a full factorial experimental design.

    PubMed

    L'Hocine, Lamia; Pitre, Mélanie

    2016-03-01

    A full factorial design was used to assess the single and interactive effects of three non-denaturing aqueous (phosphate, borate, and carbonate) buffers at various ionic strengths (I) on allergen extractability from and immunoglobulin E (IgE) immunoreactivity of peanut, almond, hazelnut, and pistachio. The results indicated that the type and ionic strength of the buffer had different effects on protein recovery from the nuts under study. Substantial differences in protein profiles, abundance, and IgE-binding intensity with different combinations of pH and ionic strength were found. A significant interaction between pH and ionic strength was observed for pistachio and almond. The optimal buffer system conditions, which maximized the IgE-binding efficiency of allergens and provided satisfactory to superior protein recovery yield and profiles, were carbonate buffer at an ionic strength of I=0.075 for peanut, carbonate buffer at I=0.15 for almond, phosphate buffer at I=0.5 for hazelnut, and borate at I=0.15 for pistachio. The buffer type and its ionic strength could be manipulated to achieve the selective solubility of desired allergens.

  8. Quantitative and qualitative optimization of allergen extraction from peanut and selected tree nuts. Part 2. Optimization of buffer and ionic strength using a full factorial experimental design.

    PubMed

    L'Hocine, Lamia; Pitre, Mélanie

    2016-03-01

    A full factorial design was used to assess the single and interactive effects of three non-denaturing aqueous (phosphate, borate, and carbonate) buffers at various ionic strengths (I) on allergen extractability from and immunoglobulin E (IgE) immunoreactivity of peanut, almond, hazelnut, and pistachio. The results indicated that the type and ionic strength of the buffer had different effects on protein recovery from the nuts under study. Substantial differences in protein profiles, abundance, and IgE-binding intensity with different combinations of pH and ionic strength were found. A significant interaction between pH and ionic strength was observed for pistachio and almond. The optimal buffer system conditions, which maximized the IgE-binding efficiency of allergens and provided satisfactory to superior protein recovery yield and profiles, were carbonate buffer at an ionic strength of I=0.075 for peanut, carbonate buffer at I=0.15 for almond, phosphate buffer at I=0.5 for hazelnut, and borate at I=0.15 for pistachio. The buffer type and its ionic strength could be manipulated to achieve the selective solubility of desired allergens. PMID:26471623

  9. Loco-regional therapies for patients with hepatocellular carcinoma awaiting liver transplantation: Selecting an optimal therapy

    PubMed Central

    Byrne, Thomas J; Rakela, Jorge

    2016-01-01

    Hepatocellular carcinoma (HCC) is a common, increasingly prevalent malignancy. For all but the smallest lesions, surgical removal of cancer via resection or liver transplantation (LT) is considered the most feasible pathway to cure. Resection - even with favorable survival - is associated with a fairly high rate of recurrence, perhaps since most HCCs occur in the setting of cirrhosis. LT offers the advantage of removing not only the cancer but the diseased liver from which the cancer has arisen, and LT outperforms resection for survival with selected patients. Since time waiting for LT is time during which HCC can progress, loco-regional therapy (LRT) is widely employed by transplant centers. The purpose of LRT is either to bridge patients to LT by preventing progression and waitlist dropout, or to downstage patients who slightly exceed standard eligibility criteria initially but can fall within it after treatment. Transarterial chemoembolization and radiofrequency ablation have been the most widely utilized LRTs to date, with favorable efficacy and safety as a bridge to LT (and for the former, as a downstaging modality). The list of potentially effective LRTs has expanded in recent years, and includes transarterial chemoembolization with drug-eluting beads, radioembolization and novel forms of extracorporal therapy. Herein we appraise the various LRT modalities for HCC, and their potential roles in specific clinical scenarios in patients awaiting LT. PMID:27358775

  10. Loco-regional therapies for patients with hepatocellular carcinoma awaiting liver transplantation: Selecting an optimal therapy.

    PubMed

    Byrne, Thomas J; Rakela, Jorge

    2016-06-24

    Hepatocellular carcinoma (HCC) is a common, increasingly prevalent malignancy. For all but the smallest lesions, surgical removal of cancer via resection or liver transplantation (LT) is considered the most feasible pathway to cure. Resection - even with favorable survival - is associated with a fairly high rate of recurrence, perhaps since most HCCs occur in the setting of cirrhosis. LT offers the advantage of removing not only the cancer but the diseased liver from which the cancer has arisen, and LT outperforms resection for survival with selected patients. Since time waiting for LT is time during which HCC can progress, loco-regional therapy (LRT) is widely employed by transplant centers. The purpose of LRT is either to bridge patients to LT by preventing progression and waitlist dropout, or to downstage patients who slightly exceed standard eligibility criteria initially but can fall within it after treatment. Transarterial chemoembolization and radiofrequency ablation have been the most widely utilized LRTs to date, with favorable efficacy and safety as a bridge to LT (and for the former, as a downstaging modality). The list of potentially effective LRTs has expanded in recent years, and includes transarterial chemoembolization with drug-eluting beads, radioembolization and novel forms of extracorporal therapy. Herein we appraise the various LRT modalities for HCC, and their potential roles in specific clinical scenarios in patients awaiting LT. PMID:27358775

  11. Optimization of chemical structure of Schottky-type selection diode for crossbar resistive memory.

    PubMed

    Kim, Gun Hwan; Lee, Jong Ho; Jeon, Woojin; Song, Seul Ji; Seok, Jun Yeong; Yoon, Jung Ho; Yoon, Kyung Jean; Park, Tae Joo; Hwang, Cheol Seong

    2012-10-24

    The electrical performances of Pt/TiO(2)/Ti/Pt stacked Schottky-type diode (SD) was systematically examined, and this performance is dependent on the chemical structures of the each layer and their interfaces. The Ti layers containing a tolerable amount of oxygen showed metallic electrical conduction characteristics, which was confirmed by sheet resistance measurement with elevating the temperature, transmission line measurement (TLM), and Auger electron spectroscopy (AES) analysis. However, the chemical structure of SD stack and resulting electrical properties were crucially affected by the dissolved oxygen concentration in the Ti layers. The lower oxidation potential of the Ti layer with initially higher oxygen concentration suppressed the oxygen deficiency of the overlying TiO(2) layer induced by consumption of the oxygen from TiO(2) layer. This structure results in the lower reverse current of SDs without significant degradation of forward-state current. Conductive atomic force microscopy (CAFM) analysis showed the current conduction through the local conduction paths in the presented SDs, which guarantees a sufficient forward-current density as a selection device for highly integrated crossbar array resistive memory.

  12. Information access in a dual-task context: testing a model of optimal strategy selection

    NASA Technical Reports Server (NTRS)

    Wickens, C. D.; Seidler, K. S.

    1997-01-01

    Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

  13. A global earthquake discrimination scheme to optimize ground-motion prediction equation selection

    USGS Publications Warehouse

    Garcia, Daniel; Wald, David J.; Hearne, Michael

    2012-01-01

    We present a new automatic earthquake discrimination procedure to determine in near-real time the tectonic regime and seismotectonic domain of an earthquake, its most likely source type, and the corresponding ground-motion prediction equation (GMPE) class to be used in the U.S. Geological Survey (USGS) Global ShakeMap system. This method makes use of the Flinn–Engdahl regionalization scheme, seismotectonic information (plate boundaries, global geology, seismicity catalogs, and regional and local studies), and the source parameters available from the USGS National Earthquake Information Center in the minutes following an earthquake to give the best estimation of the setting and mechanism of the event. Depending on the tectonic setting, additional criteria based on hypocentral depth, style of faulting, and regional seismicity may be applied. For subduction zones, these criteria include the use of focal mechanism information and detailed interface models to discriminate among outer-rise, upper-plate, interface, and intraslab seismicity. The scheme is validated against a large database of recent historical earthquakes. Though developed to assess GMPE selection in Global ShakeMap operations, we anticipate a variety of uses for this strategy, from real-time processing systems to any analysis involving tectonic classification of sources from seismic catalogs.

  14. Optimization of internals for Selective Catalytic Reduction (SCR) for NO removal.

    PubMed

    Lei, Zhigang; Wen, Cuiping; Chen, Biaohua

    2011-04-15

    This work tried to identify the relationship between the internals of selective catalytic reduction (SCR) system and mixing performance for controlling ammonia (NH(3)) slip. In the SCR flow section, arranging the flow-guided internals can improve the uniformity of velocity distribution but is unfavorable for the uniformity of NH(3) concentration distribution. The ammonia injection grids (AIG) with four kinds of nozzle diameters (i.e., 1.0 mm, 1.5 mm, 2.0 mm, and mixed diameters) were investigated, and it was found that the AIG with mixed nozzle diameters in which A3, A4, B3, and B4 nozzles' diameters are 1.0 mm and other nozzles' diameters are 1.5 mm is the most favorable for the uniformity of NH(3) concentration distribution. In the SCR reactor section, the appropriate space length between two catalyst layers, which serves as gas mixing in order to prevent maldistribution of gas concentrations into the second catalyst layer, under the investigated conditions is about 100, 1000, and 12 mm for honeycomb-like cordierite catalyst, plate-type catalysts with parallel channel arrangement, and with cross channel arrangement, respectively. Therefore, the cross channel arrangement is superior to the parallel channel arrangement in saving the SCR reactor volume.

  15. Selection of optimal chelator improves the contrast of GRPR imaging using bombesin analogue RM26.

    PubMed

    Mitran, Bogdan; Varasteh, Zohreh; Selvaraju, Ram Kumar; Lindeberg, Gunnar; Sörensen, Jens; Larhed, Mats; Tolmachev, Vladimir; Rosenström, Ulrika; Orlova, Anna

    2016-05-01

    Bombesin (BN) analogs bind with high affinity to gastrin-releasing peptide receptors (GRPRs) that are up-regulated in prostate cancer and can be used for the visualization of prostate cancer. The aim of this study was to investigate the influence of radionuclide-chelator complexes on the biodistribution pattern of the 111In-labeled bombesin antagonist PEG2-D-Phe-Gln-Trp-Ala-Val-Gly-His-Sta-Leu-NH2 (PEG2-RM26) and to identify an optimal construct for SPECT imaging. A series of RM26 analogs N-terminally conjugated with NOTA, NODAGA, DOTA and DOTAGA via a PEG2 spacer were radiolabeled with 111In and evaluated both in vitro and in vivo. The conjugates were successfully labeled with 111In with 100% purity and retained binding specificity to GRPR and high stability. The cellular processing of all compounds was characterized by slow internalization. The IC50 values were in the low nanomolar range, with lower IC50 values for positively charged natIn-NOTA-PEG2-RM26 (2.6 ± 0.1 nM) and higher values for negatively charged natIn-DOTAGA-PEG2-RM26 (4.8 ± 0.5 nM). The kinetic binding studies showed KD values in the picomolar range that followed the same pattern as the IC50 data. The biodistribution of all compounds was studied in BALB/c nu/nu mice bearing PC-3 prostate cancer xenografts. Tumor targeting and biodistribution studies displayed rapid clearance of radioactivity from the blood and normal organs via kidney excretion. All conjugates showed similar uptake in tumors at 4 h p.i. The radioactivity accumulation in GRPR-expressing organs was significantly lower for DOTA- and DOTAGA-containing constructs compared to those containing NOTA and NODAGA. 111In-NOTA-PEG2-RM26 with a positively charged complex showed the highest initial uptake and the slowest clearance of radioactivity from the liver. At 4 h p.i., DOTA- and DOTAGA-coupled analogs showed significantly higher tumor-to-organ ratios compared to NOTA- and NODAGA-containing variants. The NODAGA conjugate demonstrated the

  16. Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness.

    PubMed

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

    Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to 'small p and large n' problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

  17. Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

    PubMed Central

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

    Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

  18. In vitro selection of RNase P RNA reveals optimized catalytic activity in a highly conserved structural domain.

    PubMed

    Frank, D N; Ellington, A E; Pace, N R

    1996-12-01

    In vitro selection techniques are useful means of dissecting the functions of both natural and artificial ribozymes. Using a self-cleaving conjugate containing the Escherichia coli ribonuclease P RNA and its substrate, pre-tRNA (Frank DN, Harris ME, Pace NR, 1994, Biochemistry 33:10800-10808), we have devised a method to select for catalytically active variants of the RNase P ribozyme. A selection experiment was performed to probe the structural and sequence constraints that operate on a highly conserved region of RNase P: the J3/4-P4-J2/4 region, which lies within the core of RNase P and is thought to bind catalytically essential magnesium ions (Harris ME et al., 1994, EMBO J 13:3953-3963; Hardt WD et al., 1995, EMBO J 14:2935-2944; Harris ME, Pace NR, 1995, RNA 1:210-218). We sought to determine which, if any, of the nearly invariant nucleotides within J3/4-P4-J2/4 are required for ribozyme-mediated catalysis. Twenty-two residues in the J3/4-P4-J2/4 component of RNase P RNA were randomized and, surprisingly, after only 10 generations, each of the randomized positions returned to the wild-type sequence. This indicates that every position in J3/4-P4-J2/4 contributes to optimal catalytic activity. These results contrast sharply with selections involving other large ribozymes, which evolve improved catalytic function readily in vitro (Chapman KB, Szostak JW, 1994, Curr Opin Struct Biol 4:618-622; Joyce GF, 1994, Curr Opin Struct Biol 4:331-336; Kumar PKR, Ellington AE, 1995, FASEB J 9:1183-1195). The phylogenetic conservation of J3/4-P4-J2/4, coupled with the results reported here, suggests that the contribution of this structure to RNA-mediated catalysis was optimized very early in evolution, before the last common ancestor of all life. PMID:8972768

  19. A New Combinatorial Optimization Approach for Integrated Feature Selection Using Different Datasets: A Prostate Cancer Transcriptomic Study

    PubMed Central

    Puthiyedth, Nisha; Riveros, Carlos; Berretta, Regina; Moscato, Pablo

    2015-01-01

    Background The joint study of multiple datasets has become a common technique for increasing statistical power in detecting biomarkers obtained from smaller studies. The approach generally followed is based on the fact that as the total number of samples increases, we expect to have greater power to detect associations of interest. This methodology has been applied to genome-wide association and transcriptomic studies due to the availability of datasets in the public domain. While this approach is well established in biostatistics, the introduction of new combinatorial optimization models to address this issue has not been explored in depth. In this study, we introduce a new model for the integration of multiple datasets and we show its application in transcriptomics. Methods We propose a new combinatorial optimization problem that addresses the core issue of biomarker detection in integrated datasets. Optimal solutions for this model deliver a feature selection from a panel of prospective biomarkers. The model we propose is a generalised version of the (α,β)-k-Feature Set problem. We illustrate the performance of this new methodology via a challenging meta-analysis task involving six prostate cancer microarray datasets. The results are then compared to the popular RankProd meta-analysis tool and to what can be obtained by analysing the individual datasets by statistical and combinatorial methods alone. Results Application of the integrated method resulted in a more informative signature than the rank-based meta-analysis or individual dataset results, and overcomes problems arising from real world datasets. The set of genes identified is highly significant in the context of prostate cancer. The method used does not rely on homogenisation or transformation of values to a common scale, and at the same time is able to capture markers associated with subgroups of the disease. PMID:26106884

  20. Structural and mechanical evaluations of a topology optimized titanium interbody fusion cage fabricated by selective laser melting process.

    PubMed

    Lin, Chia-Ying; Wirtz, Tobias; LaMarca, Frank; Hollister, Scott J

    2007-11-01

    A topology optimized lumbar interbody fusion cage was made of Ti-Al6-V4 alloy by the rapid prototyping process of selective laser melting (SLM) to reproduce designed microstructure features. Radiographic characterizations and the mechanical properties were investigated to determine how the structural characteristics of the fabricated cage were reproduced from design characteristics using micro-computed tomography scanning. The mechanical modulus of the designed cage was also measured to compare with tantalum, a widely used porous metal. The designed microstructures can be clearly seen in the micrographs of the micro-CT and scanning electron microscopy examinations, showing the SLM process can reproduce intricate microscopic features from the original designs. No imaging artifacts from micro-CT were found. The average compressive modulus of the tested caged was 2.97+/-0.90 GPa, which is comparable with the reported porous tantalum modulus of 3 GPa and falls between that of cortical bone (15 GPa) and trabecular bone (0.1-0.5 GPa). The new porous Ti-6Al-4V optimal-structure cage fabricated by SLM process gave consistent mechanical properties without artifactual distortion in the imaging modalities and thus it can be a promising alternative as a porous implant for spine fusion.

  1. Optimization of Cu/activated carbon catalyst in low temperature selective catalytic reduction of NO process using response surface methodology.

    PubMed

    Amanpour, Javad; Salari, Dariush; Niaei, Aligholi; Mousavi, Seyed Mahdi; Panahi, Parvaneh Nakhostin

    2013-01-01

    Preparation of Cu/Activated Carbon (Cu/AC) catalyst was optimized for low temperature selective catalytic reduction of NO by using response surface methodology. A central composite design (CCD) was used to investigate the effects of three independent variables, namely pre-oxidization degree (HNO3%), Cu loading (wt.%) and calcination temperature on NO conversion efficiency. The CCD was consisted of 20 different preparation conditions of Cu/AC catalysts. The prepared catalysts were characterized by XRD and SEM techniques. Predicting NO conversion was carried out using a second order model obtained from designed experiments and statistical software Minitab 14. Regression and Pareto graphic analysis showed that all of the chosen parameters and some interactions were effective on the NO conversion. The optimal values were pre-oxidization in 10.2% HNO3, 6.1 wt.% Cu loading and 480°C for calcination temperature. Under the optimum condition, NO conversion (94.3%) was in a good agreement with predicted value (96.12%).

  2. MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection.

    PubMed

    Doshi, Jimit; Erus, Guray; Ou, Yangming; Resnick, Susan M; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Furth, Susan; Davatzikos, Christos

    2016-02-15

    Atlas-based automated anatomical labeling is a fundamental tool in medical image segmentation, as it defines regions of interest for subsequent analysis of structural and functional image data. The extensive investigation of multi-atlas warping and fusion techniques over the past 5 or more years has clearly demonstrated the advantages of consensus-based segmentation. However, the common approach is to use multiple atlases with a single registration method and parameter set, which is not necessarily optimal for every individual scan, anatomical region, and problem/data-type. Different registration criteria and parameter sets yield different solutions, each providing complementary information. Herein, we present a consensus labeling framework that generates a broad ensemble of labeled atlases in target image space via the use of several warping algorithms, regularization parameters, and atlases. The label fusion integrates two complementary sources of information: a local similarity ranking to select locally optimal atlases and a boundary modulation term to refine the segmentation consistently with the target image's intensity profile. The ensemble approach consistently outperforms segmentations using individual warping methods alone, achieving high accuracy on several benchmark datasets. The MUSE methodology has been used for processing thousands of scans from various datasets, producing robust and consistent results. MUSE is publicly available both as a downloadable software package, and as an application that can be run on the CBICA Image Processing Portal (https://ipp.cbica.upenn.edu), a web based platform for remote processing of medical images.

  3. Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

    PubMed

    Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

    2015-01-01

    In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

  4. Particle Swarm Optimization Based Feature Enhancement and Feature Selection for Improved Emotion Recognition in Speech and Glottal Signals

    PubMed Central

    Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

    2015-01-01

    In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature. PMID:25799141

  5. MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection.

    PubMed

    Doshi, Jimit; Erus, Guray; Ou, Yangming; Resnick, Susan M; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Furth, Susan; Davatzikos, Christos

    2016-02-15

    Atlas-based automated anatomical labeling is a fundamental tool in medical image segmentation, as it defines regions of interest for subsequent analysis of structural and functional image data. The extensive investigation of multi-atlas warping and fusion techniques over the past 5 or more years has clearly demonstrated the advantages of consensus-based segmentation. However, the common approach is to use multiple atlases with a single registration method and parameter set, which is not necessarily optimal for every individual scan, anatomical region, and problem/data-type. Different registration criteria and parameter sets yield different solutions, each providing complementary information. Herein, we present a consensus labeling framework that generates a broad ensemble of labeled atlases in target image space via the use of several warping algorithms, regularization parameters, and atlases. The label fusion integrates two complementary sources of information: a local similarity ranking to select locally optimal atlases and a boundary modulation term to refine the segmentation consistently with the target image's intensity profile. The ensemble approach consistently outperforms segmentations using individual warping methods alone, achieving high accuracy on several benchmark datasets. The MUSE methodology has been used for processing thousands of scans from various datasets, producing robust and consistent results. MUSE is publicly available both as a downloadable software package, and as an application that can be run on the CBICA Image Processing Portal (https://ipp.cbica.upenn.edu), a web based platform for remote processing of medical images. PMID:26679328

  6. Selecting training and test images for optimized anomaly detection algorithms in hyperspectral imagery through robust parameter design

    NASA Astrophysics Data System (ADS)

    Mindrup, Frank M.; Friend, Mark A.; Bauer, Kenneth W.

    2011-06-01

    There are numerous anomaly detection algorithms proposed for hyperspectral imagery. Robust parameter design (RPD) techniques have been applied to some of these algorithms in an attempt to choose robust settings capable of operating consistently across a large variety of image scenes. Typically, training and test sets of hyperspectral images are chosen randomly. Previous research developed a frameworkfor optimizing anomaly detection in HSI by considering specific image characteristics as noise variables within the context of RPD; these characteristics include the Fisher's score, ratio of target pixels and number of clusters. This paper describes a method for selecting hyperspectral image training and test subsets yielding consistent RPD results based on these noise features. These subsets are not necessarily orthogonal, but still provide improvements over random training and test subset assignments by maximizing the volume and average distance between image noise characteristics. Several different mathematical models representing the value of a training and test set based on such measures as the D-optimal score and various distance norms are tested in a simulation experiment.

  7. Conservative Extensions of Linkage Disequilibrium Measures from Pairwise to Multi-loci and Algorithms for Optimal Tagging SNP Selection

    NASA Astrophysics Data System (ADS)

    Tarpine, Ryan; Lam, Fumei; Istrail, Sorin

    We present results on two classes of problems. The first result addresses the long standing open problem of finding unifying principles for Linkage Disequilibrium (LD) measures in population genetics (Lewontin 1964 [10], Hedrick 1987 [8], Devlin and Risch 1995 [5]). Two desirable properties have been proposed in the extensive literature on this topic and the mutual consistency between these properties has remained at the heart of statistical and algorithmic difficulties with haplotype and genome-wide association study analysis. The first axiom is (1) The ability to extend LD measures to multiple loci as a conservative extension of pairwise LD. All widely used LD measures are pairwise measures. Despite significant attempts, it is not clear how to naturally extend these measures to multiple loci, leading to a "curse of the pairwise". The second axiom is (2) The Interpretability of Intermediate Values. In this paper, we resolve this mutual consistency problem by introducing a new LD measure, directed informativeness overrightarrow{I} (the directed graph theoretic counterpart of the informativeness measure introduced by Halldorsson et al. [6]) and show that it satisfies both of the above axioms. We also show the maximum informative subset of tagging SNPs based on overrightarrow{I} can be computed exactly in polynomial time for realistic genome-wide data. Furthermore, we present polynomial time algorithms for optimal genome-wide tagging SNPs selection for a number of commonly used LD measures, under the bounded neighborhood assumption for linked pairs of SNPs. One problem in the area is the search for a quality measure for tagging SNPs selection that unifies the LD-based methods such as LD-select (implemented in Tagger, de Bakker et al. 2005 [4], Carlson et al. 2004 [3]) and the information-theoretic ones such as informativeness. We show that the objective function of the LD-select algorithm is the Minimal Dominating Set (MDS) on r 2-SNP graphs and show that we can

  8. Size-based protocol optimization using automatic tube current modulation and automatic kV selection in computed tomography.

    PubMed

    MacDougall, Robert D; Kleinman, Patricia L; Callahan, Michael J

    2016-01-01

    Size-based diagnostic reference ranges (DRRs) for contrast-enhanced pediatric abdominal computed tomography (CT) have been published in order to establish practical upper and lower limits of CTDI, DLP, and SSDE. Based on these DRRs, guidelines for establishing size-based SSDE target levels from the SSDE of a standard adult by applying a linear correction factor have been published and provide a great reference for dose optimization initiatives. The necessary step of designing manufacturer-specific CT protocols to achieve established SSDE targets is the responsibility of the Qualified Medical Physicist. The task is straightforward if fixed-mA protocols are used, however, more difficult when automatic exposure control (AEC) and automatic kV selection are considered. In such cases, the physicist must deduce the operation of AEC algorithms from technical documentation or through testing, using a wide range of phantom sizes. Our study presents the results of such testing using anthropomorphic phantoms ranging in size from the newborn to the obese adult. The effect of each user-controlled parameter was modeled for a single-manufacturer AEC algorithm (Siemens CARE Dose4D) and automatic kV selection algorithm (Siemens CARE kV). Based on the results presented in this study, a process for designing mA-modulated, pediatric abdominal CT protocols that achieve user-defined SSDE and kV targets is described. PMID:26894344

  9. Selection of HyspIRI optimal band positions for the earth compositional mapping using HyTES data

    NASA Astrophysics Data System (ADS)

    Ullah, Saleem; Khalid, Noora; Iqbal, Arshad

    2016-07-01

    In near future, NASA/JPL will orbit a new space-borne sensor called HyspIRI (Hyperspectral and Infrared Imager) which will cover the spectral range from 0.4 -14μm. Two instruments will be mounted on HyspIRI platform; one is hyperspectral instrument which can sense earth surface between 0.4-2.5μm with 10 nm intervals and a multispectral TIR sensor will acquire images between 3 to 14μm in 8 (1 in MIR and 7 in TIR) spectral bands. The TIR spectral wavebands will be positioned based on their importance in various applications. This study aimed to find HyspIRI optimal TIR wavebands position for earth compositional mapping. Genetic algorithms coupled with Spectral Angle Mapper (GA-SAM) were used as spectral bands selector. High dimensional HyTES (Hyperspectral Thermal Emission Spectrometer) data comprised of 256 spectral bands of Cuprite and Death Valley regions were used to select meaningful subsets of bands for earth compositional mapping. The GA-SAM was trained for eight mineral classes and the algorithms were run iteratively 40 times. High calibration (> 98 %) and validation (> 96 %) accuracies were achieved with limited numbers (seven) of spectral bands selected by GA-SAM. Knowing the important band positions will help scientist of HyspIRI group to place spectral bands at regions were accuracies of earth compositional mapping can be enhanced.

  10. Toward chelerythrine optimization: Analogues designed by molecular simplification exhibit selective growth inhibition in non-small-cell lung cancer cells.

    PubMed

    Yang, Rosania; Tavares, Maurício T; Teixeira, Sarah F; Azevedo, Ricardo A; C Pietro, Diego; Fernandes, Thais B; Ferreira, Adilson K; Trossini, Gustavo H G; Barbuto, José A M; Parise-Filho, Roberto

    2016-10-01

    A series of novel chelerythrine analogues was designed and synthesized. Antitumor activity was evaluated against A549, NCI-H1299, NCI-H292, and NCI-H460 non-small-cell lung cancer (NSCLC) cell lines in vitro. The selectivity of the most active analogues and chelerythrine was also evaluated, and we compared their cytotoxicity in NSCLC cells and non-tumorigenic cell lines, including human umbilical vein endothelial cells (HUVECs) and LL24 human lung fibroblasts. In silico studies were performed to establish structure-activity relationships between chelerythrine and the analogues. The results showed that analogue compound 3f induced significant dose-dependent G0/G1 cell cycle arrest in A549 and NCI-H1299 cells. Theoretical studies indicated that the molecular arrangement and electron characteristics of compound 3f were closely related to the profile of chelerythrine, supporting its activity. The present study presents a new and simplified chelerythrinoid scaffold with enhanced selectivity against NSCLC tumor cells for further optimization. PMID:27561984

  11. Microcultures of lactic acid bacteria: characterization and selection of strains, optimization of nutrients and gallic acid concentration.

    PubMed

    Guzmán-López, Oswaldo; Loera, Octavio; Parada, José Luis; Castillo-Morales, Alberto; Martínez-Ramírez, Cándida; Augur, Christopher; Gaime-Perraud, Isabelle; Saucedo-Castañeda, Gerardo

    2009-01-01

    Eighteen lactic acid bacteria (LAB) strains, isolated from coffee pulp silages were characterized according to both growth and gallic acid (GA) consumption. Prussian blue method was adapted to 96-well microplates to quantify GA in LAB microcultures. Normalized data of growth and GA consumption were used to characterize strains into four phenotypes. A number of 5 LAB strains showed more than 60% of tolerance to GA at 2 g/l; whereas at 10 g/l GA growth inhibition was detected to a different extent depending on each strain, although GA consumption was observed in seven studied strains (>60%). Lactobacillus plantarum L-08 was selected for further studies based on its capacity to degrade GA at 10 g/l (97%). MRS broth and GA concentrations were varied to study the effect on growth of LAB. Cell density and growth rate were optimized by response surface methodology and kinetic analysis. Maximum growth was attained after 7.5 h of cultivation, with a dilution factor of 1-1/2 and a GA concentration between 0.625 and 2.5 g/l. Results indicated that the main factor affecting LAB growth was GA concentration. The main contribution of this study was to propose a novel adaptation of a methodology to characterize and select LAB strains with detoxifying potential of simple phenolics based on GA consumption and tolerance. In addition, the methodology presented in this study integrated the well-known RSM with an experimental design based on successive dilutions.

  12. [Method selected for the determination of creatinine in plasma or serum. Choice of optimal conditions of measurement].

    PubMed

    Labbé, D; Vassault, A; Cherruau, B; Baltassat, P; Bonète, R; Carroger, G; Costantini, A; Guérin, S; Houot, O; Lacour, B; Nicolas, A; Thioulouse, E; Trépo, D

    1996-01-01

    The method selected by the SFBC (Société française de biologie clinique) is derived from the colorimetric reaction of creatinine with alkaline picrate, measured kinetically, without any pretreatment step. The key parameters of the reaction determining the quality of the results are studied, with special regard to samples including known interferents. The aims of the study were to gain an optimal analytical sensitivity and to reduce main interferences (acetoacetate, bilirubine, glucose, protein) which plague the Jaffé reaction, through a comprehensive study of the reagents, of their concentrations and of the analytical procedures. The selected concentrations (in the test) are: 150 mmol/L sodium hydroxide, 10 mmol/L picric acid and 2 g/L sodium dodecyl sulfate. Ten millilitres of a BRIJ solution (30% volvol) are added to the reagent. The operating procedures are as follow: sample ratio 0.07 to 0.08; wavelength 505 to 510 nm; temperature 37 degrees C; incubation of the specimen with the alkaline reagent 5 mn (at least), before starting the reaction with picric acid. A seric calibrator is recommended. The first measurement is taken 20 to 40 s after starting the reaction. Total measurement time is 120 to 150 seconds.

  13. SU-E-I-60: The Correct Selection of Pitch and Rotation Time for Optimal CT Scanning : The Big Misconception

    SciTech Connect

    Ranallo, F; Szczykutowicz, T

    2014-06-01

    Purpose: To provide correct guidance in the proper selection of pitch and rotation time for optimal CT imaging with multi-slice scanners. Methods: There exists a widespread misconception concerning the role of pitch in patient dose with modern multi-slice scanners, particularly with the use of mA modulation techniques. We investigated the relationship of pitch and rotation time to image quality, dose, and scan duration, with CT scanners from different manufacturers in a way that clarifies this misconception. This source of this misconception may concern the role of pitch in single slice CT scanners. Results: We found that the image noise and dose are generally independent of the selected effective mAs (mA*time/ pitch) with manual mA technique settings and are generally independent of the selected pitch and /or rotation time with automatic mA modulation techniques. However we did find that on certain scanners the use of a pitch just above 0.5 provided images of equal image noise at a lower dose compared to the use of a pitch just below 1.0. Conclusion: The misconception that the use of a lower pitch over-irradiates patients by wasting dose is clearly false. The use of a lower pitch provides images of equal or better image quality at the same patient dose, whether using manual mA or automatic mA modulation techniques. By decreasing the pitch and the rotation times by equal amounts, both helical and patient motion artifacts can be reduced without affecting the exam time. The use of lower helical pitch also allows better scanning of larger patients by allowing a greater scan effective mAs, if the exam time can be extended. The one caution with the use of low pitch is not related to patient dose, but to the length of the scan time if the rotation time is not set short enough. Partial Research funding from GE HealthCare.

  14. The Cord Blood Apgar: a novel scoring system to optimize selection of banked cord blood grafts for transplantation

    PubMed Central

    Page, Kristin M.; Zhang, Lijun; Mendizabal, Adam; Wease, Stephen; Carter, Shelly; Shoulars, Kevin; Gentry, Tracy; Balber, Andrew E.; Kurtzberg, Joanne

    2012-01-01

    BACKGROUND Engraftment failure and delays, likely due to diminished cord blood unit (CBU) potency, remain major barriers to the overall success of unrelated umbilical cord blood transplantation (UCBT). To address this problem, we developed and retrospectively validated a novel scoring system, the Cord Blood Apgar (CBA), which is predictive of engraftment after UCBT. STUDY DESIGN AND METHODS In a single-center retrospective study, utilizing a database of 435 consecutive single cord myeloablative UCBTs performed between January 1, 2000, to December 31, 2008, precryopreservation and postthaw graft variables (total nucleated cell, CD34+, colony-forming units, mononuclear cell content, and volume) were initially correlated with neutrophil engraftment. Subsequently, based on the magnitude of hazard ratios (HRs) in univariate analysis, a weighted scoring system to predict CBU potency was developed using a randomly selected training data set and internally validated on the remaining data set. RESULTS The CBA assigns transplanted CBUs three scores: a precryopreservation score (PCS), a postthaw score (PTS), and a composite score (CS), which incorporates the PCS and PTS values. CBA-PCS scores, which could be used for initial unit selection, were predictive of neutrophil (CBA-PCS ≥ 7.75 vs. <7.75, HR 3.5; p < 0.0001) engraftment. Likewise, CBA-PTS and CS scores were strongly predictive of Day 42 neutrophil engraftment (CBA-PTS ≥ 9.5 vs. <9.5, HR 3.16, p < 0.0001; CBA-CS ≥ 17.75 vs. <17.75, HR 4.01, p < 0.0001). CONCLUSION The CBA is strongly predictive of engraftment after UCBT and shows promise for optimizing screening of CBU donors for transplantation. In the future, a segment could be assayed for the PTS score providing data to apply the CS for final CBU selection. PMID:21810098

  15. Reducing residual stresses and deformations in selective laser melting through multi-level multi-scale optimization of cellular scanning strategy

    NASA Astrophysics Data System (ADS)

    Mohanty, Sankhya; Hattel, Jesper H.

    2016-04-01

    Residual stresses and deformations continue to remain one of the primary challenges towards expanding the scope of selective laser melting as an industrial scale manufacturing process. While process monitoring and feedback-based process control of the process has shown significant potential, there is still dearth of techniques to tackle the issue. Numerical modelling of selective laser melting process has thus been an active area of research in the last few years. However, large computational resource requirements have slowed the usage of these models for optimizing the process. In this paper, a calibrated, fast, multiscale thermal model coupled with a 3D finite element mechanical model is used to simulate residual stress formation and deformations during selective laser melting. The resulting reduction in thermal model computation time allows evolutionary algorithm-based optimization of the process. A multilevel optimization strategy is adopted using a customized genetic algorithm developed for optimizing cellular scanning strategy for selective laser melting, with an objective of reducing residual stresses and deformations. The resulting thermo-mechanically optimized cellular scanning strategies are compared with standard scanning strategies and have been used to manufacture standard samples.

  16. Optimization of Cat's Whiskers Tea (Orthosiphon stamineus) Using Supercritical Carbon Dioxide and Selective Chemotherapeutic Potential against Prostate Cancer Cells

    PubMed Central

    Al-Suede, Fouad Saleih R.; Khadeer Ahamed, Mohamed B.; Abdul Majid, Aman S.; Baharetha, Hussin M.; Hassan, Loiy E. A.; Kadir, Mohd Omar A.; Nassar, Zeyad D.; Abdul Majid, Amin M. S.

    2014-01-01

    Cat's whiskers (Orthosiphon stamineus) leaves extracts were prepared using supercritical CO2 (SC-CO2) with full factorial design to determine the optimum extraction parameters. Nine extracts were obtained by varying pressure, temperature, and time. The extracts were analysed using FTIR, UV-Vis, and GC-MS. Cytotoxicity of the extracts was evaluated on human (colorectal, breast, and prostate) cancer and normal fibroblast cells. Moderate pressure (31.1 MPa) and temperature (60°C) were recorded as optimum extraction conditions with high yield (1.74%) of the extract (B2) at 60 min extraction time. The optimized extract (B2) displayed selective cytotoxicity against prostate cancer (PC3) cells (IC50 28 µg/mL) and significant antioxidant activity (IC50 42.8 µg/mL). Elevated levels of caspases 3/7 and 9 in B2-treated PC3 cells suggest the induction of apoptosis through nuclear and mitochondrial pathways. Hoechst and rhodamine assays confirmed the nuclear condensation and disruption of mitochondrial membrane potential in the cells. B2 also demonstrated inhibitory effects on motility and colonies of PC3 cells at its subcytotoxic concentrations. It is noteworthy that B2 displayed negligible toxicity against the normal cells. Chemometric analysis revealed high content of essential oils, hydrocarbon, fatty acids, esters, and aromatic sesquiterpenes in B2. This study highlights the therapeutic potentials of SC-CO2 extract of cat's whiskers in targeting prostate carcinoma. PMID:25276215

  17. An experimental transplantation to select the optimal site for restoration of the eelgrass Zostera marina in the Taehwa River estuary

    NASA Astrophysics Data System (ADS)

    Park, Jung-Im; Kim, Jeong Bae; Lee, Kun-Seop; Son, Min Ho

    2013-12-01

    To select the optimal site for the restoration of seagrass habitats in the Taehwa River estuary, we transplanted the eelgrass Zostera marina to three potential candidate sites in March 2007 and monitored the transplanted seagrass and associated environmental factors for six months. In all three sites, the transplanted seagrasses exhibited no initial morphological loss due to transplanting stress. The transplanted seagrass communities at sites 2 and 3 showed more than a 180% increase in density over the entire survey period. In contrast, despite a density increase in the first month after transplantation, most of the transplanted seagrasses at site 1 died. This may be due to the large decrease in underwater irradiance reaching the seagrass leaves at site 1 for two months during June and July, which fell below the level of compensation irradiance. The growth rate and size of the seagrass shoots were also larger at sites 2 and 3 compared with site 1. This is probably due to higher nutrient concentrations in the sediment pore water at sites 2 and 3 compared with site 1, although water depth, salinity, and the nutrient concentrations in the water columns from the three sites were similar. Therefore, for the restoration of seagrass habitats in the Taehwa River estuary, sites 2 and 3 were preferable to site 1 as transplantation sites.

  18. Synthesis and Assessment of DNA/Silver Nanoclusters Probes for Optimal and Selective Detection of Tristeza Virus Mild Strains.

    PubMed

    Shokri, Ehsan; Hosseini, Morteza; Faridbod, Farnoush; Rahaie, Mahdi

    2016-09-01

    Citrus Tristeza virus (CTV) is one of the most destructive pathogens worldwide that exist as a mixture of malicious (Sever) and tolerable (Mild) strains. Mild strains of CTV can be used to immunize healthy plants from more Severe strains damage. Recently, innovative methods based on the fluorescent properties of DNA/silver nanoclusters have been developed for molecular detection purposes. In this study, a simple procedure was followed to create more active DNA/AgNCs probe for accurate and selective detection of Tristeza Mild-RNA. To this end, four distinct DNA emitter scaffolds (C12, Red, Green, Yellow) were tethered to the Mild capture sequence and investigated in various buffers in order to find highly emissive combinations. Then, to achieve specific and reliable results, several chemical additives, including organic solvents, PEG and organo-soluble salts were used to enhance control fluorescence signals and optimize the hybridization solution. The data showed that, under adjusted conditions, the target sensitivity is enhanced by a factor of five and the high discrimination between Mild and Severe RNAs were obtained. The emission ratio of the DNA/AgNCs was dropped in the presence of target RNAs and I0/I intensity linearly ranged from 1.5 × 10(-8) M to 1.8 × 10(-6) M with the detection limit of 4.3 × 10(-9) M. PMID:27349801

  19. Self-Regulation among Youth in Four Western Cultures: Is There an Adolescence-Specific Structure of the Selection-Optimization-Compensation (SOC) Model?

    ERIC Educational Resources Information Center

    Gestsdottir, Steinunn; Geldhof, G. John; Paus, Tomáš; Freund, Alexandra M.; Adalbjarnardottir, Sigrun; Lerner, Jacqueline V.; Lerner, Richard M.

    2015-01-01

    We address how to conceptualize and measure intentional self-regulation (ISR) among adolescents from four cultures by assessing whether ISR (conceptualized by the SOC model of Selection, Optimization, and Compensation) is represented by three factors (as with adult samples) or as one "adolescence-specific" factor. A total of 4,057 14-…

  20. Genome-wide characterization and selection of expressed sequence tag simple sequence repeat primers for optimized marker distribution and reliability in peach

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Expressed sequence tag (EST) simple sequence repeats (SSRs) in Prunus were mined, and flanking primers designed and used for genome-wide characterization and selection of primers to optimize marker distribution and reliability. A total of 12,618 contigs were assembled from 84,727 ESTs, along with 34...

  1. Selection, Optimization, and Compensation: The Structure, Reliability, and Validity of Forced-Choice versus Likert-Type Measures in a Sample of Late Adolescents

    ERIC Educational Resources Information Center

    Geldhof, G. John; Gestsdottir, Steinunn; Stefansson, Kristjan; Johnson, Sara K.; Bowers, Edmond P.; Lerner, Richard M.

    2015-01-01

    Intentional self-regulation (ISR) undergoes significant development across the life span. However, our understanding of ISR's development and function remains incomplete, in part because the field's conceptualization and measurement of ISR vary greatly. A key sample case involves how Baltes and colleagues' Selection, Optimization,…

  2. Selecting optimal monitoring site locations for peak ambient particulate material concentrations using the MM5-CAMx4 numerical modelling system.

    PubMed

    Sturman, Andrew; Titov, Mikhail; Zawar-Reza, Peyman

    2011-01-15

    Installation of temporary or long term monitoring sites is expensive, so it is important to rationally identify potential locations that will achieve the requirements of regional air quality management strategies. A simple, but effective, numerical approach to selecting ambient particulate matter (PM) monitoring site locations has therefore been developed using the MM5-CAMx4 air pollution dispersion modelling system. A new method, 'site efficiency,' was developed to assess the ability of any monitoring site to provide peak ambient air pollution concentrations that are representative of the urban area. 'Site efficiency' varies from 0 to 100%, with the latter representing the most representative site location for monitoring peak PM concentrations. Four heavy pollution episodes in Christchurch (New Zealand) during winter 2005, representing 4 different aerosol dispersion patterns, were used to develop and test this site assessment technique. Evaluation of the efficiency of monitoring sites was undertaken for night and morning aerosol peaks for 4 different particulate material (PM) spatial patterns. The results demonstrate that the existing long term monitoring site at Coles Place is quite well located, with a site efficiency value of 57.8%. A temporary ambient PM monitoring site (operating during winter 2006) showed a lower ability to capture night and morning peak aerosol concentrations. Evaluation of multiple site locations used during an extensive field campaign in Christchurch (New Zealand) in 2000 indicated that the maximum efficiency achieved by any site in the city would be 60-65%, while the efficiency of a virtual background site is calculated to be about 7%. This method of assessing the appropriateness of any potential monitoring site can be used to optimize monitoring site locations for any air pollution measurement programme.

  3. Codon optimization of genes for efficient protein expression in mammalian cells by selection of only preferred human codons.

    PubMed

    Inouye, Satoshi; Sahara-Miura, Yuiko; Sato, Jun-ichi; Suzuki, Takahiro

    2015-05-01

    A simple design method for codon optimization of genes to express a heterologous protein in mammalian cells is described. Codon optimization was performed by choosing only codons preferentially used in humans and with over 60% GC content, and the method was named the "preferred human codon-optimized method." To test our simple rule for codon optimization, the preferred human codon-optimized genes for six proteins containing photoproteins (aequorin and clytin II) and luciferases (Gaussia luciferase, Renilla luciferase, and firefly luciferases from Photinus pyralis and Luciola cruciata) were chemically synthesized and transiently expressed in Chinese hamster ovary-K1 cells. All preferred human codon-optimized genes showed higher luminescence activity than the corresponding wild-type genes. Our simple design method could be used to improve protein expression in mammalian cells efficiently.

  4. Pulse-fluence-specified optimal control simulation with applications to molecular orientation and spin-isomer-selective molecular alignment

    SciTech Connect

    Yoshida, Masataka; Nakashima, Kaoru; Ohtsuki, Yukiyoshi

    2015-12-31

    We propose an optimal control simulation with specified pulse fluence and amplitude. The simulation is applied to the orientation control of CO molecules to examine the optimal combination of THz and laser pulses, and to discriminate nuclear-spin isomers of {sup 14}N{sub 2} as spatially anisotropic distributions.

  5. A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

    PubMed

    Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

    2016-09-01

    In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

  6. A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

    PubMed

    Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

    2016-09-01

    In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

  7. Data-driven input variable selection for rainfall-runoff modeling using binary-coded particle swarm optimization and Extreme Learning Machines

    NASA Astrophysics Data System (ADS)

    Taormina, Riccardo; Chau, Kwok-Wing

    2015-10-01

    Selecting an adequate set of inputs is a critical step for successful data-driven streamflow prediction. In this study, we present a novel approach for Input Variable Selection (IVS) that employs Binary-coded discrete Fully Informed Particle Swarm optimization (BFIPS) and Extreme Learning Machines (ELM) to develop fast and accurate IVS algorithms. A scheme is employed to encode the subset of selected inputs and ELM specifications into the binary particles, which are evolved using single objective and multi-objective BFIPS optimization (MBFIPS). The performances of these ELM-based methods are assessed using the evaluation criteria and the datasets included in the comprehensive IVS evaluation framework proposed by Galelli et al. (2014). From a comparison with 4 major IVS techniques used in their original study it emerges that the proposed methods compare very well in terms of selection accuracy. The best performers were found to be (1) a MBFIPS-ELM algorithm based on the concurrent minimization of an error function and the number of selected inputs, and (2) a BFIPS-ELM algorithm based on the minimization of a variant of the Akaike Information Criterion (AIC). The first technique is arguably the most accurate overall, and is able to reach an almost perfect specification of the optimal input subset for a partially synthetic rainfall-runoff experiment devised for the Kentucky River basin. In addition, MBFIPS-ELM allows for the determination of the relative importance of the selected inputs. On the other hand, the BFIPS-ELM is found to consistently reach high accuracy scores while being considerably faster. By extrapolating the results obtained on the IVS test-bed, it can be concluded that the proposed techniques are particularly suited for rainfall-runoff modeling applications characterized by high nonlinearity in the catchment dynamics.

  8. Discovery of selective 4-Amino-pyridopyrimidine inhibitors of MAP4K4 using fragment-based lead identification and optimization.

    PubMed

    Crawford, Terry D; Ndubaku, Chudi O; Chen, Huifen; Boggs, Jason W; Bravo, Brandon J; Delatorre, Kelly; Giannetti, Anthony M; Gould, Stephen E; Harris, Seth F; Magnuson, Steven R; McNamara, Erin; Murray, Lesley J; Nonomiya, Jim; Sambrone, Amy; Schmidt, Stephen; Smyczek, Tanya; Stanley, Mark; Vitorino, Philip; Wang, Lan; West, Kristina; Wu, Ping; Ye, Weilan

    2014-04-24

    Mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4) is a serine/threonine kinase implicated in the regulation of many biological processes. A fragment-based lead discovery approach was used to generate potent and selective MAP4K4 inhibitors. The fragment hit pursued in this article had excellent ligand efficiency (LE), an important attribute for subsequent successful optimization into drug-like lead compounds. The optimization efforts eventually led us to focus on the pyridopyrimidine series, from which 6-(2-fluoropyridin-4-yl)pyrido[3,2-d]pyrimidin-4-amine (29) was identified. This compound had low nanomolar potency, excellent kinase selectivity, and good in vivo exposure, and demonstrated in vivo pharmacodynamic effects in a human tumor xenograft model.

  9. A framework for joint modeling and joint assessment of efficacy and safety endpoints for probability of success evaluation and optimal dose selection.

    PubMed

    He, Weili; Cao, Xiting; Xu, Lu

    2012-02-28

    The evaluation of clinical proof of concept, optimal dose selection, and phase III probability of success has traditionally been conducted by a subjective and qualitative assessment of the efficacy and safety data. This, in part, was responsible for the numerous failed phase III programs in the past. The need to utilize more quantitative approaches to assess efficacy and safety profiles has never been greater. In this paper, we propose a framework that incorporates efficacy and safety data simultaneously for the joint evaluation of clinical proof of concept, optimal dose selection, and phase III probability of success. Simulation studies were conducted to evaluate the properties of our proposed methods. The proposed approach was applied to two real clinical studies. On the basis of the true outcome of the two clinical studies, the assessment based on our proposed approach suggested a reasonable path forward for both clinical programs.

  10. Demonstration optimization analyses of pumping from selected Arapahoe aquifer municipal wells in the west-central Denver Basin, Colorado, 2010–2109

    USGS Publications Warehouse

    Banta, Edward R.; Paschke, Suzanne S.

    2012-01-01

    Declining water levels caused by withdrawals of water from wells in the west-central part of the Denver Basin bedrock-aquifer system have raised concerns with respect to the ability of the aquifer system to sustain production. The Arapahoe aquifer in particular is heavily used in this area. Two optimization analyses were conducted to demonstrate approaches that could be used to evaluate possible future pumping scenarios intended to prolong the productivity of the aquifer and to delay excessive loss of saturated thickness. These analyses were designed as demonstrations only, and were not intended as a comprehensive optimization study. Optimization analyses were based on a groundwater-flow model of the Denver Basin developed as part of a recently published U.S. Geological Survey groundwater-availability study. For each analysis an optimization problem was set up to maximize total withdrawal rate, subject to withdrawal-rate and hydraulic-head constraints, for 119 selected municipal water-supply wells located in 96 model cells. The optimization analyses were based on 50- and 100-year simulations of groundwater withdrawals. The optimized total withdrawal rate for all selected wells for a 50-year simulation time was about 58.8 cubic feet per second. For an analysis in which the simulation time and head-constraint time were extended to 100 years, the optimized total withdrawal rate for all selected wells was about 53.0 cubic feet per second, demonstrating that a reduction in withdrawal rate of about 10 percent may extend the time before the hydraulic-head constraints are violated by 50 years, provided that pumping rates are optimally distributed. Analysis of simulation results showed that initially, the pumping produces water primarily by release of water from storage in the Arapahoe aquifer. However, because confining layers between the Denver and Arapahoe aquifers are thin, in less than 5 years, most of the water removed by managed-flows pumping likely would be supplied

  11. Optimal kVp selection for dual-energy imaging of the chest: Evaluation by task-specific observer preference tests

    SciTech Connect

    Williams, D. B.; Siewerdsen, J. H.; Tward, D. J.; Paul, N. S.; Dhanantwari, A. C.; Shkumat, N. A.; Richard, S.; Yorkston, J.; Van Metter, R.

    2007-10-15

    Human observer performance tests were conducted to identify optimal imaging techniques in dual-energy (DE) imaging of the chest with respect to a variety of visualization tasks for soft and bony tissue. Specifically, the effect of kVp selection in low- and high-energy projection pairs was investigated. DE images of an anthropomorphic chest phantom formed the basis for observer studies, decomposed from low-energy and high-energy projections in the range 60-90 kVp and 120-150 kVp, respectively, with total dose for the DE image equivalent to that of a single chest radiograph. Five expert radiologists participated in observer preference tests to evaluate differences in image quality among the DE images. For visualization of soft-tissue structures in the lung, the [60/130] kVp pair provided optimal image quality, whereas [60/140] kVp proved optimal for delineation of the descending aorta in the retrocardiac region. Such soft-tissue detectability tasks exhibited a strong dependence on the low-kVp selection (with 60 kVp providing maximum soft-tissue conspicuity) and a weaker dependence on the high-kVp selection (typically highest at 130-140 kVp). Qualitative examination of DE bone-only images suggests optimal bony visualization at a similar technique, viz., [60/140] kVp. Observer preference was largely consistent with quantitative analysis of contrast, noise, and contrast-to-noise ratio, with subtle differences likely related to the imaging task and spatial-frequency characteristics of the noise. Observer preference tests offered practical, semiquantitative identification of optimal, task-specific imaging techniques and will provide useful guidance toward clinical implementation of high-performance DE imaging systems.

  12. Method for optimizing output in ultrashort-pulse multipass laser amplifiers with selective use of a spectral filter

    DOEpatents

    Backus, Sterling J.; Kapteyn, Henry C.

    2007-07-10

    A method for optimizing multipass laser amplifier output utilizes a spectral filter in early passes but not in later passes. The pulses shift position slightly for each pass through the amplifier, and the filter is placed such that early passes intersect the filter while later passes bypass it. The filter position may be adjust offline in order to adjust the number of passes in each category. The filter may be optimized for use in a cryogenic amplifier.

  13. Optimized precursor ion selection for labile ions in a linear ion trap mass spectrometer and its impact on quantification using selected reaction monitoring.

    PubMed

    Lee, Hyun-Seok; Shin, Kyong-Oh; Jo, Sung-Chan; Lee, Yong-Moon; Yim, Yong-Hyeon

    2014-12-01

    The fragmentation of fragile ions during the application of an isolation waveform for precursor ion selection and the resulting loss of isolated ion intensity is well-known in ion trap mass spectrometry (ITMS). To obtain adequate ion intensity in the selected reaction monitoring (SRM) of fragile precursor ions, a wider ion isolation width is required. However, the increased isolation width significantly diminishes the selectivity of the channels chosen for SRM, which is a serious problem for samples with complex matrices. The sensitive and selective quantification of many lipid molecules, including ceramides from real biological samples, using a linear ion trap mass spectrometer is also hindered by the same problem because of the ease of water loss from protonated ceramide ions. In this study, a method for the reliable quantification of ceramides using SRM with near unity precursor ion isolation has been developed for ITMS by utilizing alternative precursor ions generated by in-source dissociation. The selected precursor ions allow the isolation of ions with unit mass width and the selective analysis of ceramides using SRM with negligible loss of sensitivity. The quantification of C18:0-, C24:0- and C24:1-ceramides using the present method shows excellent linearity over the concentration ranges from 6 to 100, 25 to 1000 and 25 to 1000 nM, respectively. The limits of detection of C18:0-, C24:0- and C24:1-ceramides were 0.25, 0.25 and 5 fmol, respectively. The developed method was successfully applied to quantify ceramides in fetal bovine serum.

  14. A mathematical approach to optimal selection of dose values in the additive dose method of ERP dosimetry

    SciTech Connect

    Hayes, R.B.; Haskell, E.H.; Kenner, G.H.

    1996-01-01

    Additive dose methods commonly used in electron paramagnetic resonance (EPR) dosimetry are time consuming and labor intensive. We have developed a mathematical approach for determining optimal spacing of applied doses and the number of spectra which should be taken at each dose level. Expected uncertainitites in the data points are assumed to be normally distributed with a fixed standard deviation and linearity of dose response is also assumed. The optimum spacing and number of points necessary for the minimal error can be estimated, as can the likely error in the resulting estimate. When low doses are being estimated for tooth enamel samples the optimal spacing is shown to be a concentration of points near the zero dose value with fewer spectra taken at a single high dose value within the range of known linearity. Optimization of the analytical process results in increased accuracy and sample throughput.

  15. Multifactorial optimization approach for the determination of polycyclic aromatic hydrocarbons in river sediments by gas chromatography-quadrupole ion trap selected ion storage mass spectrometry.

    PubMed

    Leite, Natalicio Ferreira; Peralta-Zamora, Patricio; Grassi, Marco Tadeu

    2008-05-30

    A procedure for the determination of very low polycyclic aromatic hydrocarbons (PAHs) concentrations in sediment samples has been developed by gas chromatography-quadrupole ion trap mass spectrometry (GC-QIT MS) after extraction with dichloromethane and purification by using silica gel cleanup. Identification and quantification of analytes were based on the selected ion storage (SIS) strategy using deuterated PAHs as internal standards. In order to search out the main factors affecting the SIS mass spectrometry efficiency, four MS parameters, including target total ion count (TTIC), waveform amplitude (WA), transfer line (XLT) and ion trap temperatures (ITT) were subjected to a complete multifactorial design. The most relevant parameters obtained (TTIC and WA) were optimized by a rotatable and orthogonal composite design. Optimum values for these parameters were selected for the development of the method involving PAH determination in sediment samples. The optimized method exhibited a range of 111-760% higher signal-to-noise (S/N) ratios for PAHs in comparison with the method operated by the default conditions, demonstrating that the multifactorial optimization contributed to substantially improve the sensitivity of the GC-QIT MS determination. The accuracy of the method was verified by analyzing NWRI EC-3 certified reference material (Lake Ontario sediment). The selectivity, sensitivity (limits of quantification were in the range of 0.02-11.0 ng g(-1)), accuracy (recoveries >or=77%) and precision (RSDselected sediment samples were analyzed, one from the Canguiri River (a slightly urbanized area), and the other from the Iguaçu River (a heavily urbanized area), illustrating the capabilities of the method to detect PAHs at the

  16. Salicornia as a crop plant in temperate regions: selection of genetically characterized ecotypes and optimization of their cultivation conditions.

    PubMed

    Singh, Devesh; Buhmann, Anne K; Flowers, Tim J; Seal, Charlotte E; Papenbrock, Jutta

    2014-01-01

    Rising sea levels and salinization of groundwater due to global climate change result in fast-dwindling sources of freshwater. Therefore, it is important to find alternatives to grow food crops and vegetables. Halophytes are naturally evolved salt-tolerant plants that are adapted to grow in environments that inhibit the growth of most glycophytic crop plants substantially. Members of the Salicornioideae are promising candidates for saline agriculture due to their high tolerance to salinity. Our aim was to develop genetically characterized lines of Salicornia and Sarcocornia for further breeding and to determine optimal cultivation conditions. To obtain a large and diverse genetic pool, seeds were collected from different countries and ecological conditions. The external transcribed spacer (ETS) sequence of 62 Salicornia and Sarcocornia accessions was analysed: ETS sequence data showed a clear distinction between the two genera and between different Salicornia taxa. However, in some cases the ETS was not sufficiently variable to resolve morphologically distinct species. For the determination of optimal cultivation conditions, experiments on germination, seedling establishment and growth to a harvestable size were performed using different accessions of Salicornia spp. Experiments revealed that the percentage germination was greatest at lower salinities and with temperatures of 20/10 °C (day/night). Salicornia spp. produced more harvestable biomass in hydroponic culture than in sand culture, but the nutrient concentration requires optimization as hydroponically grown plants showed symptoms of stress. Salicornia ramosissima produced more harvestable biomass than Salicornia dolichostachya in artificial sea water containing 257 mM NaCl. Based on preliminary tests on ease of cultivation, gain in biomass, morphology and taste, S. dolichostachya was investigated in more detail, and the optimal salinity for seedling establishment was found to be 100 mM. Harvesting of S

  17. Salicornia as a crop plant in temperate regions: selection of genetically characterized ecotypes and optimization of their cultivation conditions

    PubMed Central

    Singh, Devesh; Buhmann, Anne K.; Flowers, Tim J.; Seal, Charlotte E.; Papenbrock, Jutta

    2014-01-01

    Rising sea levels and salinization of groundwater due to global climate change result in fast-dwindling sources of freshwater. Therefore, it is important to find alternatives to grow food crops and vegetables. Halophytes are naturally evolved salt-tolerant plants that are adapted to grow in environments that inhibit the growth of most glycophytic crop plants substantially. Members of the Salicornioideae are promising candidates for saline agriculture due to their high tolerance to salinity. Our aim was to develop genetically characterized lines of Salicornia and Sarcocornia for further breeding and to determine optimal cultivation conditions. To obtain a large and diverse genetic pool, seeds were collected from different countries and ecological conditions. The external transcribed spacer (ETS) sequence of 62 Salicornia and Sarcocornia accessions was analysed: ETS sequence data showed a clear distinction between the two genera and between different Salicornia taxa. However, in some cases the ETS was not sufficiently variable to resolve morphologically distinct species. For the determination of optimal cultivation conditions, experiments on germination, seedling establishment and growth to a harvestable size were performed using different accessions of Salicornia spp. Experiments revealed that the percentage germination was greatest at lower salinities and with temperatures of 20/10 °C (day/night). Salicornia spp. produced more harvestable biomass in hydroponic culture than in sand culture, but the nutrient concentration requires optimization as hydroponically grown plants showed symptoms of stress. Salicornia ramosissima produced more harvestable biomass than Salicornia dolichostachya in artificial sea water containing 257 mM NaCl. Based on preliminary tests on ease of cultivation, gain in biomass, morphology and taste, S. dolichostachya was investigated in more detail, and the optimal salinity for seedling establishment was found to be 100 mM. Harvesting of S

  18. Optimal selection of autoregressive model coefficients for early damage detectability with an application to wind turbine blades

    NASA Astrophysics Data System (ADS)

    Hoell, Simon; Omenzetter, Piotr

    2016-03-01

    Data-driven vibration-based damage detection techniques can be competitive because of their lower instrumentation and data analysis costs. The use of autoregressive model coefficients (ARMCs) as damage sensitive features (DSFs) is one such technique. So far, like with other DSFs, either full sets of coefficients or subsets selected by trial-and-error have been used, but this can lead to suboptimal composition of multivariate DSFs and decreased damage detection performance. This study enhances the selection of ARMCs for statistical hypothesis testing for damage presence. Two approaches for systematic ARMC selection, based on either adding or eliminating the coefficients one by one or using a genetic algorithm (GA) are proposed. The methods are applied to a numerical model of an aerodynamically excited large composite wind turbine blade with disbonding damage. The GA out performs the other selection methods and enables building multivariate DSFs that markedly enhance early damage detectability and are insensitive to measurement noise.

  19. Optimal Wavelengths Selection Using Hierarchical Evolutionary Algorithm for Prediction of Firmness and Soluble Solids Content in Apples

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral scattering is a promising technique for rapid and noninvasive measurement of multiple quality attributes of apple fruit. A hierarchical evolutionary algorithm (HEA) approach, in combination with subspace decomposition and partial least squares (PLS) regression, was proposed to select o...

  20. Systematic optimization of an engineered hydrogel allows for selective control of human neural stem cell survival and differentiation after transplantation in the stroke brain.

    PubMed

    Moshayedi, Pouria; Nih, Lina R; Llorente, Irene L; Berg, Andrew R; Cinkornpumin, Jessica; Lowry, William E; Segura, Tatiana; Carmichael, S Thomas

    2016-10-01

    Stem cell therapies have shown promise in promoting recovery in stroke but have been limited by poor cell survival and differentiation. We have developed a hyaluronic acid (HA)-based self-polymerizing hydrogel that serves as a platform for adhesion of structural motifs and a depot release for growth factors to promote transplant stem cell survival and differentiation. We took an iterative approach in optimizing the complex combination of mechanical, biochemical and biological properties of an HA cell scaffold. First, we optimized stiffness for a minimal reaction of adjacent brain to the transplant. Next hydrogel crosslinkers sensitive to matrix metalloproteinases (MMP) were incorporated as they promoted vascularization. Finally, candidate adhesion motifs and growth factors were systemically changed in vitro using a design of experiment approach to optimize stem cell survival or proliferation. The optimized HA hydrogel, tested in vivo, promoted survival of encapsulated human neural progenitor cells (iPS-NPCs) after transplantation into the stroke core and differentially tuned transplanted cell fate through the promotion of glial, neuronal or immature/progenitor states. This HA hydrogel can be tracked in vivo with MRI. A hydrogel can serve as a therapeutic adjunct in a stem cell therapy through selective control of stem cell survival and differentiation in vivo. PMID:27521617

  1. Discovery and optimization of new benzimidazole- and benzoxazole-pyrimidone selective PI3Kβ inhibitors for the treatment of phosphatase and TENsin homologue (PTEN)-deficient cancers.

    PubMed

    Certal, Victor; Halley, Frank; Virone-Oddos, Angela; Delorme, Cécile; Karlsson, Andreas; Rak, Alexey; Thompson, Fabienne; Filoche-Rommé, Bruno; El-Ahmad, Youssef; Carry, Jean-Christophe; Abecassis, Pierre-Yves; Lejeune, Pascale; Vincent, Loic; Bonnevaux, Hélène; Nicolas, Jean-Paul; Bertrand, Thomas; Marquette, Jean-Pierre; Michot, Nadine; Benard, Tsiala; Below, Peter; Vade, Isabelle; Chatreaux, Fabienne; Lebourg, Gilles; Pilorge, Fabienne; Angouillant-Boniface, Odile; Louboutin, Audrey; Lengauer, Christoph; Schio, Laurent

    2012-05-24

    Most of the phosphoinositide-3 kinase (PI3K) kinase inhibitors currently in clinical trials for cancer treatment exhibit pan PI3K isoform profiles. Single PI3K isoforms differentially control tumorigenesis, and PI3Kβ has emerged as the isoform involved in the tumorigenicity of PTEN-deficient tumors. Herein we describe the discovery and optimization of a new series of benzimidazole- and benzoxazole-pyrimidones as small molecular mass PI3Kβ-selective inhibitors. Starting with compound 5 obtained from a one-pot reaction via a novel intermediate 1, medicinal chemistry optimization led to the discovery of compound 8, which showed a significant activity and selectivity for PI3Kβ and adequate in vitro pharmacokinetic properties. The X-ray costructure of compound 8 in PI3Kδ showed key interactions and structural features supporting the observed PI3Kβ isoform selectivity. Compound 8 achieved sustained target modulation and tumor growth delay at well tolerated doses when administered orally to SCID mice implanted with PTEN-deficient human tumor xenografts.

  2. Discovery and optimization of potent and selective functional antagonists of the human adenosine A2B receptor.

    PubMed

    Bedford, Simon T; Benwell, Karen R; Brooks, Teresa; Chen, Ijen; Comer, Mike; Dugdale, Sarah; Haymes, Tim; Jordan, Allan M; Kennett, Guy A; Knight, Anthony R; Klenke, Burkhard; LeStrat, Loic; Merrett, Angela; Misra, Anil; Lightowler, Sean; Padfield, Anthony; Poullennec, Karine; Reece, Mark; Simmonite, Heather; Wong, Melanie; Yule, Ian A

    2009-10-15

    We herein report the discovery of a novel class of antagonists of the human adenosine A2B receptor. This low molecular weight scaffold has been optimized to offer derivatives with potential utility for the alleviation of conditions associated with this receptor subtype, such as nociception, diabetes, asthma and COPD. Furthermore, preliminary pharmacokinetic analysis has revealed compounds with profiles suitable for either inhaled or systemic routes of administration.

  3. Highly Selective Bioconversion of Ginsenoside Rb1 to Compound K by the Mycelium of Cordyceps sinensis under Optimized Conditions.

    PubMed

    Wang, Wei-Nan; Yan, Bing-Xiong; Xu, Wen-Di; Qiu, Ye; Guo, Yun-Long; Qiu, Zhi-Dong

    2015-01-01

    Compound K (CK), a highly active and bioavailable derivative obtained from protopanaxadiol ginsenosides, displays a wide variety of pharmacological properties, especially antitumor activity. However, the inadequacy of natural sources limits its application in the pharmaceutical industry. In this study, we firstly discovered that Cordyceps sinensis was a potent biocatalyst for the biotransformation of ginsenoside Rb1 into CK. After a series of investigations on the biotransformation parameters, an optimal composition of the biotransformation culture was found to be lactose, soybean powder and MgSO₄ without controlling the pH. Also, an optimum temperature of 30 °C for the biotransformation process was suggested in a range of 25 °C-50 °C. Then, a biotransformation pathway of Rb1→Rd→F2→CK was established using high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS). Our results demonstrated that the molar bioconversion rate of Rb1 to CK was more than 82% and the purity of CK produced by C. sinensis under the optimized conditions was more than 91%. In conclusion, the combination of C. sinensis and the optimized conditions is applicable for the industrial preparation of CK for medicinal purposes. PMID:26512632

  4. Codon optimization, promoter and expression system selection that achieved high-level production of Yarrowia lipolytica lipase in Pichia pastoris.

    PubMed

    Zhou, Wen-Jing; Yang, Jiang-Ke; Mao, Lin; Miao, Li-Hong

    2015-04-01

    Lipase (EC 3.1.1.3) stands amongst the most important and promising biocatalysts for industrial applications. In this study, in order to realize a high-level expression of the Yarrowia lipolytica lipase gene in Pichia pastoris, we optimized the codon of LIP2 by de novo gene design and synthesis, which significantly improved the lipase expression when compared to the native lip2 gene. We also comparatively analyzed the effects of the promoter types (PAOX1 and PFLD1) and the Pichia expression systems, including the newly developed PichiaPink system, on lipase production and obtained the optimal recombinants. Bench-top scale fermentation studies indicated that the recombinant carrying the codon-optimized lipase gene syn-lip under the control of promoter PAOX1 has a significantly higher lipase production capacity in the fermenter than other types of recombinants. After undergoing methanol inducible expression for 96h, the wet cell weight of Pichia, the lipase activity and the protein content in the fermentation broth reached their highest values of 262g/L, 38,500U/mL and 2.82g/L, respectively. This study has not only greatly facilitated the bioapplication of lipase in industrial fields but the strategies utilized, such as de novo gene design and synthesis, the comparative analysis among promoters and different generations of Pichia expression systems will also be useful as references for future work in this field. PMID:25765312

  5. Optimization of SELEX: comparison of different methods for monitoring the progress of in vitro selection of aptamers.

    PubMed

    Mencin, Nina; Šmuc, Tina; Vraničar, Marko; Mavri, Jan; Hren, Matjaž; Galeša, Katja; Krkoč, Peter; Ulrich, Henning; Šolar, Borut

    2014-03-01

    Oligonucleotide aptamers are selected from libraries typically comprising up to 10(15) different sequences by an iterative process of binding, separation, amplification and purification, called SELEX. During this process, the diversity of the oligonucleotide pool decreases until, presumably, only sequences with highest binding affinities towards chosen targets remain. This selection technique is time-consuming, labor-intensive and expensive. Though well posed in principles, the SELEX procedure is noise sensitive, due to amplification of unspecific-binding sequences, and it is not surprising that aptamer selection is often not successful in practice. In view of that, a follow-up of the progress of selection during its course with simple yet reliable methods is necessary. In this paper, we describe five independent assays to estimate the sequence complexity of SELEX pools including qualitative restriction fragment length polymorphism analysis, melting curve analysis, quantitative fluorescence intensity measurements of bound ssDNA, real time PCR quantification and pool dissociation constant analysis during the progress of aptamer selection against streptavidin. Properties and features of each method are discussed and compared. Pool dissociation constant analysis and sequencing serve as reference methods.

  6. Construction of a novel selection system for endoglucanases exhibiting carbohydrate-binding modules optimized for biomass using yeast cell-surface engineering

    PubMed Central

    2012-01-01

    To permit direct cellulose degradation and ethanol fermentation, Saccharomyces cerevisiae BY4741 (Δsed1) codisplaying 3 cellulases (Trichoderma reesei endoglucanase II [EG], T. reesei cellobiohydrolase II [CBH], and Aspergillus aculeatus β-glucosidase I [BG]) was constructed by yeast cell-surface engineering. The EG used in this study consists of a family 1 carbohydrate-binding module (CBM) and a catalytic module. A comparison with family 1 CBMs revealed conserved amino acid residues and flexible amino acid residues. The flexible amino acid residues were at positions 18, 23, 26, and 27, through which the degrading activity for various cellulose structures in each biomass may have been optimized. To select the optimal combination of CBMs of EGs, a yeast mixture with comprehensively mutated CBM was constructed. The mixture consisted of yeasts codisplaying EG with mutated CBMs, in which 4 flexible residues were comprehensively mutated, CBH, and BG. The yeast mixture was inoculated in selection medium with newspaper as the sole carbon source. The surviving yeast consisted of RTSH yeast (the mutant sequence of CBM: N18R, S23T, S26S, and T27H) and wild-type yeast (CBM was the original) in a ratio of 1:46. The mixture (1 RTSH yeast and 46 wild-type yeasts) had a fermentation activity that was 1.5-fold higher than that of wild-type yeast alone in the early phase of saccharification and fermentation, which indicates that the yeast mixture with comprehensively mutated CBM could be used to select the optimal combination of CBMs suitable for the cellulose of each biomass. PMID:23092441

  7. A Study of the Relationship between Cognitive Emotion Regulation, Optimism, and Perceived Stress among Selected Teachers in Lutheran Schools

    ERIC Educational Resources Information Center

    Gliebe, Sudi Kate

    2012-01-01

    Problem: The problem of this study was to determine the relationship between perceived stress, as measured by the Perceived Stress Scale (PSS), and a specific set of predictor variables among selected teachers in Lutheran schools in the United States. These variables were cognitive emotion regulation strategies (positive reappraisal and…

  8. End-to-end sensor simulation for spectral band selection and optimization with application to the Sentinel-2 mission.

    PubMed

    Segl, Karl; Richter, Rudolf; Küster, Theres; Kaufmann, Hermann

    2012-02-01

    An end-to-end sensor simulation is a proper tool for the prediction of the sensor's performance over a range of conditions that cannot be easily measured. In this study, such a tool has been developed that enables the assessment of the optimum spectral resolution configuration of a sensor based on key applications. It employs the spectral molecular absorption and scattering properties of materials that are used for the identification and determination of the abundances of surface and atmospheric constituents and their interdependence on spatial resolution and signal-to-noise ratio as a basis for the detailed design and consolidation of spectral bands for the future Sentinel-2 sensor. The developed tools allow the computation of synthetic Sentinel-2 spectra that form the frame for the subsequent twofold analysis of bands in the atmospheric absorption and window regions. One part of the study comprises the assessment of optimal spatial and spectral resolution configurations for those bands used for atmospheric correction, optimized with regard to the retrieval of aerosols, water vapor, and the detection of cirrus clouds. The second part of the study presents the optimization of thematic bands, mainly driven by the spectral characteristics of vegetation constituents and minerals. The investigation is performed for different wavelength ranges because most remote sensing applications require the use of specific band combinations rather than single bands. The results from the important "red-edge" and the "short-wave infrared" domains are presented. The recommended optimum spectral design predominantly confirms the sensor parameters given by the European Space Agency. The system is capable of retrieving atmospheric and geobiophysical parameters with enhanced quality compared to existing multispectral sensors. Minor spectral changes of single bands are discussed in the context of typical remote sensing applications, supplemented by the recommendation of a few new bands for

  9. End-to-end sensor simulation for spectral band selection and optimization with application to the Sentinel-2 mission.

    PubMed

    Segl, Karl; Richter, Rudolf; Küster, Theres; Kaufmann, Hermann

    2012-02-01

    An end-to-end sensor simulation is a proper tool for the prediction of the sensor's performance over a range of conditions that cannot be easily measured. In this study, such a tool has been developed that enables the assessment of the optimum spectral resolution configuration of a sensor based on key applications. It employs the spectral molecular absorption and scattering properties of materials that are used for the identification and determination of the abundances of surface and atmospheric constituents and their interdependence on spatial resolution and signal-to-noise ratio as a basis for the detailed design and consolidation of spectral bands for the future Sentinel-2 sensor. The developed tools allow the computation of synthetic Sentinel-2 spectra that form the frame for the subsequent twofold analysis of bands in the atmospheric absorption and window regions. One part of the study comprises the assessment of optimal spatial and spectral resolution configurations for those bands used for atmospheric correction, optimized with regard to the retrieval of aerosols, water vapor, and the detection of cirrus clouds. The second part of the study presents the optimization of thematic bands, mainly driven by the spectral characteristics of vegetation constituents and minerals. The investigation is performed for different wavelength ranges because most remote sensing applications require the use of specific band combinations rather than single bands. The results from the important "red-edge" and the "short-wave infrared" domains are presented. The recommended optimum spectral design predominantly confirms the sensor parameters given by the European Space Agency. The system is capable of retrieving atmospheric and geobiophysical parameters with enhanced quality compared to existing multispectral sensors. Minor spectral changes of single bands are discussed in the context of typical remote sensing applications, supplemented by the recommendation of a few new bands for

  10. iVAX: An integrated toolkit for the selection and optimization of antigens and the design of epitope-driven vaccines.

    PubMed

    Moise, Leonard; Gutierrez, Andres; Kibria, Farzana; Martin, Rebecca; Tassone, Ryan; Liu, Rui; Terry, Frances; Martin, Bill; De Groot, Anne S

    2015-01-01

    Computational vaccine design, also known as computational vaccinology, encompasses epitope mapping, antigen selection and immunogen design using computational tools. The iVAX toolkit is an integrated set of tools that has been in development since 1998 by De Groot and Martin. It comprises a suite of immunoinformatics algorithms for triaging candidate antigens, selecting immunogenic and conserved T cell epitopes, eliminating regulatory T cell epitopes, and optimizing antigens for immunogenicity and protection against disease. iVAX has been applied to vaccine development programs for emerging infectious diseases, cancer antigens and biodefense targets. Several iVAX vaccine design projects have had success in pre-clinical studies in animal models and are progressing toward clinical studies. The toolkit now incorporates a range of immunoinformatics tools for infectious disease and cancer immunotherapy vaccine design. This article will provide a guide to the iVAX approach to computational vaccinology.

  11. Optimization of Potent and Selective Quinazolinediones: Inhibitors of Respiratory Syncytial Virus That Block RNA-Dependent RNA-Polymerase Complex Activity

    PubMed Central

    2015-01-01

    A quinazolinedione-derived screening hit 2 was discovered with cellular antiviral activity against respiratory syncytial virus (CPE EC50 = 2.1 μM), moderate efficacy in reducing viral progeny (4.2 log at 10 μM), and marginal cytotoxic liability (selectivity index, SI ∼ 24). Scaffold optimization delivered analogs with improved potency and selectivity profiles. Most notable were compounds 15 and 19 (EC50 = 300–500 nM, CC50 > 50 μM, SI > 100), which significantly reduced viral titer (>400,000-fold), and several analogs were shown to block the activity of the RNA-dependent RNA-polymerase complex of RSV. PMID:25399509

  12. iVAX: An integrated toolkit for the selection and optimization of antigens and the design of epitope-driven vaccines

    PubMed Central

    Moise, Leonard; Gutierrez, Andres; Kibria, Farzana; Martin, Rebecca; Tassone, Ryan; Liu, Rui; Terry, Frances; Martin, Bill; De Groot, Anne S

    2015-01-01

    Computational vaccine design, also known as computational vaccinology, encompasses epitope mapping, antigen selection and immunogen design using computational tools. The iVAX toolkit is an integrated set of tools that has been in development since 1998 by De Groot and Martin. It comprises a suite of immunoinformatics algorithms for triaging candidate antigens, selecting immunogenic and conserved T cell epitopes, eliminating regulatory T cell epitopes, and optimizing antigens for immunogenicity and protection against disease. iVAX has been applied to vaccine development programs for emerging infectious diseases, cancer antigens and biodefense targets. Several iVAX vaccine design projects have had success in pre-clinical studies in animal models and are progressing toward clinical studies. The toolkit now incorporates a range of immunoinformatics tools for infectious disease and cancer immunotherapy vaccine design. This article will provide a guide to the iVAX approach to computational vaccinology. PMID:26155959

  13. Optimization of an extraction protocol for organic matter from soils and sediments using high resolution mass spectrometry: selectivity and biases

    NASA Astrophysics Data System (ADS)

    Chu, R. K.; Tfaily, M. M.; Tolic, N.; Kyle, J. E.; Robinson, E. R.; Hess, N. J.; Paša-Tolić, L.

    2015-12-01

    Soil organic matter (SOM) is a complex mixture of above and belowground plant litter and microbial residues, and is a key reservoir for carbon (C) and nutrient biogeochemical cycling in different ecosystems. A limited understanding of the molecular composition of SOM prohibits the ability to routinely decipher chemical processes within soil and predict how terrestrial C fluxes will response to changing climatic conditions. Here, we present that the choice of solvent can be used to selectively extract different compositional fractions from SOM to either target a specific class of compounds or gain a better understanding of the entire composition of the soil sample using 12T Fourier transform ion cyclotron resonance mass spectrometry. Specifically, we found that hexane and chloroform were selective for lipid-like compounds with very low O:C ratios; water was selective for carbohydrates with high O:C ratios; acetonitrile preferentially extracts lignin, condensed structures, and tannin polyphenolic compounds with O:C > 0.5; methanol has higher selectivity towards lignin and lipid compounds characterized with relatively low O:C < 0.5. Hexane, chloroform, methanol, acetonitrile and water increase the number and types of organic molecules extracted from soil for a broader range of chemically diverse soil types. Since each solvent extracts a selective group of compounds, using a suite of solvents with varying polarity for analysis results in more comprehensive representation of the diversity of organic molecules present in soil and a better representation of the whole spectrum of available substrates for microorganisms. Moreover, we have developed a sequential extraction protocol that permits sampling diverse classes of organic compounds while minimizing ionization competition during ESI while increasing sample throughput and decreasing sample volume. This allowed us to hypothesize about possible chemical reactions relating classes of organic molecules that reflect abiotic

  14. Optimization of cell line development in the GS-CHO expression system using a high-throughput, single cell-based clone selection system.

    PubMed

    Nakamura, Tsuyoshi; Omasa, Takeshi

    2015-09-01

    Therapeutic antibodies are commonly produced by high-expressing, clonal and recombinant Chinese hamster ovary (CHO) cell lines. Currently, CHO cells dominate as a commercial production host because of their ease of use, established regulatory track record, and safety profile. CHO-K1SV is a suspension, protein-free-adapted CHO-K1-derived cell line employing the glutamine synthetase (GS) gene expression system (GS-CHO expression system). The selection of high-producing mammalian cell lines is a crucial step in process development for the production of therapeutic antibodies. In general, cloning by the limiting dilution method is used to isolate high-producing monoclonal CHO cells. However, the limiting dilution method is time consuming and has a low probability of monoclonality. To minimize the duration and increase the probability of obtaining high-producing clones with high monoclonality, an automated single cell-based clone selector, the ClonePix FL system, is available. In this study, we applied the high-throughput ClonePix FL system for cell line development using CHO-K1SV cells and investigated efficient conditions for single cell-based clone selection. CHO-K1SV cell growth at the pre-picking stage was improved by optimizing the formulation of semi-solid medium. The efficiency of picking and cell growth at the post-picking stage was improved by optimization of the plating time without decreasing the diversity of clones. The conditions for selection, including the medium formulation, were the most important factors for the single cell-based clone selection system to construct a high-producing CHO cell line.

  15. Using multi-criteria decision making for selection of the optimal strategy for municipal solid waste management.

    PubMed

    Jovanovic, Sasa; Savic, Slobodan; Jovicic, Nebojsa; Boskovic, Goran; Djordjevic, Zorica

    2016-09-01

    Multi-criteria decision making (MCDM) is a relatively new tool for decision makers who deal with numerous and often contradictory factors during their decision making process. This paper presents a procedure to choose the optimal municipal solid waste (MSW) management system for the area of the city of Kragujevac (Republic of Serbia) based on the MCDM method. Two methods of multiple attribute decision making, i.e. SAW (simple additive weighting method) and TOPSIS (technique for order preference by similarity to ideal solution), respectively, were used to compare the proposed waste management strategies (WMS). Each of the created strategies was simulated using the software package IWM2. Total values for eight chosen parameters were calculated for all the strategies. Contribution of each of the six waste treatment options was valorized. The SAW analysis was used to obtain the sum characteristics for all the waste management treatment strategies and they were ranked accordingly. The TOPSIS method was used to calculate the relative closeness factors to the ideal solution for all the alternatives. Then, the proposed strategies were ranked in form of tables and diagrams obtained based on both MCDM methods. As shown in this paper, the results were in good agreement, which additionally confirmed and facilitated the choice of the optimal MSW management strategy. PMID:27354012

  16. Development of functional beverages from blends of Hibiscus sabdariffa extract and selected fruit juices for optimal antioxidant properties.

    PubMed

    Ogundele, Oluwatoyin M A; Awolu, Olugbenga O; Badejo, Adebanjo A; Nwachukwu, Ifeanyi D; Fagbemi, Tayo N

    2016-09-01

    The demand for functional foods and drinks with health benefit is on the increase. The synergistic effect from mixing two or more of such drinks cannot be overemphasized. This study was carried out to formulate and investigate the effects of blends of two or more of pineapple, orange juices, carrot, and Hibiscus sabdariffa extracts (HSE) on the antioxidant properties of the juice formulations in order to obtain a combination with optimal antioxidant properties. Experimental design was carried out using optimal mixture model of response surface methodology which generated twenty experimental runs with antioxidant properties as the responses. The DPPH (1,1-diphenyl-2-picrylhydrazyl) and ABTS [2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)] radical scavenging abilities, ferric reducing antioxidant potential (FRAP), vitamin C, total phenolics, and total carotenoids contents of the formulations were evaluated as a test of antioxidant property. In all the mixtures, formulations having HSE as part of the mixture showed the highest antioxidant potential. The statistical analyzes, however, showed that the formulations containing pineapple, carrot, orange, and HSE of 40.00, 16.49, 17.20, and 26.30%, respectively, produced optimum antioxidant potential and was shown to be acceptable to a research laboratory guidance panel, thus making them viable ingredients for the production of functional beverages possessing important antioxidant properties with potential health benefits.

  17. Fabrication and Optimization of Vertically Aligned ZnO Nanorod Array-Based UV Photodetectors via Selective Hydrothermal Synthesis

    NASA Astrophysics Data System (ADS)

    Ko, Yeong Hwan; Nagaraju, Goli; Yu, Jae Su

    2015-08-01

    Vertically aligned ZnO nanorod array (NRA)-based ultraviolet (UV) photodetectors (PDs) were successfully fabricated and optimized via a facile hydrothermal process. Using a shadow mask technique, the thin ZnO seed layer was deposited between the patterned Au/Ti electrodes to bridge the electrodes. Thus, both the Au electrodes could be connected by the ZnO seed layer. As the sample was immersed into growth solution and heated at 90 °C, the ZnO NRAs were crystallized and vertically grown on the ZnO seed layer, thus creating a metal-semiconductor-metal PD structure. To investigate the size effect of ZnO NRAs on photocurrent, the PDs were readily prepared with different concentrations of growth solution. For the ZnO NRAs grown at 25 mM of concentration, the PD with 10 μm of channel width (i.e., gap distance between two electrodes) exhibited a high photocurrent of 1.91 × 10-4 A at an applied bias of 10 V under 365 nm of UV light illumination. The PD was optimized by adjusting the channel width. For 15 μm of channel width, a relatively high photocurrent on-off ratio of 37.4 and good current transient characteristics were observed at the same applied bias. These results are expected to be useful for cost-effective and practical UV PD applications.

  18. Selection and optimization of transfection enhancer additives for increased virus-like particle production in HEK293 suspension cell cultures.

    PubMed

    Cervera, Laura; Fuenmayor, Javier; González-Domínguez, Irene; Gutiérrez-Granados, Sonia; Segura, Maria Mercedes; Gòdia, Francesc

    2015-12-01

    The manufacturing of biopharmaceuticals in mammalian cells typically relies on the use of stable producer cell lines. However, in recent years, transient gene expression has emerged as a suitable technology for rapid production of biopharmaceuticals. Transient gene expression is particularly well suited for early developmental phases, where several potential therapeutic targets need to be produced and tested in vivo. As a relatively new bioprocessing modality, a number of opportunities exist for improving cell culture productivity upon transient transfection. For instance, several compounds have shown positive effects on transient gene expression. These transfection enhancers either facilitate entry of PEI/DNA transfection complexes into the cell or nucleus or increase levels of gene expression. In this work, the potential of combining transfection enhancers to increase Gag-based virus-like particle production levels upon transfection of suspension-growing HEK 293 cells is evaluated. Using Plackett-Burman design of experiments, it is first tested the effect of eight transfection enhancers: trichostatin A, valproic acid, sodium butyrate, dimethyl sulfoxide (DMSO), lithium acetate, caffeine, hydroxyurea, and nocodazole. An optimal combination of compounds exhibiting the highest effect on gene expression levels was subsequently identified using a surface response experimental design. The optimal consisted on the addition of 20 mM lithium acetate, 3.36 mM valproic acid, and 5.04 mM caffeine which increased VLP production levels 3.8-fold, while maintaining cell culture viability at 94%. PMID:26278533

  19. Development of functional beverages from blends of Hibiscus sabdariffa extract and selected fruit juices for optimal antioxidant properties.

    PubMed

    Ogundele, Oluwatoyin M A; Awolu, Olugbenga O; Badejo, Adebanjo A; Nwachukwu, Ifeanyi D; Fagbemi, Tayo N

    2016-09-01

    The demand for functional foods and drinks with health benefit is on the increase. The synergistic effect from mixing two or more of such drinks cannot be overemphasized. This study was carried out to formulate and investigate the effects of blends of two or more of pineapple, orange juices, carrot, and Hibiscus sabdariffa extracts (HSE) on the antioxidant properties of the juice formulations in order to obtain a combination with optimal antioxidant properties. Experimental design was carried out using optimal mixture model of response surface methodology which generated twenty experimental runs with antioxidant properties as the responses. The DPPH (1,1-diphenyl-2-picrylhydrazyl) and ABTS [2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)] radical scavenging abilities, ferric reducing antioxidant potential (FRAP), vitamin C, total phenolics, and total carotenoids contents of the formulations were evaluated as a test of antioxidant property. In all the mixtures, formulations having HSE as part of the mixture showed the highest antioxidant potential. The statistical analyzes, however, showed that the formulations containing pineapple, carrot, orange, and HSE of 40.00, 16.49, 17.20, and 26.30%, respectively, produced optimum antioxidant potential and was shown to be acceptable to a research laboratory guidance panel, thus making them viable ingredients for the production of functional beverages possessing important antioxidant properties with potential health benefits. PMID:27625770

  20. Using multi-criteria decision making for selection of the optimal strategy for municipal solid waste management.

    PubMed

    Jovanovic, Sasa; Savic, Slobodan; Jovicic, Nebojsa; Boskovic, Goran; Djordjevic, Zorica

    2016-09-01

    Multi-criteria decision making (MCDM) is a relatively new tool for decision makers who deal with numerous and often contradictory factors during their decision making process. This paper presents a procedure to choose the optimal municipal solid waste (MSW) management system for the area of the city of Kragujevac (Republic of Serbia) based on the MCDM method. Two methods of multiple attribute decision making, i.e. SAW (simple additive weighting method) and TOPSIS (technique for order preference by similarity to ideal solution), respectively, were used to compare the proposed waste management strategies (WMS). Each of the created strategies was simulated using the software package IWM2. Total values for eight chosen parameters were calculated for all the strategies. Contribution of each of the six waste treatment options was valorized. The SAW analysis was used to obtain the sum characteristics for all the waste management treatment strategies and they were ranked accordingly. The TOPSIS method was used to calculate the relative closeness factors to the ideal solution for all the alternatives. Then, the proposed strategies were ranked in form of tables and diagrams obtained based on both MCDM methods. As shown in this paper, the results were in good agreement, which additionally confirmed and facilitated the choice of the optimal MSW management strategy.

  1. Fluorescent magnetic iron oxide nanoparticles for cardiac precursor cell selection from stromal vascular fraction and optimization for magnetic resonance imaging

    PubMed Central

    Verma, Vinod Kumar; Kamaraju, Suguna Ratnakar; Kancherla, Ravindranath; Kona, Lakshmi K; Beevi, Syed Sultan; Debnath, Tanya; Usha, Shalini P; Vadapalli, Rammohan; Arbab, Ali Syed; Chelluri, Lakshmi Kiran

    2015-01-01

    Fluorescent magnetic iron oxide nanoparticles have been used to label cells for imaging as well as for therapeutic purposes. The purpose of this study was to modify the approach to develop a nanoprobe for cell selection and imaging with a direct therapeutic translational focus. The approach involves physical coincubation and adsorption of superparamagnetic iron oxide nanoparticle-polyethylene glycol (SPION-PEG) complexes with a monoclonal antibody (mAb) or a set of antibodies. Flow cytometry, confocal laser scanning microscopy, transmission electron microscopy, iron staining, and magnetic resonance imaging were used to assess cell viability, function, and labeling efficiency. This process has been validated by selecting adipose tissue-derived cardiac progenitor cells from the stromal vascular fraction using signal regulatory protein alpha (SIRPA)/kinase domain receptor (KDR) mAbs. These markers were chosen because of their sustained expression during cardiomyocyte differentiation. Sorting of cells positive for SIRPA and KDR allowed the enrichment of cardiac progenitors with 90% troponin-I positivity in differentiation cultures. SPION labeled cardiac progenitor cells (1×105 cells) was mixed with gel and used for 3T magnetic resonance imaging at a concentration, as low as 12.5 μg of iron. The toxicity assays, at cellular and molecular levels, did not show any detrimental effects of SPION. Our study has the potential to achieve moderate to high specific cell selection for the dual purpose of imaging and therapy. PMID:25653519

  2. Optimizing liquid waste treatment processing in PWRs: focus on modeling of the variation of ion-exchange resins selectivity coefficients

    SciTech Connect

    Gressier, Frederic; Van der Lee, Jan; Schneider, Helene; Bachet, Martin; Catalette, Hubert

    2007-07-01

    A bibliographic survey has highlighted the essential role of selectivity on resin efficiency, especially the variation of selectivity coefficients in function of the resin saturation state and the operating conditions. This phenomenon has been experimentally confirmed but is not yet implemented into an ion-exchange model specific for resins. This paper reviews the state of the art in predicting sorption capacity of ion-exchange resins. Different models accounting for ions activities inside the resin phase are available. Moreover, a comparison between the values found in the literature and our results has been done. The results of sorption experiments of cobalt chloride on a strong cationic gel type resin used in French PWRs are presented. The graph describing the variation of selectivity coefficient with respect to cobalt equivalent fraction is drawn. The parameters determined by the analysis of this graph are injected in a new physico-chemical law. Implementation of this model in the chemical speciation simulation code CHESS enables to study the overall effect of this approach for the sorption in a batch. (authors)

  3. Discovery and optimization of 1,7-disubstituted-2,2-dimethyl-2,3-dihydroquinazolin-4(1H)-ones as potent and selective PKCθ inhibitors.

    PubMed

    Katoh, Taisuke; Takai, Takafumi; Yukawa, Takafumi; Tsukamoto, Tetsuya; Watanabe, Etsurou; Mototani, Hideyuki; Arita, Takeo; Hayashi, Hiroki; Nakagawa, Hideyuki; Klein, Michael G; Zou, Hua; Sang, Bi-Ching; Snell, Gyorgy; Nakada, Yoshihisa

    2016-06-01

    A high-throughput screening campaign helped us to identify an initial lead compound (1) as a protein kinase C-θ (PKCθ) inhibitor. Using the docking model of compound 1 bound to PKCθ as a model, structure-based drug design was employed and two regions were identified that could be explored for further optimization, i.e., (a) a hydrophilic region around Thr442, unique to PKC family, in the inner part of the hinge region, and (b) a lipophilic region at the forefront of the ethyl moiety. Optimization of the hinge binder led us to find 1,3-dihydro-2H-imidazo[4,5-b]pyridin-2-one as a potent and selective hinge binder, which resulted in the discovery of compound 5. Filling the lipophilic region with a suitable lipophilic substituent boosted PKCθ inhibitory activity and led to the identification of compound 10. The co-crystal structure of compound 10 bound to PKCθ confirmed that both the hydrophilic and lipophilic regions were fully utilized. Further optimization of compound 10 led us to compound 14, which demonstrated an improved pharmacokinetic profile and inhibition of IL-2 production in a mouse. PMID:27117263

  4. Solute-solvent interactions in micellar electrokinetic chromatography. 6. Optimization of the selectivity of lithium dodecyl sulfate-lithium perfluorooctanesulfonate mixed micellar buffers.

    PubMed

    Fuguet, Elisabet; Ràfols, Clara; Torres-Lapasió, José Ramón; García-Alvarez-Coque, María Celia; Bosch, Elisabeth; Rosés, Martí

    2002-09-01

    The optimization of the composition of mixed surfactants used as micellar electrokinetic chromatography (MEKC) pseudostationary phases is proposed as an effective method for the separation of complex mixtures of analytes. The solvation parameter model is used to select two surfactants (lithium dodecyl sulfate, LDS, and lithium perfluorooctanesulfonate, LPFOS) with contrasting solvation properties. Combination of these two surfactants allows variations of the solvation properties of MEKC pseudostationary phase along a wide range. Thus, the convenient variation of the proportion of both surfactants allows an effective control of the selectivity in such systems. An algorithm that predicts the overall resolution of a given mixture of compounds is described and applied to optimize the composition of the mixed surfactant for the separation of the mixture. The algorithm is based on the calculation of peak purities on simulated chromatograms as a function of the composition of the mixed LDS/LPFOS micellar buffer from data at several micellar buffer compositions. Successful separations were achieved for mixtures containing up to 20 compounds, in less than 12 min.

  5. Alcohol from whey permeate: strain selection, temperature, and medium optimization. [Candida pseudotropicalis, Kluyveromyces fragilis, and K. lactis

    SciTech Connect

    Vienne, P.; Von Stockar, U.

    1983-01-01

    A comparative study of shaken flask cultures of some yeast strains capable of fermenting lactose showed no significant differences in alcohol yield among the four best strains. Use of whey permeate concentrated three times did not affect the yields. An optimal growth temperature of 38/sup 0/C was determined for K. fragilis NRRL 665. Elemental analysis of both the permeate and the dry cell mass of two strains indicated the possibility of a stoichiometric limitation by nitrogen. Batch cultures in laboratory fermentors confirmed this finding and revealed in addition the presence of a limitation due to growth factors. Both types of limitations could be overcome by adding yeast extract. The maximum productivity of continuous cultures could thus be improved to 5.1 g/l-h. The maximum specific growth rate was of the order of 0.310 h/sup -1/. 15 references, 10 figures, 9 tables.

  6. Experimental parameters optimization of instrumental neutron activation analysis in order to determine selected elements in some industrial soils in Turkey

    NASA Astrophysics Data System (ADS)

    Haciyakupoglu, Sevilay; Nur Esen, Ayse; Erenturk, Sema

    2014-08-01

    The purpose of this study is optimization of the experimental parameters for analysis of soil matrix by instrumental neutron activation analysis and quantitative determination of barium, cerium, lanthanum, rubidium, scandium and thorium in soil samples collected from industrialized urban areas near Istanbul. Samples were irradiated in TRIGA MARK II Research Reactor of Istanbul Technical University. Two types of reference materials were used to check the accuracy of the applied method. The achieved results were found to be in compliance with certified values of the reference materials. The calculated En numbers for mentioned elements were found to be less than 1. The presented data of element concentrations in soil samples will help to trace the pollution as an impact of urbanization and industrialization, as well as providing database for future studies.

  7. Mutant selection of Hahella chejuensis KCTC 2396 and statistical optimization of medium components for prodigiosin yield-up.

    PubMed

    Kim, Sung Jin; Lee, Hong Kum; Lee, Yoo Kyung; Yim, Joung Han

    2008-04-01

    Prodigiosin is a natural red pigment with algicidal activity against Cochlodinium polykrikoides, a major harmful red-tide microalga. To increase the yield of prodigiosin, a mutant of Hahella chejuenesis KCTC 2396, assigned M3349, was developed by an antibiotic mutagenesis using chloramphenicol. When cultured in Sucrose-based Marine Broth medium (SMB), M3349 could produce prodigiosin at 1.628+/-0.06 g/L, while wild type producing at 0.658+/-0.12 g/L under the same conditions. To increase the yield of prodigiosin production by M3349, significant medium components were determined using a two-level Plackett-Burman statistical design technique. Among fourteen components included in SMB medium, NaCl, Na2SiO3, MgCl2, H3BO3, Na2HPO4, Na2SO4, and CaCl2 were determined to be important for prodigiosin production. The medium formulation was finally optimized using a Box-Behnken design as follows: sucrose 10.0, peptone 8.0, yeast extract 2.0, NaCl 10.0, Na2SO4 12.0, CaCl2 1.8, MgCl2 0.7 g/L; and H3BO3 22.0, Na2HPO4 20.0, Na2SiO3 8.0 mg/L. The predicted maximum yield of prodigiosin in the optimized medium was 2.43 g/L by the Box-Behnken design, while the practical production was 2.60+/-0.176 g/L, which was 3.9 times higher than wild type with SMB Medium (0.658 g/L).

  8. Physics-based simulation modeling and optimization of microstructural changes induced by machining and selective laser melting processes in titanium and nickel based alloys

    NASA Astrophysics Data System (ADS)

    Arisoy, Yigit Muzaffer

    Manufacturing processes may significantly affect the quality of resultant surfaces and structural integrity of the metal end products. Controlling manufacturing process induced changes to the product's surface integrity may improve the fatigue life and overall reliability of the end product. The goal of this study is to model the phenomena that result in microstructural alterations and improve the surface integrity of the manufactured parts by utilizing physics-based process simulations and other computational methods. Two different (both conventional and advanced) manufacturing processes; i.e. machining of Titanium and Nickel-based alloys and selective laser melting of Nickel-based powder alloys are studied. 3D Finite Element (FE) process simulations are developed and experimental data that validates these process simulation models are generated to compare against predictions. Computational process modeling and optimization have been performed for machining induced microstructure that includes; i) predicting recrystallization and grain size using FE simulations and the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model, ii) predicting microhardness using non-linear regression models and the Random Forests method, and iii) multi-objective machining optimization for minimizing microstructural changes. Experimental analysis and computational process modeling of selective laser melting have been also conducted including; i) microstructural analysis of grain sizes and growth directions using SEM imaging and machine learning algorithms, ii) analysis of thermal imaging for spattering, heating/cooling rates and meltpool size, iii) predicting thermal field, meltpool size, and growth directions via thermal gradients using 3D FE simulations, iv) predicting localized solidification using the Phase Field method. These computational process models and predictive models, once utilized by industry to optimize process parameters, have the ultimate potential to improve performance of

  9. PC2D simulation and optimization of the selective emitter solar cells fabricated by screen printing phosphoric paste method

    NASA Astrophysics Data System (ADS)

    Jia, Xiaojie; Ai, Bin; Deng, Youjun; Xu, Xinxiang; Peng, Hua; Shen, Hui

    2015-08-01

    On the basis of perfect PC2D simulation to the measured current density vs voltage (J-V) curve of the best selective emitter (SE) solar cell fabricated by the CSG Company using the screen printing phosphoric paste method, we systematically investigated the effect of the parameters of gridline, base, selective emitter, back surface field (BSF) layer and surface recombination rate on performance of the SE solar cell. Among these parameters, we identified that the base minority carrier lifetime, the front and back surface recombination rate and the ratio of the sheet-resistance of heavily and lightly doped region are the four largest efficiency-affecting factors. If all the parameters have ideal values, the SE solar cell fabricated on a p-type monocrystalline silicon wafer can even obtain the efficiency of 20.45%. In addition, the simulation also shows that fine gridline combining dense gridline and increasing bus bar number while keeping the lower area ratio can offer the other ways to improve the efficiency.

  10. Relay Selection Based Double-Differential Transmission for Cooperative Networks with Multiple Carrier Frequency Offsets: Model, Analysis, and Optimization

    NASA Astrophysics Data System (ADS)

    Zhao, Kun; Zhang, Bangning; Pan, Kegang; Liu, Aijun; Guo, Daoxing

    2014-07-01

    Due to the distributed nature, cooperative networks are generally subject to multiple carrier frequency offsets (MCFOs), which make the channels time-varying and drastically degrade the system performance. In this paper, to address the MCFOs problem in detect-andforward (DetF) multi-relay cooperative networks, a robust relay selection (RS) based double-differential (DD) transmission scheme, termed RSDDT, is proposed, where the best relay is selected to forward the source's double-differentially modulated signals to the destination with the DetF protocol. The proposed RSDDT scheme can achieve excellent performance over fading channels in the presence of unknown MCFOs. Considering double-differential multiple phase-shift keying (DDMPSK) is applied, we first derive exact expressions for the outage probability and average bit error rate (BER) of the RSDDT scheme. Then, we look into the high signal-to-noise ratio (SNR) regime and present simple and informative asymptotic outage probability and average BER expressions, which reveal that the proposed scheme can achieve full diversity. Moreover, to further improve the BER performance of the RSDDT scheme, we investigate the optimum power allocation strategy among the source and the relay nodes, and simple analytical solutions are obtained. Numerical results are provided to corroborate the derived analytical expressions and it is demonstrated that the proposed optimum power allocation strategy offers substantial BER performance improvement over the equal power allocation strategy.

  11. Time-Dependent Selection of an Optimal Set of Sources to Define a Stable Celestial Reference Frame

    NASA Technical Reports Server (NTRS)

    Le Bail, Karine; Gordon, David

    2010-01-01

    Temporal statistical position stability is required for VLBI sources to define a stable Celestial Reference Frame (CRF) and has been studied in many recent papers. This study analyzes the sources from the latest realization of the International Celestial Reference Frame (ICRF2) with the Allan variance, in addition to taking into account the apparent linear motions of the sources. Focusing on the 295 defining sources shows how they are a good compromise of different criteria, such as statistical stability and sky distribution, as well as having a sufficient number of sources, despite the fact that the most stable sources of the entire ICRF2 are mostly in the Northern Hemisphere. Nevertheless, the selection of a stable set is not unique: studying different solutions (GSF005a and AUG24 from GSFC and OPA from the Paris Observatory) over different time periods (1989.5 to 2009.5 and 1999.5 to 2009.5) leads to selections that can differ in up to 20% of the sources. Observing, recording, and network improvement are some of the causes, showing better stability for the CRF over the last decade than the last twenty years. But this may also be explained by the assumption of stationarity that is not necessarily right for some sources.

  12. Polarimetric SAR decomposition parameter subset selection and their optimal dynamic range evaluation for urban area classification using Random Forest

    NASA Astrophysics Data System (ADS)

    Hariharan, Siddharth; Tirodkar, Siddhesh; Bhattacharya, Avik

    2016-02-01

    Urban area classification is important for monitoring the ever increasing urbanization and studying its environmental impact. Two NASA JPL's UAVSAR datasets of L-band (wavelength: 23 cm) were used in this study for urban area classification. The two datasets used in this study are different in terms of urban area structures, building patterns, their geometric shapes and sizes. In these datasets, some urban areas appear oriented about the radar line of sight (LOS) while some areas appear non-oriented. In this study, roll invariant polarimetric SAR decomposition parameters were used to classify these urban areas. Random Forest (RF), which is an ensemble decision tree learning technique, was used in this study. RF performs parameter subset selection as a part of its classification procedure. In this study, parameter subsets were obtained and analyzed to infer scattering mechanisms useful for urban area classification. The Cloude-Pottier α, the Touzi dominant scattering amplitude αs1 and the anisotropy A were among the top six important parameters selected for both the datasets. However, it was observed that these parameters were ranked differently for the two datasets. The urban area classification using RF was compared with the Support Vector Machine (SVM) and the Maximum Likelihood Classifier (MLC) for both the datasets. RF outperforms SVM by 4% and MLC by 12% in Dataset 1. It also outperforms SVM and MLC by 3.5% and 11% respectively in Dataset 2.

  13. Effective adsorption of Cr(VI) on mesoporous Fe-functionalized Akadama clay: Optimization, selectivity, and mechanism

    NASA Astrophysics Data System (ADS)

    Ji, Min; Su, Xiao; Zhao, Yingxin; Qi, Wenfang; Wang, Yue; Chen, Guanyi; Zhang, Zhenya

    2015-07-01

    A Japanese volcanic soil, Akadama clay, was functionalized with metal salts (FeCl3, AlCl3, CaCl2, MgCl2, MnCl2) and tested for Cr(VI) removal from aqueous solution. FeCl3 was selected as the most efficient activation agent. To quantitatively investigate the independent or interactive contribution of influencing factors (solution pH, contact time, adsorbent dose, and initial concentration) to Cr(VI) adsorption onto Fe-functionalized AC (FFAC), factorial experimental design was applied. Results showed initial concentration contributed most to adsorption capacity of Cr(VI) (53.17%), followed by adsorbent dosage (45.15%), contact time (1.12%) and the interaction between adsorbent dosage and contact time (0.37%). The adsorption showed little dependence on solution pH from 2 to 8. Adsorption selectivity of Cr(VI) was evaluated through analyzing distribution coefficient, electrical double layer theory, as well as the valence and Pauling's ionic radii of co-existing anions (Cl-, SO42-, and PO43-). EDX and XPS analyses demonstrated the adsorption mechanism of Cr(VI) onto FFAC included electrostatic attraction, ligant exchange, and redox reaction. Improved treatment for tannery wastewater shows a potential application of FFAC as a cost-effective adsorbent for Cr(VI) removal.

  14. Theoretical-physics approach to selected problems in engineering electromagnetics: Evolutionary optimization and low-dimensional nanostructures

    NASA Astrophysics Data System (ADS)

    Mikki, Said M.

    Although electromagnetism was developed originally as a branch of theoretical physics, the wide spread proliferation of wireless communications and other applications since the turn of the 20th century quickly transformed the field into a well-defined discipline standing by itself as an autonomous part of engineering. This in turn accelerated the growth of both numerical techniques and practical designs aiming all to improve technology. However, one negative drawback was the increasing isolation between the practicality of engineering electromagnetism and the depth and sophistication of the tools that had been developed solely within electromagnetic theory as a branch of theoretical physics. In this dissertation, we propose a new look to engineering electromagnetism from the perspective of theoretical physics. We show that techniques usually associated with abstract physical models in theoretical physics can be successfully employed to enhance our understanding of problems in engineering electromagnetism. Also, such adaptations of theoretical methods allow for new kinds of applications to be invented. This dissertation is organized in two main parts. Part I is concerned with the particle swarm optimization (PSO) method. We first construct a physical theory for the particle swarm optimization and show how this could open the door not just for deeper understanding of the algorithm itself, but also for new techniques to improve the performance of the method when applied to engineering electromagnetics problems. Inspired by the wider perspective derived from physics, we apply quantum effects to the basic (classical) PSO and derive a new general quantum PSO (QPSO) algorithm suitable for engineering electromagnetism. The new method will be shown to be superior to the classical counterpart when applied to some practical problems. A detailed case study that was formulated extensively in our work is the infinitesimal dipole model (IDM), which can simulate arbitrary antennas

  15. Selective In Vivo Targeting of Human Liver Tumors by Optimized AAV3 Vectors in a Murine Xenograft Model

    PubMed Central

    Wang, Yuan; Zhang, Yuanhui; Ejjigani, Anila; Yin, Zifei; Lu, Yuan; Wang, Lina; Wang, Meng; Li, Jun; Hu, Zhongbo; Aslanidi, George V.; Zhong, Li; Gao, Guangping

    2014-01-01

    Abstract Current challenges for recombinant adeno-associated virus (rAAV) vector–based cancer treatment include the low efficiency and the lack of specificity in vivo. rAAV serotype 3 (rAAV3) vectors have previously been shown to be ineffective in normal mouse tissues following systemic administration. In the present study, we report that rAAV3 vectors can efficiently target and transduce various human liver cancer cells in vivo. Elimination of specific surface-exposed serine and threonine residues on rAAV3 capsids results in further augmentation in the transduction efficiency of these vectors, without any change in the viral tropism and cellular receptor interactions. In addition, we have identified a potential chemotherapy drug, shikonin, as a multifunctional compound to inhibit liver tumor growth as well as to significantly enhance the efficacy of rAAV vector-based gene therapy in vivo. Furthermore, we also document that suppression of tumorigenesis in a human liver cancer xenograft model can be achieved through systemic administration of the optimized rAAV3 vectors carrying a therapeutic gene, and shikonin at a dose that does not lead to liver damage. Our research provides a novel means to achieve not only targeted delivery but also the potential for gene therapy of human liver cancer. PMID:25296041

  16. Sea ice concentration from satellite passive microwave algorithms: inter-comparison, validation and selection of an optimal algorithm

    NASA Astrophysics Data System (ADS)

    Ivanova, Natalia; Pedersen, Leif T.; Lavergne, Thomas; Tonboe, Rasmus T.; Saldo, Roberto; Mäkynen, Marko; Heygster, Georg; Rösel, Anja; Kern, Stefan; Dybkjær, Gorm; Sørensen, Atle; Brucker, Ludovic; Shokr, Mohammed; Korosov, Anton; Hansen, Morten W.

    2015-04-01

    Sea ice concentration (SIC) has been derived globally from satellite passive microwave observations since the 1970s by a multitude of algorithms. However, existing datasets and algorithms, although agreeing in the large-scale picture, differ substantially in the details and have disadvantages in summer and fall due to presence of melt ponds and thin ice. There is thus a need for understanding of the causes for the differences and identifying the most suitable method to retrieve SIC. Therefore, during the ESA Climate Change Initiative effort 30 algorithms have been implemented, inter-compared and validated by a standardized reference dataset. The algorithms were evaluated over low and high sea ice concentrations and thin ice. Based on the findings, an optimal approach to retrieve sea ice concentration globally for climate purposes was suggested and validated. The algorithm was implemented with atmospheric correction and dynamical tie points in order to produce the final sea ice concentration dataset with per-pixel uncertainties. The issue of melt ponds was addressed in particular because they are interpreted as open water by the algorithms and thus SIC can be underestimated by up to 40%. To improve our understanding of this issue, melt-pond signatures in AMSR2 images were investigated based on their physical properties with help of observations of melt pond fraction from optical (MODIS and MERIS) and active microwave (SAR) satellite measurements.

  17. Selective in vivo targeting of human liver tumors by optimized AAV3 vectors in a murine xenograft model.

    PubMed

    Ling, Chen; Wang, Yuan; Zhang, Yuanhui; Ejjigani, Anila; Yin, Zifei; Lu, Yuan; Wang, Lina; Wang, Meng; Li, Jun; Hu, Zhongbo; Aslanidi, George V; Zhong, Li; Gao, Guangping; Srivastava, Arun; Ling, Changquan

    2014-12-01

    Current challenges for recombinant adeno-associated virus (rAAV) vector-based cancer treatment include the low efficiency and the lack of specificity in vivo. rAAV serotype 3 (rAAV3) vectors have previously been shown to be ineffective in normal mouse tissues following systemic administration. In the present study, we report that rAAV3 vectors can efficiently target and transduce various human liver cancer cells in vivo. Elimination of specific surface-exposed serine and threonine residues on rAAV3 capsids results in further augmentation in the transduction efficiency of these vectors, without any change in the viral tropism and cellular receptor interactions. In addition, we have identified a potential chemotherapy drug, shikonin, as a multifunctional compound to inhibit liver tumor growth as well as to significantly enhance the efficacy of rAAV vector-based gene therapy in vivo. Furthermore, we also document that suppression of tumorigenesis in a human liver cancer xenograft model can be achieved through systemic administration of the optimized rAAV3 vectors carrying a therapeutic gene, and shikonin at a dose that does not lead to liver damage. Our research provides a novel means to achieve not only targeted delivery but also the potential for gene therapy of human liver cancer.

  18. Optimal portfolio selection in a Lévy market with uncontrolled cash flow and only risky assets

    NASA Astrophysics Data System (ADS)

    Zeng, Yan; Li, Zhongfei; Wu, Huiling

    2013-03-01

    This article considers an investor who has an exogenous cash flow evolving according to a Lévy process and invests in a financial market consisting of only risky assets, whose prices are governed by exponential Lévy processes. Two continuous-time portfolio selection problems are studied for the investor. One is a benchmark problem, and the other is a mean-variance problem. The first problem is solved by adopting the stochastic dynamic programming approach, and the obtained results are extended to the second problem by employing the duality theory. Closed-form solutions of these two problems are derived. Some existing results are found to be special cases of our results.

  19. Preparation of Mn-based selective catalytic reduction catalysts by three methods and optimization of process conditions.

    PubMed

    Xing, Yi; Hong, Chen; Cheng, Bei; Zhang, Kun

    2013-01-01

    Mn-based catalysts enable high NO x conversion in the selective catalytic reduction of NO x with NH3. Three catalyst-production methods, namely, co-precipitation, impregnation, and sol-gel, were used in this study to determine the optimum method and parameters. The maximum catalytic activity was found for the catalyst prepared by sol-gel with a 0.5 Mn/Ti ratio. The denitrification efficiency using this catalyst was >90%, which was higher than those of catalysts prepared by the two other methods. The critical temperature of catalytic activity was 353 K. The optimum manganese acetate concentration and weathering time were 0.10 mol and 24 h, respectively. The gas hourly space velocity and O2 concentration were determined to be 12000 h(-1) and 3%, respectively.

  20. Development of a novel class of B-RafV600E-selective inhibitors through virtual screening and hierarchical hit optimization

    PubMed Central

    Kong, Xiangqian; Qin, Jie; Li, Zeng; Vultur, Adina; Tong, Linjiang; Feng, Enguang; Rajan, Geena; Liu, Shien; Lu, Junyan; Liang, Zhongjie; Zheng, Mingyue; Zhu, Weiliang; Jiang, Hualiang; Herlyn, Meenhard; Liu, Hong; Marmorstein, Ronen; Luo, Cheng

    2012-01-01

    Oncogenic mutations in critical nodes of cellular signaling pathways have been associated with tumorigenesis and progression. The B-Raf protein kinase, a key hub in the canonical MAPK signaling cascade, is mutated in a broad range of human cancers and especially in malignant melanoma. The most prevalent B-RafV600E mutant exhibits elevated kinase activity and results in constitutive activation of the MAPK pathway, thus making it a promising drug target for cancer therapy. Herein, we described the development of novel B-RafV600E selective inhibitors via multi-step virtual screening and hierarchical hit optimization. Nine hit compounds with low micromolar IC50 values were identified as B-RafV600E inhibitors through virtual screening. Subsequent scaffold-based analogue searching and medicinal chemistry efforts significantly improved both the inhibitor potency and oncogene selectivity. In particular, compounds 22f and 22q possess nanomolar IC50 values with selectivity for B-RafV600E in vitro and exclusive cytotoxicity against B-RafV600E harboring cancer cells. PMID:22875039