Compliant flow designs for optimum lift control of wind turbine rotors

NASA Astrophysics Data System (ADS)

Williams, Theodore J. H.

An optimization approach was formulated to determine geometric designs that are most compliant to flow control devices. Single dielectric barrier discharge (SDBD) plasma actuators are used in the flow control design optimization as they are able to be incorporated into CFD simulations. An adjoint formulation was derived in order to have a numerically efficient way of calculating the shape derivatives on the surface of the geometric design. The design of a wind turbine blade retrofit for the JIMP 25kW wind turbine at Notre Dame is used to motivate analyses that utilize the optimization approach. The CFD simulations of the existing wind turbine blade were validated against wind tunnel testing. A one-parameter optimization was performed in order to design a trailing edge addition for the current wind turbine blade. The trailing edge addition was designed to meet a desired lift target while maximizing the lift-to-drag ratio. This analysis was performed at seven radial locations on the wind turbine blade. The new trailing edge retrofits were able to achieve the lift target for the outboard radial locations. The designed geometry has been fabricated and is currently being validated on a full-scale turbine and it is predicted to have an increase in annual energy production of 4.30%. The design of a trailing edge retrofit that includes the use of a SDBD plasma actuator was performed using a two-parameter optimization. The objective of this analysis was to meet the lift target and maximize the controllability of the design. The controllability is defined as the difference in lift between plasma on and plasma off cases. A trailing edge retrofit with the plasma actuator located on the pressure side was able to achieve the target passive lift increase while using plasma flow control to reduce the lift to below the original design. This design resulted in a highly compliant flow.

Constant-Envelope Waveform Design for Optimal Target-Detection and Autocorrelation Performances

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

Sen, Satyabrata

2013-01-01

We propose an algorithm to directly synthesize in time-domain a constant-envelope transmit waveform that achieves the optimal performance in detecting an extended target in the presence of signal-dependent interference. This approach is in contrast to the traditional indirect methods that synthesize the transmit signal following the computation of the optimal energy spectral density. Additionally, we aim to maintain a good autocorrelation property of the designed signal. Therefore, our waveform design technique solves a bi-objective optimization problem in order to simultaneously improve the detection and autocorrelation performances, which are in general conflicting in nature. We demonstrate this compromising characteristics of themore » detection and autocorrelation performances with numerical examples. Furthermore, in the absence of the autocorrelation criterion, our designed signal is shown to achieve a near-optimum detection performance.« less

Optimization study on structural analyses for the J-PARC mercury target vessel

NASA Astrophysics Data System (ADS)

Guan, Wenhai; Wakai, Eiichi; Naoe, Takashi; Kogawa, Hiroyuki; Wakui, Takashi; Haga, Katsuhiro; Takada, Hiroshi; Futakawa, Masatoshi

2018-06-01

The spallation neutron source at the Japan Proton Accelerator Research Complex (J-PARC) mercury target vessel is used for various materials science studies, work is underway to achieve stable operation at 1 MW. This is very important for enhancing the structural integrity and durability of the target vessel, which is being developed for 1 MW operation. In the present study, to reduce thermal stress and relax stress concentrations more effectively in the existing target vessel in J-PARC, an optimization approach called the Taguchi method (TM) is applied to thermo-mechanical analysis. The ribs and their relative parameters, as well as the thickness of the mercury vessel and shrouds, were selected as important design parameters for this investigation. According to the analytical results of 18 model types designed using the TM, the optimal design was determined. It is characterized by discrete ribs and a thicker vessel wall than the current design. The maximum thermal stresses in the mercury vessel and the outer shroud were reduced by 14% and 15%, respectively. Furthermore, it was indicated that variations in rib width, left/right rib intervals, and shroud thickness could influence the maximum thermal stress performance. It is therefore concluded that the TM was useful for optimizing the structure of the target vessel and to reduce the thermal stress in a small number of calculation cases.

Divertor target shape optimization in realistic edge plasma geometry

NASA Astrophysics Data System (ADS)

Dekeyser, W.; Reiter, D.; Baelmans, M.

2014-07-01

Tokamak divertor design for next-step fusion reactors heavily relies on numerical simulations of the plasma edge. Currently, the design process is mainly done in a forward approach, where the designer is strongly guided by his experience and physical intuition in proposing divertor shapes, which are then thoroughly assessed by numerical computations. On the other hand, automated design methods based on optimization have proven very successful in the related field of aerodynamic design. By recasting design objectives and constraints into the framework of a mathematical optimization problem, efficient forward-adjoint based algorithms can be used to automatically compute the divertor shape which performs the best with respect to the selected edge plasma model and design criteria. In the past years, we have extended these methods to automated divertor target shape design, using somewhat simplified edge plasma models and geometries. In this paper, we build on and extend previous work to apply these shape optimization methods for the first time in more realistic, single null edge plasma and divertor geometry, as commonly used in current divertor design studies. In a case study with JET-like parameters, we show that the so-called one-shot method is very effective is solving divertor target design problems. Furthermore, by detailed shape sensitivity analysis we demonstrate that the development of the method already at the present state provides physically plausible trends, allowing to achieve a divertor design with an almost perfectly uniform power load for our particular choice of edge plasma model and design criteria.

Structure-Based Design of Highly Selective Inhibitors of the CREB Binding Protein Bromodomain.

PubMed

Denny, R Aldrin; Flick, Andrew C; Coe, Jotham; Langille, Jonathan; Basak, Arindrajit; Liu, Shenping; Stock, Ingrid; Sahasrabudhe, Parag; Bonin, Paul; Hay, Duncan A; Brennan, Paul E; Pletcher, Mathew; Jones, Lyn H; Chekler, Eugene L Piatnitski

2017-07-13

Chemical probes are required for preclinical target validation to interrogate novel biological targets and pathways. Selective inhibitors of the CREB binding protein (CREBBP)/EP300 bromodomains are required to facilitate the elucidation of biology associated with these important epigenetic targets. Medicinal chemistry optimization that paid particular attention to physiochemical properties delivered chemical probes with desirable potency, selectivity, and permeability attributes. An important feature of the optimization process was the successful application of rational structure-based drug design to address bromodomain selectivity issues (particularly against the structurally related BRD4 protein).

Optimization of vascular-targeting drugs in a computational model of tumor growth

NASA Astrophysics Data System (ADS)

Gevertz, Jana

2012-04-01

A biophysical tool is introduced that seeks to provide a theoretical basis for helping drug design teams assess the most promising drug targets and design optimal treatment strategies. The tool is grounded in a previously validated computational model of the feedback that occurs between a growing tumor and the evolving vasculature. In this paper, the model is particularly used to explore the therapeutic effectiveness of two drugs that target the tumor vasculature: angiogenesis inhibitors (AIs) and vascular disrupting agents (VDAs). Using sensitivity analyses, the impact of VDA dosing parameters is explored, as is the effects of administering a VDA with an AI. Further, a stochastic optimization scheme is utilized to identify an optimal dosing schedule for treatment with an AI and a chemotherapeutic. The treatment regimen identified can successfully halt simulated tumor growth, even after the cessation of therapy.

An automated approach to magnetic divertor configuration design

NASA Astrophysics Data System (ADS)

Blommaert, M.; Dekeyser, W.; Baelmans, M.; Gauger, N. R.; Reiter, D.

2015-01-01

Automated methods based on optimization can greatly assist computational engineering design in many areas. In this paper an optimization approach to the magnetic design of a nuclear fusion reactor divertor is proposed and applied to a tokamak edge magnetic configuration in a first feasibility study. The approach is based on reduced models for magnetic field and plasma edge, which are integrated with a grid generator into one sensitivity code. The design objective chosen here for demonstrative purposes is to spread the divertor target heat load as much as possible over the entire target area. Constraints on the separatrix position are introduced to eliminate physically irrelevant magnetic field configurations during the optimization cycle. A gradient projection method is used to ensure stable cost function evaluations during optimization. The concept is applied to a configuration with typical Joint European Torus (JET) parameters and it automatically provides plausible configurations with reduced heat load.

A novel experimental design method to optimize hydrophilic matrix formulations with drug release profiles and mechanical properties.

PubMed

Choi, Du Hyung; Lim, Jun Yeul; Shin, Sangmun; Choi, Won Jun; Jeong, Seong Hoon; Lee, Sangkil

2014-10-01

To investigate the effects of hydrophilic polymers on the matrix system, an experimental design method was developed to integrate response surface methodology and the time series modeling. Moreover, the relationships among polymers on the matrix system were studied with the evaluation of physical properties including water uptake, mass loss, diffusion, and gelling index. A mixture simplex lattice design was proposed while considering eight input control factors: Polyethylene glycol 6000 (x1 ), polyethylene oxide (PEO) N-10 (x2 ), PEO 301 (x3 ), PEO coagulant (x4 ), PEO 303 (x5 ), hydroxypropyl methylcellulose (HPMC) 100SR (x6 ), HPMC 4000SR (x7 ), and HPMC 10(5) SR (x8 ). With the modeling, optimal formulations were obtained depending on the four types of targets. The optimal formulations showed the four significant factors (x1 , x2 , x3 , and x8 ) and other four input factors (x4 , x5 , x6 , and x7 ) were not significant based on drug release profiles. Moreover, the optimization results were analyzed with estimated values, targets values, absolute biases, and relative biases based on observed times for the drug release rates with four different targets. The result showed that optimal solutions and target values had consistent patterns with small biases. On the basis of the physical properties of the optimal solutions, the type and ratio of the hydrophilic polymer and the relationships between polymers significantly influenced the physical properties of the system and drug release. This experimental design method is very useful in formulating a matrix system with optimal drug release. Moreover, it can distinctly confirm the relationships between excipients and the effects on the system with extensive and intensive evaluations. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Design of transcranial magnetic stimulation coils with optimal trade-off between depth, focality, and energy.

PubMed

Gomez, Luis J; Goetz, Stefan M; Peterchev, Angel V

2018-08-01

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique used for research and clinical applications. Existent TMS coils are limited in their precision of spatial targeting (focality), especially for deeper targets. This paper presents a methodology for designing TMS coils to achieve optimal trade-off between the depth and focality of the induced electric field (E-field), as well as the energy required by the coil. A multi-objective optimization technique is used for computationally designing TMS coils that achieve optimal trade-offs between E-field focality, depth, and energy (fdTMS coils). The fdTMS coil winding(s) maximize focality (minimize the volume of the brain region with E-field above a given threshold) while reaching a target at a specified depth and not exceeding predefined peak E-field strength and required coil energy. Spherical and MRI-derived head models are used to compute the fundamental depth-focality trade-off as well as focality-energy trade-offs for specific target depths. Across stimulation target depths of 1.0-3.4 cm from the brain surface, the suprathreshold volume can be theoretically decreased by 42%-55% compared to existing TMS coil designs. The suprathreshold volume of a figure-8 coil can be decreased by 36%, 44%, or 46%, for matched, doubled, or quadrupled energy. For matched focality and energy, the depth of a figure-8 coil can be increased by 22%. Computational design of TMS coils could enable more selective targeting of the induced E-field. The presented results appear to be the first significant advancement in the depth-focality trade-off of TMS coils since the introduction of the figure-8 coil three decades ago, and likely represent the fundamental physical limit.

Optimal Design of Gradient Materials and Bi-Level Optimization of Topology Using Targets (BOTT)

NASA Astrophysics Data System (ADS)

Garland, Anthony

The objective of this research is to understand the fundamental relationships necessary to develop a method to optimize both the topology and the internal gradient material distribution of a single object while meeting constraints and conflicting objectives. Functionally gradient material (FGM) objects possess continuous varying material properties throughout the object, and they allow an engineer to tailor individual regions of an object to have specific mechanical properties by locally modifying the internal material composition. A variety of techniques exists for topology optimization, and several methods exist for FGM optimization, but combining the two together is difficult. Understanding the relationship between topology and material gradient optimization enables the selection of an appropriate model and the development of algorithms, which allow engineers to design high-performance parts that better meet design objectives than optimized homogeneous material objects. For this research effort, topology optimization means finding the optimal connected structure with an optimal shape. FGM optimization means finding the optimal macroscopic material properties within an object. Tailoring the material constitutive matrix as a function of position results in gradient properties. Once, the target macroscopic properties are known, a mesostructure or a particular material nanostructure can be found which gives the target material properties at each macroscopic point. This research demonstrates that topology and gradient materials can both be optimized together for a single part. The algorithms use a discretized model of the domain and gradient based optimization algorithms. In addition, when considering two conflicting objectives the algorithms in this research generate clear 'features' within a single part. This tailoring of material properties within different areas of a single part (automated design of 'features') using computational design tools is a novel benefit of gradient material designs. A macroscopic gradient can be achieved by varying the microstructure or the mesostructures of an object. The mesostructure interpretation allows for more design freedom since the mesostructures can be tuned to have non-isotropic material properties. A new algorithm called Bi-level Optimization of Topology using Targets (BOTT) seeks to find the best distribution of mesostructure designs throughout a single object in order to minimize an objective value. On the macro level, the BOTT algorithm optimizes the macro topology and gradient material properties within the object. The BOTT algorithm optimizes the material gradient by finding the best constitutive matrix at each location with the object. In order to enhance the likelihood that a mesostructure can be generated with the same equivalent constitutive matrix, the variability of the constitutive matrix is constrained to be an orthotropic material. The stiffness in the X and Y directions (of the base coordinate system) can change in addition to rotating the orthotropic material to align with the loading at each region. Second, the BOTT algorithm designs mesostructures with macroscopic properties equal to the target properties found in step one while at the same time the algorithm seeks to minimize material usage in each mesostructure. The mesostructure algorithm maximizes the strain energy of the mesostructures unit cell when a pseudo strain is applied to the cell. A set of experiments reveals the fundamental relationship between target cell density and the strain (or pseudo strain) applied to a unit cell and the output effective properties of the mesostructure. At low density, a few mesostructure unit cell design are possible, while at higher density the mesostructure unit cell designs have many possibilities. Therefore, at low densities the effective properties of the mesostructure are a step function of the applied pseudo strain. At high densities, the effective properties of the mesostructure are continuous function of the applied pseudo strain. Finally, the macro and mesostructure designs are coordinated so that the macro and meso levels agree on the material properties at each macro region. In addition, a coordination effort seeks to coordinate the boundaries of adjacent mesostructure designs so that the macro load path is transmitted from one mesostructure design to its neighbors. The BOTT algorithm has several advantages over existing algorithms within the literature. First, the BOTT algorithm significantly reduces the computational power required to run the algorithm. Second, the BOTT algorithm indirectly enforces a minimum mesostructure density constraint which increases the manufacturability of the final design. Third, the BOTT algorithm seeks to transfer the load from one mesostructure to its neighbors by coordinating the boundaries of adjacent mesostructure designs. However, the BOTT algorithm can still be improved since it may have difficulty converging due to the step function nature of the mesostructure design problem at low density.

Inverse design of bulk morphologies in block copolymers using particle swarm optimization

NASA Astrophysics Data System (ADS)

Khadilkar, Mihir; Delaney, Kris; Fredrickson, Glenn

Multiblock polymers are a versatile platform for creating a large range of nanostructured materials with novel morphologies and properties. However, achieving desired structures or property combinations is difficult due to a vast design space comprised of parameters including monomer species, block sequence, block molecular weights and dispersity, copolymer architecture, and binary interaction parameters. Navigating through such vast design spaces to achieve an optimal formulation for a target structure or property set requires an efficient global optimization tool wrapped around a forward simulation technique such as self-consistent field theory (SCFT). We report on such an inverse design strategy utilizing particle swarm optimization (PSO) as the global optimizer and SCFT as the forward prediction engine. To avoid metastable states in forward prediction, we utilize pseudo-spectral variable cell SCFT initiated from a library of defect free seeds of known block copolymer morphologies. We demonstrate that our approach allows for robust identification of block copolymers and copolymer alloys that self-assemble into a targeted structure, optimizing parameters such as block fractions, blend fractions, and Flory chi parameters.

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Achieving Conservation when Opportunity Costs Are High: Optimizing Reserve Design in Alberta's Oil Sands Region

PubMed Central

Schneider, Richard R.; Hauer, Grant; Farr, Dan; Adamowicz, W. L.; Boutin, Stan

2011-01-01

Recent studies have shown that conservation gains can be achieved when the spatial distributions of biological benefits and economic costs are incorporated in the conservation planning process. Using Alberta, Canada, as a case study we apply these techniques in the context of coarse-filter reserve design. Because targets for ecosystem representation and other coarse-filter design elements are difficult to define objectively we use a trade-off analysis to systematically explore the relationship between conservation targets and economic opportunity costs. We use the Marxan conservation planning software to generate reserve designs at each level of conservation target to ensure that our quantification of conservation and economic outcomes represents the optimal allocation of resources in each case. Opportunity cost is most affected by the ecological representation target and this relationship is nonlinear. Although petroleum resources are present throughout most of Alberta, and include highly valuable oil sands deposits, our analysis indicates that over 30% of public lands could be protected while maintaining access to more than 97% of the value of the region's resources. Our case study demonstrates that optimal resource allocation can be usefully employed to support strategic decision making in the context of land-use planning, even when conservation targets are not well defined. PMID:21858046

Targeted polymeric therapeutic nanoparticles: design, development and clinical translation†

PubMed Central

Kamaly, Nazila; Xiao, Zeyu; Valencia, Pedro M.; Radovic-Moreno, Aleksandar F.; Farokhzad, Omid C.

2013-01-01

Polymeric materials have been used in a range of pharmaceutical and biotechnology products for more than 40 years. These materials have evolved from their earlier use as biodegradable products such as resorbable sutures, orthopaedic implants, macroscale and microscale drug delivery systems such as microparticles and wafers used as controlled drug release depots, to multifunctional nanoparticles (NPs) capable of targeting, and controlled release of therapeutic and diagnostic agents. These newer generations of targeted and controlled release polymeric NPs are now engineered to navigate the complex in vivo environment, and incorporate functionalities for achieving target specificity, control of drug concentration and exposure kinetics at the tissue, cell, and subcellular levels. Indeed this optimization of drug pharmacology as aided by careful design of multifunctional NPs can lead to improved drug safety and efficacy, and may be complimentary to drug enhancements that are traditionally achieved by medicinal chemistry. In this regard, polymeric NPs have the potential to result in a highly differentiated new class of therapeutics, distinct from the original active drugs used in their composition, and distinct from first generation NPs that largely facilitated drug formulation. A greater flexibility in the design of drug molecules themselves may also be facilitated following their incorporation into NPs, as drug properties (solubility, metabolism, plasma binding, biodistribution, target tissue accumulation) will no longer be constrained to the same extent by drug chemical composition, but also become in-part the function of the physicochemical properties of the NP. The combination of optimally designed drugs with optimally engineered polymeric NPs opens up the possibility of improved clinical outcomes that may not be achievable with the administration of drugs in their conventional form. In this critical review, we aim to provide insights into the design and development of targeted polymeric NPs and to highlight the challenges associated with the engineering of this novel class of therapeutics, including considerations of NP design optimization, development and biophysicochemical properties. Additionally, we highlight some recent examples from the literature, which demonstrate current trends and novel concepts in both the design and utility of targeted polymeric NPs (444 references). PMID:22388185

PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

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

Sen, Satyabrata

We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratiomore » (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.« less

Investigating a multi-purpose target for electron linac based photoneutron sources for BNCT of deep-seated tumors

NASA Astrophysics Data System (ADS)

Masoudi, S. Farhad; Rasouli, Fatemeh S.

2015-08-01

Recent studies in BNCT have focused on investigating appropriate neutron sources as alternatives for nuclear reactors. As the most prominent facilities, the electron linac based photoneutron sources benefit from two consecutive reactions, (e, γ) and (γ, n). The photoneutron sources designed so far are composed of bipartite targets which involve practical problems and are far from the objective of achieving an optimized neutron source. This simulation study deals with designing a compact, optimized, and geometrically simple target for a photoneutron source based on an electron linac. Based on a set of MCNPX simulations, tungsten is found to have the potential of utilizing as both photon converter and photoneutron target. Besides, it is shown that an optimized dimension for such a target slows-down the produced neutrons toward the desired energy range while keeping them economy, which makes achieving the recommended criteria for BNCT of deep-tumors more available. This multi-purpose target does not involve complicated designing, and can be considered as a significant step toward finding application of photoneutron sources for in-hospital treatments. In order to shape the neutron beam emitted from such a target, the beam is planned to pass through an optimized arrangement of materials composed of moderators, filters, reflector, and collimator. By assessment with the recommended in-air parameters, it is shown that the designed beam provides high intensity of desired neutrons, as well as low background contamination. The last section of this study is devoted to investigate the performance of the resultant beam in deep tissue. A typical simulated liver tumor, located within a phantom of human body, was subjected to the irradiation of the designed spectrum. The dosimetric results, including evaluated depth-dose curves and carried out in-phantom parameters show that the proposed configuration establishes acceptable agreement between the appropriate neutron intensity, and penetrating deep in tissue in a reasonable treatment time.

Advanced Information Technology in Simulation Based Life Cycle Design

NASA Technical Reports Server (NTRS)

Renaud, John E.

2003-01-01

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.

Optimization of the NIF ignition point design hohlraum

NASA Astrophysics Data System (ADS)

Callahan, D. A.; Hinkel, D. E.; Berger, R. L.; Divol, L.; Dixit, S. N.; Edwards, M. J.; Haan, S. W.; Jones, O. S.; Lindl, J. D.; Meezan, N. B.; Michel, P. A.; Pollaine, S. M.; Suter, L. J.; Town, R. P. J.; Bradley, P. A.

2008-05-01

In preparation for the start of NIF ignition experiments, we have designed a porfolio of targets that span the temperature range that is consistent with initial NIF operations: 300 eV, 285 eV, and 270 eV. Because these targets are quite complicated, we have developed a plan for choosing the optimum hohlraum for the first ignition attempt that is based on this portfolio of designs coupled with early NIF experiements using 96 beams. These early experiments will measure the laser plasma instabilities of the candidate designs and will demonstrate our ability to tune symmetry in these designs. These experimental results, coupled with the theory and simulations that went into the designs, will allow us to choose the optimal hohlraum for the first NIF ignition attempt.

Design of a secondary ionization target for direct production of a C- beam from CO2 pulses for online AMS.

PubMed

Salazar, Gary; Ognibene, Ted

2013-01-01

We designed and optimized a novel device "target" that directs a CO 2 gas pulse onto a Ti surface where a Cs + beam generates C - from the CO 2 . This secondary ionization target enables an accelerator mass spectrometer to ionize pulses of CO 2 in the negative mode to measure 14 C/ 12 C isotopic ratios in real time. The design of the targets were based on computational flow dynamics, ionization mechanism and empirical optimization. As part of the ionization mechanism, the adsorption of CO 2 on the Ti surface was fitted with the Jovanovic-Freundlich isotherm model using empirical and simulation data. The inferred adsorption constants were in good agreement with other works. The empirical optimization showed that amount of injected carbon and the flow speed of the helium carrier gas improve the ionization efficiency and the amount of 12 C - produced until reaching a saturation point. Linear dynamic range between 150 and 1000 ng of C and optimum carrier gas flow speed of around 0.1 mL/min were shown. It was also shown that the ionization depends on the area of the Ti surface and Cs + beam cross-section. A range of ionization efficiency of 1-2.5% was obtained by optimizing the described parameters.

Investigations into the design principles in the chemotactic behavior of Escherichia coli.

PubMed

Kim, Tae-Hwan; Jung, Sung Hoon; Cho, Kwang-Hyun

2008-01-01

Inspired by the recent studies on the analysis of biased random walk behavior of Escherichia coli[Passino, K.M., 2002. Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst. Mag. 22 (3), 52-67; Passino, K.M., 2005. Biomimicry for Optimization, Control and Automation. Springer-Verlag, pp. 768-798; Liu, Y., Passino, K.M., 2002. Biomimicry of social foraging bacteria for distributed optimization: models, principles, and emergent behaviors. J. Optim. Theory Appl. 115 (3), 603-628], we have developed a model describing the motile behavior of E. coli by specifying some simple rules on the chemotaxis. Based on this model, we have analyzed the role of some key parameters involved in the chemotactic behavior to unravel the underlying design principles. By investigating the target tracking capability of E. coli in a maze through computer simulations, we found that E. coli clusters can be controlled as target trackers in a complex micro-scale-environment. In addition, we have explored the dynamical characteristics of this target tracking mechanism through perturbation of parameters under noisy environments. It turns out that the E. coli chemotaxis mechanism might be designed such that it is sensitive enough to efficiently track the target and also robust enough to overcome environmental noises.

Systematic design of 3D auxetic lattice materials with programmable Poisson's ratio for finite strains

NASA Astrophysics Data System (ADS)

Wang, Fengwen

2018-05-01

This paper presents a systematic approach for designing 3D auxetic lattice materials, which exhibit constant negative Poisson's ratios over large strain intervals. A unit cell model mimicking tensile tests is established and based on the proposed model, the secant Poisson's ratio is defined as the negative ratio between the lateral and the longitudinal engineering strains. The optimization problem for designing a material unit cell with a target Poisson's ratio is formulated to minimize the average lateral engineering stresses under the prescribed deformations. Numerical results demonstrate that 3D auxetic lattice materials with constant Poisson's ratios can be achieved by the proposed optimization formulation and that two sets of material architectures are obtained by imposing different symmetry on the unit cell. Moreover, inspired by the topology-optimized material architecture, a subsequent shape optimization is proposed by parametrizing material architectures using super-ellipsoids. By designing two geometrical parameters, simple optimized material microstructures with different target Poisson's ratios are obtained. By interpolating these two parameters as polynomial functions of Poisson's ratios, material architectures for any Poisson's ratio in the interval of ν ∈ [ - 0.78 , 0.00 ] are explicitly presented. Numerical evaluations show that interpolated auxetic lattice materials exhibit constant Poisson's ratios in the target strain interval of [0.00, 0.20] and that 3D auxetic lattice material architectures with programmable Poisson's ratio are achievable.

Waveform Design and Diversity for Advanced Space-Time Adaptive Processing and Multiple Input Multiple Output Systems

DTIC Science & Technology

2012-08-01

It suggests that a smart use of some a-priori information about the operating environment, when processing the received signal and designing the...random variable with the same variance of the backscattering target amplitude αT , and D ( αT , α G T ) is the Kullback − Leibler divergence, see [65...MI . Proof. See Appendix 3.6.6. Thus, we can use the optimization procedure of Algorithm 4 to optimize the Mutual Information between the target

Computational design of nanoparticle drug delivery systems for selective targeting

NASA Astrophysics Data System (ADS)

Duncan, Gregg A.; Bevan, Michael A.

2015-09-01

Ligand-functionalized nanoparticles capable of selectively binding to diseased versus healthy cell populations are attractive for improved efficacy of nanoparticle-based drug and gene therapies. However, nanoparticles functionalized with high affinity targeting ligands may lead to undesired off-target binding to healthy cells. In this work, Monte Carlo simulations were used to quantitatively determine net surface interactions, binding valency, and selectivity between targeted nanoparticles and cell surfaces. Dissociation constant, KD, and target membrane protein density, ρR, are explored over a range representative of healthy and cancerous cell surfaces. Our findings show highly selective binding to diseased cell surfaces can be achieved with multiple, weaker affinity targeting ligands that can be further optimized by varying the targeting ligand density, ρL. Using the approach developed in this work, nanomedicines can be optimally designed for exclusively targeting diseased cells and tissues.Ligand-functionalized nanoparticles capable of selectively binding to diseased versus healthy cell populations are attractive for improved efficacy of nanoparticle-based drug and gene therapies. However, nanoparticles functionalized with high affinity targeting ligands may lead to undesired off-target binding to healthy cells. In this work, Monte Carlo simulations were used to quantitatively determine net surface interactions, binding valency, and selectivity between targeted nanoparticles and cell surfaces. Dissociation constant, KD, and target membrane protein density, ρR, are explored over a range representative of healthy and cancerous cell surfaces. Our findings show highly selective binding to diseased cell surfaces can be achieved with multiple, weaker affinity targeting ligands that can be further optimized by varying the targeting ligand density, ρL. Using the approach developed in this work, nanomedicines can be optimally designed for exclusively targeting diseased cells and tissues. Electronic supplementary information (ESI) available: Movie showing simulation renderings of targeted (ρL = 1820/μm2, KD = 120 μM) nanoparticle selective binding to cancer (ρR = 256/μm2) vs. healthy (ρR = 64/μm2) cell surfaces. Target membrane proteins have linear color scale depending on binding energy ranging from white when unbound (URL = 0) to red when tightly bound (URL = UM). See DOI: 10.1039/c5nr03691g

An automated design process for short pulse laser driven opacity experiments

DOE PAGES

Martin, M. E.; London, R. A.; Goluoglu, S.; ...

2017-12-21

Stellar-relevant conditions can be reached by heating a buried layer target with a short pulse laser. Previous design studies of iron buried layer targets found that plasma conditions are dominantly controlled by the laser energy while the accuracy of the inferred opacity is limited by tamper emission and optical depth effects. In this paper, we developed a process to simultaneously optimize laser and target parameters to meet a variety of design goals. We explored two sets of design cases: a set focused on conditions relevant to the upper radiative zone of the sun (electron temperatures of 200 to 400 eVmore » and densities greater than 1/10 of solid density) and a set focused on reaching temperatures consistent with deep within the radiative zone of the sun (500 to 1000 eV) at a fixed density. We found optimized designs for iron targets and determined that the appropriate dopant, for inferring plasma conditions, depends on the goal temperature: magnesium for up to 300 eV, aluminum for 300 to 500 eV, and sulfur for 500 to 1000 eV. The optimal laser energy and buried layer thickness increase with goal temperature. The accuracy of the inferred opacity is limited to between 11% and 31%, depending on the design. Finally, overall, short pulse laser heated iron experiments reaching stellar-relevant conditions have been designed with consideration of minimizing tamper emission and optical depth effects while meeting plasma condition and x-ray emission goals.« less

An automated design process for short pulse laser driven opacity experiments

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

Martin, M. E.; London, R. A.; Goluoglu, S.

Stellar-relevant conditions can be reached by heating a buried layer target with a short pulse laser. Previous design studies of iron buried layer targets found that plasma conditions are dominantly controlled by the laser energy while the accuracy of the inferred opacity is limited by tamper emission and optical depth effects. In this paper, we developed a process to simultaneously optimize laser and target parameters to meet a variety of design goals. We explored two sets of design cases: a set focused on conditions relevant to the upper radiative zone of the sun (electron temperatures of 200 to 400 eVmore » and densities greater than 1/10 of solid density) and a set focused on reaching temperatures consistent with deep within the radiative zone of the sun (500 to 1000 eV) at a fixed density. We found optimized designs for iron targets and determined that the appropriate dopant, for inferring plasma conditions, depends on the goal temperature: magnesium for up to 300 eV, aluminum for 300 to 500 eV, and sulfur for 500 to 1000 eV. The optimal laser energy and buried layer thickness increase with goal temperature. The accuracy of the inferred opacity is limited to between 11% and 31%, depending on the design. Finally, overall, short pulse laser heated iron experiments reaching stellar-relevant conditions have been designed with consideration of minimizing tamper emission and optical depth effects while meeting plasma condition and x-ray emission goals.« less

Closed-Loop Multitarget Optimization for Discovery of New Emulsion Polymerization Recipes

PubMed Central

2015-01-01

Self-optimization of chemical reactions enables faster optimization of reaction conditions or discovery of molecules with required target properties. The technology of self-optimization has been expanded to discovery of new process recipes for manufacture of complex functional products. A new machine-learning algorithm, specifically designed for multiobjective target optimization with an explicit aim to minimize the number of “expensive” experiments, guides the discovery process. This “black-box” approach assumes no a priori knowledge of chemical system and hence particularly suited to rapid development of processes to manufacture specialist low-volume, high-value products. The approach was demonstrated in discovery of process recipes for a semibatch emulsion copolymerization, targeting a specific particle size and full conversion. PMID:26435638

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment‐Based Drug Design Facilitated by Dynamic Combinatorial Chemistry

PubMed Central

Mondal, Milon; Radeva, Nedyalka; Fanlo‐Virgós, Hugo; Otto, Sijbren; Klebe, Gerhard

2016-01-01

Abstract Fragment‐based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit‐identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X‐ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis‐acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240‐fold improvement in potency compared to the parent hits. Subsequent X‐ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit‐identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit‐to‐lead optimization. PMID:27400756

Small-Tip-Angle Spokes Pulse Design Using Interleaved Greedy and Local Optimization Methods

PubMed Central

Grissom, William A.; Khalighi, Mohammad-Mehdi; Sacolick, Laura I.; Rutt, Brian K.; Vogel, Mika W.

2013-01-01

Current spokes pulse design methods can be grouped into methods based either on sparse approximation or on iterative local (gradient descent-based) optimization of the transverse-plane spatial frequency locations visited by the spokes. These two classes of methods have complementary strengths and weaknesses: sparse approximation-based methods perform an efficient search over a large swath of candidate spatial frequency locations but most are incompatible with off-resonance compensation, multifrequency designs, and target phase relaxation, while local methods can accommodate off-resonance and target phase relaxation but are sensitive to initialization and suboptimal local cost function minima. This article introduces a method that interleaves local iterations, which optimize the radiofrequency pulses, target phase patterns, and spatial frequency locations, with a greedy method to choose new locations. Simulations and experiments at 3 and 7 T show that the method consistently produces single- and multifrequency spokes pulses with lower flip angle inhomogeneity compared to current methods. PMID:22392822

Genetic algorithm to optimize the design of main combustor and gas generator in liquid rocket engines

NASA Astrophysics Data System (ADS)

Son, Min; Ko, Sangho; Koo, Jaye

2014-06-01

A genetic algorithm was used to develop optimal design methods for the regenerative cooled combustor and fuel-rich gas generator of a liquid rocket engine. For the combustor design, a chemical equilibrium analysis was applied, and the profile was calculated using Rao's method. One-dimensional heat transfer was assumed along the profile, and cooling channels were designed. For the gas-generator design, non-equilibrium properties were derived from a counterflow analysis, and a vaporization model for the fuel droplet was adopted to calculate residence time. Finally, a genetic algorithm was adopted to optimize the designs. The combustor and gas generator were optimally designed for 30-tonf, 75-tonf, and 150-tonf engines. The optimized combustors demonstrated superior design characteristics when compared with previous non-optimized results. Wall temperatures at the nozzle throat were optimized to satisfy the requirement of 800 K, and specific impulses were maximized. In addition, the target turbine power and a burned-gas temperature of 1000 K were obtained from the optimized gas-generator design.

Genetic algorithm in the structural design of Cooke triplet lenses

NASA Astrophysics Data System (ADS)

Hazra, Lakshminarayan; Banerjee, Saswatee

1999-08-01

This paper is in tune with our efforts to develop a systematic method for multicomponent lens design. Our aim is to find a suitable starting point in the final configuration space, so that popular local search methods like damped least squares (DLS) may directly lead to a useful solution. For 'ab initio' design problems, a thin lens layout specifying the powers of the individual components and the intercomponent separations are worked out analytically. Requirements of central aberration targets for the individual components in order to satisfy the prespecified primary aberration targets for the overall system are then determined by nonlinear optimization. The next step involves structural design of the individual components by optimization techniques. This general method may be adapted for the design of triplets and their derivatives. However, for the thin lens design of a Cooke triplet composed of three airspaced singlets, the two steps of optimization mentioned above may be combined into a single optimization procedure. The optimum configuration for each of the single set, catering to the required Gaussian specification and primary aberration targets for the Cooke triplet, are determined by an application of genetic algorithm (GA). Our implementation of this algorithm is based on simulations of some complex tools of natural evolution, like selection, crossover and mutation. Our version of GA may or may not converge to a unique optimum, depending on some of the algorithm specific parameter values. With our algorithm, practically useful solutions are always available, although convergence to a global optimum can not be guaranteed. This is perfectly in keeping with our need to allow 'floating' of aberration targets in the subproblem level. Some numerical results dealing with our preliminary investigations on this problem are presented.

Adaptive waveform optimization design for target detection in cognitive radar

NASA Astrophysics Data System (ADS)

Zhang, Xiaowen; Wang, Kaizhi; Liu, Xingzhao

2017-01-01

The problem of adaptive waveform design for target detection in cognitive radar (CR) is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended target with unknown target impulse response (TIR). In order to estimate the TIR accurately, the Kalman filter is used in target tracking. In each Kalman filtering iteration, a flexible online waveform spectrum optimization design taking both detection and range resolution into account is modeled in Fourier domain. Unlike existing CR waveform, the proposed waveform can be simultaneously updated according to the environment information fed back by receiver and radar performance demands. Moreover, the influence of waveform spectral phase to radar performance is analyzed. Simulation results demonstrate that CR with the proposed waveform performs better than a traditional radar system with a fixed waveform and offers more flexibility and suitability. In addition, waveform spectral phase will not influence tracking, detection, and range resolution performance but will greatly influence waveform forming speed and peak-to-average power ratio.

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

PubMed

Yao, Yu; Zhao, Junhui; Wu, Lenan

2018-05-29

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

Lightweight design of automobile frame based on magnesium alloy

NASA Astrophysics Data System (ADS)

Lyu, R.; Jiang, X.; Minoru, O.; Ju, D. Y.

2018-06-01

The structural performance and lightweighting of car base frame design is a challenging task due to all the performance targets that must be satisfied. In this paper, three kinds of materials (iron, aluminum and magnesium alloy) replacement along with section design optimization strategy is proposed to develop a lightweight car frame structure to satisfy the tensile and safety while reducing weight. Two kinds of cross-sections are considered as the design variables. Using Ansys static structure, the design optimization problem is solved, comparing the results of each step, structure of the base flame is optimized for lightweight.

Waveform design for detection of weapons based on signature exploitation

NASA Astrophysics Data System (ADS)

Ahmad, Fauzia; Amin, Moeness G.; Dogaru, Traian

2010-04-01

We present waveform design based on signature exploitation techniques for improved detection of weapons in urban sensing applications. A single-antenna monostatic radar system is considered. Under the assumption of exact knowledge of the target orientation and, hence, known impulse response, matched illumination approach is used for optimal target detection. For the case of unknown target orientation, we analyze the target signatures as random processes and perform signal-to-noise-ratio based waveform optimization. Numerical electromagnetic modeling is used to provide the impulse responses of an AK-47 assault rifle for various target aspect angles relative to the radar. Simulation results depict an improvement in the signal-to-noise-ratio at the output of the matched filter receiver for both matched illumination and stochastic waveforms as compared to a chirp waveform of the same duration and energy.

Illumination system development using design and analysis of computer experiments

NASA Astrophysics Data System (ADS)

Keresztes, Janos C.; De Ketelaere, Bart; Audenaert, Jan; Koshel, R. J.; Saeys, Wouter

2015-09-01

Computer assisted optimal illumination design is crucial when developing cost-effective machine vision systems. Standard local optimization methods, such as downhill simplex optimization (DHSO), often result in an optimal solution that is influenced by the starting point by converging to a local minimum, especially when dealing with high dimensional illumination designs or nonlinear merit spaces. This work presents a novel nonlinear optimization approach, based on design and analysis of computer experiments (DACE). The methodology is first illustrated with a 2D case study of four light sources symmetrically positioned along a fixed arc in order to obtain optimal irradiance uniformity on a flat Lambertian reflecting target at the arc center. The first step consists of choosing angular positions with no overlap between sources using a fast, flexible space filling design. Ray-tracing simulations are then performed at the design points and a merit function is used for each configuration to quantify the homogeneity of the irradiance at the target. The obtained homogeneities at the design points are further used as input to a Gaussian Process (GP), which develops a preliminary distribution for the expected merit space. Global optimization is then performed on the GP more likely providing optimal parameters. Next, the light positioning case study is further investigated by varying the radius of the arc, and by adding two spots symmetrically positioned along an arc diametrically opposed to the first one. The added value of using DACE with regard to the performance in convergence is 6 times faster than the standard simplex method for equal uniformity of 97%. The obtained results were successfully validated experimentally using a short-wavelength infrared (SWIR) hyperspectral imager monitoring a Spectralon panel illuminated by tungsten halogen sources with 10% of relative error.

Optimization of LDL targeted nanostructured lipid carriers of 5-FU by a full factorial design.

PubMed

Andalib, Sare; Varshosaz, Jaleh; Hassanzadeh, Farshid; Sadeghi, Hojjat

2012-01-01

Nanostructured lipid carriers (NLC) are a mixture of solid and liquid lipids or oils as colloidal carrier systems that lead to an imperfect matrix structure with high ability for loading water soluble drugs. The aim of this study was to find the best proportion of liquid and solid lipids of different types for optimization of the production of LDL targeted NLCs used in carrying 5-Fu by the emulsification-solvent evaporation method. The influence of the lipid type, cholesterol or cholesteryl stearate for targeting LDL receptors, oil type (oleic acid or octanol), lipid and oil% on particle size, surface charge, drug loading efficiency, and drug released percent from the NLCs were studied by a full factorial design. The NLCs prepared by 54.5% cholesterol and 25% of oleic acid, showed optimum results with particle size of 105.8 nm, relatively high zeta potential of -25 mV, drug loading efficiency of 38% and release efficiency of about 40%. Scanning electron microscopy of nanoparticles confirmed the results of dynamic light scattering method used in measuring the particle size of NLCs. The optimization method by a full factorial statistical design is a useful optimization method for production of nanostructured lipid carriers.

Optimization of scaffold design for bone tissue engineering: A computational and experimental study.

PubMed

Dias, Marta R; Guedes, José M; Flanagan, Colleen L; Hollister, Scott J; Fernandes, Paulo R

2014-04-01

In bone tissue engineering, the scaffold has not only to allow the diffusion of cells, nutrients and oxygen but also provide adequate mechanical support. One way to ensure the scaffold has the right properties is to use computational tools to design such a scaffold coupled with additive manufacturing to build the scaffolds to the resulting optimized design specifications. In this study a topology optimization algorithm is proposed as a technique to design scaffolds that meet specific requirements for mass transport and mechanical load bearing. Several micro-structures obtained computationally are presented. Designed scaffolds were then built using selective laser sintering and the actual features of the fabricated scaffolds were measured and compared to the designed values. It was possible to obtain scaffolds with an internal geometry that reasonably matched the computational design (within 14% of porosity target, 40% for strut size and 55% for throat size in the building direction and 15% for strut size and 17% for throat size perpendicular to the building direction). These results support the use of these kind of computational algorithms to design optimized scaffolds with specific target properties and confirm the value of these techniques for bone tissue engineering. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Designs of infrared nonpolarizing beam splitters with a Ag layer in a glass cube.

PubMed

Shi, Jin Hui; Wang, Zheng Ping

2008-05-10

A novel design of a nonpolarizing beam splitter with a Ag layer in a cube was proposed and optimized, based on the needle optimization. The digital simulations of the reflectance and reflection-induced retardance were presented. The simulation results showed that both the amplitude and the phase characteristics of the nonpolarizing beam splitter could realize the design targets. The difference between the simulated and the target reflectance of 50% is less than 0.4% and the simulated and the reflection-induced retardance is less than 0.62 degrees in the 1260 -1360 nm range for both p and s components.

From laptop to benchtop to bedside: Structure-based Drug Design on Protein Targets

PubMed Central

Chen, Lu; Morrow, John K.; Tran, Hoang T.; Phatak, Sharangdhar S.; Du-Cuny, Lei; Zhang, Shuxing

2013-01-01

As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches. PMID:22316152

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

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

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

An optimization methodology for heterogeneous minor actinides transmutation

NASA Astrophysics Data System (ADS)

Kooyman, Timothée; Buiron, Laurent; Rimpault, Gérald

2018-04-01

In the case of a closed fuel cycle, minor actinides transmutation can lead to a strong reduction in spent fuel radiotoxicity and decay heat. In the heterogeneous approach, minor actinides are loaded in dedicated targets located at the core periphery so that long-lived minor actinides undergo fission and are turned in shorter-lived fission products. However, such targets require a specific design process due to high helium production in the fuel, high flux gradient at the core periphery and low power production. Additionally, the targets are generally manufactured with a high content in minor actinides in order to compensate for the low flux level at the core periphery. This leads to negative impacts on the fuel cycle in terms of neutron source and decay heat of the irradiated targets, which penalize their handling and reprocessing. In this paper, a simplified methodology for the design of targets is coupled with a method for the optimization of transmutation which takes into account both transmutation performances and fuel cycle impacts. The uncertainties and performances of this methodology are evaluated and shown to be sufficient to carry out scoping studies. An illustration is then made by considering the use of moderating material in the targets, which has a positive impact on the minor actinides consumption but a negative impact both on fuel cycle constraints (higher decay heat and neutron) and on assembly design (higher helium production and lower fuel volume fraction). It is shown that the use of moderating material is an optimal solution of the transmutation problem with regards to consumption and fuel cycle impacts, even when taking geometrical design considerations into account.

LEO cooperative multi-spacecraft refueling mission optimization considering J2 perturbation and target's surplus propellant constraint

NASA Astrophysics Data System (ADS)

Zhao, Zhao; Zhang, Jin; Li, Hai-yang; Zhou, Jian-yong

2017-01-01

The optimization of an LEO cooperative multi-spacecraft refueling mission considering the J2 perturbation and target's surplus propellant constraint is studied in the paper. First, a mission scenario is introduced. One service spacecraft and several target spacecraft run on an LEO near-circular orbit, the service spacecraft rendezvouses with some service positions one by one, and target spacecraft transfer to corresponding service positions respectively. Each target spacecraft returns to its original position after obtaining required propellant and the service spacecraft returns to its original position after refueling all target spacecraft. Next, an optimization model of this mission is built. The service sequence, orbital transfer time, and service position are used as deign variables, whereas the propellant cost is used as the design objective. The J2 perturbation, time constraint and the target spacecraft's surplus propellant capability constraint are taken into account. Then, a hybrid two-level optimization approach is presented to solve the formulated mixed integer nonlinear programming (MINLP) problem. A hybrid-encoding genetic algorithm is adopted to seek the near optimal solution in the up-level optimization, while a linear relative dynamic equation considering the J2 perturbation is used to obtain the impulses of orbital transfer in the low-level optimization. Finally, the effectiveness of the proposed model and method is validated by numerical examples.

Using High Resolution Design Spaces for Aerodynamic Shape Optimization Under Uncertainty

NASA Technical Reports Server (NTRS)

Li, Wu; Padula, Sharon

2004-01-01

This paper explains why high resolution design spaces encourage traditional airfoil optimization algorithms to generate noisy shape modifications, which lead to inaccurate linear predictions of aerodynamic coefficients and potential failure of descent methods. By using auxiliary drag constraints for a simultaneous drag reduction at all design points and the least shape distortion to achieve the targeted drag reduction, an improved algorithm generates relatively smooth optimal airfoils with no severe off-design performance degradation over a range of flight conditions, in high resolution design spaces parameterized by cubic B-spline functions. Simulation results using FUN2D in Euler flows are included to show the capability of the robust aerodynamic shape optimization method over a range of flight conditions.

A Requirements-Driven Optimization Method for Acoustic Liners Using Analytic Derivatives

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.; Lopes, Leonard V.

2017-01-01

More than ever, there is flexibility and freedom in acoustic liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. In a previous paper on this subject, a method deriving the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground was described. A simple code-wrapping approach was used to evaluate a community noise objective function for an external optimizer. Gradients were evaluated using a finite difference formula. The subject of this paper is an application of analytic derivatives that supply precise gradients to an optimization process. Analytic derivatives improve the efficiency and accuracy of gradient-based optimization methods and allow consideration of more design variables. In addition, the benefit of variable impedance liners is explored using a multi-objective optimization.

Optimization of design parameters for bulk micromachined silicon membranes for piezoresistive pressure sensing application

NASA Astrophysics Data System (ADS)

Belwanshi, Vinod; Topkar, Anita

2016-05-01

Finite element analysis study has been carried out to optimize the design parameters for bulk micro-machined silicon membranes for piezoresistive pressure sensing applications. The design is targeted for measurement of pressure up to 200 bar for nuclear reactor applications. The mechanical behavior of bulk micro-machined silicon membranes in terms of deflection and stress generation has been simulated. Based on the simulation results, optimization of the membrane design parameters in terms of length, width and thickness has been carried out. Subsequent to optimization of membrane geometrical parameters, the dimensions and location of the high stress concentration region for implantation of piezoresistors have been obtained for sensing of pressure using piezoresistive sensing technique.

Target design optimization for an electron accelerator driven subcritical facility with circular and square beam profiles.

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

Gohar, M. Y. A; Sofu, T.; Zhong, Z.

2008-10-30

A subcritical facility driven by an electron accelerator is planned at the Kharkov Institute of Physics and Technology (KIPT) in Ukraine for medical isotope production, materials research, training, and education. The conceptual design of the facility is being pursued through collaborations between ANL and KIPT. As part of the design effort, the high-fidelity analyses of various target options are performed with formulations to reflect the realistic configuration and the three dimensional geometry of each design. This report summarizes the results of target design optimization studies for electron beams with two different beam profiles. The target design optimization is performed viamore » the sequential neutronic, thermal-hydraulic, and structural analyses for a comprehensive assessment of each configuration. First, a target CAD model is developed with proper emphasis on manufacturability to provide a basis for separate but consistent models for subsequent neutronic, thermal-hydraulic, and structural analyses. The optimizations are pursued for maximizing the neutron yield, streamlining the flow field to avoid hotspots, and minimizing the thermal stresses to increase the durability. In addition to general geometric modifications, the inlet/outlet channel configurations, target plate partitioning schemes, flow manipulations and rates, electron beam diameter/width options, and cladding material choices are included in the design optimizations. The electron beam interactions with the target assembly and the neutronic response of the subcritical facility are evaluated using the MCNPX code. the results for the electron beam energy deposition, neutron generation, and utilization in the subcritical pile are then used to characterize the axisymmetric heat generation profiles in the target assembly with explicit simulations of the beam tube, the coolant, the clad, and the target materials. Both tungsten and uranium are considered as target materials. Neutron spectra from tungsten and uranium are very similar allowing the use of either material in the subcritical assembly without changing its characteristics. However, the uranium target has a higher neutron yield, which increases the neutron flux of the subcritical assembly. Based on the considered dimensions and heat generation profiles, the commercial CFD software Star-CD is used for the thermal-hydraulic analysis of each target design to satisfy a set of thermal criteria, the most limiting of which being to maintain the water temperature 50 below the boiling point. It is found that the turbulence in the inlet channels dissipates quickly in narrow gaps between the target plates and, as a result, the heat transfer is limited by the laminar flow conditions. On average, 3-D CFD analyses of target assemblies agree well with 1-D calculations using RELAP (performed by KIPT). However, the recirculation and stagnation zones predicted with the CFD models prove the importance of a 3-D analysis to avoid the resulting hotspots. The calculated temperatures are subsequently used for the structural analysis of each target configuration to satisfy the other engineering design requirements. The thermo-structural calculations are performed mostly with NASTRAN and the results occasionally compared with the results from MARC. Both, NASTRAN and MARC are commercially available structural-mechanics analysis software. Although, a significant thermal gradient forms in target elements along the beam direction, the high thermal stresses are generally observed peripherally around the edge of thin target disks/plates. Due to its high thermal conductivity, temperatures and thermal stresses in tungsten target are estimated to be significantly lower than in uranium target. The deformations of the target disks/plates are found to be insignificant, which eliminate concerns for flow blockages in narrow coolant channels. Consistent with the specifications of the KIPT accelerator to be used in this facility, the electron beam power is 100-kW with electron energy in the range of 100 to 200 MeV. As expected, the 100 MeV electrons deposit their energy faster while the 200-MeV electrons spread their energy deposition further along the beam direction. However in that electron energy range, the energy deposition profiles near the beam window require very thin target plates/disks to limit the temperatures and thermal stresses.« less

Inverse design of multicomponent assemblies

NASA Astrophysics Data System (ADS)

Piñeros, William D.; Lindquist, Beth A.; Jadrich, Ryan B.; Truskett, Thomas M.

2018-03-01

Inverse design can be a useful strategy for discovering interactions that drive particles to spontaneously self-assemble into a desired structure. Here, we extend an inverse design methodology—relative entropy optimization—to determine isotropic interactions that promote assembly of targeted multicomponent phases, and we apply this extension to design interactions for a variety of binary crystals ranging from compact triangular and square architectures to highly open structures with dodecagonal and octadecagonal motifs. We compare the resulting optimized (self- and cross) interactions for the binary assemblies to those obtained from optimization of analogous single-component systems. This comparison reveals that self-interactions act as a "primer" to position particles at approximately correct coordination shell distances, while cross interactions act as the "binder" that refines and locks the system into the desired configuration. For simpler binary targets, it is possible to successfully design self-assembling systems while restricting one of these interaction types to be a hard-core-like potential. However, optimization of both self- and cross interaction types appears necessary to design for assembly of more complex or open structures.

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment-Based Drug Design Facilitated by Dynamic Combinatorial Chemistry.

PubMed

Mondal, Milon; Radeva, Nedyalka; Fanlo-Virgós, Hugo; Otto, Sijbren; Klebe, Gerhard; Hirsch, Anna K H

2016-08-01

Fragment-based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit-identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X-ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis-acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240-fold improvement in potency compared to the parent hits. Subsequent X-ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit-identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit-to-lead optimization. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

An optimal stratified Simon two-stage design.

PubMed

Parashar, Deepak; Bowden, Jack; Starr, Colin; Wernisch, Lorenz; Mander, Adrian

2016-07-01

In Phase II oncology trials, therapies are increasingly being evaluated for their effectiveness in specific populations of interest. Such targeted trials require designs that allow for stratification based on the participants' molecular characterisation. A targeted design proposed by Jones and Holmgren (JH) Jones CL, Holmgren E: 'An adaptive Simon two-stage design for phase 2 studies of targeted therapies', Contemporary Clinical Trials 28 (2007) 654-661.determines whether a drug only has activity in a disease sub-population or in the wider disease population. Their adaptive design uses results from a single interim analysis to decide whether to enrich the study population with a subgroup or not; it is based on two parallel Simon two-stage designs. We study the JH design in detail and extend it by providing a few alternative ways to control the familywise error rate, in the weak sense as well as the strong sense. We also introduce a novel optimal design by minimising the expected sample size. Our extended design contributes to the much needed framework for conducting Phase II trials in stratified medicine. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd. © 2016 The Authors Pharmaceutical Statistics Published by John Wiley & Sons Ltd.

Global Optimization of Low-Thrust Interplanetary Trajectories Subject to Operational Constraints

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Vavrina, Matthew A.; Hinckley, David

2016-01-01

Low-thrust interplanetary space missions are highly complex and there can be many locally optimal solutions. While several techniques exist to search for globally optimal solutions to low-thrust trajectory design problems, they are typically limited to unconstrained trajectories. The operational design community in turn has largely avoided using such techniques and has primarily focused on accurate constrained local optimization combined with grid searches and intuitive design processes at the expense of efficient exploration of the global design space. This work is an attempt to bridge the gap between the global optimization and operational design communities by presenting a mathematical framework for global optimization of low-thrust trajectories subject to complex constraints including the targeting of planetary landing sites, a solar range constraint to simplify the thermal design of the spacecraft, and a real-world multi-thruster electric propulsion system that must switch thrusters on and off as available power changes over the course of a mission.

Spatial targeting of agri-environmental policy using bilevel evolutionary optimization

USDA-ARS?s Scientific Manuscript database

In this study we describe the optimal designation of agri-environmental policy as a bilevel optimization problem and propose an integrated solution method using a hybrid genetic algorithm. The problem is characterized by a single leader, the agency, that establishes a policy with the goal of optimiz...

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

NASA Technical Reports Server (NTRS)

Burt, Adam O.; Hull, Patrick V.

2014-01-01

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

Features of Modularly Assembled Compounds That Impart Bioactivity Against an RNA Target

PubMed Central

Rzuczek, Suzanne G.; Gao, Yu; Tang, Zhen-Zhi; Thornton, Charles A.; Kodadek, Thomas; Disney, Matthew D.

2013-01-01

Transcriptomes provide a myriad of potential RNAs that could be the targets of therapeutics or chemical genetic probes of function. Cell permeable small molecules, however, generally do not exploit these targets, owing to the difficulty in the design of high affinity, specific small molecules targeting RNA. As part of a general program to study RNA function using small molecules, we designed bioactive, modularly assembled small molecules that target the non-coding expanded RNA repeat that causes myotonic dystrophy type 1 (DM1), r(CUG)exp. Herein, we present a rigorous study to elucidate features in modularly assembled compounds that afford bioactivity. Different modular assembly scaffolds were investigated including polyamines, α-peptides, β-peptides, and peptide tertiary amides (PTAs). Based on activity as assessed by improvement of DM1-associated defects, stability against proteases, cellular permeability, and toxicity, we discovered that constrained backbones, namely PTAs, are optimal. Notably, we determined that r(CUG)exp is the target of the optimal PTA in cellular models and that the optimal PTA improves DM1-associated defects in a mouse model. Biophysical analyses were employed to investigate potential sources of bioactivity. These investigations show that modularly assembled compounds have increased residence times on their targets and faster on rates than the RNA-binding modules from which they were derived and faster on rates than the protein that binds r(CUG)exp, the inactivation of which gives rise to DM1-associated defects. These studies provide information about features of small molecules that are programmable for targeting RNA, allowing for the facile optimization of therapeutics or chemical probes against other cellular RNA targets. PMID:24032410

Features of modularly assembled compounds that impart bioactivity against an RNA target.

PubMed

Rzuczek, Suzanne G; Gao, Yu; Tang, Zhen-Zhi; Thornton, Charles A; Kodadek, Thomas; Disney, Matthew D

2013-10-18

Transcriptomes provide a myriad of potential RNAs that could be the targets of therapeutics or chemical genetic probes of function. Cell-permeable small molecules, however, generally do not exploit these targets, owing to the difficulty in the design of high affinity, specific small molecules targeting RNA. As part of a general program to study RNA function using small molecules, we designed bioactive, modularly assembled small molecules that target the noncoding expanded RNA repeat that causes myotonic dystrophy type 1 (DM1), r(CUG)(exp). Herein, we present a rigorous study to elucidate features in modularly assembled compounds that afford bioactivity. Different modular assembly scaffolds were investigated, including polyamines, α-peptides, β-peptides, and peptide tertiary amides (PTAs). On the basis of activity as assessed by improvement of DM1-associated defects, stability against proteases, cellular permeability, and toxicity, we discovered that constrained backbones, namely, PTAs, are optimal. Notably, we determined that r(CUG)(exp) is the target of the optimal PTA in cellular models and that the optimal PTA improves DM1-associated defects in a mouse model. Biophysical analyses were employed to investigate potential sources of bioactivity. These investigations show that modularly assembled compounds have increased residence times on their targets and faster on rates than the RNA-binding modules from which they were derived. Moreover, they have faster on rates than the protein that binds r(CUG)(exp), the inactivation of which gives rise to DM1-associated defects. These studies provide information about features of small molecules that are programmable for targeting RNA, allowing for the facile optimization of therapeutics or chemical probes against other cellular RNA targets.

An Analytic Model for the Success Rate of a Robotic Actuator System in Hitting Random Targets.

PubMed

Bradley, Stuart

2015-11-20

Autonomous robotic systems are increasingly being used in a wide range of applications such as precision agriculture, medicine, and the military. These systems have common features which often includes an action by an "actuator" interacting with a target. While simulations and measurements exist for the success rate of hitting targets by some systems, there is a dearth of analytic models which can give insight into, and guidance on optimization, of new robotic systems. The present paper develops a simple model for estimation of the success rate for hitting random targets from a moving platform. The model has two main dimensionless parameters: the ratio of actuator spacing to target diameter; and the ratio of platform distance moved (between actuator "firings") to the target diameter. It is found that regions of parameter space having specified high success are described by simple equations, providing guidance on design. The role of a "cost function" is introduced which, when minimized, provides optimization of design, operating, and risk mitigation costs.

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

Iterative optimization method for design of quantitative magnetization transfer imaging experiments.

PubMed

Levesque, Ives R; Sled, John G; Pike, G Bruce

2011-09-01

Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging. Copyright © 2011 Wiley-Liss, Inc.

Ridge filter design and optimization for the broad-beam three-dimensional irradiation system for heavy-ion radiotherapy.

PubMed

Schaffner, B; Kanai, T; Futami, Y; Shimbo, M; Urakabe, E

2000-04-01

The broad-beam three-dimensional irradiation system under development at National Institute of Radiological Sciences (NIRS) requires a small ridge filter to spread the initially monoenergetic heavy-ion beam to a small spread-out Bragg peak (SOBP). A large SOBP covering the target volume is then achieved by a superposition of differently weighted and displaced small SOBPs. Two approaches were studied for the definition of a suitable ridge filter and experimental verifications were performed. Both approaches show a good agreement between the calculated and measured dose and lead to a good homogeneity of the biological dose in the target. However, the ridge filter design that produces a Gaussian-shaped spectrum of the particle ranges was found to be more robust to small errors and uncertainties in the beam application. Furthermore, an optimization procedure for two fields was applied to compensate for the missing dose from the fragmentation tail for the case of a simple-geometry target. The optimized biological dose distributions show that a very good homogeneity is achievable in the target.

Comparison of evolutionary algorithms for LPDA antenna optimization

NASA Astrophysics Data System (ADS)

Lazaridis, Pavlos I.; Tziris, Emmanouil N.; Zaharis, Zaharias D.; Xenos, Thomas D.; Cosmas, John P.; Gallion, Philippe B.; Holmes, Violeta; Glover, Ian A.

2016-08-01

A novel approach to broadband log-periodic antenna design is presented, where some of the most powerful evolutionary algorithms are applied and compared for the optimal design of wire log-periodic dipole arrays (LPDA) using Numerical Electromagnetics Code. The target is to achieve an optimal antenna design with respect to maximum gain, gain flatness, front-to-rear ratio (F/R) and standing wave ratio. The parameters of the LPDA optimized are the dipole lengths, the spacing between the dipoles, and the dipole wire diameters. The evolutionary algorithms compared are the Differential Evolution (DE), Particle Swarm (PSO), Taguchi, Invasive Weed (IWO), and Adaptive Invasive Weed Optimization (ADIWO). Superior performance is achieved by the IWO (best results) and PSO (fast convergence) algorithms.

Multi-disciplinary optimization of railway wheels

NASA Astrophysics Data System (ADS)

Nielsen, J. C. O.; Fredö, C. R.

2006-06-01

A numerical procedure for multi-disciplinary optimization of railway wheels, based on Design of Experiments (DOE) methodology and automated design, is presented. The target is a wheel design that meets the requirements for fatigue strength, while minimizing the unsprung mass and rolling noise. A 3-level full factorial (3LFF) DOE is used to collect data points required to set up Response Surface Models (RSM) relating design and response variables in the design space. Computationally efficient simulations are thereafter performed using the RSM to identify the solution that best fits the design target. A demonstration example, including four geometric design variables in a parametric finite element (FE) model, is presented. The design variables are wheel radius, web thickness, lateral offset between rim and hub, and radii at the transitions rim/web and hub/web, but more variables (including material properties) can be added if needed. To improve further the performance of the wheel design, a constrained layer damping (CLD) treatment is applied on the web. For a given load case, compared to a reference wheel design without CLD, a combination of wheel shape and damping optimization leads to the conclusion that a reduction in the wheel component of A-weighted rolling noise of 11 dB can be achieved if a simultaneous increase in wheel mass of 14 kg is accepted.

Adaptive Aft Signature Shaping of a Low-Boom Supersonic Aircraft Using Off-Body Pressures

NASA Technical Reports Server (NTRS)

Ordaz, Irian; Li, Wu

2012-01-01

The design and optimization of a low-boom supersonic aircraft using the state-of-the- art o -body aerodynamics and sonic boom analysis has long been a challenging problem. The focus of this paper is to demonstrate an e ective geometry parameterization scheme and a numerical optimization approach for the aft shaping of a low-boom supersonic aircraft using o -body pressure calculations. A gradient-based numerical optimization algorithm that models the objective and constraints as response surface equations is used to drive the aft ground signature toward a ramp shape. The design objective is the minimization of the variation between the ground signature and the target signature subject to several geometric and signature constraints. The target signature is computed by using a least-squares regression of the aft portion of the ground signature. The parameterization and the deformation of the geometry is performed with a NASA in- house shaping tool. The optimization algorithm uses the shaping tool to drive the geometric deformation of a horizontal tail with a parameterization scheme that consists of seven camber design variables and an additional design variable that describes the spanwise location of the midspan section. The demonstration cases show that numerical optimization using the state-of-the-art o -body aerodynamic calculations is not only feasible and repeatable but also allows the exploration of complex design spaces for which a knowledge-based design method becomes less effective.

Research on the optimization of quota design in real estate

NASA Astrophysics Data System (ADS)

Sun, Chunling; Ma, Susu; Zhong, Weichao

2017-11-01

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

Regional Delivery of Chimeric Antigen Receptor-Engineered T Cells Effectively Targets HER2+ Breast Cancer Metastasis to the Brain.

PubMed

Priceman, Saul J; Tilakawardane, Dileshni; Jeang, Brook; Aguilar, Brenda; Murad, John P; Park, Anthony K; Chang, Wen-Chung; Ostberg, Julie R; Neman, Josh; Jandial, Rahul; Portnow, Jana; Forman, Stephen J; Brown, Christine E

2018-01-01

Purpose: Metastasis to the brain from breast cancer remains a significant clinical challenge, and may be targeted with CAR-based immunotherapy. CAR design optimization for solid tumors is crucial due to the absence of truly restricted antigen expression and potential safety concerns with "on-target off-tumor" activity. Here, we have optimized HER2-CAR T cells for the treatment of breast to brain metastases, and determined optimal second-generation CAR design and route of administration for xenograft mouse models of breast metastatic brain tumors, including multifocal and leptomeningeal disease. Experimental Design: HER2-CAR constructs containing either CD28 or 4-1BB intracellular costimulatory signaling domains were compared for functional activity in vitro by measuring cytokine production, T-cell proliferation, and tumor killing capacity. We also evaluated HER2-CAR T cells delivered by intravenous, local intratumoral, or regional intraventricular routes of administration using in vivo human xenograft models of breast cancer that have metastasized to the brain. Results: Here, we have shown that HER2-CARs containing the 4-1BB costimulatory domain confer improved tumor targeting with reduced T-cell exhaustion phenotype and enhanced proliferative capacity compared with HER2-CARs containing the CD28 costimulatory domain. Local intracranial delivery of HER2-CARs showed potent in vivo antitumor activity in orthotopic xenograft models. Importantly, we demonstrated robust antitumor efficacy following regional intraventricular delivery of HER2-CAR T cells for the treatment of multifocal brain metastases and leptomeningeal disease. Conclusions: Our study shows the importance of CAR design in defining an optimized CAR T cell, and highlights intraventricular delivery of HER2-CAR T cells for treating multifocal brain metastases. Clin Cancer Res; 24(1); 95-105. ©2017 AACR . ©2017 American Association for Cancer Research.

Optimal design of the satellite constellation arrangement reconfiguration process

NASA Astrophysics Data System (ADS)

Fakoor, Mahdi; Bakhtiari, Majid; Soleymani, Mahshid

2016-08-01

In this article, a novel approach is introduced for the satellite constellation reconfiguration based on Lambert's theorem. Some critical problems are raised in reconfiguration phase, such as overall fuel cost minimization, collision avoidance between the satellites on the final orbital pattern, and necessary maneuvers for the satellites in order to be deployed in the desired position on the target constellation. To implement the reconfiguration phase of the satellite constellation arrangement at minimal cost, the hybrid Invasive Weed Optimization/Particle Swarm Optimization (IWO/PSO) algorithm is used to design sub-optimal transfer orbits for the satellites existing in the constellation. Also, the dynamic model of the problem will be modeled in such a way that, optimal assignment of the satellites to the initial and target orbits and optimal orbital transfer are combined in one step. Finally, we claim that our presented idea i.e. coupled non-simultaneous flight of satellites from the initial orbital pattern will lead to minimal cost. The obtained results show that by employing the presented method, the cost of reconfiguration process is reduced obviously.

Crysalis: an integrated server for computational analysis and design of protein crystallization.

PubMed

Wang, Huilin; Feng, Liubin; Zhang, Ziding; Webb, Geoffrey I; Lin, Donghai; Song, Jiangning

2016-02-24

The failure of multi-step experimental procedures to yield diffraction-quality crystals is a major bottleneck in protein structure determination. Accordingly, several bioinformatics methods have been successfully developed and employed to select crystallizable proteins. Unfortunately, the majority of existing in silico methods only allow the prediction of crystallization propensity, seldom enabling computational design of protein mutants that can be targeted for enhancing protein crystallizability. Here, we present Crysalis, an integrated crystallization analysis tool that builds on support-vector regression (SVR) models to facilitate computational protein crystallization prediction, analysis, and design. More specifically, the functionality of this new tool includes: (1) rapid selection of target crystallizable proteins at the proteome level, (2) identification of site non-optimality for protein crystallization and systematic analysis of all potential single-point mutations that might enhance protein crystallization propensity, and (3) annotation of target protein based on predicted structural properties. We applied the design mode of Crysalis to identify site non-optimality for protein crystallization on a proteome-scale, focusing on proteins currently classified as non-crystallizable. Our results revealed that site non-optimality is based on biases related to residues, predicted structures, physicochemical properties, and sequence loci, which provides in-depth understanding of the features influencing protein crystallization. Crysalis is freely available at http://nmrcen.xmu.edu.cn/crysalis/.

Crysalis: an integrated server for computational analysis and design of protein crystallization

PubMed Central

Wang, Huilin; Feng, Liubin; Zhang, Ziding; Webb, Geoffrey I.; Lin, Donghai; Song, Jiangning

2016-01-01

The failure of multi-step experimental procedures to yield diffraction-quality crystals is a major bottleneck in protein structure determination. Accordingly, several bioinformatics methods have been successfully developed and employed to select crystallizable proteins. Unfortunately, the majority of existing in silico methods only allow the prediction of crystallization propensity, seldom enabling computational design of protein mutants that can be targeted for enhancing protein crystallizability. Here, we present Crysalis, an integrated crystallization analysis tool that builds on support-vector regression (SVR) models to facilitate computational protein crystallization prediction, analysis, and design. More specifically, the functionality of this new tool includes: (1) rapid selection of target crystallizable proteins at the proteome level, (2) identification of site non-optimality for protein crystallization and systematic analysis of all potential single-point mutations that might enhance protein crystallization propensity, and (3) annotation of target protein based on predicted structural properties. We applied the design mode of Crysalis to identify site non-optimality for protein crystallization on a proteome-scale, focusing on proteins currently classified as non-crystallizable. Our results revealed that site non-optimality is based on biases related to residues, predicted structures, physicochemical properties, and sequence loci, which provides in-depth understanding of the features influencing protein crystallization. Crysalis is freely available at http://nmrcen.xmu.edu.cn/crysalis/. PMID:26906024

Toward Optimal Target Placement for Neural Prosthetic Devices

PubMed Central

Cunningham, John P.; Yu, Byron M.; Gilja, Vikash; Ryu, Stephen I.; Shenoy, Krishna V.

2008-01-01

Neural prosthetic systems have been designed to estimate continuous reach trajectories (motor prostheses) and to predict discrete reach targets (communication prostheses). In the latter case, reach targets are typically decoded from neural spiking activity during an instructed delay period before the reach begins. Such systems use targets placed in radially symmetric geometries independent of the tuning properties of the neurons available. Here we seek to automate the target placement process and increase decode accuracy in communication prostheses by selecting target locations based on the neural population at hand. Motor prostheses that incorporate intended target information could also benefit from this consideration. We present an optimal target placement algorithm that approximately maximizes decode accuracy with respect to target locations. In simulated neural spiking data fit from two monkeys, the optimal target placement algorithm yielded statistically significant improvements up to 8 and 9% for two and sixteen targets, respectively. For four and eight targets, gains were more modest, as the target layouts found by the algorithm closely resembled the canonical layouts. We trained a monkey in this paradigm and tested the algorithm with experimental neural data to confirm some of the results found in simulation. In all, the algorithm can serve not only to create new target layouts that outperform canonical layouts, but it can also confirm or help select among multiple canonical layouts. The optimal target placement algorithm developed here is the first algorithm of its kind, and it should both improve decode accuracy and help automate target placement for neural prostheses. PMID:18829845

A polymer dataset for accelerated property prediction and design.

PubMed

Huan, Tran Doan; Mannodi-Kanakkithodi, Arun; Kim, Chiho; Sharma, Vinit; Pilania, Ghanshyam; Ramprasad, Rampi

2016-03-01

Emerging computation- and data-driven approaches are particularly useful for rationally designing materials with targeted properties. Generally, these approaches rely on identifying structure-property relationships by learning from a dataset of sufficiently large number of relevant materials. The learned information can then be used to predict the properties of materials not already in the dataset, thus accelerating the materials design. Herein, we develop a dataset of 1,073 polymers and related materials and make it available at http://khazana.uconn.edu/. This dataset is uniformly prepared using first-principles calculations with structures obtained either from other sources or by using structure search methods. Because the immediate target of this work is to assist the design of high dielectric constant polymers, it is initially designed to include the optimized structures, atomization energies, band gaps, and dielectric constants. It will be progressively expanded by accumulating new materials and including additional properties calculated for the optimized structures provided.

EUVL back-insertion layout optimization

NASA Astrophysics Data System (ADS)

Civay, D.; Laffosse, E.; Chesneau, A.

2018-03-01

Extreme ultraviolet lithography (EUVL) is targeted for front-up insertion at advanced technology nodes but will be evaluated for back insertion at more mature nodes. EUVL can put two or more mask levels back on one mask, depending upon what level(s) in the process insertion occurs. In this paper, layout optimization methods are discussed that can be implemented when EUVL back insertion is implemented. The layout optimizations can be focused on improving yield, reliability or density, depending upon the design needs. The proposed methodology modifies the original two or more colored layers and generates an optimized single color EUVL layout design.

Mission planning for on-orbit servicing through multiple servicing satellites: A new approach

NASA Astrophysics Data System (ADS)

Daneshjou, K.; Mohammadi-Dehabadi, A. A.; Bakhtiari, M.

2017-09-01

In this paper, a novel approach is proposed for the mission planning of on-orbit servicing such as visual inspection, active debris removal and refueling through multiple servicing satellites (SSs). The scheduling has been done with the aim of minimization of fuel consumption and mission duration. So a multi-objective optimization problem is dealt with here which is solved by employing particle swarm optimization algorithm. Also, Taguchi technique is employed for robust design of effective parameters of optimization problem. The day that the SSs have to leave parking orbit, transfer duration from parking orbit to final orbit, transfer duration between one target to another, and time spent for the SS on each target are the decision parameters which are obtained from the optimization problem. The raised idea is that in addition to the aforementioned decision parameters, eccentricity and inclination related to the initial orbit and also phase difference between the SSs on the initial orbit are identified by means of optimization problem, so that the designer has not much role on determining them. Furthermore, it is considered that the SS and the target rendezvous at the servicing point and the SS does not perform any phasing maneuver to reach the target. It should be noted that Lambert theorem is used for determination of the transfer orbit. The results show that the proposed approach reduces the fuel consumption and the mission duration significantly in comparison with the conventional approaches.

Two-step design method for highly compact three-dimensional freeform optical system for LED surface light source.

PubMed

Mao, Xianglong; Li, Hongtao; Han, Yanjun; Luo, Yi

2014-10-20

Designing an illumination system for a surface light source with a strict compactness requirement is quite challenging, especially for the general three-dimensional (3D) case. In accordance with the two key features of an expected illumination distribution, i.e., a well-controlled boundary and a precise illumination pattern, a two-step design method is proposed in this paper for highly compact 3D freeform illumination systems. In the first step, a target shape scaling strategy is combined with an iterative feedback modification algorithm to generate an optimized freeform optical system with a well-controlled boundary of the target distribution. In the second step, a set of selected radii of the system obtained in the first step are optimized to further improve the illuminating quality within the target region. The method is quite flexible and effective to design highly compact optical systems with almost no restriction on the shape of the desired target field. As examples, three highly compact freeform lenses with ratio of center height h of the lens and the maximum dimension D of the source ≤ 2.5:1 are designed for LED surface light sources to form a uniform illumination distribution on a rectangular, a cross-shaped and a complex cross pierced target plane respectively. High light control efficiency of η > 0.7 as well as low relative standard illumination deviation of RSD < 0.07 is obtained simultaneously for all the three design examples.

Optimizing an experimental design for an electromagnetic experiment

NASA Astrophysics Data System (ADS)

Roux, Estelle; Garcia, Xavier

2013-04-01

Most of geophysical studies focus on data acquisition and analysis, but another aspect which is gaining importance is the discussion on acquisition of suitable datasets. This can be done through the design of an optimal experiment. Optimizing an experimental design implies a compromise between maximizing the information we get about the target and reducing the cost of the experiment, considering a wide range of constraints (logistical, financial, experimental …). We are currently developing a method to design an optimal controlled-source electromagnetic (CSEM) experiment to detect a potential CO2 reservoir and monitor this reservoir during and after CO2 injection. Our statistical algorithm combines the use of linearized inverse theory (to evaluate the quality of one given design via the objective function) and stochastic optimization methods like genetic algorithm (to examine a wide range of possible surveys). The particularity of our method is that it uses a multi-objective genetic algorithm that searches for designs that fit several objective functions simultaneously. One main advantage of this kind of technique to design an experiment is that it does not require the acquisition of any data and can thus be easily conducted before any geophysical survey. Our new experimental design algorithm has been tested with a realistic one-dimensional resistivity model of the Earth in the region of study (northern Spain CO2 sequestration test site). We show that a small number of well distributed observations have the potential to resolve the target. This simple test also points out the importance of a well chosen objective function. Finally, in the context of CO2 sequestration that motivates this study, we might be interested in maximizing the information we get about the reservoir layer. In that case, we show how the combination of two different objective functions considerably improve its resolution.

Design of freeze-drying processes for pharmaceuticals: practical advice.

PubMed

Tang, Xiaolin; Pikal, Michael J

2004-02-01

Design of freeze-drying processes is often approached with a "trial and error" experimental plan or, worse yet, the protocol used in the first laboratory run is adopted without further attempts at optimization. Consequently, commercial freeze-drying processes are often neither robust nor efficient. It is our thesis that design of an "optimized" freeze-drying process is not particularly difficult for most products, as long as some simple rules based on well-accepted scientific principles are followed. It is the purpose of this review to discuss the scientific foundations of the freeze-drying process design and then to consolidate these principles into a set of guidelines for rational process design and optimization. General advice is given concerning common stability issues with proteins, but unusual and difficult stability issues are beyond the scope of this review. Control of ice nucleation and crystallization during the freezing step is discussed, and the impact of freezing on the rest of the process and final product quality is reviewed. Representative freezing protocols are presented. The significance of the collapse temperature and the thermal transition, denoted Tg', are discussed, and procedures for the selection of the "target product temperature" for primary drying are presented. Furthermore, guidelines are given for selection of the optimal shelf temperature and chamber pressure settings required to achieve the target product temperature without thermal and/or mass transfer overload of the freeze dryer. Finally, guidelines and "rules" for optimization of secondary drying and representative secondary drying protocols are presented.

Time-oriented experimental design method to optimize hydrophilic matrix formulations with gelation kinetics and drug release profiles.

PubMed

Shin, Sangmun; Choi, Du Hyung; Truong, Nguyen Khoa Viet; Kim, Nam Ah; Chu, Kyung Rok; Jeong, Seong Hoon

2011-04-04

A new experimental design methodology was developed by integrating the response surface methodology and the time series modeling. The major purposes were to identify significant factors in determining swelling and release rate from matrix tablets and their relative factor levels for optimizing the experimental responses. Properties of tablet swelling and drug release were assessed with ten factors and two default factors, a hydrophilic model drug (terazosin) and magnesium stearate, and compared with target values. The selected input control factors were arranged in a mixture simplex lattice design with 21 experimental runs. The obtained optimal settings for gelation were PEO, LH-11, Syloid, and Pharmacoat with weight ratios of 215.33 (88.50%), 5.68 (2.33%), 19.27 (7.92%), and 3.04 (1.25%), respectively. The optimal settings for drug release were PEO and citric acid with weight ratios of 191.99 (78.91%) and 51.32 (21.09%), respectively. Based on the results of matrix swelling and drug release, the optimal solutions, target values, and validation experiment results over time were similar and showed consistent patterns with very small biases. The experimental design methodology could be a very promising experimental design method to obtain maximum information with limited time and resources. It could also be very useful in formulation studies by providing a systematic and reliable screening method to characterize significant factors in the sustained release matrix tablet. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimal de novo design of MRM experiments for rapid assay development in targeted proteomics.

PubMed

Bertsch, Andreas; Jung, Stephan; Zerck, Alexandra; Pfeifer, Nico; Nahnsen, Sven; Henneges, Carsten; Nordheim, Alfred; Kohlbacher, Oliver

2010-05-07

Targeted proteomic approaches such as multiple reaction monitoring (MRM) overcome problems associated with classical shotgun mass spectrometry experiments. Developing MRM quantitation assays can be time consuming, because relevant peptide representatives of the proteins must be found and their retention time and the product ions must be determined. Given the transitions, hundreds to thousands of them can be scheduled into one experiment run. However, it is difficult to select which of the transitions should be included into a measurement. We present a novel algorithm that allows the construction of MRM assays from the sequence of the targeted proteins alone. This enables the rapid development of targeted MRM experiments without large libraries of transitions or peptide spectra. The approach relies on combinatorial optimization in combination with machine learning techniques to predict proteotypicity, retention time, and fragmentation of peptides. The resulting potential transitions are scheduled optimally by solving an integer linear program. We demonstrate that fully automated construction of MRM experiments from protein sequences alone is possible and over 80% coverage of the targeted proteins can be achieved without further optimization of the assay.

Mechanistic and quantitative insight into cell surface targeted molecular imaging agent design.

PubMed

Zhang, Liang; Bhatnagar, Sumit; Deschenes, Emily; Thurber, Greg M

2016-05-05

Molecular imaging agent design involves simultaneously optimizing multiple probe properties. While several desired characteristics are straightforward, including high affinity and low non-specific background signal, in practice there are quantitative trade-offs between these properties. These include plasma clearance, where fast clearance lowers background signal but can reduce target uptake, and binding, where high affinity compounds sometimes suffer from lower stability or increased non-specific interactions. Further complicating probe development, many of the optimal parameters vary depending on both target tissue and imaging agent properties, making empirical approaches or previous experience difficult to translate. Here, we focus on low molecular weight compounds targeting extracellular receptors, which have some of the highest contrast values for imaging agents. We use a mechanistic approach to provide a quantitative framework for weighing trade-offs between molecules. Our results show that specific target uptake is well-described by quantitative simulations for a variety of targeting agents, whereas non-specific background signal is more difficult to predict. Two in vitro experimental methods for estimating background signal in vivo are compared - non-specific cellular uptake and plasma protein binding. Together, these data provide a quantitative method to guide probe design and focus animal work for more cost-effective and time-efficient development of molecular imaging agents.

Bioengineering Strategies for Designing Targeted Cancer Therapies

PubMed Central

Wen, Xuejun

2014-01-01

The goals of bioengineering strategies for targeted cancer therapies are (1) to deliver a high dose of an anticancer drug directly to a cancer tumor, (2) to enhance drug uptake by malignant cells, and (3) to minimize drug uptake by nonmalignant cells. Effective cancer-targeting therapies will require both passive- and active targeting strategies and a thorough understanding of physiologic barriers to targeted drug delivery. Designing a targeted therapy includes the selection and optimization of a nanoparticle delivery vehicle for passive accumulation in tumors, a targeting moiety for active receptor-mediated uptake, and stimuli-responsive polymers for control of drug release. The future direction of cancer targeting is a combinatorial approach, in which targeting therapies are designed to use multiple targeting strategies. The combinatorial approach will enable combination therapy for delivery of multiple drugs and dual ligand targeting to improve targeting specificity. Targeted cancer treatments in development and the new combinatorial approaches show promise for improving targeted anticancer drug delivery and improving treatment outcomes. PMID:23768509

Development of a chromatographic method with multi-criteria decision making design for simultaneous determination of nifedipine and atenolol in content uniformity testing.

PubMed

Ahmed, Sameh; Alqurshi, Abdulmalik; Mohamed, Abdel-Maaboud Ismail

2018-07-01

A new robust and reliable high-performance liquid chromatography (HPLC) method with multi-criteria decision making (MCDM) approach was developed to allow simultaneous quantification of atenolol (ATN) and nifedipine (NFD) in content uniformity testing. Felodipine (FLD) was used as an internal standard (I.S.) in this study. A novel marriage between a new interactive response optimizer and a HPLC method was suggested for multiple response optimizations of target responses. An interactive response optimizer was used as a decision and prediction tool for the optimal settings of target responses, according to specified criteria, based on Derringer's desirability. Four independent variables were considered in this study: Acetonitrile%, buffer pH and concentration along with column temperature. Eight responses were optimized: retention times of ATN, NFD, and FLD, resolutions between ATN/NFD and NFD/FLD, and plate numbers for ATN, NFD, and FLD. Multiple regression analysis was applied in order to scan the influences of the most significant variables for the regression models. The experimental design was set to give minimum retention times, maximum resolution and plate numbers. The interactive response optimizer allowed prediction of optimum conditions according to these criteria with a good composite desirability value of 0.98156. The developed method was validated according to the International Conference on Harmonization (ICH) guidelines with the aid of the experimental design. The developed MCDM-HPLC method showed superior robustness and resolution in short analysis time allowing successful simultaneous content uniformity testing of ATN and NFD in marketed capsules. The current work presents an interactive response optimizer as an efficient platform to optimize, predict responses, and validate HPLC methodology with tolerable design space for assay in quality control laboratories. Copyright © 2018 Elsevier B.V. All rights reserved.

A multiple-alignment based primer design algorithm for genetically highly variable DNA targets

PubMed Central

2013-01-01

Background Primer design for highly variable DNA sequences is difficult, and experimental success requires attention to many interacting constraints. The advent of next-generation sequencing methods allows the investigation of rare variants otherwise hidden deep in large populations, but requires attention to population diversity and primer localization in relatively conserved regions, in addition to recognized constraints typically considered in primer design. Results Design constraints include degenerate sites to maximize population coverage, matching of melting temperatures, optimizing de novo sequence length, finding optimal bio-barcodes to allow efficient downstream analyses, and minimizing risk of dimerization. To facilitate primer design addressing these and other constraints, we created a novel computer program (PrimerDesign) that automates this complex procedure. We show its powers and limitations and give examples of successful designs for the analysis of HIV-1 populations. Conclusions PrimerDesign is useful for researchers who want to design DNA primers and probes for analyzing highly variable DNA populations. It can be used to design primers for PCR, RT-PCR, Sanger sequencing, next-generation sequencing, and other experimental protocols targeting highly variable DNA samples. PMID:23965160

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2008-01-01

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization (MDAO) tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2008-01-01

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization [MDAO] tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

New method to design stellarator coils without the winding surface

NASA Astrophysics Data System (ADS)

Zhu, Caoxiang; Hudson, Stuart R.; Song, Yuntao; Wan, Yuanxi

2018-01-01

Finding an easy-to-build coils set has been a critical issue for stellarator design for decades. Conventional approaches assume a toroidal ‘winding’ surface, but a poorly chosen winding surface can unnecessarily constrain the coil optimization algorithm, This article presents a new method to design coils for stellarators. Each discrete coil is represented as an arbitrary, closed, one-dimensional curve embedded in three-dimensional space. A target function to be minimized that includes both physical requirements and engineering constraints is constructed. The derivatives of the target function with respect to the parameters describing the coil geometries and currents are calculated analytically. A numerical code, named flexible optimized coils using space curves (FOCUS), has been developed. Applications to a simple stellarator configuration, W7-X and LHD vacuum fields are presented.

Application of Adjoint Methodology in Various Aspects of Sonic Boom Design

NASA Technical Reports Server (NTRS)

Rallabhandi, Sriram K.

2014-01-01

One of the advances in computational design has been the development of adjoint methods allowing efficient calculation of sensitivities in gradient-based shape optimization. This paper discusses two new applications of adjoint methodology that have been developed to aid in sonic boom mitigation exercises. In the first, equivalent area targets are generated using adjoint sensitivities of selected boom metrics. These targets may then be used to drive the vehicle shape during optimization. The second application is the computation of adjoint sensitivities of boom metrics on the ground with respect to parameters such as flight conditions, propagation sampling rate, and selected inputs to the propagation algorithms. These sensitivities enable the designer to make more informed selections of flight conditions at which the chosen cost functionals are less sensitive.

A performance-oriented power transformer design methodology using multi-objective evolutionary optimization

PubMed Central

Adly, Amr A.; Abd-El-Hafiz, Salwa K.

2014-01-01

Transformers are regarded as crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower costs. In this paper, a power transformer design methodology using multi-objective evolutionary optimization is proposed. Using this methodology, which is tailored to be target performance design-oriented, quick rough estimation of transformer design specifics may be inferred. Testing of the suggested approach revealed significant qualitative and quantitative match with measured design and performance values. Details of the proposed methodology as well as sample design results are reported in the paper. PMID:26257939

A performance-oriented power transformer design methodology using multi-objective evolutionary optimization.

PubMed

Adly, Amr A; Abd-El-Hafiz, Salwa K

2015-05-01

Transformers are regarded as crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower costs. In this paper, a power transformer design methodology using multi-objective evolutionary optimization is proposed. Using this methodology, which is tailored to be target performance design-oriented, quick rough estimation of transformer design specifics may be inferred. Testing of the suggested approach revealed significant qualitative and quantitative match with measured design and performance values. Details of the proposed methodology as well as sample design results are reported in the paper.

Framework for Multidisciplinary Analysis, Design, and Optimization with High-Fidelity Analysis Tools

NASA Technical Reports Server (NTRS)

Orr, Stanley A.; Narducci, Robert P.

2009-01-01

A plan is presented for the development of a high fidelity multidisciplinary optimization process for rotorcraft. The plan formulates individual disciplinary design problems, identifies practical high-fidelity tools and processes that can be incorporated in an automated optimization environment, and establishes statements of the multidisciplinary design problem including objectives, constraints, design variables, and cross-disciplinary dependencies. Five key disciplinary areas are selected in the development plan. These are rotor aerodynamics, rotor structures and dynamics, fuselage aerodynamics, fuselage structures, and propulsion / drive system. Flying qualities and noise are included as ancillary areas. Consistency across engineering disciplines is maintained with a central geometry engine that supports all multidisciplinary analysis. The multidisciplinary optimization process targets the preliminary design cycle where gross elements of the helicopter have been defined. These might include number of rotors and rotor configuration (tandem, coaxial, etc.). It is at this stage that sufficient configuration information is defined to perform high-fidelity analysis. At the same time there is enough design freedom to influence a design. The rotorcraft multidisciplinary optimization tool is built and substantiated throughout its development cycle in a staged approach by incorporating disciplines sequentially.

Design of materials with prescribed nonlinear properties

NASA Astrophysics Data System (ADS)

Wang, F.; Sigmund, O.; Jensen, J. S.

2014-09-01

We systematically design materials using topology optimization to achieve prescribed nonlinear properties under finite deformation. Instead of a formal homogenization procedure, a numerical experiment is proposed to evaluate the material performance in longitudinal and transverse tensile tests under finite deformation, i.e. stress-strain relations and Poissons ratio. By minimizing errors between actual and prescribed properties, materials are tailored to achieve the target. Both two dimensional (2D) truss-based and continuum materials are designed with various prescribed nonlinear properties. The numerical examples illustrate optimized materials with rubber-like behavior and also optimized materials with extreme strain-independent Poissons ratio for axial strain intervals of εi∈[0.00, 0.30].

Analysis of static and dynamic characteristic of spindle system and its structure optimization in camshaft grinding machine

NASA Astrophysics Data System (ADS)

Feng, Jianjun; Li, Chengzhe; Wu, Zhi

2017-08-01

As an important part of the valve opening and closing controller in engine, camshaft has high machining accuracy requirement in designing. Taking the high-speed camshaft grinder spindle system as the research object and the spindle system performance as the optimizing target, this paper firstly uses Solidworks to establish the three-dimensional finite element model (FEM) of spindle system, then conducts static analysis and the modal analysis by applying the established FEM in ANSYS Workbench, and finally uses the design optimization function of the ANSYS Workbench to optimize the structure parameter in the spindle system. The study results prove that the design of the spindle system fully meets the production requirements, and the performance of the optimized spindle system is promoted. Besides, this paper provides an analysis and optimization method for other grinder spindle systems.

Changing paradigm from one target one ligand towards multi target directed ligand design for key drug targets of Alzheimer disease: An important role of Insilco methods in multi target directed ligands design.

PubMed

Kumar, Akhil; Tiwari, Ashish; Sharma, Ashok

2018-03-15

Alzheimer disease (AD) is now considered as a multifactorial neurodegenerative disorder and rapidly increasing to an alarming situation and causing higher death rate. One target one ligand hypothesis is not able to provide complete solution of AD due to multifactorial nature of disease and one target one drug seems to fail to provide better treatment against AD. Moreover, current available treatments are limited and most of the upcoming treatments under clinical trials are based on modulating single target. So the current AD drug discovery research shifting towards new approach for better solution that simultaneously modulate more than one targets in the neurodegenerative cascade. This can be achieved by network pharmacology, multi-modal therapies, multifaceted, and/or the more recently proposed term "multi-targeted designed drugs. Drug discovery project is tedious, costly and long term project. Moreover, multi target AD drug discovery added extra challenges such as good binding affinity of ligands for multiple targets, optimal ADME/T properties, no/less off target side effect and crossing of the blood brain barrier. These hurdles may be addressed by insilico methods for efficient solution in less time and cost as computational methods successfully applied to single target drug discovery project. Here we are summarizing some of the most prominent and computationally explored single target against AD and further we discussed successful example of dual or multiple inhibitors for same targets. Moreover we focused on ligand and structure based computational approach to design MTDL against AD. However is not an easy task to balance dual activity in a single molecule but computational approach such as virtual screening docking, QSAR, simulation and free energy are useful in future MTDLs drug discovery alone or in combination with fragment based method. However, rational and logical implementations of computational drug designing methods are capable of assisting AD drug discovery and play an important role in optimizing multi-target drug discovery. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Optimal Navigation of Self-Propelled Colloids in Microstructured Mazes

NASA Astrophysics Data System (ADS)

Yang, Yuguang; Bevan, Michael

Controlling navigation of self-propelled microscopic `robots' subject to random Brownian motion in complex microstructured environments (e.g., porous media, tumor vasculature) is important to many emerging applications (e.g., enhanced oil recovery, drug delivery). In this work, we design an optimal feedback policy to navigate an active self-propelled colloidal rod in complex mazes with various obstacle types. Actuation of the rods is modelled based on a light-controlled osmotic flow mechanism, which produces different propulsion velocities along the rod's long axis. Actuator-parameterized Langevin equations, with soft rod-obstacle repulsive interactions, are developed to describe the system dynamics. A Markov decision process (MDP) framework is used for optimal policy calculations with design goals of colloidal rods reaching target end points in minimum time. Simulations show that optimal MDP-based policies are able to control rod trajectories to reach target regions order-of-magnitudes faster than uncontrolled rods, which diverges as maze complexity increases. An efficient multi-graph based implementation for MDP is also presented, which scales linearly with the maze dimension.

E-RNAi: a web application for the multi-species design of RNAi reagents—2010 update

PubMed Central

Horn, Thomas; Boutros, Michael

2010-01-01

The design of RNA interference (RNAi) reagents is an essential step for performing loss-of-function studies in many experimental systems. The availability of sequenced and annotated genomes greatly facilitates RNAi experiments in an increasing number of organisms that were previously not genetically tractable. The E-RNAi web-service, accessible at http://www.e-rnai.org/, provides a computational resource for the optimized design and evaluation of RNAi reagents. The 2010 update of E-RNAi now covers 12 genomes, including Drosophila, Caenorhabditis elegans, human, emerging model organisms such as Schmidtea mediterranea and Acyrthosiphon pisum, as well as the medically relevant vectors Anopheles gambiae and Aedes aegypti. The web service calculates RNAi reagents based on the input of target sequences, sequence identifiers or by visual selection of target regions through a genome browser interface. It identifies optimized RNAi target-sites by ranking sequences according to their predicted specificity, efficiency and complexity. E-RNAi also facilitates the design of secondary RNAi reagents for validation experiments, evaluation of pooled siRNA reagents and batch design. Results are presented online, as a downloadable HTML report and as tab-delimited files. PMID:20444868

A Requirements-Driven Optimization Method for Acoustic Treatment Design

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.

2016-01-01

Acoustic treatment designers have long been able to target specific noise sources inside turbofan engines. Facesheet porosity and cavity depth are key design variables of perforate-over-honeycomb liners that determine levels of noise suppression as well as the frequencies at which suppression occurs. Layers of these structures can be combined to create a robust attenuation spectrum that covers a wide range of frequencies. Looking to the future, rapidly-emerging additive manufacturing technologies are enabling new liners with multiple degrees of freedom, and new adaptive liners with variable impedance are showing promise. More than ever, there is greater flexibility and freedom in liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. The subject of this paper is an analytical method that derives the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground.

Formulation and optimization of oxaliplatin immuno-nanoparticles using Box-Behnken design and cytotoxicity assessment for synergistic and receptor-mediated targeting in the treatment of colorectal cancer.

PubMed

Tummala, Shashank; Gowthamarajan, K; Satish Kumar, M N; Praveen, T K; Yamjala, Karthik; Tripuraneni, Naga Srinivas; Prakash, Ashwati

2016-12-01

Conventional chemotherapy majorly lacks clinical application attributed to its inspecificity, adverse effects and inability to penetrate into tumor cells. Hence, the aim of the study was to prepare oxaliplatin solid lipid nanoparticles (OP-SLN) by microemulsion method optimizing it by Box-Behnken design and then covalently conjugated to TRAIL (CD-253) monoclonal antibody (TR-OP-SLN) for targeting colorectal cancer cells. The optimized OP-SLN3 has shown an appreciable particle size (121 ± 1.22 nm), entrapment efficiency (78 ± 0.09%) and drug loading (32 ± 1.01%). Fluorescence study and the Bradford assay further confirmed the binding of the protein. A 1.5-fold increase in cytotoxicity of immuno-nanoparticles (4.9 μM) was observed.

[Application of an artificial neural network in the design of sustained-release dosage forms].

PubMed

Wei, X H; Wu, J J; Liang, W Q

2001-09-01

To use the artificial neural network (ANN) in Matlab 5.1 tool-boxes to predict the formulations of sustained-release tablets. The solubilities of nine drugs and various ratios of HPMC: Dextrin for 63 tablet formulations were used as the ANN model input, and in vitro accumulation released at 6 sampling times were used as output. The ANN model was constructed by selecting the optimal number of iterations (25) and model structure in which there are one hidden layer and five hidden layer nodes. The optimized ANN model was used for prediction of formulation based on desired target in vitro dissolution-time profiles. ANN predicted profiles based on ANN predicted formulations were closely similar to the target profiles. The ANN could be used for predicting the dissolution profiles of sustained release dosage form and for the design of optimal formulation.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets.

PubMed

Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

PubMed Central

Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817

Selection and trajectory design to mission secondary targets

NASA Astrophysics Data System (ADS)

Victorino Sarli, Bruno; Kawakatsu, Yasuhiro

2017-02-01

Recently, with new trajectory design techniques and use of low-thrust propulsion systems, missions have become more efficient and cheaper with respect to propellant. As a way to increase the mission's value and scientific return, secondary targets close to the main trajectory are often added with a small change in the transfer trajectory. As a result of their large number, importance and facility to perform a flyby, asteroids are commonly used as such targets. This work uses the Primer Vector theory to define the direction and magnitude of the thrust for a minimum fuel consumption problem. The design of a low-thrust trajectory with a midcourse asteroid flyby is not only challenging for the low-thrust problem solution, but also with respect to the selection of a target and its flyby point. Currently more than 700,000 minor bodies have been identified, which generates a very large number of possible flyby points. This work uses a combination of reachability, reference orbit, and linear theory to select appropriate candidates, drastically reducing the simulation time, to be later included in the main trajectory and optimized. Two test cases are presented using the aforementioned selection process and optimization to add and design a secondary flyby to a mission with the primary objective of 3200 Phaethon flyby and 25143 Itokawa rendezvous.

THz optical design considerations and optimization for medical imaging applications

NASA Astrophysics Data System (ADS)

Sung, Shijun; Garritano, James; Bajwa, Neha; Nowroozi, Bryan; Llombart, Nuria; Grundfest, Warren; Taylor, Zachary D.

2014-09-01

THz imaging system design will play an important role making possible imaging of targets with arbitrary properties and geometries. This study discusses design consideration and imaging performance optimization techniques in THz quasioptical imaging system optics. Analysis of field and polarization distortion by off-axis parabolic (OAP) mirrors in THz imaging optics shows how distortions are carried in a series of mirrors while guiding the THz beam. While distortions of the beam profile by individual mirrors are not significant, these effects are compounded by a series of mirrors in antisymmetric orientation. It is shown that symmetric orientation of the OAP mirror effectively cancels this distortion to recover the original beam profile. Additionally, symmetric orientation can correct for some geometrical off-focusing due to misalignment. We also demonstrate an alternative method to test for overall system optics alignment by investigating the imaging performance of the tilted target plane. Asymmetric signal profile as a function of the target plane's tilt angle indicates when one or more imaging components are misaligned, giving a preferred tilt direction. Such analysis can offer additional insight into often elusive source device misalignment at an integrated system. Imaging plane tilting characteristics are representative of a 3-D modulation transfer function of the imaging system. A symmetric tilted plane is preferred to optimize imaging performance.

Optimization Techniques for Design Problems in Selected Areas in WSNs: A Tutorial

PubMed Central

Ibrahim, Ahmed; Alfa, Attahiru

2017-01-01

This paper is intended to serve as an overview of, and mostly a tutorial to illustrate, the optimization techniques used in several different key design aspects that have been considered in the literature of wireless sensor networks (WSNs). It targets the researchers who are new to the mathematical optimization tool, and wish to apply it to WSN design problems. We hence divide the paper into two main parts. One part is dedicated to introduce optimization theory and an overview on some of its techniques that could be helpful in design problem in WSNs. In the second part, we present a number of design aspects that we came across in the WSN literature in which mathematical optimization methods have been used in the design. For each design aspect, a key paper is selected, and for each we explain the formulation techniques and the solution methods implemented. We also provide in-depth analyses and assessments of the problem formulations, the corresponding solution techniques and experimental procedures in some of these papers. The analyses and assessments, which are provided in the form of comments, are meant to reflect the points that we believe should be taken into account when using optimization as a tool for design purposes. PMID:28763039

Optimization Techniques for Design Problems in Selected Areas in WSNs: A Tutorial.

PubMed

Ibrahim, Ahmed; Alfa, Attahiru

2017-08-01

This paper is intended to serve as an overview of, and mostly a tutorial to illustrate, the optimization techniques used in several different key design aspects that have been considered in the literature of wireless sensor networks (WSNs). It targets the researchers who are new to the mathematical optimization tool, and wish to apply it to WSN design problems. We hence divide the paper into two main parts. One part is dedicated to introduce optimization theory and an overview on some of its techniques that could be helpful in design problem in WSNs. In the second part, we present a number of design aspects that we came across in the WSN literature in which mathematical optimization methods have been used in the design. For each design aspect, a key paper is selected, and for each we explain the formulation techniques and the solution methods implemented. We also provide in-depth analyses and assessments of the problem formulations, the corresponding solution techniques and experimental procedures in some of these papers. The analyses and assessments, which are provided in the form of comments, are meant to reflect the points that we believe should be taken into account when using optimization as a tool for design purposes.

On the optimal two-impulse maneuver

NASA Technical Reports Server (NTRS)

Bonneau, F. G.; Diarra, C. M.

1992-01-01

An algorithm and a solution to the optimal two-impulse maneuver for the Ulysses spacecraft is presented. The option in which both maneuvers are designed using the critical plane strategy, which further reduces the propellant budget, is included. Results show savings of 12.4 and 16.7 m/s for full targeting and critical plane strategy, respectively. It is argued that this software will play an important role in the area of multimission maneuver design.

Designing divertor targets for uniform power load

NASA Astrophysics Data System (ADS)

Dekeyser, W.; Reiter, D.; Baelmans, M.

2015-08-01

Divertor design for next step fusion reactors heavily relies on 2D edge plasma modeling with codes as e.g. B2-EIRENE. While these codes are typically used in a design-by-analysis approach, in previous work we have shown that divertor design can alternatively be posed as a mathematical optimization problem, and solved very efficiently using adjoint methods adapted from computational aerodynamics. This approach has been applied successfully to divertor target shape design for more uniform power load. In this paper, the concept is further extended to include all contributions to the target power load, with particular focus on radiation. In a simplified test problem, we show the potential benefits of fully including the radiation load in the design cycle as compared to only assessing this load in a post-processing step.

Identification of functional features of synthetic SINEUPs, antisense lncRNAs that specifically enhance protein translation

PubMed Central

Kozhuharova, Ana; Sharma, Harshita; Ohyama, Takako; Fasolo, Francesca; Yamazaki, Toshio; Cotella, Diego; Santoro, Claudio; Zucchelli, Silvia; Gustincich, Stefano; Carninci, Piero

2018-01-01

SINEUPs are antisense long noncoding RNAs, in which an embedded SINE B2 element UP-regulates translation of partially overlapping target sense mRNAs. SINEUPs contain two functional domains. First, the binding domain (BD) is located in the region antisense to the target, providing specific targeting to the overlapping mRNA. Second, the inverted SINE B2 represents the effector domain (ED) and enhances translation. To adapt SINEUP technology to a broader number of targets, we took advantage of a high-throughput, semi-automated imaging system to optimize synthetic SINEUP BD and ED design in HEK293T cell lines. Using SINEUP-GFP as a model SINEUP, we extensively screened variants of the BD to map features needed for optimal design. We found that most active SINEUPs overlap an AUG-Kozak sequence. Moreover, we report our screening of the inverted SINE B2 sequence to identify active sub-domains and map the length of the minimal active ED. Our synthetic SINEUP-GFP screening of both BDs and EDs constitutes a broad test with flexible applications to any target gene of interest. PMID:29414979

Process-time Optimization of Vacuum Degassing Using a Genetic Alloy Design Approach

PubMed Central

Dilner, David; Lu, Qi; Mao, Huahai; Xu, Wei; van der Zwaag, Sybrand; Selleby, Malin

2014-01-01

This paper demonstrates the use of a new model consisting of a genetic algorithm in combination with thermodynamic calculations and analytical process models to minimize the processing time during a vacuum degassing treatment of liquid steel. The model sets multiple simultaneous targets for final S, N, O, Si and Al levels and uses the total slag mass, the slag composition, the steel composition and the start temperature as optimization variables. The predicted optimal conditions agree well with industrial practice. For those conditions leading to the shortest process time the target compositions for S, N and O are reached almost simultaneously. PMID:28788286

New method to design stellarator coils without the winding surface

DOE PAGES

Zhu, Caoxiang; Hudson, Stuart R.; Song, Yuntao; ...

2017-11-06

Finding an easy-to-build coils set has been a critical issue for stellarator design for decades. Conventional approaches assume a toroidal 'winding' surface, but a poorly chosen winding surface can unnecessarily constrain the coil optimization algorithm, This article presents a new method to design coils for stellarators. Each discrete coil is represented as an arbitrary, closed, one-dimensional curve embedded in three-dimensional space. A target function to be minimized that includes both physical requirements and engineering constraints is constructed. The derivatives of the target function with respect to the parameters describing the coil geometries and currents are calculated analytically. A numerical code,more » named flexible optimized coils using space curves (FOCUS), has been developed. Furthermore, applications to a simple stellarator configuration, W7-X and LHD vacuum fields are presented.« less

New method to design stellarator coils without the winding surface

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

Zhu, Caoxiang; Hudson, Stuart R.; Song, Yuntao

Finding an easy-to-build coils set has been a critical issue for stellarator design for decades. Conventional approaches assume a toroidal 'winding' surface, but a poorly chosen winding surface can unnecessarily constrain the coil optimization algorithm, This article presents a new method to design coils for stellarators. Each discrete coil is represented as an arbitrary, closed, one-dimensional curve embedded in three-dimensional space. A target function to be minimized that includes both physical requirements and engineering constraints is constructed. The derivatives of the target function with respect to the parameters describing the coil geometries and currents are calculated analytically. A numerical code,more » named flexible optimized coils using space curves (FOCUS), has been developed. Furthermore, applications to a simple stellarator configuration, W7-X and LHD vacuum fields are presented.« less

TARGETED SEQUENTIAL DESIGN FOR TARGETED LEARNING INFERENCE OF THE OPTIMAL TREATMENT RULE AND ITS MEAN REWARD.

PubMed

Chambaz, Antoine; Zheng, Wenjing; van der Laan, Mark J

2017-01-01

This article studies the targeted sequential inference of an optimal treatment rule (TR) and its mean reward in the non-exceptional case, i.e. , assuming that there is no stratum of the baseline covariates where treatment is neither beneficial nor harmful, and under a companion margin assumption. Our pivotal estimator, whose definition hinges on the targeted minimum loss estimation (TMLE) principle, actually infers the mean reward under the current estimate of the optimal TR. This data-adaptive statistical parameter is worthy of interest on its own. Our main result is a central limit theorem which enables the construction of confidence intervals on both mean rewards under the current estimate of the optimal TR and under the optimal TR itself. The asymptotic variance of the estimator takes the form of the variance of an efficient influence curve at a limiting distribution, allowing to discuss the efficiency of inference. As a by product, we also derive confidence intervals on two cumulated pseudo-regrets, a key notion in the study of bandits problems. A simulation study illustrates the procedure. One of the corner-stones of the theoretical study is a new maximal inequality for martingales with respect to the uniform entropy integral.

Optical system design of solar-blind UV target simulator with long focal length

NASA Astrophysics Data System (ADS)

Chen, Yu; Huo, Furong; Zheng, Liqin

2014-11-01

Ultraviolet (UV) radiation of 200nm-300nm waveband from the sun is absorbed by atmosphere, which is often referred to the solar-blind region of the solar spectrum. Solar-blind characteristics of this waveband have important application value, especially in military fields. The application of solar-blind waveband has developed very rapidly, which is receiving more and more attention. Sometimes, to test the performance of a UV optical system, a standard solar-blind UV target simulator is needed as the UV light source. In this paper, an optical system of a solar-blind UV target simulator is designed with waveband 240nm-280nm. To simulate a far UV target, the focal length of this UV optical system needs to be long. Besides, different field of view (FOV) of the system should meet aplanatic condition. The optional materials are very few for UV optical systems, in which only CaF2 and JGS1 are commonly used. Various aberrations are difficult to be corrected. To save production cost and enhance the precision of fabrication and test, aspheric surfaces and binary elements are not adopted in the system. Moreover, doublet or triplet cannot be used in UV optical system considering possible cracking for different thermal expansion coefficients of different materials. After optimization, the system is composed of 4 lenses with focal length 500mm. MTF curves of different FOV coincide together. The maximum RMS radius of the optimized system has almost the same size as Airy disk, which proves the good image quality after system optimization. The aplanatic condition is met very well in this system. In the spot diagram, root mean square (RMS) radius changes from 3 microns to 3.6 microns, which has similar size with Airy disk and meets aplanatic condition very well. This optical system of solar-blind UV target simulator also has relatively loose tolerance data, which can prove the system is designed in an optimal state.

RARtool: A MATLAB Software Package for Designing Response-Adaptive Randomized Clinical Trials with Time-to-Event Outcomes.

PubMed

Ryeznik, Yevgen; Sverdlov, Oleksandr; Wong, Weng Kee

2015-08-01

Response-adaptive randomization designs are becoming increasingly popular in clinical trial practice. In this paper, we present RARtool , a user interface software developed in MATLAB for designing response-adaptive randomized comparative clinical trials with censored time-to-event outcomes. The RARtool software can compute different types of optimal treatment allocation designs, and it can simulate response-adaptive randomization procedures targeting selected optimal allocations. Through simulations, an investigator can assess design characteristics under a variety of experimental scenarios and select the best procedure for practical implementation. We illustrate the utility of our RARtool software by redesigning a survival trial from the literature.

Advanced Targeting Cost Function Design for Evolutionary Optimization of Control of Logistic Equation

NASA Astrophysics Data System (ADS)

Senkerik, Roman; Zelinka, Ivan; Davendra, Donald; Oplatkova, Zuzana

2010-06-01

This research deals with the optimization of the control of chaos by means of evolutionary algorithms. This work is aimed on an explanation of how to use evolutionary algorithms (EAs) and how to properly define the advanced targeting cost function (CF) securing very fast and precise stabilization of desired state for any initial conditions. As a model of deterministic chaotic system, the one dimensional Logistic equation was used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, repeated simulations were conducted to outline the effectiveness and robustness of used method and targeting CF.

The quality estimation of exterior wall’s and window filling’s construction design

NASA Astrophysics Data System (ADS)

Saltykov, Ivan; Bovsunovskaya, Maria

2017-10-01

The article reveals the term of “artificial envelope” in dwelling building. Authors offer a complex multifactorial approach to the design quality estimation of external fencing structures, which is based on various parameters impact. These referred parameters are: functional, exploitation, cost, and also, the environmental index is among them. The quality design index Qк is inputting for the complex characteristic of observed above parameters. The mathematical relation of this index from these parameters is the target function for the quality design estimation. For instance, the article shows the search of optimal variant for wall and window designs in small, middle and large square dwelling premises of economic class buildings. The graphs of target function single parameters are expressed for the three types of residual chamber’s dimensions. As a result of the showing example, there is a choice of window opening’s dimensions, which make the wall’s and window’s constructions properly correspondent to the producible complex requirements. The authors reveal the comparison of recommended window filling’s square in accordance with the building standards, and the square, due to the finding of the optimal variant of the design quality index. The multifactorial approach for optimal design searching, which is mentioned in this article, can be used in consideration of various construction elements of dwelling buildings in accounting of suitable climate, social and economic construction area features.

Creating targeted initial populations for genetic product searches in heterogeneous markets

NASA Astrophysics Data System (ADS)

Foster, Garrett; Turner, Callaway; Ferguson, Scott; Donndelinger, Joseph

2014-12-01

Genetic searches often use randomly generated initial populations to maximize diversity and enable a thorough sampling of the design space. While many of these initial configurations perform poorly, the trade-off between population diversity and solution quality is typically acceptable for small-scale problems. Navigating complex design spaces, however, often requires computationally intelligent approaches that improve solution quality. This article draws on research advances in market-based product design and heuristic optimization to strategically construct 'targeted' initial populations. Targeted initial designs are created using respondent-level part-worths estimated from discrete choice models. These designs are then integrated into a traditional genetic search. Two case study problems of differing complexity are presented to illustrate the benefits of this approach. In both problems, targeted populations lead to computational savings and product configurations with improved market share of preferences. Future research efforts to tailor this approach and extend it towards multiple objectives are also discussed.

Computational design of high efficiency release targets for use at ISOL facilities

NASA Astrophysics Data System (ADS)

Liu, Y.; Alton, G. D.; Middleton, J. W.

1999-06-01

This report describes efforts made at the Oak Ridge National Laboratory to design high-efficiency-release targets that simultaneously incorporate the short diffusion lengths, high permeabilities, controllable temperatures, and heat removal properties required for the generation of useful radioactive ion beam (RIB) intensities for nuclear physics and astrophysics research using the isotope separation on-line (ISOL) technique. Short diffusion lengths are achieved either by using thin fibrous target materials or by coating thin layers of selected target material onto low-density carbon fibers such as reticulated vitreous carbon fiber (RVCF) or carbon-bonded-carbon-fiber (CBCF) to form highly permeable composite target matrices. Computational studies which simulate the generation and removal of primary beam deposited heat from target materials have been conducted to optimize the design of target/heat-sink systems for generating RIBs. The results derived from diffusion release-rate simulation studies for selected targets and thermal analyses of temperature distributions within a prototype target/heat-sink system subjected to primary ion beam irradiation will be presented in this report.

High-efficiency-release targets for use at ISOL facilities: computational design

NASA Astrophysics Data System (ADS)

Liu, Y.; Alton, G. D.

1999-12-01

This report describes efforts made at the Oak Ridge National Laboratory to design high-efficiency-release targets that simultaneously incorporate the short diffusion lengths, high permeabilities, controllable temperatures, and heat-removal properties required for the generation of useful radioactive ion beam (RIB) intensities for nuclear physics and astrophysics research using the isotope separation on-line (ISOL) technique. Short diffusion lengths are achieved either by using thin fibrous target materials or by coating thin layers of selected target material onto low-density carbon fibers such as reticulated-vitreous-carbon fiber (RVCF) or carbon-bonded-carbon fiber (CBCF) to form highly permeable composite target matrices. Computational studies that simulate the generation and removal of primary beam deposited heat from target materials have been conducted to optimize the design of target/heat-sink systems for generating RIBs. The results derived from diffusion release-rate simulation studies for selected targets and thermal analyses of temperature distributions within a prototype target/heat-sink system subjected to primary ion beam irradiation are presented in this report.

Optimization of the photoneutron target geometry for e-accelerator based BNCT.

PubMed

Chegeni, Nahid; Pur, Saleh Boveiry; Razmjoo, Sasan; Hoseini, Seydeh Khadijed

2017-06-01

Today, electron accelerators are taken into consideration as photoneutron sources. Therefore, for maximum production of epithermal neutron flux, designing a photoneutron target is of significant importance. In this paper, the effect of thickness and geometric shape of a photoneutron target on neutron output were investigated. In this study, a pencil photon source with 13, 15, 18, 20 and 25 MeV energies and a diameter of 2 mm was investigated using Monte Carlo simulation method using MCNP code. To optimize the design of the photoneutron target, the tungsten target with various geometries and thicknesses was investigated. The maximum neutron flux produced for all target geometries and thicknesses occurred at neutron energy peak of around 0.46 MeV. As the thickness increased to 2 cm, neutron flux increased and then a decreasing trend was observed. For various geometrical shapes, the determining factor in photoneutron output was the effective target thickness in the photon interaction path that increased by the increase in the area of interaction. Another factor was the angle of the photon's incidence with the target surface that resulted in a significant decrease in photoneutron output in cone-shaped targets. Three factors including the total neutron flux, neutrons energy spectrum, and convergence of neutrons plays an important role in the selection of geometry and shape of the target that should be investigated considering beam shaping assembly (BSA) shape.

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

NASA Astrophysics Data System (ADS)

Ekawati, Y.; Hapsari, A. A.

2018-03-01

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

Optimization of Actuating Origami Networks

NASA Astrophysics Data System (ADS)

Buskohl, Philip; Fuchi, Kazuko; Bazzan, Giorgio; Joo, James; Gregory, Reich; Vaia, Richard

2015-03-01

Origami structures morph between 2D and 3D conformations along predetermined fold lines that efficiently program the form, function and mobility of the structure. By leveraging design concepts from action origami, a subset of origami art focused on kinematic mechanisms, reversible folding patterns for applications such as solar array packaging, tunable antennae, and deployable sensing platforms may be designed. However, the enormity of the design space and the need to identify the requisite actuation forces within the structure places a severe limitation on design strategies based on intuition and geometry alone. The present work proposes a topology optimization method, using truss and frame element analysis, to distribute foldline mechanical properties within a reference crease pattern. Known actuating patterns are placed within a reference grid and the optimizer adjusts the fold stiffness of the network to optimally connect them. Design objectives may include a target motion, stress level, or mechanical energy distribution. Results include the validation of known action origami structures and their optimal connectivity within a larger network. This design suite offers an important step toward systematic incorporation of origami design concepts into new, novel and reconfigurable engineering devices. This research is supported under the Air Force Office of Scientific Research (AFOSR) funding, LRIR 13RQ02COR.

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

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

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

1994-12-01

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

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm.

PubMed

Hoffmann, Thomas J; Zhan, Yiping; Kvale, Mark N; Hesselson, Stephanie E; Gollub, Jeremy; Iribarren, Carlos; Lu, Yontao; Mei, Gangwu; Purdy, Matthew M; Quesenberry, Charles; Rowell, Sarah; Shapero, Michael H; Smethurst, David; Somkin, Carol P; Van den Eeden, Stephen K; Walter, Larry; Webster, Teresa; Whitmer, Rachel A; Finn, Andrea; Schaefer, Catherine; Kwok, Pui-Yan; Risch, Neil

2011-12-01

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies. Copyright © 2011 Elsevier Inc. All rights reserved.

The Inverse Optimal Control Problem for a Three-Loop Missile Autopilot

NASA Astrophysics Data System (ADS)

Hwang, Donghyeok; Tahk, Min-Jea

2018-04-01

The performance characteristics of the autopilot must have a fast response to intercept a maneuvering target and reasonable robustness for system stability under the effect of un-modeled dynamics and noise. By the conventional approach, the three-loop autopilot design is handled by time constant, damping factor and open-loop crossover frequency to achieve the desired performance requirements. Note that the general optimal theory can be also used to obtain the same gain as obtained from the conventional approach. The key idea of using optimal control technique for feedback gain design revolves around appropriate selection and interpretation of the performance index for which the control is optimal. This paper derives an explicit expression, which relates the weight parameters appearing in the quadratic performance index to the design parameters such as open-loop crossover frequency, phase margin, damping factor, or time constant, etc. Since all set of selection of design parameters do not guarantee existence of optimal control law, explicit inequalities, which are named the optimality criteria for the three-loop autopilot (OC3L), are derived to find out all set of design parameters for which the control law is optimal. Finally, based on OC3L, an efficient gain selection procedure is developed, where time constant is set to design objective and open-loop crossover frequency and phase margin as design constraints. The effectiveness of the proposed technique is illustrated through numerical simulations.

Food and Drug Administration Perspective on Negative Symptoms in Schizophrenia as a Target for a Drug Treatment Claim

PubMed Central

Laughren, Thomas; Levin, Robert

2006-01-01

Negative symptoms of schizophrenia are not adequately addressed by available treatments for schizophrenia. Thus, it is reasonable to consider them as a target for a drug claim. This article describes the thought process that the Food and Drug Administration (FDA) will undertake in considering negative symptoms of schizophrenia as a novel and distinct drug target. Beyond this basic question, this article identifies a number of design issues that the FDA needs to consider regarding how best to conduct studies to support claims for this target. These design issues include (1) what population to study, (2) what phase of illness to target, (3) whether to focus on the negative symptom domain overall or on some specific aspect of negative symptoms, (4) the role of functional measures in negative symptom trials, and (5) optimal designs for targeting drugs for add-on therapy or broad-spectrum agents. PMID:16079389

MCMC-ODPR: primer design optimization using Markov Chain Monte Carlo sampling.

PubMed

Kitchen, James L; Moore, Jonathan D; Palmer, Sarah A; Allaby, Robin G

2012-11-05

Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR) algorithm. After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively. MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base.

MCMC-ODPR: Primer design optimization using Markov Chain Monte Carlo sampling

PubMed Central

2012-01-01

Background Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR) algorithm. Results After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively. Conclusions MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base. PMID:23126469

In vitro/in vivo characterization of nanoemulsion formulation of metronidazole with improved skin targeting and anti-rosacea properties.

PubMed

Yu, Meng; Ma, Huixian; Lei, Mingzhu; Li, Nan; Tan, Fengping

2014-09-01

Topical skin treatment was limited due to the lack of suitable delivery system with significant cutaneous localization and systemic safety. The aim of this study was to develop and optimize a nanoemulsion (NE) to enhance targeting localization of metronidazole (MTZ) in skin layers. In vitro studies were used to optimize NE formulations, and a series of experiments were carried in vitro and in vivo to validate the therapeutic efficacy of MTZ-loaded optimal NE. NE type selection and D-optimal design study were applied to optimize NE formulation with maximum skin retention and minimum skin penetration. Three formulation variables: Oil X1 (Labrafil), Smix X2 (a mixture of Cremophor EL/Tetraethylene glycol, 2:1 w/w) and water X3 were included in D-design. The system was assessed for skin retention Y1, cumulative MTZ amount after 24 h Y2 and droplet size Y3. Following optimization, the values of formulation components (X1, X2 and X3) were 4.13%, 16.42% and 79.45%, respectively. The optimized NE was assessed for viscosity, droplet size, morphological study and in vitro permeation in pig skin. Distributions of MTZ were validated by confocal laser scanning microscopy (CLSM). Active agent of NE transferred into deeper skin and localized in epidermal/dermal layers after 24 h, which showed significant advantages of the optimal NE over Gel. The skin targeting localization and minimal systemic escape of optimal NE was further proved by in vivo study on rat skin. Current in vitro-in vivo correlation (IVIVC) enabled the prediction of pharmacokinetic profile of MTZ from in vitro permeation results. Further, the in vivo anti-rosacea efficacy of optimal formulation was investigated by pharmacodynamics study on mice ear. Copyright © 2014 Elsevier B.V. All rights reserved.

Method for Household Refrigerators Efficiency Increasing

NASA Astrophysics Data System (ADS)

Lebedev, V. V.; Sumzina, L. V.; Maksimov, A. V.

2017-11-01

The relevance of working processes parameters optimization in air conditioning systems is proved in the work. The research is performed with the use of the simulation modeling method. The parameters optimization criteria are considered, the analysis of target functions is given while the key factors of technical and economic optimization are considered in the article. The search for the optimal solution at multi-purpose optimization of the system is made by finding out the minimum of the dual-target vector created by the Pareto method of linear and weight compromises from target functions of the total capital costs and total operating costs. The tasks are solved in the MathCAD environment. The research results show that the values of technical and economic parameters of air conditioning systems in the areas relating to the optimum solutions’ areas manifest considerable deviations from the minimum values. At the same time, the tendencies for significant growth in deviations take place at removal of technical parameters from the optimal values of both the capital investments and operating costs. The production and operation of conditioners with the parameters which are considerably deviating from the optimal values will lead to the increase of material and power costs. The research allows one to establish the borders of the area of the optimal values for technical and economic parameters at air conditioning systems’ design.

Rapid Design of Gravity Assist Trajectories

NASA Technical Reports Server (NTRS)

Carrico, J.; Hooper, H. L.; Roszman, L.; Gramling, C.

1991-01-01

Several International Solar Terrestrial Physics (ISTP) missions require the design of complex gravity assisted trajectories in order to investigate the interaction of the solar wind with the Earth's magnetic field. These trajectories present a formidable trajectory design and optimization problem. The philosophy and methodology that enable an analyst to design and analyse such trajectories are discussed. The so called 'floating end point' targeting, which allows the inherently nonlinear multiple body problem to be solved with simple linear techniques, is described. The combination of floating end point targeting with analytic approximations with a Newton method targeter to achieve trajectory design goals quickly, even for the very sensitive double lunar swingby trajectories used by the ISTP missions, is demonstrated. A multiconic orbit integration scheme allows fast and accurate orbit propagation. A prototype software tool, Swingby, built for trajectory design and launch window analysis, is described.

A Combinatorial Platform for the Optimization of Peptidomimetic Methyl-Lysine Reader Antagonists

NASA Astrophysics Data System (ADS)

Barnash, Kimberly D.

Post-translational modification of histone N-terminal tails mediates chromatin compaction and, consequently, DNA replication, transcription, and repair. While numerous post-translational modifications decorate histone tails, lysine methylation is an abundant mark important for both gene activation and repression. Methyl-lysine (Kme) readers function through binding mono-, di-, or trimethyl-lysine. Chemical intervention of Kme readers faces numerous challenges due to the broad surface-groove interactions between readers and their cognate histone peptides; yet, the increasing interest in understanding chromatin-modifying complexes suggests tractable lead compounds for Kme readers are critical for elucidating the mechanisms of chromatin dysregulation in disease states and validating the druggability of these domains and complexes. The successful discovery of a peptide-derived chemical probe, UNC3866, for the Polycomb repressive complex 1 (PRC1) chromodomain Kme readers has proven the potential for selective peptidomimetic inhibition of reader function. Unfortunately, the systematic modification of peptides-to-peptidomimetics is a costly and inefficient strategy for target-class hit discovery against Kme readers. Through the exploration of biased chemical space via combinatorial on-bead libraries, we have developed two concurrent methodologies for Kme reader chemical probe discovery. We employ biased peptide combinatorial libraries as a hit discovery strategy with subsequent optimization via iterative targeted libraries. Peptide-to-peptidomimetic optimization through targeted library design was applied based on structure-guided library design around the interaction of the endogenous peptide ligand with three target Kme readers. Efforts targeting the WD40 reader EED led to the discovery of the 3-mer peptidomimetic ligand UNC5115 while combinatorial repurposing of UNC3866 for off-target chromodomains resulted in the discovery of UNC4991, a CDYL/2-selective ligand, and UNC4848, a MPP8 and CDYL/2 ligand. Ultimately, our efforts demonstrate the generalizability of a peptidomimetic combinatorial platform for the optimization of Kme reader ligands in a target class manner.

Neutron beam optimization based on a 7Li(p,n)7Be reaction for treatment of deep-seated brain tumors by BNCT

NASA Astrophysics Data System (ADS)

Zahra Ahmadi, Ganjeh; S. Farhad, Masoudi

2014-10-01

Neutron beam optimization for accelerator-based Boron Neutron Capture Therapy (BNCT) is investigated using a 7Li(p,n)7Be reaction. Design and optimization have been carried out for the target, cooling system, moderator, filter, reflector, and collimator to achieve a high flux of epithermal neutron and satisfy the IAEA criteria. Also, the performance of the designed beam in tissue is assessed by using a simulated Snyder head phantom. The results show that the optimization of the collimator and reflector is critical to finding the best neutron beam based on the 7Li(p,n)7Be reaction. Our designed beam has 2.49×109n/cm2s epithermal neutron flux and is suitable for BNCT of deep-seated brain tumors.

Design, Synthesis, and Pharmacokinetics of a Bone-Targeting Dual-Action Prodrug for the Treatment of Osteoporosis.

PubMed

Xie, Haibo; Chen, Gang; Young, Robert N

2017-08-24

A dual-action bone-targeting prodrug has been designed, synthesized, and evaluated for in vitro and in vivo metabolic stability, in vivo tissue distribution, and rates of release of the active constituents after binding to bones through the use of differentially double-labeled derivatives. The conjugate (general structure 7) embodies the merger of a very potent and proven anabolic selective agonist of the prostaglandin EP4 receptor, compound 5, and alendronic acid, a potent inhibitor of bone resorption, optimally linked through a differentially hydrolyzable linker unit, N-4-carboxymethylphenyl-methyloxycarbonyl-leucinyl-argininyl-para-aminophenylmethylalcohol (Leu-Arg-PABA). Optimized conjugate 16 was designed so that esterase activity will liberate 5 and cathepsin K cleavage of the Leu-Arg-PABA element will liberate alendronic acid. Studies with doubly radiolabeled 16 provide a proof-of-concept for the use of a cathepsin K cleavable peptide-linked conjugate for targeting of bisphosphonate prodrugs to bone and slow release liberation of the active constituents in vivo. Such conjugates are potential therapies for the treatment of bone disorders such as osteoporosis.

Research and application of borehole structure optimization based on pre-drill risk assessment

NASA Astrophysics Data System (ADS)

Zhang, Guohui; Liu, Xinyun; Chenrong; Hugui; Yu, Wenhua; Sheng, Yanan; Guan, Zhichuan

2017-11-01

Borehole structure design based on pre-drill risk assessment and considering risks related to drilling operation is the pre-condition for safe and smooth drilling operation. Major risks of drilling operation include lost circulation, blowout, sidewall collapsing, sticking and failure of drilling tools etc. In the study, studying data from neighboring wells was used to calculate the profile of formation pressure with credibility in the target well, then the borehole structure design for the target well assessment by using the drilling risk assessment to predict engineering risks before drilling. Finally, the prediction results were used to optimize borehole structure design to prevent such drilling risks. The newly-developed technique provides a scientific basis for lowering probability and frequency of drilling engineering risks, and shortening time required to drill a well, which is of great significance for safe and high-efficient drilling.

Optimal synthesis and design of the number of cycles in the leaching process for surimi production.

PubMed

Reinheimer, M Agustina; Scenna, Nicolás J; Mussati, Sergio F

2016-12-01

Water consumption required during the leaching stage in the surimi manufacturing process strongly depends on the design and the number and size of stages connected in series for the soluble protein extraction target, and it is considered as the main contributor to the operating costs. Therefore, the optimal synthesis and design of the leaching stage is essential to minimize the total annual cost. In this study, a mathematical optimization model for the optimal design of the leaching operation is presented. Precisely, a detailed Mixed Integer Nonlinear Programming (MINLP) model including operating and geometric constraints was developed based on our previous optimization model (NLP model). Aspects about quality, water consumption and main operating parameters were considered. The minimization of total annual costs, which considered a trade-off between investment and operating costs, led to an optimal solution with lesser number of stages (2 instead of 3 stages) and higher volumes of the leaching tanks comparing with previous results. An analysis was performed in order to investigate how the optimal solution was influenced by the variations of the unitary cost of fresh water, waste treatment and capital investment.

Multi-Objective Optimization of Spacecraft Trajectories for Small-Body Coverage Missions

NASA Technical Reports Server (NTRS)

Hinckley, David, Jr.; Englander, Jacob; Hitt, Darren

2017-01-01

Visual coverage of surface elements of a small-body object requires multiple images to be taken that meet many requirements on their viewing angles, illumination angles, times of day, and combinations thereof. Designing trajectories capable of maximizing total possible coverage may not be useful since the image target sequence and the feasibility of said sequence given the rotation-rate limitations of the spacecraft are not taken into account. This work presents a means of optimizing, in a multi-objective manner, surface target sequences that account for such limitations.

Generation of Parametric Equivalent-Area Targets for Design of Low-Boom Supersonic Concepts

NASA Technical Reports Server (NTRS)

Li, Wu; Shields, Elwood

2011-01-01

A tool with an Excel visual interface is developed to generate equivalent-area (A(sub e)) targets that satisfy the volume constraints for a low-boom supersonic configuration. The new parametric Ae target explorer allows users to interactively study the tradeoffs between the aircraft volume constraints and the low-boom characteristics (e.g., loudness) of the ground signature. Moreover, numerical optimization can be used to generate the optimal A(sub e) target for given A(sub e) volume constraints. A case study is used to demonstrate how a generated low-boom Ae target can be matched by a supersonic configuration that includes a fuselage, wing, nacelle, pylon, aft pod, horizontal tail, and vertical tail. The low-boom configuration is verified by sonic-boom analysis with an off-body pressure distribution at three body lengths below the configuration

SU-F-P-28: A Method of Maximize the Noncoplanar Beam Orientations and Assure the Beam Delivery Clearance for Stereotactic Body Radiation Therapy (SBRT)

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

Zhu, J

2016-06-15

Purpose: Develop a method to maximize the noncoplanar beam orientations and assure the beam delivery clearance for SBRT, therefore, optimize the dose conformality to the target, increase the dose sparing to the critical normal organs and reduce the hot spots in the body. Methods: A SBRT body frame (Elekta, Stockholm, Sweden) was used for patient immobilization and target localization. The SBRT body frame has CT fiducials on its side frames. After patient’s CT scan, the radiation treatment isocenter was defined and its coordinators referring to the body frame was calculated in the radiation treatment planning process. Meanwhile, initial beam orientationsmore » were designed based on the patient target and critical organ anatomy. The body frame was put on the linear accelerator couch and positioned to the calculated isocenter. Initially designed beam orientations were manually measured by tuning the body frame position on the couch, the gantry and couch angles. The finalized beam orientations were put into the treatment planning for dosimetric calculations. Results: Without patient presence, an optimal set of beam orientations were designed and validated. The radiation treatment plan was optimized and guaranteed for delivery clearance. Conclusion: The developed method is beneficial and effective in SBRT treatment planning for individual patient. It first allows maximizing the achievable noncoplanar beam orientation space, therefore, optimize the treatment plan for specific patient. It eliminates the risk that a plan needs to be modified due to the gantry and couch collision during patient setup.« less

Computer-Simulation Surrogates for Optimization: Application to Trapezoidal Ducts and Axisymmetric Bodies

NASA Technical Reports Server (NTRS)

Otto, John C.; Paraschivoiu, Marius; Yesilyurt, Serhat; Patera, Anthony T.

1995-01-01

Engineering design and optimization efforts using computational systems rapidly become resource intensive. The goal of the surrogate-based approach is to perform a complete optimization with limited resources. In this paper we present a Bayesian-validated approach that informs the designer as to how well the surrogate performs; in particular, our surrogate framework provides precise (albeit probabilistic) bounds on the errors incurred in the surrogate-for-simulation substitution. The theory and algorithms of our computer{simulation surrogate framework are first described. The utility of the framework is then demonstrated through two illustrative examples: maximization of the flowrate of fully developed ow in trapezoidal ducts; and design of an axisymmetric body that achieves a target Stokes drag.

Efficient Parameter Searches for Colloidal Materials Design with Digital Alchemy

NASA Astrophysics Data System (ADS)

Dodd, Paul, M.; Geng, Yina; van Anders, Greg; Glotzer, Sharon C.

Optimal colloidal materials design is challenging, even for high-throughput or genomic approaches, because the design space provided by modern colloid synthesis techniques can easily have dozens of dimensions. In this talk we present the methodology of an inverse approach we term ''digital alchemy'' to perform rapid searches of design-paramenter spaces with up to 188 dimensions that yield thermodynamically optimal colloid parameters for target crystal structures with up to 20 particles in a unit cell. The method relies only on fundamental principles of statistical mechanics and Metropolis Monte Carlo techniques, and yields particle attribute tolerances via analogues of familiar stress-strain relationships.

Grain Propellant Optimization Using Real Code Genetic Algorithm (RCGA)

NASA Astrophysics Data System (ADS)

Farizi, Muhammad Farraz Al; Oktovianus Bura, Romie; Fajar Junjunan, Soleh; Jihad, Bagus H.

2018-04-01

Grain propellant design is important in rocket motor design. The total impulse and ISP of the rocket motor is influenced by the grain propellant design. One way to get a grain propellant shape that generates the maximum total impulse value is to use the Real Code Genetic Algorithm (RCGA) method. In this paper RCGA is applied to star grain Rx-450. To find burn area of propellant used analytical method. While the combustion chamber pressures are sought with zero-dimensional equations. The optimization result can reach the desired target and increase the total impulse value by 3.3% from the initial design of Rx-450.

Efficient droplet router for digital microfluidic biochip using particle swarm optimizer

NASA Astrophysics Data System (ADS)

Pan, Indrajit; Samanta, Tuhina

2013-01-01

Digital Microfluidic Biochip has emerged as a revolutionary finding in the field of micro-electromechanical research. Different complex bioassays and pathological analysis are being efficiently performed on this miniaturized chip with negligible amount of sample specimens. Initially biochip was invented on continuous-fluid-flow mechanism but later it has evolved with more efficient concept of digital-fluid-flow. These second generation biochips are capable of serving more complex bioassays. This operational change in biochip technology emerged with the requirement of high end computer aided design needs for physical design automation. The change also paved new avenues of research to assist the proficient design automation. Droplet routing is one of those major aspects where it necessarily requires minimization of both routing completion time and total electrode usage. This task involves optimization of multiple associated parameters. In this paper we have proposed a particle swarm optimization based approach for droplet outing. The process mainly operates in two phases where initially we perform clustering of state space and classification of nets into designated clusters. This helps us to reduce solution space by redefining local sub optimal target in the interleaved space between source and global target of a net. In the next phase we resolve the concurrent routing issues of every sub optimal situation to generate final routing schedule. The method was applied on some standard test benches and hard test sets. Comparative analysis of experimental results shows good improvement on the aspect of unit cell usage, routing completion time and execution time over some well existing methods.

[Optimization study on extraction technology of the seed of Ziziphus jujuba var. spinosa by orthogonal design with multi-targets].

PubMed

Wang, Xiao-liang; Zhang, Yu-jie; Chen, Ming-xia; Wang, Ze-feng

2005-05-01

To optimize extraction technology of the seed of Ziziphus jujuba var. spinosa with the targets of the total saponin, total jujuboside A and B and total flavonoids. In the method of one-way and orthogonal tests, ethanol concentration, amount of ethanol, extraction time and extraction times were the factors in orthogonal test, and each factor with three levels. Ethanol concentration and extraction times had significant effect on all the targets, other factors should be selected in accordance with production practice. The best extraction technology is to extract for three times with 8 fold ethanol solution (60%), and 1.5 h each time.

Targeted Nanotechnology for Cancer Imaging

PubMed Central

Toy, Randall; Bauer, Lisa; Hoimes, Christopher; Ghaghada, Ketan B.; Karathanasis, Efstathios

2014-01-01

Targeted nanoparticle imaging agents provide many benefits and new opportunities to facilitate accurate diagnosis of cancer and significantly impact patient outcome. Due to the highly engineerable nature of nanotechnology, targeted nanoparticles exhibit significant advantages including increased contrast sensitivity, binding avidity and targeting specificity. Considering the various nanoparticle designs and their adjustable ability to target a specific site and generate detectable signals, nanoparticles can be optimally designed in terms of biophysical interactions (i.e., intravascular and interstitial transport) and biochemical interactions (i.e., targeting avidity towards cancer-related biomarkers) for site-specific detection of very distinct microenvironments. This review seeks to illustrate that the design of a nanoparticle dictates its in vivo journey and targeting of hard-to-reach cancer sites, facilitating early and accurate diagnosis and interrogation of the most aggressive forms of cancer. We will report various targeted nanoparticles for cancer imaging using X-ray computed tomography, ultrasound, magnetic resonance imaging, nuclear imaging and optical imaging. Finally, to realize the full potential of targeted nanotechnology for cancer imaging, we will describe the challenges and opportunities for the clinical translation and widespread adaptation of targeted nanoparticles imaging agents. PMID:25116445

Advancing cancer drug discovery towards more agile development of targeted combination therapies.

PubMed

Carragher, Neil O; Unciti-Broceta, Asier; Cameron, David A

2012-01-01

Current drug-discovery strategies are typically 'target-centric' and are based upon high-throughput screening of large chemical libraries against nominated targets and a selection of lead compounds with optimized 'on-target' potency and selectivity profiles. However, high attrition of targeted agents in clinical development suggest that combinations of targeted agents will be most effective in treating solid tumors if the biological networks that permit cancer cells to subvert monotherapies are identified and retargeted. Conventional drug-discovery and development strategies are suboptimal for the rational design and development of novel drug combinations. In this article, we highlight a series of emerging technologies supporting a less reductionist, more agile, drug-discovery and development approach for the rational design, validation, prioritization and clinical development of novel drug combinations.

Parameters optimization for magnetic resonance coupling wireless power transmission.

PubMed

Li, Changsheng; Zhang, He; Jiang, Xiaohua

2014-01-01

Taking maximum power transmission and power stable transmission as research objectives, optimal design for the wireless power transmission system based on magnetic resonance coupling is carried out in this paper. Firstly, based on the mutual coupling model, mathematical expressions of optimal coupling coefficients for the maximum power transmission target are deduced. Whereafter, methods of enhancing power transmission stability based on parameters optimal design are investigated. It is found that the sensitivity of the load power to the transmission parameters can be reduced and the power transmission stability can be enhanced by improving the system resonance frequency or coupling coefficient between the driving/pick-up coil and the transmission/receiving coil. Experiment results are well conformed to the theoretical analysis conclusions.

Superconducting nanowire single-photon detectors with non-periodic dielectric multilayers.

PubMed

Yamashita, Taro; Waki, Kentaro; Miki, Shigehito; Kirkwood, Robert A; Hadfield, Robert H; Terai, Hirotaka

2016-10-24

We present superconducting nanowire single-photon detectors (SSPDs) on non-periodic dielectric multilayers, which enable us to design a variety of wavelength dependences of optical absorptance by optimizing the dielectric multilayer. By adopting a robust simulation to optimize the dielectric multilayer, we designed three types of SSPDs with target wavelengths of 500 nm, 800 nm, and telecom range respectively. We fabricated SSPDs based on the optimized designs for 500 and 800 nm, and evaluated the system detection efficiency at various wavelengths. The results obtained confirm that the designed SSPDs with non-periodic dielectric multilayers worked well. This versatile device structure can be effective for multidisciplinary applications in fields such as the life sciences and remote sensing that require high efficiency over a precise spectral range and strong signal rejection at other wavelengths.

DESTINY

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

2015-03-10

DESTINY is a comprehensive tool for modeling 3D and 2D cache designs using SRAM,embedded DRAM (eDRAM), spin transfer torque RAM (STT-RAM), resistive RAM (ReRAM), and phase change RAM (PCN). In its purpose, it is similar to CACTI, CACTI-3DD or NVSim. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g. latency, area or energy-delay product) for agiven memory technology, choosing the suitable memory technology or fabrication method (i.e. 2D v/s 3D) for a given optimization target, etc. DESTINY has been validated against several cache prototypes. DESTINY is expected to boost studies ofmore » next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers.« less

A Bayesian approach for incorporating economic factors in sample size design for clinical trials of individual drugs and portfolios of drugs.

PubMed

Patel, Nitin R; Ankolekar, Suresh

2007-11-30

Classical approaches to clinical trial design ignore economic factors that determine economic viability of a new drug. We address the choice of sample size in Phase III trials as a decision theory problem using a hybrid approach that takes a Bayesian view from the perspective of a drug company and a classical Neyman-Pearson view from the perspective of regulatory authorities. We incorporate relevant economic factors in the analysis to determine the optimal sample size to maximize the expected profit for the company. We extend the analysis to account for risk by using a 'satisficing' objective function that maximizes the chance of meeting a management-specified target level of profit. We extend the models for single drugs to a portfolio of clinical trials and optimize the sample sizes to maximize the expected profit subject to budget constraints. Further, we address the portfolio risk and optimize the sample sizes to maximize the probability of achieving a given target of expected profit.

Present and future breast cancer management--bench to bedside and back: a positioning paper of academia, regulatory authorities and pharmaceutical industry.

PubMed

Bartsch, R; Frings, S; Marty, M; Awada, A; Berghoff, A S; Conte, P; Dickin, S; Enzmann, H; Gnant, M; Hasmann, M; Hendriks, H R; Llombart, A; Massacesi, C; von Minckwitz, G; Penault-Llorca, F; Scaltriti, M; Yarden, Y; Zwierzina, H; Zielinski, C C

2014-04-01

Insights into tumour biology of breast cancer have led the path towards the introduction of targeted treatment approaches; still, breast cancer-related mortality remains relatively high. Efforts in the field of basic research revealed new druggable targets which now await validation within the context of clinical trials. Therefore, questions concerning the optimal design of future studies are becoming even more pertinent. Aspects such as the ideal end point, availability of predictive markers to identify the optimal cohort for drug testing, or potential mechanisms of resistance need to be resolved. An expert panel representing the academic community, the pharmaceutical industry, as well as European Regulatory Authorities met in Vienna, Austria, in November 2012, in order to discuss breast cancer biology, identification of novel biological targets and optimal drug development with the aim of treatment individualization. This article summarizes statements and perspectives provided by the meeting participants.

Using in Vitro Evolution and Whole Genome Analysis To Discover Next Generation Targets for Antimalarial Drug Discovery

PubMed Central

2018-01-01

Although many new anti-infectives have been discovered and developed solely using phenotypic cellular screening and assay optimization, most researchers recognize that structure-guided drug design is more practical and less costly. In addition, a greater chemical space can be interrogated with structure-guided drug design. The practicality of structure-guided drug design has launched a search for the targets of compounds discovered in phenotypic screens. One method that has been used extensively in malaria parasites for target discovery and chemical validation is in vitro evolution and whole genome analysis (IVIEWGA). Here, small molecules from phenotypic screens with demonstrated antiparasitic activity are used in genome-based target discovery methods. In this Review, we discuss the newest, most promising druggable targets discovered or further validated by evolution-based methods, as well as some exceptions. PMID:29451780

Reliability Assessment of a Robust Design Under Uncertainty for a 3-D Flexible Wing

NASA Technical Reports Server (NTRS)

Gumbert, Clyde R.; Hou, Gene J. -W.; Newman, Perry A.

2003-01-01

The paper presents reliability assessment results for the robust designs under uncertainty of a 3-D flexible wing previously reported by the authors. Reliability assessments (additional optimization problems) of the active constraints at the various probabilistic robust design points are obtained and compared with the constraint values or target constraint probabilities specified in the robust design. In addition, reliability-based sensitivity derivatives with respect to design variable mean values are also obtained and shown to agree with finite difference values. These derivatives allow one to perform reliability based design without having to obtain second-order sensitivity derivatives. However, an inner-loop optimization problem must be solved for each active constraint to find the most probable point on that constraint failure surface.

Design of photon converter and photoneutron target for High power electron accelerator based BNCT.

PubMed

Rahmani, Faezeh; Seifi, Samaneh; Anbaran, Hossein Tavakoli; Ghasemi, Farshad

2015-12-01

An electron accelerator, ILU-14, with current of 10 mA and 100 kW in power has been considered as one of the options for neutron source in Boron Neutron Capture Therapy (BNCT). The final design of neutron target has been obtained using MCNPX to optimize the neutron production. Tungsten in strip shape and D2O in cylindrical form have been proposed as the photon converter and the photoneutron target, respectively. In addition calculation of heat deposition in the photon target design has been considered to ensure mechanical stability of target. The results show that about 8.37×10(12) photoneutron/s with average energy of 615 keV can be produced by this neutron source design. In addition, using an appropriate beam shaping assembly an epithermal neutron flux of the order of 1.24×10(8) cm(-2) s(-1) can be obtained for BNCT applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimization of the photoneutron target geometry for e-accelerator based BNCT

PubMed Central

Chegeni, Nahid; Pur, Saleh Boveiry; Razmjoo, Sasan; Hoseini, Seydeh Khadijed

2017-01-01

Background and aim Today, electron accelerators are taken into consideration as photoneutron sources. Therefore, for maximum production of epithermal neutron flux, designing a photoneutron target is of significant importance. In this paper, the effect of thickness and geometric shape of a photoneutron target on neutron output were investigated. Methods In this study, a pencil photon source with 13, 15, 18, 20 and 25 MeV energies and a diameter of 2 mm was investigated using Monte Carlo simulation method using MCNP code. To optimize the design of the photoneutron target, the tungsten target with various geometries and thicknesses was investigated. Results The maximum neutron flux produced for all target geometries and thicknesses occurred at neutron energy peak of around 0.46 MeV. As the thickness increased to 2 cm, neutron flux increased and then a decreasing trend was observed. For various geometrical shapes, the determining factor in photoneutron output was the effective target thickness in the photon interaction path that increased by the increase in the area of interaction. Another factor was the angle of the photon’s incidence with the target surface that resulted in a significant decrease in photoneutron output in cone-shaped targets Conclusion Three factors including the total neutron flux, neutrons energy spectrum, and convergence of neutrons plays an important role in the selection of geometry and shape of the target that should be investigated considering beam shaping assembly (BSA) shape. PMID:28848635

A Simple Method for Amplifying RNA Targets (SMART)

PubMed Central

McCalla, Stephanie E.; Ong, Carmichael; Sarma, Aartik; Opal, Steven M.; Artenstein, Andrew W.; Tripathi, Anubhav

2012-01-01

We present a novel and simple method for amplifying RNA targets (named by its acronym, SMART), and for detection, using engineered amplification probes that overcome existing limitations of current RNA-based technologies. This system amplifies and detects optimal engineered ssDNA probes that hybridize to target RNA. The amplifiable probe-target RNA complex is captured on magnetic beads using a sequence-specific capture probe and is separated from unbound probe using a novel microfluidic technique. Hybridization sequences are not constrained as they are in conventional target-amplification reactions such as nucleic acid sequence amplification (NASBA). Our engineered ssDNA probe was amplified both off-chip and in a microchip reservoir at the end of the separation microchannel using isothermal NASBA. Optimal solution conditions for ssDNA amplification were investigated. Although KCl and MgCl2 are typically found in NASBA reactions, replacing 70 mmol/L of the 82 mmol/L total chloride ions with acetate resulted in optimal reaction conditions, particularly for low but clinically relevant probe concentrations (≤100 fmol/L). With the optimal probe design and solution conditions, we also successfully removed the initial heating step of NASBA, thus achieving a true isothermal reaction. The SMART assay using a synthetic model influenza DNA target sequence served as a fundamental demonstration of the efficacy of the capture and microfluidic separation system, thus bridging our system to a clinically relevant detection problem. PMID:22691910

Optimal two-stage enrichment design correcting for biomarker misclassification.

PubMed

Zang, Yong; Guo, Beibei

2018-01-01

The enrichment design is an important clinical trial design to detect the treatment effect of the molecularly targeted agent (MTA) in personalized medicine. Under this design, patients are stratified into marker-positive and marker-negative subgroups based on their biomarker statuses and only the marker-positive patients are enrolled into the trial and randomized to receive either the MTA or a standard treatment. As the biomarker plays a key role in determining the enrollment of the trial, a misclassification of the biomarker can induce substantial bias, undermine the integrity of the trial, and seriously affect the treatment evaluation. In this paper, we propose a two-stage optimal enrichment design that utilizes the surrogate marker to correct for the biomarker misclassification. The proposed design is optimal in the sense that it maximizes the probability of correctly classifying each patient's biomarker status based on the surrogate marker information. In addition, after analytically deriving the bias caused by the biomarker misclassification, we develop a likelihood ratio test based on the EM algorithm to correct for such bias. We conduct comprehensive simulation studies to investigate the operating characteristics of the optimal design and the results confirm the desirable performance of the proposed design.

On Efficient Deployment of Wireless Sensors for Coverage and Connectivity in Constrained 3D Space.

PubMed

Wu, Chase Q; Wang, Li

2017-10-10

Sensor networks have been used in a rapidly increasing number of applications in many fields. This work generalizes a sensor deployment problem to place a minimum set of wireless sensors at candidate locations in constrained 3D space to k -cover a given set of target objects. By exhausting the combinations of discreteness/continuousness constraints on either sensor locations or target objects, we formulate four classes of sensor deployment problems in 3D space: deploy sensors at Discrete/Continuous Locations (D/CL) to cover Discrete/Continuous Targets (D/CT). We begin with the design of an approximate algorithm for DLDT and then reduce DLCT, CLDT, and CLCT to DLDT by discretizing continuous sensor locations or target objects into a set of divisions without sacrificing sensing precision. Furthermore, we consider a connected version of each problem where the deployed sensors must form a connected network, and design an approximation algorithm to minimize the number of deployed sensors with connectivity guarantee. For performance comparison, we design and implement an optimal solution and a genetic algorithm (GA)-based approach. Extensive simulation results show that the proposed deployment algorithms consistently outperform the GA-based heuristic and achieve a close-to-optimal performance in small-scale problem instances and a significantly superior overall performance than the theoretical upper bound.

Interactive Inverse Design Optimization of Fuselage Shape for Low-Boom Supersonic Concepts

NASA Technical Reports Server (NTRS)

Li, Wu; Shields, Elwood; Le, Daniel

2008-01-01

This paper introduces a tool called BOSS (Boom Optimization using Smoothest Shape modifications). BOSS utilizes interactive inverse design optimization to develop a fuselage shape that yields a low-boom aircraft configuration. A fundamental reason for developing BOSS is the need to generate feasible low-boom conceptual designs that are appropriate for further refinement using computational fluid dynamics (CFD) based preliminary design methods. BOSS was not developed to provide a numerical solution to the inverse design problem. Instead, BOSS was intended to help designers find the right configuration among an infinite number of possible configurations that are equally good using any numerical figure of merit. BOSS uses the smoothest shape modification strategy for modifying the fuselage radius distribution at 100 or more longitudinal locations to find a smooth fuselage shape that reduces the discrepancies between the design and target equivalent area distributions over any specified range of effective distance. For any given supersonic concept (with wing, fuselage, nacelles, tails, and/or canards), a designer can examine the differences between the design and target equivalent areas, decide which part of the design equivalent area curve needs to be modified, choose a desirable rate for the reduction of the discrepancies over the specified range, and select a parameter for smoothness control of the fuselage shape. BOSS will then generate a fuselage shape based on the designer's inputs in a matter of seconds. Using BOSS, within a few hours, a designer can either generate a realistic fuselage shape that yields a supersonic configuration with a low-boom ground signature or quickly eliminate any configuration that cannot achieve low-boom characteristics with fuselage shaping alone. A conceptual design case study is documented to demonstrate how BOSS can be used to develop a low-boom supersonic concept from a low-drag supersonic concept. The paper also contains a study on how perturbations in the equivalent area distribution affect the ground signature shape and how new target area distributions for low-boom signatures can be constructed using superposition of equivalent area distributions derived from the Seebass-George-Darden (SGD) theory.

Trajectory Design Employing Convex Optimization for Landing on Irregularly Shaped Asteroids

NASA Technical Reports Server (NTRS)

Pinson, Robin M.; Lu, Ping

2016-01-01

Mission proposals that land on asteroids are becoming popular. However, in order to have a successful mission the spacecraft must reliably and softly land at the intended landing site. The problem under investigation is how to design a fuel-optimal powered descent trajectory that can be quickly computed on- board the spacecraft, without interaction from ground control. An optimal trajectory designed immediately prior to the descent burn has many advantages. These advantages include the ability to use the actual vehicle starting state as the initial condition in the trajectory design and the ease of updating the landing target site if the original landing site is no longer viable. For long trajectories, the trajectory can be updated periodically by a redesign of the optimal trajectory based on current vehicle conditions to improve the guidance performance. One of the key drivers for being completely autonomous is the infrequent and delayed communication between ground control and the vehicle. Challenges that arise from designing an asteroid powered descent trajectory include complicated nonlinear gravity fields, small rotating bodies and low thrust vehicles. There are two previous studies that form the background to the current investigation. The first set looked in-depth at applying convex optimization to a powered descent trajectory on Mars with promising results.1, 2 This showed that the powered descent equations of motion can be relaxed and formed into a convex optimization problem and that the optimal solution of the relaxed problem is indeed a feasible solution to the original problem. This analysis used a constant gravity field. The second area applied a successive solution process to formulate a second order cone program that designs rendezvous and proximity operations trajectories.3, 4 These trajectories included a Newtonian gravity model. The equivalence of the solutions between the relaxed and the original problem is theoretically established. The proposed solution for designing the asteroid powered descent trajectory is to use convex optimization, a gravity model with higher fidelity than Newtonian, and an iterative solution process to design the fuel optimal trajectory. The solution to the convex optimization problem is the thrust profile, magnitude and direction, that will yield the minimum fuel trajectory for a soft landing at the target site, subject to various mission and operational constraints. The equations of motion are formulated in a rotating coordinate system and includes a high fidelity gravity model. The vehicle's thrust magnitude can vary between maximum and minimum bounds during the burn. Also, constraints are included to ensure that the vehicle does not run out of propellant, or go below the asteroid's surface, and any vehicle pointing requirements. The equations of motion are discretized and propagated with the trapezoidal rule in order to produce equality constraints for the optimization problem. These equality constraints allow the optimization algorithm to solve the entire problem, without including a propagator inside the optimization algorithm.

Computational modeling and in-vitro/in-silico correlation of phospholipid-based prodrugs for targeted drug delivery in inflammatory bowel disease

NASA Astrophysics Data System (ADS)

Dahan, Arik; Markovic, Milica; Keinan, Shahar; Kurnikov, Igor; Aponick, Aaron; Zimmermann, Ellen M.; Ben-Shabat, Shimon

2017-11-01

Targeting drugs to the inflamed intestinal tissue(s) represents a major advancement in the treatment of inflammatory bowel disease (IBD). In this work we present a powerful in-silico modeling approach to guide the molecular design of novel prodrugs targeting the enzyme PLA2, which is overexpressed in the inflamed tissues of IBD patients. The prodrug consists of the drug moiety bound to the sn-2 position of phospholipid (PL) through a carbonic linker, aiming to allow PLA2 to release the free drug. The linker length dictates the affinity of the PL-drug conjugate to PLA2, and the optimal linker will enable maximal PLA2-mediated activation. Thermodynamic integration and Weighted Histogram Analysis Method (WHAM)/Umbrella Sampling method were used to compute the changes in PLA2 transition state binding free energy of the prodrug molecule (ΔΔGtr) associated with decreasing/increasing linker length. The simulations revealed that 6-carbons linker is the optimal one, whereas shorter or longer linkers resulted in decreased PLA2-mediated activation. These in-silico results were shown to be in excellent correlation with experimental in-vitro data. Overall, this modern computational approach enables optimization of the molecular design of novel prodrugs, which may allow targeting the free drug specifically to the diseased intestinal tissue of IBD patients.

Multi-Stage System for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

2010-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Flexible Fusion Structure-Based Performance Optimization Learning for Multisensor Target Tracking

PubMed Central

Ge, Quanbo; Wei, Zhongliang; Cheng, Tianfa; Chen, Shaodong; Wang, Xiangfeng

2017-01-01

Compared with the fixed fusion structure, the flexible fusion structure with mixed fusion methods has better adjustment performance for the complex air task network systems, and it can effectively help the system to achieve the goal under the given constraints. Because of the time-varying situation of the task network system induced by moving nodes and non-cooperative target, and limitations such as communication bandwidth and measurement distance, it is necessary to dynamically adjust the system fusion structure including sensors and fusion methods in a given adjustment period. Aiming at this, this paper studies the design of a flexible fusion algorithm by using an optimization learning technology. The purpose is to dynamically determine the sensors’ numbers and the associated sensors to take part in the centralized and distributed fusion processes, respectively, herein termed sensor subsets selection. Firstly, two system performance indexes are introduced. Especially, the survivability index is presented and defined. Secondly, based on the two indexes and considering other conditions such as communication bandwidth and measurement distance, optimization models for both single target tracking and multi-target tracking are established. Correspondingly, solution steps are given for the two optimization models in detail. Simulation examples are demonstrated to validate the proposed algorithms. PMID:28481243

Flat-walled multilayered anechoic linings: Optimization and application

NASA Astrophysics Data System (ADS)

Xu, Jingfeng; Buchholz, Jörg M.; Fricke, Fergus R.

2005-11-01

The concept of flat-walled multilayered absorbent linings for anechoic rooms was proposed three decades ago. Flat-walled linings have the advantage of being less complicated and, hence, less costly to manufacture and install than the individual units such as wedges. However, there are difficulties in optimizing the design of such absorbent linings. In the present work, the design of a flat-walled multilayered anechoic lining that targeted a 250 Hz cut-off frequency and a 300 mm maximum lining thickness was first optimized using an evolutionary algorithm. Sixteen of the most commonly used commercial fibrous building insulation materials available in Australia were investigated and fourteen design options (i.e., material combinations) were found by the evolutionary algorithm. These options were then evaluated in accordance with their costs and measured acoustic absorption performances. Finally, the completed anechoic room, where the optimized design was applied, was qualified and the results showed that a large percentage (75%-85%) of the distance between the sound source and the room boundaries, on the traverses made, were anechoic.

TU-AB-BRB-00: New Methods to Ensure Target Coverage

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

NONE

2015-06-15

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

Optimal Power Flow Pursuit

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

Dall'Anese, Emiliano; Simonetto, Andrea

This paper considers distribution networks featuring inverter-interfaced distributed energy resources, and develops distributed feedback controllers that continuously drive the inverter output powers to solutions of AC optimal power flow (OPF) problems. Particularly, the controllers update the power setpoints based on voltage measurements as well as given (time-varying) OPF targets, and entail elementary operations implementable onto low-cost microcontrollers that accompany power-electronics interfaces of gateways and inverters. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. Convergence and OPF-target tracking capabilities of the controllers are analytically established. Overall,more » the proposed method allows to bypass traditional hierarchical setups where feedback control and optimization operate at distinct time scales, and to enable real-time optimization of distribution systems.« less

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library design.

PubMed

Ebalunode, Jerry O; Zheng, Weifan; Tropsha, Alexander

2011-01-01

Optimization of chemical library composition affords more efficient identification of hits from biological screening experiments. The optimization could be achieved through rational selection of reagents used in combinatorial library synthesis. However, with a rapid advent of parallel synthesis methods and availability of millions of compounds synthesized by many vendors, it may be more efficient to design targeted libraries by means of virtual screening of commercial compound collections. This chapter reviews the application of advanced cheminformatics approaches such as quantitative structure-activity relationships (QSAR) and pharmacophore modeling (both ligand and structure based) for virtual screening. Both approaches rely on empirical SAR data to build models; thus, the emphasis is placed on achieving models of the highest rigor and external predictive power. We present several examples of successful applications of both approaches for virtual screening to illustrate their utility. We suggest that the expert use of both QSAR and pharmacophore models, either independently or in combination, enables users to achieve targeted libraries enriched with experimentally confirmed hit compounds.

Design of the LBNF Beamline Target Station

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

Tariq, S.; Ammigan, K.; Anderson, K.

2016-10-01

The Long Baseline Neutrino Facility (LBNF) project will build a beamline located at Fermilab to create and aim an intense neutrino beam of appropriate energy range toward the DUNE detectors at the SURF facility in Lead, South Dakota. Neutrino production starts in the Target Station, which consists of a solid target, magnetic focusing horns, and the associated sub-systems and shielding infrastructure. Protons hit the target producing mesons which are then focused by the horns into a helium-filled decay pipe where they decay into muons and neutrinos. The target and horns are encased in actively cooled steel and concrete shielding inmore » a chamber called the target chase. The reference design chase is filled with air, but nitrogen and helium are being evaluated as alternatives. A replaceable beam window separates the decay pipe from the target chase. The facility is designed for initial operation at 1.2 MW, with the ability to upgrade to 2.4 MW, and is taking advantage of the experience gained by operating Fermilab’s NuMI facility. We discuss here the design status, associated challenges, and ongoing R&D and physics-driven component optimization of the Target Station.« less

Full space device optimization for solar cells.

PubMed

Baloch, Ahmer A B; Aly, Shahzada P; Hossain, Mohammad I; El-Mellouhi, Fedwa; Tabet, Nouar; Alharbi, Fahhad H

2017-09-20

Advances in computational materials have paved a way to design efficient solar cells by identifying the optimal properties of the device layers. Conventionally, the device optimization has been governed by single or double descriptors for an individual layer; mostly the absorbing layer. However, the performance of the device depends collectively on all the properties of the material and the geometry of each layer in the cell. To address this issue of multi-property optimization and to avoid the paradigm of reoccurring materials in the solar cell field, a full space material-independent optimization approach is developed and presented in this paper. The method is employed to obtain an optimized material data set for maximum efficiency and for targeted functionality for each layer. To ensure the robustness of the method, two cases are studied; namely perovskite solar cells device optimization and cadmium-free CIGS solar cell. The implementation determines the desirable optoelectronic properties of transport mediums and contacts that can maximize the efficiency for both cases. The resulted data sets of material properties can be matched with those in materials databases or by further microscopic material design. Moreover, the presented multi-property optimization framework can be extended to design any solid-state device.

Computer-Aided Drug Design Methods.

PubMed

Yu, Wenbo; MacKerell, Alexander D

2017-01-01

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

Transport Simulations for Fast Ignition on NIF

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

Strozzi, D J; Tabak, M; Grote, D P

2009-10-26

We are designing a full hydro-scale cone-guided, indirect-drive FI coupling experiment, for NIF, with the ARC-FIDO short-pulse laser. Current rad-hydro designs with limited fuel jetting into cone tip are not yet adequate for ignition. Designs are improving. Electron beam transport simulations (implicit-PIC LSP) show: (1) Magnetic fields and smaller angular spreads increase coupling to ignition-relevant 'hot spot' (20 um radius); (2) Plastic CD (for a warm target) produces somewhat better coupling than pure D (cryogenic target) due to enhanced resistive B fields; and (3) The optimal T{sub hot} for this target is {approx} 1 MeV; coupling falls by 3x asmore » T{sub hot} rises to 4 MeV.« less

RobOKoD: microbial strain design for (over)production of target compounds.

PubMed

Stanford, Natalie J; Millard, Pierre; Swainston, Neil

2015-01-01

Sustainable production of target compounds such as biofuels and high-value chemicals for pharmaceutical, agrochemical, and chemical industries is becoming an increasing priority given their current dependency upon diminishing petrochemical resources. Designing these strains is difficult, with current methods focusing primarily on knocking-out genes, dismissing other vital steps of strain design including the overexpression and dampening of genes. The design predictions from current methods also do not translate well-into successful strains in the laboratory. Here, we introduce RobOKoD (Robust, Overexpression, Knockout and Dampening), a method for predicting strain designs for overproduction of targets. The method uses flux variability analysis to profile each reaction within the system under differing production percentages of target-compound and biomass. Using these profiles, reactions are identified as potential knockout, overexpression, or dampening targets. The identified reactions are ranked according to their suitability, providing flexibility in strain design for users. The software was tested by designing a butanol-producing Escherichia coli strain, and was compared against the popular OptKnock and RobustKnock methods. RobOKoD shows favorable design predictions, when predictions from these methods are compared to a successful butanol-producing experimentally-validated strain. Overall RobOKoD provides users with rankings of predicted beneficial genetic interventions with which to support optimized strain design.

RobOKoD: microbial strain design for (over)production of target compounds

PubMed Central

Stanford, Natalie J.; Millard, Pierre; Swainston, Neil

2015-01-01

Sustainable production of target compounds such as biofuels and high-value chemicals for pharmaceutical, agrochemical, and chemical industries is becoming an increasing priority given their current dependency upon diminishing petrochemical resources. Designing these strains is difficult, with current methods focusing primarily on knocking-out genes, dismissing other vital steps of strain design including the overexpression and dampening of genes. The design predictions from current methods also do not translate well-into successful strains in the laboratory. Here, we introduce RobOKoD (Robust, Overexpression, Knockout and Dampening), a method for predicting strain designs for overproduction of targets. The method uses flux variability analysis to profile each reaction within the system under differing production percentages of target-compound and biomass. Using these profiles, reactions are identified as potential knockout, overexpression, or dampening targets. The identified reactions are ranked according to their suitability, providing flexibility in strain design for users. The software was tested by designing a butanol-producing Escherichia coli strain, and was compared against the popular OptKnock and RobustKnock methods. RobOKoD shows favorable design predictions, when predictions from these methods are compared to a successful butanol-producing experimentally-validated strain. Overall RobOKoD provides users with rankings of predicted beneficial genetic interventions with which to support optimized strain design. PMID:25853130

Advanced power analysis methodology targeted to the optimization of a digital pixel readout chip design and its critical serial powering system

NASA Astrophysics Data System (ADS)

Marconi, S.; Orfanelli, S.; Karagounis, M.; Hemperek, T.; Christiansen, J.; Placidi, P.

2017-02-01

A dedicated power analysis methodology, based on modern digital design tools and integrated with the VEPIX53 simulation framework developed within RD53 collaboration, is being used to guide vital choices for the design and optimization of the next generation ATLAS and CMS pixel chips and their critical serial powering circuit (shunt-LDO). Power consumption is studied at different stages of the design flow under different operating conditions. Significant effort is put into extensive investigations of dynamic power variations in relation with the decoupling seen by the powering network. Shunt-LDO simulations are also reported to prove the reliability at the system level.

Targeted Structural Optimization with Additive Manufacturing of Metals

NASA Technical Reports Server (NTRS)

Burt, Adam; Hull, Patrick

2015-01-01

The recent advances in additive manufacturing (AM) of metals have now improved the state-of-the-art such that traditionally non-producible parts can be readily produced in a cost-effective way. Because of these advances in manufacturing technology, structural optimization techniques are well positioned to supplement and advance this new technology. The goal of this project is to develop a structural design, analysis, and optimization framework combined with AM to significantly light-weight the interior of metallic structures while maintaining the selected structural properties of the original solid. This is a new state-of-the-art capability to significantly reduce mass, while maintaining the structural integrity of the original design, something that can only be done with AM. In addition, this framework will couple the design, analysis, and fabrication process, meaning that what has been designed directly represents the produced part, thus closing the loop on the design cycle and removing human iteration between design and fabrication. This fundamental concept has applications from light-weighting launch vehicle components to in situ resource fabrication.

A numerically optimized active shield for improved TMS targeting

PubMed Central

Hernandez-Garcia, Luis; Hall, Timothy; Gomez, Luis; Michielssen, Eric

2010-01-01

Transcranial magnetic stimulation (TMS) devices suffer of poor targeting and penetration depth. A new approach to designing TMS coils is introduced in order to improve the focus of the stimulation region through the use of actively shielded probes. Iterative optimization techniques were used to design different active shielding coils for TMS probes. The new approach aims to increase the amount of energy deposited in a thin cylindrical region below the probe relative to the energy deposited elsewhere in the region (“sharpness”), while simultaneously increase the induced electric field deep in the target region relative to the surface (“penetration”). After convergence, the resulting designs showed that there is a clear tradeoff between sharpness and penetration that can be controlled by the choice of a tuning parameter. The resulting designs were tested on a realistic human head conductivity model, taking the contribution from surface charges into account. The design of choice reduced penetration depths by 16.7%. The activated surface area was reduced by 24.1 % and the volume of the activation was reduced from 42.6% by the shield. Restoring the lost penetration could be achieved by increasing the total power to the coil by 16.3%, but in that case, the stimulated volume reduction was only 13.1% and there was a slight increase in the stimulated surface area (2.9 %) PMID:20965451

A numerically optimized active shield for improved transcranial magnetic stimulation targeting.

PubMed

Hernandez-Garcia, Luis; Hall, Timothy; Gomez, Luis; Michielssen, Eric

2010-10-01

Transcranial magnetic stimulation (TMS) devices suffer of poor targeting and penetration depth. A new approach to designing TMS coils is introduced in order to improve the focus of the stimulation region through the use of actively shielded probes. Iterative optimization techniques were used to design different active shielding coils for TMS probes. The new approach aims to increase the amount of energy deposited in a thin cylindrical region below the probe relative to the energy deposited elsewhere in the region ("sharpness"), whereas, simultaneously increase the induced electric field deep in the target region relative to the surface ("penetration"). After convergence, the resulting designs showed that there is a clear tradeoff between sharpness and penetration that can be controlled by the choice of a tuning parameter. The resulting designs were tested on a realistic human head conductivity model, taking the contribution from surface charges into account. The design of choice reduced penetration depths by 16.7%. The activated surface area was reduced by 24.1% and the volume of the activation was reduced from 42.6% by the shield. Restoring the lost penetration could be achieved by increasing the total power to the coil by 16.3%, but in that case, the stimulated volume reduction was only 13.1% and there was a slight increase in the stimulated surface area (2.9%). Copyright © 2010 Elsevier Inc. All rights reserved.

Blood pressure and LDL-cholesterol targets for prevention of recurrent strokes and cognitive decline in the hypertensive patient: design of the European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment randomized trial.

PubMed

Zanchetti, Alberto; Liu, Lisheng; Mancia, Giuseppe; Parati, Gianfranco; Grassi, Guido; Stramba-Badiale, Marco; Silani, Vincenzo; Bilo, Grzegorz; Corrao, Giovanni; Zambon, Antonella; Scotti, Lorenza; Zhang, Xinhua; Wang, HayYan; Zhang, Yuqing; Zhang, Xuezhong; Guan, Ting Rui; Berge, Eivind; Redon, Josep; Narkiewicz, Krzysztof; Dominiczak, Anna; Nilsson, Peter; Viigimaa, Margus; Laurent, Stéphane; Agabiti-Rosei, Enrico; Wu, Zhaosu; Zhu, Dingliang; Rodicio, José Luis; Ruilope, Luis Miguel; Martell-Claros, Nieves; Pinto, Fernando; Schmieder, Roland E; Burnier, Michel; Banach, Maciej; Cifkova, Renata; Farsang, Csaba; Konradi, Alexandra; Lazareva, Irina; Sirenko, Yuriy; Dorobantu, Maria; Postadzhiyan, Arman; Accetto, Rok; Jelakovic, Bojan; Lovic, Dragan; Manolis, Athanasios J; Stylianou, Philippos; Erdine, Serap; Dicker, Dror; Wei, Gangzhi; Xu, Chengbin; Xie, Hengge; Coca, Antonio; O'Brien, John; Ford, Gary

2014-09-01

The SBP values to be achieved by antihypertensive therapy in order to maximize reduction of cardiovascular outcomes are unknown; neither is it clear whether in patients with a previous cardiovascular event, the optimal values are lower than in the low-to-moderate risk hypertensive patients, or a more cautious blood pressure (BP) reduction should be obtained. Because of the uncertainty whether 'the lower the better' or the 'J-curve' hypothesis is correct, the European Society of Hypertension and the Chinese Hypertension League have promoted a randomized trial comparing antihypertensive treatment strategies aiming at three different SBP targets in hypertensive patients with a recent stroke or transient ischaemic attack. As the optimal level of low-density lipoprotein cholesterol (LDL-C) level is also unknown in these patients, LDL-C-lowering has been included in the design. The European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment trial is a prospective multinational, randomized trial with a 3 × 2 factorial design comparing: three different SBP targets (1, <145-135; 2, <135-125; 3, <125  mmHg); two different LDL-C targets (target A, 2.8-1.8; target B, <1.8  mmol/l). The trial is to be conducted on 7500 patients aged at least 65 years (2500 in Europe, 5000 in China) with hypertension and a stroke or transient ischaemic attack 1-6 months before randomization. Antihypertensive and statin treatments will be initiated or modified using suitable registered agents chosen by the investigators, in order to maintain patients within the randomized SBP and LDL-C windows. All patients will be followed up every 3 months for BP and every 6 months for LDL-C. Ambulatory BP will be measured yearly. Primary outcome is time to stroke (fatal and non-fatal). Important secondary outcomes are: time to first major cardiovascular event; cognitive decline (Montreal Cognitive Assessment) and dementia. All major outcomes will be adjudicated by committees blind to randomized allocation. A Data and Safety Monitoring Board has open access to data and can recommend trial interruption for safety. It has been calculated that 925 patients would reach the primary outcome after a mean 4-year follow-up, and this should provide at least 80% power to detect a 25% stroke difference between SBP targets and a 20% difference between LDL-C targets.

Optimized Non-Obstructive Particle Damping (NOPD) Treatment for Composite Honeycomb Structures

NASA Technical Reports Server (NTRS)

Panossian, H.

2008-01-01

Non-Obstructive Particle Damping (NOPD) technology is a passive vibration damping approach whereby metallic or non-metallic particles in spherical or irregular shapes, of heavy or light consistency, and even liquid particles are placed inside cavities or attached to structures by an appropriate means at strategic locations, to absorb vibration energy. The objective of the work described herein is the development of a design optimization procedure and discussion of test results for such a NOPD treatment on honeycomb (HC) composite structures, based on finite element modeling (FEM) analyses, optimization and tests. Modeling and predictions were performed and tests were carried out to correlate the test data with the FEM. The optimization procedure consisted of defining a global objective function, using finite difference methods, to determine the optimal values of the design variables through quadratic linear programming. The optimization process was carried out by targeting the highest dynamic displacements of several vibration modes of the structure and finding an optimal treatment configuration that will minimize them. An optimal design was thus derived and laboratory tests were conducted to evaluate its performance under different vibration environments. Three honeycomb composite beams, with Nomex core and aluminum face sheets, empty (untreated), uniformly treated with NOPD, and optimally treated with NOPD, according to the analytically predicted optimal design configuration, were tested in the laboratory. It is shown that the beam with optimal treatment has the lowest response amplitude. Described below are results of modal vibration tests and FEM analyses from predictions of the modal characteristics of honeycomb beams under zero, 50% uniform treatment and an optimal NOPD treatment design configuration and verification with test data.

Enriching peptide libraries for binding affinity and specificity through computationally directed library design

PubMed Central

Foight, Glenna Wink; Chen, T. Scott; Richman, Daniel; Keating, Amy E.

2017-01-01

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model. PMID:28236241

Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design.

PubMed

Foight, Glenna Wink; Chen, T Scott; Richman, Daniel; Keating, Amy E

2017-01-01

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model.

Hydraulic analysis and optimization design in Guri rehabilitation project

NASA Astrophysics Data System (ADS)

Cheng, H.; Zhou, L. J.; Gong, L.; Wang, Z. N.; Wen, Q.; Zhao, Y. Z.; Wang, Y. L.

2016-11-01

Recently Dongfang was awarded the contract for rehabilitation of 6 units in Guri power plant, the biggest hydro power project in Venezuela. The rehabilitation includes, but not limited to, the extension of output capacity by about 50% and enhancement of efficiency level. To achieve the targets the runner and the guide vanes will be replaced by the newly optimized designs. In addition, the out-of-date stay vanes with straight plate shape will be modified into proper profiles after considering the application feasibility in field. The runner and vane profiles were optimized by using state-of-the-art flow simulation techniques. And the hydraulic performances were confirmed by the following model tests. This paper describes the flow analysis during the optimization procedure and the comparison between various technical concepts.

Genetic algorithms for GNC settings and DACS design application to an asteroid Kinetic Impactor

NASA Astrophysics Data System (ADS)

Vernis, P.; Oliviero, V.

2018-06-01

This paper deals with an application of Genetic Algorithm (GA) tools in order to perform and optimize the settings phase of the Guidance, Navigation, and Control (GNC) data set for the endgame phase of a Kinetic Impactor (KI) targeting a medium-size Near Earth Object (NEO). A coupled optimization of the GNC settings and of the GC-oriented design of the Divert and Attitude Control System (DACS) is also proposed. The illustration of the developed principles is made considering the NEOShield study frame.

Histone-Targeted Nucleic Acid Delivery for Tissue Regenerative Applications

NASA Astrophysics Data System (ADS)

Munsell, Erik V.

Nucleic acid delivery has garnered significant attention as an innovative therapeutic approach for treating a wide variety of diseases. However, the design of non-viral delivery systems that negotiate efficient intracellular trafficking and nuclear entry represents a significant challenge. Overcoming these hurdles requires a combination of well-controlled materials approaches with techniques to understand and direct cellular delivery. Recent investigations have highlighted the roles histone tail sequences play in directing nuclear delivery and retention, as well as activating DNA transcription. We established the ability to recapitulate these natural histone tail activities within non-viral gene nanocarriers, driving gene transfer/expression by enabling effective navigation to the nucleus via retrograde vesicular trafficking. A unique finding of this histone-targeted approach was that nanocarriers gained enhanced access to the nucleus during mitosis. The work described in this dissertation builds off of these fundamental insights to facilitate the translation of this histone-targeted delivery approach toward regenerative medicine applications. During native tissue repair, actively proliferating mesenchymal stem cells (MSCs) respond to a complex series of growth factor signals that direct their differentiation. Accordingly, the investigations in this work focused on utilizing the histone-targeted nanocarriers to enhance osteogenic growth factor gene transfer in dividing MSCs leading to augmented MSC chondrogenic differentiation, an essential first step in skeletal tissue repair. Concurrently, additional studies focused on optimizing the histone-targeted nanocarrier design strategy to enable improved plasmid DNA (pDNA) binding stability and tunable harnessing of native cellular processing pathways for enhanced gene transfer. Overall, the work presented herein demonstrated substantial increases in growth factor expression following histone-targeted gene transfer. This enhanced expression enabled more robust levels of chondrogenesis in MSCs than treatments with equivalent amounts of recombinant growth factor protein. Additionally, nanocarrier design optimization provided effective pDNA condensation and controllable interactions with native histone effectors. Importantly, these optimized nanocarriers conferred stable nanoplex formation and maintained transfection efficiency under physiologically relevant conditions. Taken together, these advances may help drive the clinical translation of histone-targeted nucleic acid delivery strategies for the regeneration of damaged tissue following traumatic injury.

Design of the Blood Pressure Goals in Dialysis pilot study.

PubMed

Gul, Ambreen; Miskulin, Dana; Gassman, Jennifer; Harford, Antonia; Horowitz, Bruce; Chen, Joline; Paine, Susan; Bedrick, Edward; Kusek, John W; Unruh, Mark; Zager, Philip

2014-02-01

Cardiovascular disease (CVD) is markedly increased among hemodialysis (HD) patients. Optimizing blood pressure (BP) among HD patients may present an important opportunity to reduce the disparity in CVD rates between HD patients and the general population. The optimal target predialysis systolic BP (SBP) among HD patients is unknown. Current international guidelines, calling for a predialysis SBP < 140 mm Hg, are based on the opinion and extrapolation from the general population. Existing randomized controlled trials (RCTs) were small and did not include prespecified BP targets. The authors described the design of the Blood Pressure in Dialysis (BID) Study, a pilot, multicenter RCT where HD patients are randomized to either a target-standardized predialysis SBP of 110 to 140 mm Hg or 155 to 165 mm Hg. This is the first study to randomize HD patients to 2 different SBP targets. Primary outcomes are feasibility and safety. Feasibility parameters include recruitment and retention rates, adherence with prescribed BP measurements and achievement and maintenance of selected BP targets. Safety parameters include rates of hypotension and other adverse and serious adverse events. The authors obtained preliminary data on changes in left ventricular mass, aortic pulse wave velocity, vascular access thromboses and health-related quality of life across study arms, which may be the secondary outcomes in the full-scale study. The data acquired in the pilot RCT will determine the feasibility and safety and inform the design of a full-scale trial, powered for hard outcomes, which may require 2000 participants.

Shape optimization techniques for musical instrument design

NASA Astrophysics Data System (ADS)

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

2002-11-01

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

Topology optimization for design of segmented permanent magnet arrays with ferromagnetic materials

NASA Astrophysics Data System (ADS)

Lee, Jaewook; Yoon, Minho; Nomura, Tsuyoshi; Dede, Ercan M.

2018-03-01

This paper presents multi-material topology optimization for the co-design of permanent magnet segments and iron material. Specifically, a co-design methodology is proposed to find an optimal border of permanent magnet segments, a pattern of magnetization directions, and an iron shape. A material interpolation scheme is proposed for material property representation among air, permanent magnet, and iron materials. In this scheme, the permanent magnet strength and permeability are controlled by density design variables, and permanent magnet magnetization directions are controlled by angle design variables. In addition, a scheme to penalize intermediate magnetization direction is proposed to achieve segmented permanent magnet arrays with discrete magnetization directions. In this scheme, permanent magnet strength is controlled depending on magnetization direction, and consequently the final permanent magnet design converges into permanent magnet segments having target discrete directions. To validate the effectiveness of the proposed approach, three design examples are provided. The examples include the design of a dipole Halbach cylinder, magnetic system with arbitrarily-shaped cavity, and multi-objective problem resembling a magnetic refrigeration device.

Aerodynamic shape optimization using control theory

NASA Technical Reports Server (NTRS)

Reuther, James

1996-01-01

Aerodynamic shape design has long persisted as a difficult scientific challenge due its highly nonlinear flow physics and daunting geometric complexity. However, with the emergence of Computational Fluid Dynamics (CFD) it has become possible to make accurate predictions of flows which are not dominated by viscous effects. It is thus worthwhile to explore the extension of CFD methods for flow analysis to the treatment of aerodynamic shape design. Two new aerodynamic shape design methods are developed which combine existing CFD technology, optimal control theory, and numerical optimization techniques. Flow analysis methods for the potential flow equation and the Euler equations form the basis of the two respective design methods. In each case, optimal control theory is used to derive the adjoint differential equations, the solution of which provides the necessary gradient information to a numerical optimization method much more efficiently then by conventional finite differencing. Each technique uses a quasi-Newton numerical optimization algorithm to drive an aerodynamic objective function toward a minimum. An analytic grid perturbation method is developed to modify body fitted meshes to accommodate shape changes during the design process. Both Hicks-Henne perturbation functions and B-spline control points are explored as suitable design variables. The new methods prove to be computationally efficient and robust, and can be used for practical airfoil design including geometric and aerodynamic constraints. Objective functions are chosen to allow both inverse design to a target pressure distribution and wave drag minimization. Several design cases are presented for each method illustrating its practicality and efficiency. These include non-lifting and lifting airfoils operating at both subsonic and transonic conditions.

An Investigation to Manufacturing Analytical Services Composition using the Analytical Target Cascading Method.

PubMed

Tien, Kai-Wen; Kulvatunyou, Boonserm; Jung, Kiwook; Prabhu, Vittaldas

2017-01-01

As cloud computing is increasingly adopted, the trend is to offer software functions as modular services and compose them into larger, more meaningful ones. The trend is attractive to analytical problems in the manufacturing system design and performance improvement domain because 1) finding a global optimization for the system is a complex problem; and 2) sub-problems are typically compartmentalized by the organizational structure. However, solving sub-problems by independent services can result in a sub-optimal solution at the system level. This paper investigates the technique called Analytical Target Cascading (ATC) to coordinate the optimization of loosely-coupled sub-problems, each may be modularly formulated by differing departments and be solved by modular analytical services. The result demonstrates that ATC is a promising method in that it offers system-level optimal solutions that can scale up by exploiting distributed and modular executions while allowing easier management of the problem formulation.

Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.

PubMed

Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted

2017-01-01

Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.

Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies

PubMed Central

Abel zur Wiesch, Pia; Cohen, Ted

2017-01-01

Identifying optimal dosing of antibiotics has proven challenging—some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood. PMID:28060813

Data on cost-optimal Nearly Zero Energy Buildings (NZEBs) across Europe.

PubMed

D'Agostino, Delia; Parker, Danny

2018-04-01

This data article refers to the research paper A model for the cost-optimal design of Nearly Zero Energy Buildings (NZEBs) in representative climates across Europe [1]. The reported data deal with the design optimization of a residential building prototype located in representative European locations. The study focus on the research of cost-optimal choices and efficiency measures in new buildings depending on the climate. The data linked within this article relate to the modelled building energy consumption, renewable production, potential energy savings, and costs. Data allow to visualize energy consumption before and after the optimization, selected efficiency measures, costs and renewable production. The reduction of electricity and natural gas consumption towards the NZEB target can be visualized together with incremental and cumulative costs in each location. Further data is available about building geometry, costs, CO 2 emissions, envelope, materials, lighting, appliances and systems.

Optimal Deployment of Sensor Nodes Based on Performance Surface of Underwater Acoustic Communication

PubMed Central

Choi, Jee Woong

2017-01-01

The underwater acoustic sensor network (UWASN) is a system that exchanges data between numerous sensor nodes deployed in the sea. The UWASN uses an underwater acoustic communication technique to exchange data. Therefore, it is important to design a robust system that will function even in severely fluctuating underwater communication conditions, along with variations in the ocean environment. In this paper, a new algorithm to find the optimal deployment positions of underwater sensor nodes is proposed. The algorithm uses the communication performance surface, which is a map showing the underwater acoustic communication performance of a targeted area. A virtual force-particle swarm optimization algorithm is then used as an optimization technique to find the optimal deployment positions of the sensor nodes, using the performance surface information to estimate the communication radii of the sensor nodes in each generation. The algorithm is evaluated by comparing simulation results between two different seasons (summer and winter) for an area located off the eastern coast of Korea as the selected targeted area. PMID:29053569

Design of the hairpin ribozyme for targeting specific RNA sequences.

PubMed

Hampel, A; DeYoung, M B; Galasinski, S; Siwkowski, A

1997-01-01

The following steps should be taken when designing the hairpin ribozyme to cleave a specific target sequence: 1. Select a target sequence containing BN*GUC where B is C, G, or U. 2. Select the target sequence in areas least likely to have extensive interfering structure. 3. Design the conventional hairpin ribozyme as shown in Fig. 1, such that it can form a 4 bp helix 2 and helix 1 lengths up to 10 bp. 4. Synthesize this ribozyme from single-stranded DNA templates with a double-stranded T7 promoter. 5. Prepare a series of short substrates capable of forming a range of helix 1 lengths of 5-10 bp. 6. Identify these by direct RNA sequencing. 7. Assay the extent of cleavage of each substrate to identify the optimal length of helix 1. 8. Prepare the hairpin tetraloop ribozyme to determine if catalytic efficiency can be improved.

Optimizing Soft Tissue Management and Spacer Design in Segmental Bone Defects

DTIC Science & Technology

2015-10-01

were found with Tukey’s HSD post hoc analysis. Several target genes such as Oct4, Sox2, TGFB, and Col1A1 were generally up-regulated in all sections...samples presented several upregulated target genes such as Oct4, Sox2, TGFB, and Col1A1 in all sections. No significant main effects were found for

Development And Characterization Of A Liner-On-Target Injector For Staged Z-Pinch Experiments

NASA Astrophysics Data System (ADS)

Valenzuela, J. C.; Conti, F.; Krasheninnikov, I.; Narkis, J.; Beg, F.; Wessel, F. J.; Rahman, H. U.

2016-10-01

We present the design and optimization of a liner-on-target injector for Staged Z-pinch experiments. The injector is composed of an annular high atomic number (e.g. Ar, Kr) gas-puff and an on-axis plasma gun that delivers the ionized deuterium target. The liner nozzle injector has been carefully studied using Computational Fluid Dynamics (CFD) simulations to produce a highly collimated 1 cm radius gas profile that satisfies the theoretical requirement for best performance on the 1 MA Zebra current driver. The CFD simulations produce density profiles as a function of the nozzle shape and gas. These profiles are initialized in the MHD MACH2 code to find the optimal liner density for a stable, uniform implosion. We use a simple Snowplow model to study the plasma sheath acceleration in a coaxial plasma gun to help us properly design the target injector. We have performed line-integrated density measurements using a CW He-Ne laser to characterize the liner gas and the plasma gun density as a function of time. The measurements are compared with models and calculations and benchmarked accordingly. Advanced Research Projects Agency - Energy, DE-AR0000569.

Stable Gene Targeting in Human Cells Using Single-Strand Oligonucleotides with Modified Bases

PubMed Central

Rios, Xavier; Briggs, Adrian W.; Christodoulou, Danos; Gorham, Josh M.; Seidman, Jonathan G.; Church, George M.

2012-01-01

Recent advances allow multiplexed genome engineering in E. coli, employing easily designed oligonucleotides to edit multiple loci simultaneously. A similar technology in human cells would greatly expedite functional genomics, both by enhancing our ability to test how individual variants such as single nucleotide polymorphisms (SNPs) are related to specific phenotypes, and potentially allowing simultaneous mutation of multiple loci. However, oligo-mediated targeting of human cells is currently limited by low targeting efficiencies and low survival of modified cells. Using a HeLa-based EGFP-rescue reporter system we show that use of modified base analogs can increase targeting efficiency, in part by avoiding the mismatch repair machinery. We investigate the effects of oligonucleotide toxicity and find a strong correlation between the number of phosphorothioate bonds and toxicity. Stably EGFP-corrected cells were generated at a frequency of ~0.05% with an optimized oligonucleotide design combining modified bases and reduced number of phosphorothioate bonds. We provide evidence from comparative RNA-seq analysis suggesting cellular immunity induced by the oligonucleotides might contribute to the low viability of oligo-corrected cells. Further optimization of this method should allow rapid and scalable genome engineering in human cells. PMID:22615794

Rapid Method Development in Hydrophilic Interaction Liquid Chromatography for Pharmaceutical Analysis Using a Combination of Quantitative Structure-Retention Relationships and Design of Experiments.

PubMed

Taraji, Maryam; Haddad, Paul R; Amos, Ruth I J; Talebi, Mohammad; Szucs, Roman; Dolan, John W; Pohl, Chris A

2017-02-07

A design-of-experiment (DoE) model was developed, able to describe the retention times of a mixture of pharmaceutical compounds in hydrophilic interaction liquid chromatography (HILIC) under all possible combinations of acetonitrile content, salt concentration, and mobile-phase pH with R 2 > 0.95. Further, a quantitative structure-retention relationship (QSRR) model was developed to predict retention times for new analytes, based only on their chemical structures, with a root-mean-square error of prediction (RMSEP) as low as 0.81%. A compound classification based on the concept of similarity was applied prior to QSRR modeling. Finally, we utilized a combined QSRR-DoE approach to propose an optimal design space in a quality-by-design (QbD) workflow to facilitate the HILIC method development. The mathematical QSRR-DoE model was shown to be highly predictive when applied to an independent test set of unseen compounds in unseen conditions with a RMSEP value of 5.83%. The QSRR-DoE computed retention time of pharmaceutical test analytes and subsequently calculated separation selectivity was used to optimize the chromatographic conditions for efficient separation of targets. A Monte Carlo simulation was performed to evaluate the risk of uncertainty in the model's prediction, and to define the design space where the desired quality criterion was met. Experimental realization of peak selectivity between targets under the selected optimal working conditions confirmed the theoretical predictions. These results demonstrate how discovery of optimal conditions for the separation of new analytes can be accelerated by the use of appropriate theoretical tools.

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning

PubMed Central

Baykal, Cenk; Torres, Luis G.; Alterovitz, Ron

2015-01-01

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot’s behavior and reachable workspace. Optimizing a robot’s design by appropriately selecting tube parameters can improve the robot’s effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot’s configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy. PMID:26951790

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning.

PubMed

Baykal, Cenk; Torres, Luis G; Alterovitz, Ron

2015-09-28

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot's behavior and reachable workspace. Optimizing a robot's design by appropriately selecting tube parameters can improve the robot's effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot's configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy.

Multi-kilobase homozygous targeted gene replacement in human induced pluripotent stem cells.

PubMed

Byrne, Susan M; Ortiz, Luis; Mali, Prashant; Aach, John; Church, George M

2015-02-18

Sequence-specific nucleases such as TALEN and the CRISPR/Cas9 system have so far been used to disrupt, correct or insert transgenes at precise locations in mammalian genomes. We demonstrate efficient 'knock-in' targeted replacement of multi-kilobase genes in human induced pluripotent stem cells (iPSC). Using a model system replacing endogenous human genes with their mouse counterpart, we performed a comprehensive study of targeting vector design parameters for homologous recombination. A 2.7 kilobase (kb) homozygous gene replacement was achieved in up to 11% of iPSC without selection. The optimal homology arm length was around 2 kb, with homology length being especially critical on the arm not adjacent to the cut site. Homologous sequence inside the cut sites was detrimental to targeting efficiency, consistent with a synthesis-dependent strand annealing (SDSA) mechanism. Using two nuclease sites, we observed a high degree of gene excisions and inversions, which sometimes occurred more frequently than indel mutations. While homozygous deletions of 86 kb were achieved with up to 8% frequency, deletion frequencies were not solely a function of nuclease activity and deletion size. Our results analyzing the optimal parameters for targeting vector design will inform future gene targeting efforts involving multi-kilobase gene segments, particularly in human iPSC. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Computational design optimization for microfluidic magnetophoresis

PubMed Central

Plouffe, Brian D.; Lewis, Laura H.; Murthy, Shashi K.

2011-01-01

Current macro- and microfluidic approaches for the isolation of mammalian cells are limited in both efficiency and purity. In order to design a robust platform for the enumeration of a target cell population, high collection efficiencies are required. Additionally, the ability to isolate pure populations with minimal biological perturbation and efficient off-chip recovery will enable subcellular analyses of these cells for applications in personalized medicine. Here, a rational design approach for a simple and efficient device that isolates target cell populations via magnetic tagging is presented. In this work, two magnetophoretic microfluidic device designs are described, with optimized dimensions and operating conditions determined from a force balance equation that considers two dominant and opposing driving forces exerted on a magnetic-particle-tagged cell, namely, magnetic and viscous drag. Quantitative design criteria for an electromagnetic field displacement-based approach are presented, wherein target cells labeled with commercial magnetic microparticles flowing in a central sample stream are shifted laterally into a collection stream. Furthermore, the final device design is constrained to fit on standard rectangular glass coverslip (60 (L)×24 (W)×0.15 (H) mm3) to accommodate small sample volume and point-of-care design considerations. The anticipated performance of the device is examined via a parametric analysis of several key variables within the model. It is observed that minimal currents (<500 mA) are required to generate magnetic fields sufficient to separate cells from the sample streams flowing at rate as high as 7 ml∕h, comparable to the performance of current state-of-the-art magnet-activated cell sorting systems currently used in clinical settings. Experimental validation of the presented model illustrates that a device designed according to the derived rational optimization can effectively isolate (∼100%) a magnetic-particle-tagged cell population from a homogeneous suspension even in a low abundance. Overall, this design analysis provides a rational basis to select the operating conditions, including chamber and wire geometry, flow rates, and applied currents, for a magnetic-microfluidic cell separation device. PMID:21526007

Time and frequency constrained sonar signal design for optimal detection of elastic objects.

PubMed

Hamschin, Brandon; Loughlin, Patrick J

2013-04-01

In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

Design and analysis of metal-dielectric nonpolarizing beam splitters in a glass cube.

PubMed

Shi, Jin Hui; Guan, Chun Ying; Wang, Zheng Ping

2009-06-20

A novel design of a 25-layer metal-dielectric nonpolarizing beam splitter in a cube is proposed by use of the optimization method and is theoretically investigated. The simulations of the reflectance and differential phases induced by reflection and transmission are presented. The simulation results reveal that both the amplitude and the phase characteristics of the nonpolarizing beam splitter could realize the design targets, the differences between the simulated and the target reflectance of 50% are less than 2%, and the differential phases are less than 3 degrees in the range of 530 nm-570 nm for both p and s components.

Whole-Genome Thermodynamic Analysis Reduces siRNA Off-Target Effects

PubMed Central

Chen, Xi; Liu, Peng; Chou, Hui-Hsien

2013-01-01

Small interfering RNAs (siRNAs) are important tools for knocking down targeted genes, and have been widely applied to biological and biomedical research. To design siRNAs, two important aspects must be considered: the potency in knocking down target genes and the off-target effect on any nontarget genes. Although many studies have produced useful tools to design potent siRNAs, off-target prevention has mostly been delegated to sequence-level alignment tools such as BLAST. We hypothesize that whole-genome thermodynamic analysis can identify potential off-targets with higher precision and help us avoid siRNAs that may have strong off-target effects. To validate this hypothesis, two siRNA sets were designed to target three human genes IDH1, ITPR2 and TRIM28. They were selected from the output of two popular siRNA design tools, siDirect and siDesign. Both siRNA design tools have incorporated sequence-level screening to avoid off-targets, thus their output is believed to be optimal. However, one of the sets we tested has off-target genes predicted by Picky, a whole-genome thermodynamic analysis tool. Picky can identify off-target genes that may hybridize to a siRNA within a user-specified melting temperature range. Our experiments validated that some off-target genes predicted by Picky can indeed be inhibited by siRNAs. Similar experiments were performed using commercially available siRNAs and a few off-target genes were also found to be inhibited as predicted by Picky. In summary, we demonstrate that whole-genome thermodynamic analysis can identify off-target genes that are missed in sequence-level screening. Because Picky prediction is deterministic according to thermodynamics, if a siRNA candidate has no Picky predicted off-targets, it is unlikely to cause off-target effects. Therefore, we recommend including Picky as an additional screening step in siRNA design. PMID:23484018

TU-AB-BRB-01: Coverage Evaluation and Probabilistic Treatment Planning as a Margin Alternative

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

Siebers, J.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

TU-AB-BRB-03: Coverage-Based Treatment Planning to Accommodate Organ Deformable Motions and Contouring Uncertainties for Prostate Treatment

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

Xu, H.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

TU-AB-BRB-02: Stochastic Programming Methods for Handling Uncertainty and Motion in IMRT Planning

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

Unkelbach, J.

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. Themore » treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: To understand robust-planning as a clinical alternative to using margin-based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques.« less

Statistical optimization of medium composition and culture condition for the production of recombinant anti-lipopolysaccharide factor of Eriocheir sinensis in Escherichia coli

NASA Astrophysics Data System (ADS)

Jiang, Shan; Liu, Mei; Wang, Baojie; Jiang, Keyong; Wang, Lei

2011-11-01

Anti-lipopolysaccharide factors (ALFs) are important antimicrobial peptides that are isolated from some aquatic species. In a previous study, we isolated ALF genes from Chinese mitten crab, Eriocheir sinensis. In this study, we optimized the production of a recombinant ALF by expressing E. sinensis ALF genes in Escherichia coli maintained in shake-flasks. In particular, we focused on optimization of both the medium composition and the culture condition. Various medium components were analyzed by the Plackett-Burman design, and two significant screened factors, (NH4)2SO4 and KH2PO4, were further optimized via the central composite design (CCD). Based on the CCD analysis, we investigated the induction start-up time, the isopropylthio-D-galactoside (IPTG) concentration, the post-induction time, and the temperature by response surface methodology. We found that the highest level of ALF fusion protein was achieved in the medium containing 1.89 g/L (NH4)2SO4 and 3.18 g/L KH2PO4, with a cell optical density of 0.8 at 600 nm before induction, an IPTG concentration of 0.5 mmol/L, a post-induction temperature of 32.7°C, and a post-induction time of 4 h. Applying the whole optimization strategy using all optimal factors improved the target protein content from 6.1% (without optimization) to 13.2%. We further applied the optimized medium and conditions in high cell density cultivation, and determined that the soluble target protein constituted 10.5% of the total protein. Our identification of the economic medium composition, optimal culture conditions, and details of the fermentation process should facilitate the potential application of ALF for further research.

Performance of a Liner-on-Target Injector for Staged Z-Pinch Experiments

NASA Astrophysics Data System (ADS)

Conti, F.; Valenzuela, J. C.; Narkis, J.; Krasheninnikov, I.; Beg, F.; Wessel, F. J.; Ruskov, E.; Rahman, H. U.; McGee, E.

2016-10-01

We present the design and characterization of a compact liner-on-target injector, used in the Staged Z-pinch experiments conducted on the UNR-NTF Zebra Facility. Previous experiments and analysis indicate that high-Z gas liners produce a uniform and efficient implosion on a low-Z target plasma. The liner gas shell is produced by an annular solenoid valve and a converging-diverging nozzle designed to achieve a collimated, supersonic, Mach-5 flow. The on-axis target is produced by a coaxial plasma gun, where a high voltage pulse is applied to ionize neutral gas and accelerate the plasma by the J-> × B-> force. Measurements of the liner and target dynamics, resolved by interferometry in space and time, fast imaging, and collection of the emitted light, are presented. The results are compared to the predictions from Computational Fluid Dynamics and MHD simulations that model the injector. Optimization of the design parameters, for upcoming Staged Z-pinch experiments, will be discussed. Advanced Research Projects Agency - Energy, DE-AR0000569.

Immunotherapy for B-Cell Neoplasms using T Cells expressing Chimeric Antigen Receptors

PubMed Central

Boulassel, Mohamed-Rachid; Galal, Ahmed

2012-01-01

Immunotherapy with T cells expressing chimeric antigen receptors (CAR) is being evaluated as a potential treatment for B-cell neoplasms. In recent clinical trials it has shown promising results. As the number of potential candidate antigens expands, the choice of suitable target antigens becomes more challenging to design studies and to assess optimal efficacy of CAR. Careful evaluation of candidate target antigens is required to ensure that T cells expressing CAR will preferentially kill malignant cells with a minimal toxicity against normal tissues. B cells express specific surface antigens that can theoretically act as targets for CAR design. Although many of these antigens can stimulate effective cellular immune responses in vivo, their implementation in clinical settings remains a challenge. Only targeted B-cell antigens CD19 and CD20 have been tested in clinical trials. This article reviews exploitable B cell surface antigens for CAR design and examines obstacles that could interfere with the identification of potentially useful cellular targets. PMID:23269948

An Explicit Linear Filtering Solution for the Optimization of Guidance Systems with Statistical Inputs

NASA Technical Reports Server (NTRS)

Stewart, Elwood C.

1961-01-01

The determination of optimum filtering characteristics for guidance system design is generally a tedious process which cannot usually be carried out in general terms. In this report a simple explicit solution is given which is applicable to many different types of problems. It is shown to be applicable to problems which involve optimization of constant-coefficient guidance systems and time-varying homing type systems for several stationary and nonstationary inputs. The solution is also applicable to off-design performance, that is, the evaluation of system performance for inputs for which the system was not specifically optimized. The solution is given in generalized form in terms of the minimum theoretical error, the optimum transfer functions, and the optimum transient response. The effects of input signal, contaminating noise, and limitations on the response are included. From the results given, it is possible in an interception problem, for example, to rapidly assess the effects on minimum theoretical error of such factors as target noise and missile acceleration. It is also possible to answer important questions regarding the effect of type of target maneuver on optimum performance.

A novel guidance law using fast terminal sliding mode control with impact angle constraints.

PubMed

Sun, Lianghua; Wang, Weihong; Yi, Ran; Xiong, Shaofeng

2016-09-01

This paper is concerned with the question of, for a missile interception with impact angle constraints, how to design a guidance law. Firstly, missile interception with impact angle constraints is modeled; secondly, a novel guidance law using fast terminal sliding mode control based on extended state observer is proposed to optimize the trajectory and time of interception; finally, for stationary targets, constant velocity targets and maneuvering targets, the guidance law and the stability of the closed loop system is analyzed and the stability of the closed loop system is analyzed, respectively. Simulation results show that when missile and target are on a collision course, the novel guidance law using fast terminal sliding mode control with extended state observer has more optimized trajectory and effectively reduces the time of interception which has a great significance in modern warfare. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A geometrically based method for automated radiosurgery planning.

PubMed

Wagner, T H; Yi, T; Meeks, S L; Bova, F J; Brechner, B L; Chen, Y; Buatti, J M; Friedman, W A; Foote, K D; Bouchet, L G

2000-12-01

A geometrically based method of multiple isocenter linear accelerator radiosurgery treatment planning optimization was developed, based on a target's solid shape. Our method uses an edge detection process to determine the optimal sphere packing arrangement with which to cover the planning target. The sphere packing arrangement is converted into a radiosurgery treatment plan by substituting the isocenter locations and collimator sizes for the spheres. This method is demonstrated on a set of 5 irregularly shaped phantom targets, as well as a set of 10 clinical example cases ranging from simple to very complex in planning difficulty. Using a prototype implementation of the method and standard dosimetric radiosurgery treatment planning tools, feasible treatment plans were developed for each target. The treatment plans generated for the phantom targets showed excellent dose conformity and acceptable dose homogeneity within the target volume. The algorithm was able to generate a radiosurgery plan conforming to the Radiation Therapy Oncology Group (RTOG) guidelines on radiosurgery for every clinical and phantom target examined. This automated planning method can serve as a valuable tool to assist treatment planners in rapidly and consistently designing conformal multiple isocenter radiosurgery treatment plans.

Design of ligand-targeted nanoparticles for enhanced cancer targeting

NASA Astrophysics Data System (ADS)

Stefanick, Jared F.

Ligand-targeted nanoparticles are increasingly used as drug delivery vehicles for cancer therapy, yet have not consistently produced successful clinical outcomes. Although these inconsistencies may arise from differences in disease models and target receptors, nanoparticle design parameters can significantly influence therapeutic efficacy. By employing a multifaceted synthetic strategy to prepare peptide-targeted nanoparticles with high purity, reproducibility, and precisely controlled stoichiometry of functionalities, this work evaluates the roles of polyethylene glycol (PEG) coating, ethylene glycol (EG) peptide-linker length, peptide hydrophilicity, peptide density, and nanoparticle size on tumor targeting in a systematic manner. These parameters were analyzed in multiple disease models by targeting human epidermal growth factor receptor 2 (HER2) in breast cancer and very late antigen-4 (VLA-4) in multiple myeloma to demonstrate the widespread applicability of this approach. By increasing the hydrophilicity of the targeting peptide sequence and simultaneously optimizing the EG peptide-linker length, the in vitro cellular uptake of targeted liposomes was significantly enhanced. Specifically, including a short oligolysine chain adjacent to the targeting peptide sequence effectively increased cellular uptake ~80-fold using an EG6 peptide-linker compared to ~10-fold using an EG45 linker. In vivo, targeted liposomes prepared in a traditional manner lacking the oligolysine chain demonstrated similar biodistribution and tumor uptake to non-targeted liposomes. However, by including the oligolysine chain, targeted liposomes using an EG45 linker significantly improved tumor uptake ~8-fold over non-targeted liposomes, while the use of an EG6 linker decreased tumor accumulation and uptake, owing to differences in cellular uptake kinetics, clearance mechanisms, and binding site barrier effects. To further improve tumor targeting and enhance the selectivity of targeted nanoparticles, a dual-receptor targeted approach was evaluated by targeting multiple cell surface receptors simultaneously. Liposomes functionalized with two distinct peptide antagonists to target VLA-4 and Leukocyte Peyer's Patch Adhesion Molecule-1 (LPAM-1) demonstrated synergistically enhanced cellular uptake by cells overexpressing both target receptors and negligible uptake by cells that do not simultaneously express both receptors, providing a strategy to improve selectivity over conventional single receptor-targeted designs. Taken together, this process of systematic optimization of well-defined nanoparticle drug delivery systems has the potential to improve cancer therapy for a broader patient population.

Thermodynamic Studies for Drug Design and Screening

PubMed Central

Garbett, Nichola C.; Chaires, Jonathan B.

2012-01-01

Introduction A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions. Areas covered This review discusses the information that can be obtained from thermodynamic measurements and how this can be applied to the drug development process. Current approaches for the measurement and optimization of thermodynamic parameters are presented, specifically higher throughput and calorimetric methods. Relevant literature for this review was identified in part by bibliographic searches for the period 2004 – 2011 using the Science Citation Index and PUBMED and the keywords listed below. Expert opinion The most effective drug design and development platform comes from an integrated process utilizing all available information from structural, thermodynamic and biological studies. Continuing evolution in our understanding of the energetic basis of molecular interactions and advances in thermodynamic methods for widespread application are essential to realize the goal of thermodynamically-driven drug design. Comprehensive thermodynamic evaluation is vital early in the drug development process to speed drug development towards an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now matured to provide proven utility in design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design. PMID:22458502

Rational Design of an Ultrasensitive Quorum-Sensing Switch.

PubMed

Zeng, Weiqian; Du, Pei; Lou, Qiuli; Wu, Lili; Zhang, Haoqian M; Lou, Chunbo; Wang, Hongli; Ouyang, Qi

2017-08-18

One of the purposes of synthetic biology is to develop rational methods that accelerate the design of genetic circuits, saving time and effort spent on experiments and providing reliably predictable circuit performance. We applied a reverse engineering approach to design an ultrasensitive transcriptional quorum-sensing switch. We want to explore how systems biology can guide synthetic biology in the choice of specific DNA sequences and their regulatory relations to achieve a targeted function. The workflow comprises network enumeration that achieves the target function robustly, experimental restriction of the obtained candidate networks, global parameter optimization via mathematical analysis, selection and engineering of parts based on these calculations, and finally, circuit construction based on the principles of standardization and modularization. The performance of realized quorum-sensing switches was in good qualitative agreement with the computational predictions. This study provides practical principles for the rational design of genetic circuits with targeted functions.

Multidisciplinary conceptual design optimization of aircraft using a sound-matching-based objective function

NASA Astrophysics Data System (ADS)

Diez, Matteo; Iemma, Umberto

2012-05-01

The article presents a novel approach to include community noise considerations based on sound quality in the Multidisciplinary Conceptual Design Optimization (MCDO) of civil transportation aircraft. The novelty stems from the use of an unconventional objective function, defined as a measure of the difference between the noise emission of the aircraft under analysis and a reference 'weakly annoying' noise, the target sound. The minimization of such a merit factor yields an aircraft concept with a noise signature as close as possible to the given target. The reference sound is one of the outcomes of the European Research Project SEFA (Sound Engineering For Aircraft, VI Framework Programme, 2004-2007), and used here as an external input. The aim of the present work is to address the definition and the inclusion of the sound-matching-based objective function in the MCDO of aircraft.

Computer program for optimal BWR congtrol rod programming

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

Taner, M.S.; Levine, S.H.; Carmody, J.M.

1995-12-31

A fully automated computer program has been developed for designing optimal control rod (CR) patterns for boiling water reactors (BWRs). The new program, called OCTOPUS-3, is based on the OCTOPUS code and employs SIMULATE-3 (Ref. 2) for the analysis. There are three aspects of OCTOPUS-3 that make it successful for use at PECO Energy. It incorporates a new feasibility algorithm that makes the CR design meet all constraints, it has been coupled to a Bourne Shell program 3 to allow the user to run the code interactively without the need for a manual, and it develops a low axial peakmore » to extend the cycle. For PECO Energy Co.`s limericks it increased the energy output by 1 to 2% over the traditional PECO Energy design. The objective of the optimization in OCTOPUS-3 is to approximate a very low axial peaked target power distribution while maintaining criticality, keeping the nodal and assembly peaks below the allowed maximum, and meeting the other constraints. The user-specified input for each exposure point includes: CR groups allowed-to-move, target k{sub eff}, and amount of core flow. The OCTOPUS-3 code uses the CR pattern from the previous step as the initial guess unless indicated otherwise.« less

LED light design method for high contrast and uniform illumination imaging in machine vision.

PubMed

Wu, Xiaojun; Gao, Guangming

2018-03-01

In machine vision, illumination is very critical to determine the complexity of the inspection algorithms. Proper lights can obtain clear and sharp images with the highest contrast and low noise between the interested object and the background, which is conducive to the target being located, measured, or inspected. Contrary to the empirically based trial-and-error convention to select the off-the-shelf LED light in machine vision, an optimization algorithm for LED light design is proposed in this paper. It is composed of the contrast optimization modeling and the uniform illumination technology for non-normal incidence (UINI). The contrast optimization model is built based on the surface reflection characteristics, e.g., the roughness, the reflective index, and light direction, etc., to maximize the contrast between the features of interest and the background. The UINI can keep the uniformity of the optimized lighting by the contrast optimization model. The simulation and experimental results demonstrate that the optimization algorithm is effective and suitable to produce images with the highest contrast and uniformity, which is very inspirational to the design of LED illumination systems in machine vision.

Choosing colors for map display icons using models of visual search.

PubMed

Shive, Joshua; Francis, Gregory

2013-04-01

We show how to choose colors for icons on maps to minimize search time using predictions of a model of visual search. The model analyzes digital images of a search target (an icon on a map) and a search display (the map containing the icon) and predicts search time as a function of target-distractor color distinctiveness and target eccentricity. We parameterized the model using data from a visual search task and performed a series of optimization tasks to test the model's ability to choose colors for icons to minimize search time across icons. Map display designs made by this procedure were tested experimentally. In a follow-up experiment, we examined the model's flexibility to assign colors in novel search situations. The model fits human performance, performs well on the optimization tasks, and can choose colors for icons on maps with novel stimuli to minimize search time without requiring additional model parameter fitting. Models of visual search can suggest color choices that produce search time reductions for display icons. Designers should consider constructing visual search models as a low-cost method of evaluating color assignments.

Taguchi's off line method and Multivariate loss function approach for quality management and optimization of process parameters -A review

NASA Astrophysics Data System (ADS)

Bharti, P. K.; Khan, M. I.; Singh, Harbinder

2010-10-01

Off-line quality control is considered to be an effective approach to improve product quality at a relatively low cost. The Taguchi method is one of the conventional approaches for this purpose. Through this approach, engineers can determine a feasible combination of design parameters such that the variability of a product's response can be reduced and the mean is close to the desired target. The traditional Taguchi method was focused on ensuring good performance at the parameter design stage with one quality characteristic, but most products and processes have multiple quality characteristics. The optimal parameter design minimizes the total quality loss for multiple quality characteristics. Several studies have presented approaches addressing multiple quality characteristics. Most of these papers were concerned with maximizing the parameter combination of signal to noise (SN) ratios. The results reveal the advantages of this approach are that the optimal parameter design is the same as the traditional Taguchi method for the single quality characteristic; the optimal design maximizes the amount of reduction of total quality loss for multiple quality characteristics. This paper presents a literature review on solving multi-response problems in the Taguchi method and its successful implementation in various industries.

Automated optimization of an aspheric light-emitting diode lens for uniform illumination.

PubMed

Luo, Xiaoxia; Liu, Hua; Lu, Zhenwu; Wang, Yao

2011-07-10

In this paper, an automated optimization method in the sequential mode of ZEMAX is proposed in the design of an aspheric lens with uniform illuminance for an LED source. A feedback modification is introduced in the design for the LED extended source. The user-defined merit function is written out by using ZEMAX programming language macros language and, as an example, optimum parameters of an aspheric lens are obtained via running an optimization. The optical simulation results show that the illumination efficiency and uniformity can reach 83% and 90%, respectively, on a target surface of 40 mm diameter and at 60 mm away for a 1×1 mm LED source. © 2011 Optical Society of America

Optimization of chiral structures for microscale propulsion.

PubMed

Keaveny, Eric E; Walker, Shawn W; Shelley, Michael J

2013-02-13

Recent advances in micro- and nanoscale fabrication techniques allow for the construction of rigid, helically shaped microswimmers that can be actuated using applied magnetic fields. These swimmers represent the first steps toward the development of microrobots for targeted drug delivery and minimally invasive surgical procedures. To assess the performance of these devices and improve on their design, we perform shape optimization computations to determine swimmer geometries that maximize speed in the direction of a given applied magnetic torque. We directly assess aspects of swimmer shapes that have been developed in previous experimental studies, including helical propellers with elongated cross sections and attached payloads. From these optimizations, we identify key improvements to existing designs that result in swimming speeds that are 70-470% of their original values.

A software methodology for compiling quantum programs

NASA Astrophysics Data System (ADS)

Häner, Thomas; Steiger, Damian S.; Svore, Krysta; Troyer, Matthias

2018-04-01

Quantum computers promise to transform our notions of computation by offering a completely new paradigm. To achieve scalable quantum computation, optimizing compilers and a corresponding software design flow will be essential. We present a software architecture for compiling quantum programs from a high-level language program to hardware-specific instructions. We describe the necessary layers of abstraction and their differences and similarities to classical layers of a computer-aided design flow. For each layer of the stack, we discuss the underlying methods for compilation and optimization. Our software methodology facilitates more rapid innovation among quantum algorithm designers, quantum hardware engineers, and experimentalists. It enables scalable compilation of complex quantum algorithms and can be targeted to any specific quantum hardware implementation.

Rapid freeze-drying cycle optimization using computer programs developed based on heat and mass transfer models and facilitated by tunable diode laser absorption spectroscopy (TDLAS).

PubMed

Kuu, Wei Y; Nail, Steven L

2009-09-01

Computer programs in FORTRAN were developed to rapidly determine the optimal shelf temperature, T(f), and chamber pressure, P(c), to achieve the shortest primary drying time. The constraint for the optimization is to ensure that the product temperature profile, T(b), is below the target temperature, T(target). Five percent mannitol was chosen as the model formulation. After obtaining the optimal sets of T(f) and P(c), each cycle was assigned with a cycle rank number in terms of the length of drying time. Further optimization was achieved by dividing the drying time into a series of ramping steps for T(f), in a cascading manner (termed the cascading T(f) cycle), to further shorten the cycle time. For the purpose of demonstrating the validity of the optimized T(f) and P(c), four cycles with different predicted lengths of drying time, along with the cascading T(f) cycle, were chosen for experimental cycle runs. Tunable diode laser absorption spectroscopy (TDLAS) was used to continuously measure the sublimation rate. As predicted, maximum product temperatures were controlled slightly below the target temperature of -25 degrees C, and the cascading T(f)-ramping cycle is the most efficient cycle design. In addition, the experimental cycle rank order closely matches with that determined by modeling.

Flume Computer-Aided Design (CAD): Integrated CAD for Microflume Components and Systems

DTIC Science & Technology

2002-04-01

31 3.3: Matching the Mix Ratio (Part B...sizes) will be optimized based on the required flow rates and mixing ratios of the different species. The influence of etch depth is investigated on a...Inhibition Study In this network, the target protein is mixed with protease (i.e. enzyme that cleaves the target protein) and the protease inhibitor (the

Efforts towards the optimization of a bi-aryl class of potent IRAK4 inhibitors

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

Hanisak, Jennifer; Seganish, W. Michael; McElroy, William T.

2016-09-01

IRAK4 has been identified as potential therapeutic target for inflammatory and autoimmune diseases. Herein we report the identification and initial SAR studies of a new class of pyrazole containing IRAK4 inhibitors designed to expand chemical diversity and improve off target activity of a previously identified series. These compounds maintain potent IRAK4 activity and desirable ligand efficiency. Rat clearance and a variety of off target activities were also examined, resulting in encouraging data with tractable SAR.

Statistical controversies in clinical research: requiem for the 3 + 3 design for phase I trials.

PubMed

Paoletti, X; Ezzalfani, M; Le Tourneau, C

2015-09-01

More than 95% of published phase I trials have used the 3 + 3 design to identify the dose to be recommended for phase II trials. However, the statistical community agrees on the limitations of the 3 + 3 design compared with model-based approaches. Moreover, the mechanisms of action of targeted agents strongly challenge the hypothesis that the maximum tolerated dose constitutes the optimal dose, and more outcomes including clinical and biological activity increasingly need to be taken into account to identify the optimal dose. We review key elements from clinical publications and from the statistical literature to show that the 3 + 3 design lacks the necessary flexibility to address the challenges of targeted agents. The design issues raised by expansion cohorts, new definitions of dose-limiting toxicity and trials of combinations are not easily addressed by the 3 + 3 design or its extensions. Alternative statistical proposals have been developed to make a better use of the complex data generated by phase I trials. Their applications require a close collaboration between all actors of early phase clinical trials. © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Optimal mission planning of GEO on-orbit refueling in mixed strategy

NASA Astrophysics Data System (ADS)

Chen, Xiao-qian; Yu, Jing

2017-04-01

The mission planning of GEO on-orbit refueling (OOR) in Mixed strategy is studied in this paper. Specifically, one SSc will be launched to an orbital slot near the depot when multiple GEO satellites are reaching their end of lives. The SSc replenishes fuel from the depot and then extends the lifespan of the target satellites via refueling. In the mixed scenario, only some of the target satellites could be served by the SSc, and the remaining ones will be fueled by Pseudo SScs (the target satellite which has already been refueled by the SSc and now has sufficient fuel for its operation as well as the fuel to refuel other target satellites is called Pseudo SSc here). The mission sequences and fuel mass of the SSc and Pseudo SScs, the dry mass of the SSc are used as design variables, whereas the economic benefit of the whole mission is used as design objective. The economic cost and benefit models are stated first, and then a mathematical optimization model is proposed. A comprehensive solution method involving enumeration, particle swarm optimization and modification is developed. Numerical examples are carried out to demonstrate the effectiveness of the model and solution method. Economic efficiencies of different OOR strategies are compared and discussed. The mixed strategy would perform better than the other strategies only when the target satellites satisfy some conditions. This paper presents an available mixed strategy scheme for users and analyzes its advantages and disadvantages by comparing with some other OOR strategies, providing helpful references to decision makers. The best strategy in practical applications depends on the specific demands and user preference.

Genetic evolutionary taboo search for optimal marker placement in infrared patient setup

NASA Astrophysics Data System (ADS)

Riboldi, M.; Baroni, G.; Spadea, M. F.; Tagaste, B.; Garibaldi, C.; Cambria, R.; Orecchia, R.; Pedotti, A.

2007-09-01

In infrared patient setup adequate selection of the external fiducial configuration is required for compensating inner target displacements (target registration error, TRE). Genetic algorithms (GA) and taboo search (TS) were applied in a newly designed approach to optimal marker placement: the genetic evolutionary taboo search (GETS) algorithm. In the GETS paradigm, multiple solutions are simultaneously tested in a stochastic evolutionary scheme, where taboo-based decision making and adaptive memory guide the optimization process. The GETS algorithm was tested on a group of ten prostate patients, to be compared to standard optimization and to randomly selected configurations. The changes in the optimal marker configuration, when TRE is minimized for OARs, were specifically examined. Optimal GETS configurations ensured a 26.5% mean decrease in the TRE value, versus 19.4% for conventional quasi-Newton optimization. Common features in GETS marker configurations were highlighted in the dataset of ten patients, even when multiple runs of the stochastic algorithm were performed. Including OARs in TRE minimization did not considerably affect the spatial distribution of GETS marker configurations. In conclusion, the GETS algorithm proved to be highly effective in solving the optimal marker placement problem. Further work is needed to embed site-specific deformation models in the optimization process.

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

PubMed

Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

2016-01-01

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation

PubMed Central

Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

2016-01-01

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality. PMID:26954783

Multiobjective generalized extremal optimization algorithm for simulation of daylight illuminants

NASA Astrophysics Data System (ADS)

Kumar, Srividya Ravindra; Kurian, Ciji Pearl; Gomes-Borges, Marcos Eduardo

2017-10-01

Daylight illuminants are widely used as references for color quality testing and optical vision testing applications. Presently used daylight simulators make use of fluorescent bulbs that are not tunable and occupy more space inside the quality testing chambers. By designing a spectrally tunable LED light source with an optimal number of LEDs, cost, space, and energy can be saved. This paper describes an application of the generalized extremal optimization (GEO) algorithm for selection of the appropriate quantity and quality of LEDs that compose the light source. The multiobjective approach of this algorithm tries to get the best spectral simulation with minimum fitness error toward the target spectrum, correlated color temperature (CCT) the same as the target spectrum, high color rendering index (CRI), and luminous flux as required for testing applications. GEO is a global search algorithm based on phenomena of natural evolution and is especially designed to be used in complex optimization problems. Several simulations have been conducted to validate the performance of the algorithm. The methodology applied to model the LEDs, together with the theoretical basis for CCT and CRI calculation, is presented in this paper. A comparative result analysis of M-GEO evolutionary algorithm with the Levenberg-Marquardt conventional deterministic algorithm is also presented.

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

DOE PAGES

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...

2014-10-23

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

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

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

Learning optimal embedded cascades.

PubMed

Saberian, Mohammad Javad; Vasconcelos, Nuno

2012-10-01

The problem of automatic and optimal design of embedded object detector cascades is considered. Two main challenges are identified: optimization of the cascade configuration and optimization of individual cascade stages, so as to achieve the best tradeoff between classification accuracy and speed, under a detection rate constraint. Two novel boosting algorithms are proposed to address these problems. The first, RCBoost, formulates boosting as a constrained optimization problem which is solved with a barrier penalty method. The constraint is the target detection rate, which is met at all iterations of the boosting process. This enables the design of embedded cascades of known configuration without extensive cross validation or heuristics. The second, ECBoost, searches over cascade configurations to achieve the optimal tradeoff between classification risk and speed. The two algorithms are combined into an overall boosting procedure, RCECBoost, which optimizes both the cascade configuration and its stages under a detection rate constraint, in a fully automated manner. Extensive experiments in face, car, pedestrian, and panda detection show that the resulting detectors achieve an accuracy versus speed tradeoff superior to those of previous methods.

PhylArray: phylogenetic probe design algorithm for microarray.

PubMed

Militon, Cécile; Rimour, Sébastien; Missaoui, Mohieddine; Biderre, Corinne; Barra, Vincent; Hill, David; Moné, Anne; Gagne, Geneviève; Meier, Harald; Peyretaillade, Eric; Peyret, Pierre

2007-10-01

Microbial diversity is still largely unknown in most environments, such as soils. In order to get access to this microbial 'black-box', the development of powerful tools such as microarrays are necessary. However, the reliability of this approach relies on probe efficiency, in particular sensitivity, specificity and explorative power, in order to obtain an image of the microbial communities that is close to reality. We propose a new probe design algorithm that is able to select microarray probes targeting SSU rRNA at any phylogenetic level. This original approach, implemented in a program called 'PhylArray', designs a combination of degenerate and non-degenerate probes for each target taxon. Comparative experimental evaluations indicate that probes designed with PhylArray yield a higher sensitivity and specificity than those designed by conventional approaches. Applying the combined PhyArray/GoArrays strategy helps to optimize the hybridization performance of short probes. Finally, hybridizations with environmental targets have shown that the use of the PhylArray strategy can draw attention to even previously unknown bacteria.

Designing Isoform-selective Inhibitors Against Classical HDACs for Effective Anticancer Therapy: Insight and Perspectives from In Silico.

PubMed

Ganai, Shabir Ahmad

2018-01-01

Histone deacetylase inhibitors, the small molecules modulating the biological activity of histone deacetylases are emerging as potent chemotherapeutic agents. Despite their considerable therapeutic benefits in disease models, the lack of isoform specificity culminates in debilitating off target effects, raising serious concerns regarding their applicability. This emphasizes the pressing and unmet medical need of designing isoform selective inhibitors for safe and effective anticancer therapy. Keeping these grim facts in view, the current article sheds light on structural basis of off-targeting. Furthermore, the article discusses extensively the role of in silico strategies such as Molecular Docking, Molecular Dynamics Simulation and Energetically-optimized structure based pharmacophore approach in designing on-target inhibitors against classical HDACs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Optimal design of reflectometer density profile measurements using a radar systems approach (invited) (abstract)

NASA Astrophysics Data System (ADS)

Doyle, E. J.; Kim, K. W.; Peebles, W. A.; Rhodes, T. L.

1997-01-01

Reflectometry is an attractive and versatile diagnostic technique that can address a wide range of measurement needs on fusion devices. However, progress in the area of profile measurement has been hampered by the lack of a well-understood basis for the optimum design and implementation of such systems. Such a design basis is provided by the realization that reflectometer systems utilized for density profile measurements are in fact specialized forms of radar systems. In this article five criteria are introduced by which reflectometer systems can be systematically designed for optimal performance: range resolution, spatial sampling, turbulence immunity, bandwidth optimization, and the need for adaptive data processing. Many of these criteria are familiar from radar systems analysis, and are applicable to reflectometry after allowance is made for differences stemming from the nature of the plasma target. These criteria are utilized to critically evaluate current reflectometer density profile techniques and indicate improvements that can impact current and next step devices, such as ITER.

Optimizing the physical ergonomics indices for the use of partial pressure suits.

PubMed

Ding, Li; Li, Xianxue; Hedge, Alan; Hu, Huimin; Feathers, David; Qin, Zhifeng; Xiao, Huajun; Xue, Lihao; Zhou, Qianxiang

2015-03-01

This study developed an ergonomic evaluation system for the design of high-altitude partial pressure suits (PPSs). A total of twenty-one Chinese males participated in the experiment which tested three types of ergonomics indices (manipulative mission, operational reach and operational strength) were studied using a three-dimensional video-based motion capture system, a target-pointing board, a hand dynamometer, and a step-tread apparatus. In total, 36 ergonomics indices were evaluated and optimized using regression and fitting analysis. Some indices that were found to be linearly related and redundant were removed from the study. An optimal ergonomics index system was established that can be used to conveniently and quickly evaluate the performance of different pressurized/non-pressurized suit designs. The resulting ergonomics index system will provide a theoretical basis and practical guidance for mission planners, suit designers and engineers to design equipment for human use, and to aid in assessing partial pressure suits. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Design and Optimization of Multi-Pixel Transition-Edge Sensors for X-Ray Astronomy Applications

NASA Technical Reports Server (NTRS)

Smith, Stephen J.; Adams, Joseph S.; Bandler, Simon R.; Chervenak, James A.; Datesman, Aaron Michael; Eckart, Megan E.; Ewin, Audrey J.; Finkbeiner, Fred M.; Kelley, Richard L.; Kilbourne, Caroline A.;

Designing with non-linear viscoelastic fluids

NASA Astrophysics Data System (ADS)

Schuh, Jonathon; Lee, Yong Hoon; Allison, James; Ewoldt, Randy

2017-11-01

Material design is typically limited to hard materials or simple fluids; however, design with more complex materials can provide ways to enhance performance. Using the Criminale-Ericksen-Filbey (CEF) constitutive model in the thin film lubrication limit, we derive a modified Reynolds Equation (based on asymptotic analysis) that includes shear thinning, first normal stress, and terminal regime viscoelastic effects. This allows for designing non-linear viscoelastic fluids in thin-film creeping flow scenarios, i.e. optimizing the shape of rheological material properties to achieve different design objectives. We solve the modified Reynolds equation using the pseudo-spectral method, and describe a case study in full-film lubricated sliding where optimal fluid properties are identified. These material-agnostic property targets can then guide formulation of complex fluids which may use polymeric, colloidal, or other creative approaches to achieve the desired non-Newtonian properties.

Fragment-based design of kinase inhibitors: a practical guide.

PubMed

Erickson, Jon A

2015-01-01

Fragment-based drug design has become an important strategy for drug design and development over the last decade. It has been used with particular success in the development of kinase inhibitors, which are one of the most widely explored classes of drug targets today. The application of fragment-based methods to discovering and optimizing kinase inhibitors can be a complicated and daunting task; however, a general process has emerged that has been highly fruitful. Here a practical outline of the fragment process used in kinase inhibitor design and development is laid out with specific examples. A guide to the overall process from initial discovery through fragment screening, including the difficulties in detection, to the computational methods available for use in optimization of the discovered fragments is reported.

"Off-Spotter": very fast and exhaustive enumeration of genomic lookalikes for designing CRISPR/Cas guide RNAs.

PubMed

Pliatsika, Venetia; Rigoutsos, Isidore

2015-01-29

CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated nucleases) is a powerful component of the prokaryotic immune system that has been adapted for targeted genetic engineering in higher organisms. A key element of CRISPR/Cas is the "guide" RNA (gRNA) that is ~20 nucleotides (nts) in length and designed to be complementary to the intended target site. An integral requirement of the CRISPR/Cas system is that the target site be followed by a protospacer adjacent motif (PAM). Care needs to be exercised during gRNA design to avoid unintended ("off-target") interactions. We designed and implemented the Off-Spotter algorithm to assist with the design of optimal gRNAs. When presented with a candidate gRNA sequence and a PAM, Off-Spotter quickly and exhaustively identifies all genomic sites that satisfy the PAM constraint and are identical or nearly-identical to the provided gRNA. Off-Spotter achieves its extreme performance through purely algorithmic means and not through hardware accelerators such as graphical processing units (GPUs). Off-Spotter also allows the user to identify on-the-fly how many and which nucleotides of the gRNA comprise the "seed". Off-Spotter's output includes a histogram showing the number of potential off-targets as a function of the number of mismatches. The output also includes for each potential off-target the site's genomic location, a human genome browser hyperlink to the corresponding location, genomic annotation in the vicinity of the off-target, GC content, etc. Off-Spotter is very fast and flexible and can help in the design of optimal gRNAs by providing several PAM choices, a run-time definition of the seed and of the allowed number of mismatches, and a flexible output interface that allows sorting of the results, optional viewing/hiding of columns, etc. A key element of Off-Spotter is that it does not have a rigid definition of the seed: instead, the user can declare both the seed's location and extent on-the-fly. We expect that this flexibility in combination with Off-Spotter's speed and richly annotated output will enable experimenters to interactively and quickly explore different scenarios and gRNA possibilities.

Targeting legume loci: A comparison of three methods for target enrichment bait design in Leguminosae phylogenomics.

PubMed

Vatanparast, Mohammad; Powell, Adrian; Doyle, Jeff J; Egan, Ashley N

2018-03-01

The development of pipelines for locus discovery has spurred the use of target enrichment for plant phylogenomics. However, few studies have compared pipelines from locus discovery and bait design, through validation, to tree inference. We compared three methods within Leguminosae (Fabaceae) and present a workflow for future efforts. Using 30 transcriptomes, we compared Hyb-Seq, MarkerMiner, and the Yang and Smith (Y&S) pipelines for locus discovery, validated 7501 baits targeting 507 loci across 25 genera via Illumina sequencing, and inferred gene and species trees via concatenation- and coalescent-based methods. Hyb-Seq discovered loci with the longest mean length. MarkerMiner discovered the most conserved loci with the least flagged as paralogous. Y&S offered the most parsimony-informative sites and putative orthologs. Target recovery averaged 93% across taxa. We optimized our targeted locus set based on a workflow designed to minimize paralog/ortholog conflation and thus present 423 loci for legume phylogenomics. Methods differed across criteria important for phylogenetic marker development. We recommend Hyb-Seq as a method that may be useful for most phylogenomic projects. Our targeted locus set is a resource for future, community-driven efforts to reconstruct the legume tree of life.

High speed civil transport aerodynamic optimization

NASA Technical Reports Server (NTRS)

Ryan, James S.

1994-01-01

This is a report of work in support of the Computational Aerosciences (CAS) element of the Federal HPCC program. Specifically, CFD and aerodynamic optimization are being performed on parallel computers. The long-range goal of this work is to facilitate teraflops-rate multidisciplinary optimization of aerospace vehicles. This year's work is targeted for application to the High Speed Civil Transport (HSCT), one of four CAS grand challenges identified in the HPCC FY 1995 Blue Book. This vehicle is to be a passenger aircraft, with the promise of cutting overseas flight time by more than half. To meet fuel economy, operational costs, environmental impact, noise production, and range requirements, improved design tools are required, and these tools must eventually integrate optimization, external aerodynamics, propulsion, structures, heat transfer, controls, and perhaps other disciplines. The fundamental goal of this project is to contribute to improved design tools for U.S. industry, and thus to the nation's economic competitiveness.

Design of an optimal preview controller for linear discrete-time descriptor systems with state delay

NASA Astrophysics Data System (ADS)

Cao, Mengjuan; Liao, Fucheng

2015-04-01

In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.

Multi-objective Optimization Strategies Using Adjoint Method and Game Theory in Aerodynamics

NASA Astrophysics Data System (ADS)

Tang, Zhili

2006-08-01

There are currently three different game strategies originated in economics: (1) Cooperative games (Pareto front), (2) Competitive games (Nash game) and (3) Hierarchical games (Stackelberg game). Each game achieves different equilibria with different performance, and their players play different roles in the games. Here, we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multi-criteria aerodynamic optimization problems. The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments. We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method. The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front. Non-dominated Pareto front solutions are obtained, however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.

RchyOptimyx: Cellular Hierarchy Optimization for Flow Cytometry

PubMed Central

Aghaeepour, Nima; Jalali, Adrin; O’Neill, Kieran; Chattopadhyay, Pratip K.; Roederer, Mario; Hoos, Holger H.; Brinkman, Ryan R.

2013-01-01

Analysis of high-dimensional flow cytometry datasets can reveal novel cell populations with poorly understood biology. Following discovery, characterization of these populations in terms of the critical markers involved is an important step, as this can help to both better understand the biology of these populations and aid in designing simpler marker panels to identify them on simpler instruments and with fewer reagents (i.e., in resource poor or highly regulated clinical settings). However, current tools to design panels based on the biological characteristics of the target cell populations work exclusively based on technical parameters (e.g., instrument configurations, spectral overlap, and reagent availability). To address this shortcoming, we developed RchyOptimyx (cellular hieraRCHY OPTIMization), a computational tool that constructs cellular hierarchies by combining automated gating with dynamic programming and graph theory to provide the best gating strategies to identify a target population to a desired level of purity or correlation with a clinical outcome, using the simplest possible marker panels. RchyOptimyx can assess and graphically present the trade-offs between marker choice and population specificity in high-dimensional flow or mass cytometry datasets. We present three proof-of-concept use cases for RchyOptimyx that involve 1) designing a panel of surface markers for identification of rare populations that are primarily characterized using their intracellular signature; 2) simplifying the gating strategy for identification of a target cell population; 3) identification of a non-redundant marker set to identify a target cell population. PMID:23044634

Crispr-mediated Gene Targeting of Human Induced Pluripotent Stem Cells.

PubMed

Byrne, Susan M; Church, George M

2015-01-01

CRISPR/Cas9 nuclease systems can create double-stranded DNA breaks at specific sequences to efficiently and precisely disrupt, excise, mutate, insert, or replace genes. However, human embryonic stem or induced pluripotent stem cells (iPSCs) are more difficult to transfect and less resilient to DNA damage than immortalized tumor cell lines. Here, we describe an optimized protocol for genome engineering of human iPSCs using a simple transient transfection of plasmids and/or single-stranded oligonucleotides. With this protocol, we achieve transfection efficiencies greater than 60%, with gene disruption efficiencies from 1-25% and gene insertion/replacement efficiencies from 0.5-10% without any further selection or enrichment steps. We also describe how to design and assess optimal sgRNA target sites and donor targeting vectors; cloning individual iPSC by single cell FACS sorting, and genotyping successfully edited cells.

Optimal Incentives for Public Sector Workers: The Case of Teacher-Designed Incentive Pay in Texas. Working Paper 2009-05

ERIC Educational Resources Information Center

Taylor, Lori L.; Springer, Matthew G.

2009-01-01

Pay for performance is a popular public education reform, and millions of dollars are currently being targeted for pay for performance programs. These reforms are popular because economic and management theories suggest that well-designed incentive pay programs could improve teacher effectiveness. There is little evidence about the characteristics…

Evolutionary engineering for industrial microbiology.

PubMed

Vanee, Niti; Fisher, Adam B; Fong, Stephen S

2012-01-01

Superficially, evolutionary engineering is a paradoxical field that balances competing interests. In natural settings, evolution iteratively selects and enriches subpopulations that are best adapted to a particular ecological niche using random processes such as genetic mutation. In engineering desired approaches utilize rational prospective design to address targeted problems. When considering details of evolutionary and engineering processes, more commonality can be found. Engineering relies on detailed knowledge of the problem parameters and design properties in order to predict design outcomes that would be an optimized solution. When detailed knowledge of a system is lacking, engineers often employ algorithmic search strategies to identify empirical solutions. Evolution epitomizes this iterative optimization by continuously diversifying design options from a parental design, and then selecting the progeny designs that represent satisfactory solutions. In this chapter, the technique of applying the natural principles of evolution to engineer microbes for industrial applications is discussed to highlight the challenges and principles of evolutionary engineering.

Candidate molten salt investigation for an accelerator driven subcritical core

NASA Astrophysics Data System (ADS)

Sooby, E.; Baty, A.; Beneš, O.; McIntyre, P.; Pogue, N.; Salanne, M.; Sattarov, A.

2013-09-01

We report a design for accelerator-driven subcritical fission in a molten salt core (ADSMS) that utilizes a fuel salt composed of NaCl and transuranic (TRU) chlorides. The ADSMS core is designed for fast neutronics (28% of neutrons >1 MeV) to optimize TRU destruction. The choice of a NaCl-based salt offers benefits for corrosion, operating temperature, and actinide solubility as compared with LiF-based fuel salts. A molecular dynamics (MD) code has been used to estimate properties of the molten salt system which are important for ADSMS design but have never been measured experimentally. Results from the MD studies are reported. Experimental measurements of fuel salt properties and studies of corrosion and radiation damage on candidate metals for the core vessel are anticipated. A special thanks is due to Prof. Paul Madden for introducing the ADSMS group to the concept of using the molten salt as the spallation target, rather than a conventional heavy metal spallation target. This feature helps to optimize this core as a Pu/TRU burner.

Optical Quality, Threshold Target Identification, and Military Target Task Performance After Advanced Keratorefractive Surgery

DTIC Science & Technology

2011-05-01

WFG) photorefractive keratectomy (PRK), WFG laser in situ keratomileusis ( LASIK ), wavefront optimized (WFO) PRK or WFO LASIK (56 in each group...design will enable comparison to preoperative performance as well as comparisons between treatment groups. Military, Refractive Surgery, PRK, LASIK ...randomized treatment trial we will enroll 224 nearsighted soldiers to WFG photorefractive keratectomy (PRK), WFG LASIK , WFO PRK or WFO LASIK (56 in

Mathematical modeling of vesicle drug delivery systems 2: targeted vesicle interactions with cells, tumors, and the body.

PubMed

Ying, Chong T; Wang, Juntian; Lamm, Robert J; Kamei, Daniel T

2013-02-01

Vesicles have been studied for several years in their ability to deliver drugs. Mathematical models have much potential in reducing time and resources required to engineer optimal vesicles, and this review article summarizes these models that aid in understanding the ability of targeted vesicles to bind and internalize into cancer cells, diffuse into tumors, and distribute in the body. With regard to binding and internalization, radiolabeling and surface plasmon resonance experiments can be performed to determine optimal vesicle size and the number and type of ligands conjugated. Binding and internalization properties are also inputs into a mathematical model of vesicle diffusion into tumor spheroids, which highlights the importance of the vesicle diffusion coefficient and the binding affinity of the targeting ligand. Biodistribution of vesicles in the body, along with their half-life, can be predicted with compartmental models for pharmacokinetics that include the effect of targeting ligands, and these predictions can be used in conjunction with in vivo models to aid in the design of drug carriers. Mathematical models can prove to be very useful in drug carrier design, and our hope is that this review will encourage more investigators to combine modeling with quantitative experimentation in the field of vesicle-based drug delivery.

Instrument Design Optimization With Computational Methods

NASA Astrophysics Data System (ADS)

Moore, Michael H.

Using Finite Element Analysis to approximate the solution of differential equations, two different instruments in experimental Hall C at the Thomas Jefferson National Accelerator Facility are analyzed. The time dependence of density fluctuations from the liquid hydrogen (LH2) target used in the Qweak experiment (2011-2012) are studied with Computational Fluid Dynamics (CFD) and the simulation results compared to data from the experiment. The 2.5 kW liquid hydrogen target was the highest power LH2 target in the world and the first to be designed with CFD at Jefferson Lab. The first complete magnetic field simulation of the Super High Momentum Spectrometer (SHMS) is presented with a focus on primary electron beam deflection downstream of the target. The SHMS consists of a superconducting horizontal bending magnet (HB) and three superconducting quadrupole magnets. The HB allows particles scattered at an angle of 5.5° to the beam line to be steered into the quadrupole magnets which make up the optics of the spectrometer. Without mitigation, remnant fields from the SHMS may steer the unscattered beam outside of the acceptable envelope on the beam dump and limit beam operations at small scattering angles. A solution is proposed using optimal placement of a minimal amount of shielding iron around the beam line.

Instrument design optimization with computational methods

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

Moore, Michael H.

Using Finite Element Analysis to approximate the solution of differential equations, two different instruments in experimental Hall C at the Thomas Jefferson National Accelerator Facility are analyzed. The time dependence of density uctuations from the liquid hydrogen (LH2) target used in the Q weak experiment (2011-2012) are studied with Computational Fluid Dynamics (CFD) and the simulation results compared to data from the experiment. The 2.5 kW liquid hydrogen target was the highest power LH2 target in the world and the first to be designed with CFD at Jefferson Lab. The first complete magnetic field simulation of the Super High Momentummore » Spectrometer (SHMS) is presented with a focus on primary electron beam deflection downstream of the target. The SHMS consists of a superconducting horizontal bending magnet (HB) and three superconducting quadrupole magnets. The HB allows particles scattered at an angle of 5:5 deg to the beam line to be steered into the quadrupole magnets which make up the optics of the spectrometer. Without mitigation, remnant fields from the SHMS may steer the unscattered beam outside of the acceptable envelope on the beam dump and limit beam operations at small scattering angles. A solution is proposed using optimal placement of a minimal amount of shielding iron around the beam line.« less

A nested array of rRNA targeted probes for the detection and identification of enterococci by reverse hybridization.

PubMed

Behr, T; Koob, C; Schedl, M; Mehlen, A; Meier, H; Knopp, D; Frahm, E; Obst, U; Schleifer, K; Niessner, R; Ludwig, W

2000-12-01

Complete 23S and almost complete 16S rRNA gene sequences were determined for the type strains of the validly described Enterococcus species, Melissococcus pluton and Tetragenococcus halophilus. A comprehensive set of rRNA targeted specific oligonucleotide hybridization probes was designed according to the multiple probe concept. In silico probe design and evaluation was performed using the respective tools of the ARB program package in combination with the ARB databases comprising the currently available 16S as well as 23S rRNA primary structures. The probes were optimized with respect to their application for reverse hybridization in microplate format. The target comprising 16S and 23S rDNA was amplified and labeled by PCR (polymerase chain reaction) using general primers targeting a wide spectrum of bacteria. Alternatively, amplification of two adjacent rDNA fragments of enterococci was performed by using specific primers. In vitro evaluation of the probe set was done including all Enterococcus type strains, and a selection of other representatives of the gram-positive bacteria with a low genomic DNA G+C content. The optimized probe set was used to analyze enriched drinking water samples as well as original samples from waste water treatment plants.

Optimization of Perovskite Gas Sensor Performance: Characterization, Measurement and Experimental Design.

PubMed

Bertocci, Francesco; Fort, Ada; Vignoli, Valerio; Mugnaini, Marco; Berni, Rossella

2017-06-10

Eight different types of nanostructured perovskites based on YCoO 3 with different chemical compositions are prepared as gas sensor materials, and they are studied with two target gases NO 2 and CO. Moreover, a statistical approach is adopted to optimize their performance. The innovative contribution is carried out through a split-plot design planning and modeling, also involving random effects, for studying Metal Oxide Semiconductors (MOX) sensors in a robust design context. The statistical results prove the validity of the proposed approach; in fact, for each material type, the variation of the electrical resistance achieves a satisfactory optimized value conditional to the working temperature and by controlling for the gas concentration variability. Just to mention some results, the sensing material YCo 0 . 9 Pd 0 . 1 O 3 (Mt1) achieved excellent solutions during the optimization procedure. In particular, Mt1 resulted in being useful and feasible for the detection of both gases, with optimal response equal to +10.23% and working temperature at 312 ∘ C for CO (284 ppm, from design) and response equal to -14.17% at 185 ∘ C for NO 2 (16 ppm, from design). Analogously, for NO 2 (16 ppm, from design), the material type YCo 0 . 9 O 2 . 85 + 1 % Pd (Mt8) allows for optimizing the response value at - 15 . 39 % with a working temperature at 181 . 0 ∘ C, whereas for YCo 0 . 95 Pd 0 . 05 O 3 (Mt3), the best response value is achieved at - 15 . 40 % with the temperature equal to 204 ∘ C.

Optimization of Perovskite Gas Sensor Performance: Characterization, Measurement and Experimental Design

PubMed Central

Bertocci, Francesco; Fort, Ada; Vignoli, Valerio; Mugnaini, Marco; Berni, Rossella

2017-01-01

Eight different types of nanostructured perovskites based on YCoO3 with different chemical compositions are prepared as gas sensor materials, and they are studied with two target gases NO2 and CO. Moreover, a statistical approach is adopted to optimize their performance. The innovative contribution is carried out through a split-plot design planning and modeling, also involving random effects, for studying Metal Oxide Semiconductors (MOX) sensors in a robust design context. The statistical results prove the validity of the proposed approach; in fact, for each material type, the variation of the electrical resistance achieves a satisfactory optimized value conditional to the working temperature and by controlling for the gas concentration variability. Just to mention some results, the sensing material YCo0.9Pd0.1O3 (Mt1) achieved excellent solutions during the optimization procedure. In particular, Mt1 resulted in being useful and feasible for the detection of both gases, with optimal response equal to +10.23% and working temperature at 312∘C for CO (284 ppm, from design) and response equal to −14.17% at 185∘C for NO2 (16 ppm, from design). Analogously, for NO2 (16 ppm, from design), the material type YCo0.9O2.85+1%Pd (Mt8) allows for optimizing the response value at −15.39% with a working temperature at 181.0∘C, whereas for YCo0.95Pd0.05O3 (Mt3), the best response value is achieved at −15.40% with the temperature equal to 204∘C. PMID:28604587

MSP-HTPrimer: a high-throughput primer design tool to improve assay design for DNA methylation analysis in epigenetics.

PubMed

Pandey, Ram Vinay; Pulverer, Walter; Kallmeyer, Rainer; Beikircher, Gabriel; Pabinger, Stephan; Kriegner, Albert; Weinhäusel, Andreas

2016-01-01

Bisulfite (BS) conversion-based and methylation-sensitive restriction enzyme (MSRE)-based PCR methods have been the most commonly used techniques for locus-specific DNA methylation analysis. However, both methods have advantages and limitations. Thus, an integrated approach would be extremely useful to quantify the DNA methylation status successfully with great sensitivity and specificity. Designing specific and optimized primers for target regions is the most critical and challenging step in obtaining the adequate DNA methylation results using PCR-based methods. Currently, no integrated, optimized, and high-throughput methylation-specific primer design software methods are available for both BS- and MSRE-based methods. Therefore an integrated, powerful, and easy-to-use methylation-specific primer design pipeline with great accuracy and success rate will be very useful. We have developed a new web-based pipeline, called MSP-HTPrimer, to design primers pairs for MSP, BSP, pyrosequencing, COBRA, and MSRE assays on both genomic strands. First, our pipeline converts all target sequences into bisulfite-treated templates for both forward and reverse strand and designs all possible primer pairs, followed by filtering for single nucleotide polymorphisms (SNPs) and known repeat regions. Next, each primer pairs are annotated with the upstream and downstream RefSeq genes, CpG island, and cut sites (for COBRA and MSRE). Finally, MSP-HTPrimer selects specific primers from both strands based on custom and user-defined hierarchical selection criteria. MSP-HTPrimer produces a primer pair summary output table in TXT and HTML format for display and UCSC custom tracks for resulting primer pairs in GTF format. MSP-HTPrimer is an integrated, web-based, and high-throughput pipeline and has no limitation on the number and size of target sequences and designs MSP, BSP, pyrosequencing, COBRA, and MSRE assays. It is the only pipeline, which automatically designs primers on both genomic strands to increase the success rate. It is a standalone web-based pipeline, which is fully configured within a virtual machine and thus can be readily used without any configuration. We have experimentally validated primer pairs designed by our pipeline and shown a very high success rate of primer pairs: out of 66 BSP primer pairs, 63 were successfully validated without any further optimization step and using the same qPCR conditions. The MSP-HTPrimer pipeline is freely available from http://sourceforge.net/p/msp-htprimer.

Self-adaptive multi-objective harmony search for optimal design of water distribution networks

NASA Astrophysics Data System (ADS)

Choi, Young Hwan; Lee, Ho Min; Yoo, Do Guen; Kim, Joong Hoon

2017-11-01

In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.

Adaptable setups for magnetic drug targeting in human muscular arteries: Design and implementation

NASA Astrophysics Data System (ADS)

Hajiaghajani, Amirhossein; Hashemi, Soheil; Abdolali, Ali

2017-09-01

Magnetic drug targeting has been used to steer magnetic therapeutic agents and has received much attention for capillaries and human brain arteries. In this paper, we focus on noninvasive targeting of nanoparticles in muscular arteries, in where the vessel diameter and blood flow are much challengingly higher than brain capillaries. We aim to design a low intensity magnetic field which avoids potential side effects on blood cells while steers particles with high targeting rate. The setup design procedure is considerably flexible to be used in a wide variety of large vessels. Using particle tracing, a new method is proposed to connect the geometry of the vessel under the action of targeting to the required magnetic force. Specifications of the coil which is placed outside the body are derived based on this required force. Mutual effects of coil dimensions on the produced magnetic force are elaborated and summarized in a design flowchart to be used for arbitrary muscular vessel sizes. The performance of the optimized coil is validated by in vitro experiments and it is shown that particles are steered with the average efficiency of 80.2% for various conditions.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Concerning the electrosynthesis of hydrogen peroxide and peroxodisulfates. Section 2: Optimization of electrolysis cells using an electrolyzer for peroxodisulfuric acid as an example

NASA Technical Reports Server (NTRS)

Schleiff, M.; Thiele, W.; Matschiner, H.

1986-01-01

The model is presented of an electrolyzer for peroxodisulfuric acid, and it is analyzed mathematically. Its application for engineering and economic optimization is investigated in detail. The mathematical analysis leads to conclusions concerning the change in position of the optimum with respect to the various target functions due to changes of the individual design-caused and economic parameters.

Application of mathematical model methods for optimization tasks in construction materials technology

NASA Astrophysics Data System (ADS)

Fomina, E. V.; Kozhukhova, N. I.; Sverguzova, S. V.; Fomin, A. E.

2018-05-01

In this paper, the regression equations method for design of construction material was studied. Regression and polynomial equations representing the correlation between the studied parameters were proposed. The logic design and software interface of the regression equations method focused on parameter optimization to provide the energy saving effect at the stage of autoclave aerated concrete design considering the replacement of traditionally used quartz sand by coal mining by-product such as argillite. The mathematical model represented by a quadric polynomial for the design of experiment was obtained using calculated and experimental data. This allowed the estimation of relationship between the composition and final properties of the aerated concrete. The surface response graphically presented in a nomogram allowed the estimation of concrete properties in response to variation of composition within the x-space. The optimal range of argillite content was obtained leading to a reduction of raw materials demand, development of target plastic strength of aerated concrete as well as a reduction of curing time before autoclave treatment. Generally, this method allows the design of autoclave aerated concrete with required performance without additional resource and time costs.

1L Mark-IV Target Design Review

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

Koehler, Paul E.

This presentation includes General Design Considerations; Current (Mark-III) Lower Tier; Mark-III Upper Tier; Performance Metrics; General Improvements for Material Science; General Improvements for Nuclear Science; Improving FOM for Nuclear Science; General Design Considerations Summary; Design Optimization Studies; Expected Mark-IV Performance: Material Science; Expected Mark-IV Performance: Nuclear Science (Disk); Mark IV Enables Much Wider Range of Nuclear-Science FOM Gains than Mark III; Mark-IV Performance Summary; Rod or Disk? Center or Real FOV?; and Project Cost and Schedule.

A novel method for biomaterial scaffold internal architecture design to match bone elastic properties with desired porosity.

PubMed

Lin, Cheng Yu; Kikuchi, Noboru; Hollister, Scott J

2004-05-01

An often-proposed tissue engineering design hypothesis is that the scaffold should provide a biomimetic mechanical environment for initial function and appropriate remodeling of regenerating tissue while concurrently providing sufficient porosity for cell migration and cell/gene delivery. To provide a systematic study of this hypothesis, the ability to precisely design and manufacture biomaterial scaffolds is needed. Traditional methods for scaffold design and fabrication cannot provide the control over scaffold architecture design to achieve specified properties within fixed limits on porosity. The purpose of this paper was to develop a general design optimization scheme for 3D internal scaffold architecture to match desired elastic properties and porosity simultaneously, by introducing the homogenization-based topology optimization algorithm (also known as general layout optimization). With an initial target for bone tissue engineering, we demonstrate that the method can produce highly porous structures that match human trabecular bone anisotropic stiffness using accepted biomaterials. In addition, we show that anisotropic bone stiffness may be matched with scaffolds of widely different porosity. Finally, we also demonstrate that prototypes of the designed structures can be fabricated using solid free-form fabrication (SFF) techniques.

GLRS-R 2-colour retroreflector target design and predicted performance

NASA Astrophysics Data System (ADS)

Lund, Glenn

The retroreflector ground target design for the GLRS-R spaceborne dual wavelength laser ranging system is described. The passive design flows down from the requirements of high station autonomy, high global field of view, little or no multiple pulse returns, and adequate optical cross section for most ranging geometries. The solution makes use of five hollow cube corner retroreflectors of which one points to the zenith and the remaining four are inclined from the vertical at uniform azimuthal spacings. The need for large retroreflectors is expected to generate narrow diffraction lobes. A good compromise solution is found by spoiling just one of the retroereflector dihedral angles from 90 deg, thus generating two symmetrically oriented diffraction lobes in the return beam. The required spoil angles are found to have little dependance on ground target latitude. Various link budget analyses are presented. They show the influence of such factors as point ahead optimization, turbulence, ranging angle, atmospheric visibility, and ground target thermal deformations.

Rational optimization of drug-target residence time: Insights from inhibitor binding to the S. aureus FabI enzyme-product complex

PubMed Central

Chang, Andrew; Schiebel, Johannes; Yu, Weixuan; Bommineni, Gopal R.; Pan, Pan; Baxter, Michael V.; Khanna, Avinash; Sotriffer, Christoph A.; Kisker, Caroline; Tonge, Peter J.

2013-01-01

Drug-target kinetics has recently emerged as an especially important facet of the drug discovery process. In particular, prolonged drug-target residence times may confer enhanced efficacy and selectivity in the open in vivo system. However, the lack of accurate kinetic and structural data for series of congeneric compounds hinders the rational design of inhibitors with decreased off-rates. Therefore, we chose the Staphylococcus aureus enoyl-ACP reductase (saFabI) - an important target for the development of new anti-staphylococcal drugs - as a model system to rationalize and optimize the drug-target residence time on a structural basis. Using our new, efficient and widely applicable mechanistically informed kinetic approach, we obtained a full characterization of saFabI inhibition by a series of 20 diphenyl ethers complemented by a collection of 9 saFabI-inhibitor crystal structures. We identified a strong correlation between the affinities of the investigated saFabI diphenyl ether inhibitors and their corresponding residence times, which can be rationalized on a structural basis. Due to its favorable interactions with the enzyme, the residence time of our most potent compound exceeds 10 hours. In addition, we found that affinity and residence time in this system can be significantly enhanced by modifications predictable by a careful consideration of catalysis. Our study provides a blueprint for investigating and prolonging drug-target kinetics and may aid in the rational design of long-residence-time inhibitors targeting the essential saFabI enzyme. PMID:23697754

Selection is more intelligent than design: improving the affinity of a bivalent ligand through directed evolution.

PubMed

Ahmad, Kareem M; Xiao, Yi; Soh, H Tom

2012-12-01

Multivalent molecular interactions can be exploited to dramatically enhance the performance of an affinity reagent. The enhancement in affinity and specificity achieved with a multivalent construct depends critically on the effectiveness of the scaffold that joins the ligands, as this determines their positions and orientations with respect to the target molecule. Currently, no generalizable design rules exist for construction of an optimal multivalent ligand for targets with known structures, and the design challenge remains an insurmountable obstacle for the large number of proteins whose structures are not known. As an alternative to such design-based strategies, we report here a directed evolution-based method for generating optimal bivalent aptamers. To demonstrate this approach, we fused two thrombin aptamers with a randomized DNA sequence and used a microfluidic in vitro selection strategy to isolate scaffolds with exceptionally high affinities. Within five rounds of selection, we generated a bivalent aptamer that binds thrombin with an apparent dissociation constant (K(d)) <10 pM, representing a ∼200-fold improvement in binding affinity over the monomeric aptamers and a ∼15-fold improvement over the best designed bivalent construct. The process described here can be used to produce high-affinity multivalent aptamers and could potentially be adapted to other classes of biomolecules.

Design space pruning heuristics and global optimization method for conceptual design of low-thrust asteroid tour missions

NASA Astrophysics Data System (ADS)

Alemany, Kristina

Electric propulsion has recently become a viable technology for spacecraft, enabling shorter flight times, fewer required planetary gravity assists, larger payloads, and/or smaller launch vehicles. With the maturation of this technology, however, comes a new set of challenges in the area of trajectory design. Because low-thrust trajectory optimization has historically required long run-times and significant user-manipulation, mission design has relied on expert-based knowledge for selecting departure and arrival dates, times of flight, and/or target bodies and gravitational swing-bys. These choices are generally based on known configurations that have worked well in previous analyses or simply on trial and error. At the conceptual design level, however, the ability to explore the full extent of the design space is imperative to locating the best solutions in terms of mass and/or flight times. Beginning in 2005, the Global Trajectory Optimization Competition posed a series of difficult mission design problems, all requiring low-thrust propulsion and visiting one or more asteroids. These problems all had large ranges on the continuous variables---launch date, time of flight, and asteroid stay times (when applicable)---as well as being characterized by millions or even billions of possible asteroid sequences. Even with recent advances in low-thrust trajectory optimization, full enumeration of these problems was not possible within the stringent time limits of the competition. This investigation develops a systematic methodology for determining a broad suite of good solutions to the combinatorial, low-thrust, asteroid tour problem. The target application is for conceptual design, where broad exploration of the design space is critical, with the goal being to rapidly identify a reasonable number of promising solutions for future analysis. The proposed methodology has two steps. The first step applies a three-level heuristic sequence developed from the physics of the problem, which allows for efficient pruning of the design space. The second phase applies a global optimization scheme to locate a broad suite of good solutions to the reduced problem. The global optimization scheme developed combines a novel branch-and-bound algorithm with a genetic algorithm and an industry-standard low-thrust trajectory optimization program to solve for the following design variables: asteroid sequence, launch date, times of flight, and asteroid stay times. The methodology is developed based on a small sample problem, which is enumerated and solved so that all possible discretized solutions are known. The methodology is then validated by applying it to a larger intermediate sample problem, which also has a known solution. Next, the methodology is applied to several larger combinatorial asteroid rendezvous problems, using previously identified good solutions as validation benchmarks. These problems include the 2nd and 3rd Global Trajectory Optimization Competition problems. The methodology is shown to be capable of achieving a reduction in the number of asteroid sequences of 6-7 orders of magnitude, in terms of the number of sequences that require low-thrust optimization as compared to the number of sequences in the original problem. More than 70% of the previously known good solutions are identified, along with several new solutions that were not previously reported by any of the competitors. Overall, the methodology developed in this investigation provides an organized search technique for the low-thrust mission design of asteroid rendezvous problems.

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

PubMed

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

2016-01-01

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

Meeting report from the Prostate Cancer Foundation PSMA-directed radionuclide scientific working group.

PubMed

Miyahira, Andrea K; Pienta, Kenneth J; Morris, Michael J; Bander, Neil H; Baum, Richard P; Fendler, Wolfgang P; Goeckeler, William; Gorin, Michael A; Hennekes, Hartwig; Pomper, Martin G; Sartor, Oliver; Tagawa, Scott T; Williams, Scott; Soule, Howard R

2018-05-01

The Prostate Cancer Foundation (PCF) convened a PSMA-Directed Radionuclide Scientific Working Group on November 14, 2017, at Weill Cornell Medicine, New York, NY. The meeting was attended by 35 global investigators with expertise in prostate cancer biology, radionuclide therapy, molecular imaging, prostate-specific membrane antigen (PSMA)-targeted agents, drug development, and prostate cancer clinical trials. The goal of this meeting was to discuss the potential for using PSMA-targeted radionuclide agents for the treatment of advanced prostate cancer and to define the studies and clinical trials necessary for validating and optimizing the use of these agents. Several major topic areas were discussed including the overview of PSMA biology, lessons and applications of PSMA-targeted PET imaging, the nuances of designing PSMA-targeted radionuclide agents, clinical experiences with PSMA-targeted radionuclides, PCF-funded projects to accelerate PSMA-targeted radionuclide therapy, and barriers to the use of radionuclide treatments in widespread clinical practice. This article reviews the major topics discussed at the meeting with the goal of promoting research that will validate and optimize the use of PSMA-targeted radionuclide therapies for the treatment of advanced prostate cancer. © 2018 Wiley Periodicals, Inc.

Up-cycling waste glass to minimal water adsorption/absorption lightweight aggregate by rapid low temperature sintering: optimization by dual process-mixture response surface methodology.

PubMed

Velis, Costas A; Franco-Salinas, Claudia; O'Sullivan, Catherine; Najorka, Jens; Boccaccini, Aldo R; Cheeseman, Christopher R

2014-07-01

Mixed color waste glass extracted from municipal solid waste is either not recycled, in which case it is an environmental and financial liability, or it is used in relatively low value applications such as normal weight aggregate. Here, we report on converting it into a novel glass-ceramic lightweight aggregate (LWA), potentially suitable for high added value applications in structural concrete (upcycling). The artificial LWA particles were formed by rapidly sintering (<10 min) waste glass powder with clay mixes using sodium silicate as binder and borate salt as flux. Composition and processing were optimized using response surface methodology (RSM) modeling, and specifically (i) a combined process-mixture dual RSM, and (ii) multiobjective optimization functions. The optimization considered raw materials and energy costs. Mineralogical and physical transformations occur during sintering and a cellular vesicular glass-ceramic composite microstructure is formed, with strong correlations existing between bloating/shrinkage during sintering, density and water adsorption/absorption. The diametrical expansion could be effectively modeled via the RSM and controlled to meet a wide range of specifications; here we optimized for LWA structural concrete. The optimally designed LWA is sintered in comparatively low temperatures (825-835 °C), thus potentially saving costs and lowering emissions; it had exceptionally low water adsorption/absorption (6.1-7.2% w/wd; optimization target: 1.5-7.5% w/wd); while remaining substantially lightweight (density: 1.24-1.28 g.cm(-3); target: 0.9-1.3 g.cm(-3)). This is a considerable advancement for designing effective environmentally friendly lightweight concrete constructions, and boosting resource efficiency of waste glass flows.

Optimal design of leak-proof SRAM cell using MCDM method

NASA Astrophysics Data System (ADS)

Wang, Qi; Kang, Sung-Mo

2003-04-01

As deep-submicron CMOS technology advances, on-chip cache has become a bottleneck on microprocessor's performance. Meanwhile, it also occupies a big percentage of processor area and consumes large power. Speed, power and area of SRAM are mutually contradicting, and not easy to be met simultaneously. Many existent leakage suppression techniques have been proposed, but they limit the circuit's performance. We apply a Multi-Criteria Decision Making strategy to perform a minimum delay-power-area optimization on SRAM circuit under some certain constraints. Based on an integrated device and circuit-level approach, we search for a process that yields a targeted composite performance. In consideration of the huge amount of simulation workload involved in the optimal design-seeking process, most of this process is automated to facilitate our goal-pursuant. With varying emphasis put on delay, power or area, different optimal SRAM designs are derived and a gate-oxide thickness scaling limit is projected. The result seems to indicate that a better composite performance could be achieved under a thinner oxide thickness. Under the derived optimal oxide thickness, the static leakage power consumption contributes less than 1% in the total power dissipation.

Rational chemical design of the next generation of molecular imaging probes based on physics and biology: mixing modalities, colors and signals

PubMed Central

Longmire, Michelle R.; Ogawa, Mikako; Choyke, Peter L.

2012-01-01

In recent years, numerous in vivo molecular imaging probes have been developed. As a consequence, much has been published on the design and synthesis of molecular imaging probes focusing on each modality, each type of material, or each target disease. More recently, second generation molecular imaging probes with unique, multi-functional, or multiplexed characteristics have been designed. This critical review focuses on (i) molecular imaging using combinations of modalities and signals that employ the full range of the electromagnetic spectra, (ii) optimized chemical design of molecular imaging probes for in vivo kinetics based on biology and physiology across a range of physical sizes, (iii) practical examples of second generation molecular imaging probes designed to extract complementary data from targets using multiple modalities, color, and comprehensive signals (277 references). PMID:21607237

Design and optimal control of on-orbit servicing trajectory for target vehicle in non-coplanar elliptical orbit

NASA Astrophysics Data System (ADS)

Zhou, Wenyong; Yuan, Jianping; Luo, Jianjun

2005-11-01

Autonomous on-orbit servicing provides flexibility to space systems and has great value both in civil and in military. When a satellite performs on-orbit servicing tasks, flying around is the basic type of motion. This paper is concerned with the design and control problems of a chaser satellite flying around a target spacecraft in non-coplanar elliptical orbit for a long time. At first, a mathematical model used to design a long-term flying around trajectory is presented, which is applicable to the situation that the target spacecraft flies in an elliptical orbit. The conditions of the target at the centre of the flying around path are deduced. Considering the safety and task requirements, a long-term flying around trajectory is designed. Taking into account perturbations and navigation errors which can cause the trajectory unstable and mission impossible, a two-impulse control method is put forward. Genetic algorithm is used to minimize the cost function which considers fuel consumption and bias simultaneously. Some simulation works are carried out and the results indicate the flying around mathematical model and the trajectory control method can be used in the design and control of a long-term flying around trajectory.

Method for depleting BWRs using optimal control rod patterns

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

Taner, M.S.; Levine, S.H.; Hsiao, M.Y.

1991-01-01

Control rod (CR) programming is an essential core management activity for boiling water reactors (BWRs). After establishing a core reload design for a BWR, CR programming is performed to develop a sequence of exposure-dependent CR patterns that assure the safe and effective depletion of the core through a reactor cycle. A time-variant target power distribution approach has been assumed in this study. The authors have developed OCTOPUS to implement a new two-step method for designing semioptimal CR programs for BWRs. The optimization procedure of OCTOPUS is based on the method of approximation programming and uses the SIMULATE-E code for nucleonicsmore » calculations.« less

Examination of CRISPR/Cas9 design tools and the effect of target site accessibility on Cas9 activity.

PubMed

Lee, Ciaran M; Davis, Timothy H; Bao, Gang

2018-04-01

What is the topic of this review? In this review, we analyse the performance of recently described tools for CRISPR/Cas9 guide RNA design, in particular, design tools that predict CRISPR/Cas9 activity. What advances does it highlight? Recently, many tools designed to predict CRISPR/Cas9 activity have been reported. However, the majority of these tools lack experimental validation. Our analyses indicate that these tools have poor predictive power. Our preliminary results suggest that target site accessibility should be considered in order to develop better guide RNA design tools with improved predictive power. The recent adaptation of the clustered regulatory interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system for targeted genome engineering has led to its widespread application in many fields worldwide. In order to gain a better understanding of the design rules of CRISPR/Cas9 systems, several groups have carried out large library-based screens leading to some insight into sequence preferences among highly active target sites. To facilitate CRISPR/Cas9 design, these studies have spawned a plethora of guide RNA (gRNA) design tools with algorithms based solely on direct or indirect sequence features. Here, we demonstrate that the predictive power of these tools is poor, suggesting that sequence features alone cannot accurately inform the cutting efficiency of a particular CRISPR/Cas9 gRNA design. Furthermore, we demonstrate that DNA target site accessibility influences the activity of CRISPR/Cas9. With further optimization, we hypothesize that it will be possible to increase the predictive power of gRNA design tools by including both sequence and target site accessibility metrics. © 2017 The Authors. Experimental Physiology © 2017 The Physiological Society.

Optimal Reference Strain Structure for Studying Dynamic Responses of Flexible Rockets

NASA Technical Reports Server (NTRS)

Tsushima, Natsuki; Su, Weihua; Wolf, Michael G.; Griffin, Edwin D.; Dumoulin, Marie P.

2017-01-01

In the proposed paper, the optimal design of reference strain structures (RSS) will be performed targeting for the accurate observation of the dynamic bending and torsion deformation of a flexible rocket. It will provide the detailed description of the finite-element (FE) model of a notional flexible rocket created in MSC.Patran. The RSS will be attached longitudinally along the side of the rocket and to track the deformation of the thin-walled structure under external loads. An integrated surrogate-based multi-objective optimization approach will be developed to find the optimal design of the RSS using the FE model. The Kriging method will be used to construct the surrogate model. For the data sampling and the performance evaluation, static/transient analyses will be performed with MSC.Natran/Patran. The multi-objective optimization will be solved with NSGA-II to minimize the difference between the strains of the launch vehicle and RSS. Finally, the performance of the optimal RSS will be evaluated by checking its strain-tracking capability in different numerical simulations of the flexible rocket.

Targeting the UPR to Circumvent Endocrine Resistance in Breast Cancer

DTIC Science & Technology

2014-10-01

activity relationship analyses ( QSAR ) to develop rationally designed NPPTA analogs with increased potency and optimized pharmacologic properties...vitro, with the strongest candidates being studied in vivo to provide preclinical safety, efficacy, and toxicology data to support later first-in-human

Targeted ENO schemes with tailored resolution property for hyperbolic conservation laws

NASA Astrophysics Data System (ADS)

Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.

2017-11-01

In this paper, we extend the range of targeted ENO (TENO) schemes (Fu et al. (2016) [18]) by proposing an eighth-order TENO8 scheme. A general formulation to construct the high-order undivided difference τK within the weighting strategy is proposed. With the underlying scale-separation strategy, sixth-order accuracy for τK in the smooth solution regions is designed for good performance and robustness. Furthermore, a unified framework to optimize independently the dispersion and dissipation properties of high-order finite-difference schemes is proposed. The new framework enables tailoring of dispersion and dissipation as function of wavenumber. The optimal linear scheme has minimum dispersion error and a dissipation error that satisfies a dispersion-dissipation relation. Employing the optimal linear scheme, a sixth-order TENO8-opt scheme is constructed. A set of benchmark cases involving strong discontinuities and broadband fluctuations is computed to demonstrate the high-resolution properties of the new schemes.

Designing pH induced fold switch in proteins

NASA Astrophysics Data System (ADS)

Baruah, Anupaul; Biswas, Parbati

2015-05-01

This work investigates the computational design of a pH induced protein fold switch based on a self-consistent mean-field approach by identifying the ensemble averaged characteristics of sequences that encode a fold switch. The primary challenge to balance the alternative sets of interactions present in both target structures is overcome by simultaneously optimizing two foldability criteria corresponding to two target structures. The change in pH is modeled by altering the residual charge on the amino acids. The energy landscape of the fold switch protein is found to be double funneled. The fold switch sequences stabilize the interactions of the sites with similar relative surface accessibility in both target structures. Fold switch sequences have low sequence complexity and hence lower sequence entropy. The pH induced fold switch is mediated by attractive electrostatic interactions rather than hydrophobic-hydrophobic contacts. This study may provide valuable insights to the design of fold switch proteins.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Internalization, Trafficking, Intracellular Processing and Actions of Antibody-Drug Conjugates.

PubMed

Xu, Shi

2015-11-01

This review discusses the molecular mechanism involved in the targeting and delivery of antibody-drug conjugates (ADCs), the new class of biopharmaceuticals mainly designed for targeted cancer therapy. this review goes over major progress in preclinical and clinical studies of ADCs, in the past 5 years. The pharmacokinetics and pharmacodynamics of ADCs involve multiple mechanisms, including internalization of ADCs by target cells, intracellular trafficking, release of conjugated drugs, and payload. These mechanisms actually jointly determine the efficacy of ADCs. Therefore, the optimization of ADCs should take them as necessary rationales.

Systematic optimization model and algorithm for binding sequence selection in computational enzyme design

PubMed Central

Huang, Xiaoqiang; Han, Kehang; Zhu, Yushan

2013-01-01

A systematic optimization model for binding sequence selection in computational enzyme design was developed based on the transition state theory of enzyme catalysis and graph-theoretical modeling. The saddle point on the free energy surface of the reaction system was represented by catalytic geometrical constraints, and the binding energy between the active site and transition state was minimized to reduce the activation energy barrier. The resulting hyperscale combinatorial optimization problem was tackled using a novel heuristic global optimization algorithm, which was inspired and tested by the protein core sequence selection problem. The sequence recapitulation tests on native active sites for two enzyme catalyzed hydrolytic reactions were applied to evaluate the predictive power of the design methodology. The results of the calculation show that most of the native binding sites can be successfully identified if the catalytic geometrical constraints and the structural motifs of the substrate are taken into account. Reliably predicting active site sequences may have significant implications for the creation of novel enzymes that are capable of catalyzing targeted chemical reactions. PMID:23649589

In vivo therapeutic potential of Dicer-hunting siRNAs targeting infectious hepatitis C virus.

PubMed

Watanabe, Tsunamasa; Hatakeyama, Hiroto; Matsuda-Yasui, Chiho; Sato, Yusuke; Sudoh, Masayuki; Takagi, Asako; Hirata, Yuichi; Ohtsuki, Takahiro; Arai, Masaaki; Inoue, Kazuaki; Harashima, Hideyoshi; Kohara, Michinori

2014-04-23

The development of RNA interference (RNAi)-based therapy faces two major obstacles: selecting small interfering RNA (siRNA) sequences with strong activity, and identifying a carrier that allows efficient delivery to target organs. Additionally, conservative region at nucleotide level must be targeted for RNAi in applying to virus because hepatitis C virus (HCV) could escape from therapeutic pressure with genome mutations. In vitro preparation of Dicer-generated siRNAs targeting a conserved, highly ordered HCV 5' untranslated region are capable of inducing strong RNAi activity. By dissecting the 5'-end of an RNAi-mediated cleavage site in the HCV genome, we identified potent siRNA sequences, which we designate as Dicer-hunting siRNAs (dh-siRNAs). Furthermore, formulation of the dh-siRNAs in an optimized multifunctional envelope-type nano device inhibited ongoing infectious HCV replication in human hepatocytes in vivo. Our efforts using both identification of optimal siRNA sequences and delivery to human hepatocytes suggest therapeutic potential of siRNA for a virus.

Production of Selected Key Ductile Iron Castings Used in Large-Scale Windmills

NASA Astrophysics Data System (ADS)

Pan, Yung-Ning; Lin, Hsuan-Te; Lin, Chi-Chia; Chang, Re-Mo

Both the optimal alloy design and microstructures that conform to the mechanical properties requirements of selected key components used in large-scale windmills have been established in this study. The target specifications in this study are EN-GJS-350-22U-LT, EN-GJS-350-22U-LT and EN-GJS-700-2U. In order to meet the impact requirement of spec. EN-GJS-350-22U-LT, the Si content should be kept below 1.97%, and also the maximum pearlite content shouldn't exceed 7.8%. On the other hand, Si content below 2.15% and pearlite content below 12.5% were registered for specification EN-GJS-400-18U-LT. On the other hand, the optimal alloy designs that can comply with specification EN-GJS-700-2U include 0.25%Mn+0.6%Cu+0.05%Sn, 0.25%Mn+0.8%Cu+0.01%Sn and 0.45%Mn+0.6%Cu+0.01%Sn. Furthermore, based upon the experimental results, multiple regression analyses have been performed to correlate the mechanical properties with chemical compositions and microstructures. The derived regression equations can be used to attain the optimal alloy design for castings with target specifications. Furthermore, by employing these regression equations, the mechanical properties can be predicted based upon the chemical compositions and microstructures of cast irons.

Optimizing the design of vertical seismic profiling (VSP) for imaging fracture zones over hardrock basement geothermal environments

NASA Astrophysics Data System (ADS)

Reiser, Fabienne; Schmelzbach, Cedric; Maurer, Hansruedi; Greenhalgh, Stewart; Hellwig, Olaf

2017-04-01

A primary focus of geothermal seismic imaging is to map dipping faults and fracture zones that control rock permeability and fluid flow. Vertical seismic profiling (VSP) is therefore a most valuable means to image the immediate surroundings of an existing borehole to guide, for example, the placing of new boreholes to optimize production from known faults and fractures. We simulated 2D and 3D acoustic synthetic seismic data and processed it through to pre-stack depth migration to optimize VSP survey layouts for mapping moderately to steeply dipping fracture zones within possible basement geothermal reservoirs. Our VSP survey optimization procedure for sequentially selecting source locations to define the area where source points are best located for optimal imaging makes use of a cross-correlation statistic, by which a subset of migrated shot gathers is compared with a target or reference image from a comprehensive set of source gathers. In geothermal exploration at established sites, it is reasonable to assume that sufficient à priori information is available to construct such a target image. We generally obtained good results with a relatively small number of optimally chosen source positions distributed over an ideal source location area for different fracture zone scenarios (different dips, azimuths, and distances from the surveying borehole). Adding further sources outside the optimal source area did not necessarily improve the results, but rather resulted in image distortions. It was found that fracture zones located at borehole-receiver depths and laterally offset from the borehole by 300 m can be imaged reliably for a range of the different dips, but more source positions and large offsets between sources and the borehole are required for imaging steeply dipping interfaces. When such features cross-cut the borehole, they are particularly difficult to image. For fracture zones with different azimuths, 3D effects are observed. Far offset source positions contribute less to the image quality as fracture zone azimuth increases. Our optimization methodology is best suited for designing future field surveys with a favorable benefit-cost ratio in areas with significant à priori knowledge. Moreover, our optimization workflow is valuable for selecting useful subsets of acquired data for optimum target-oriented processing.

Validating a new methodology for optical probe design and image registration in fNIRS studies

PubMed Central

Wijeakumar, Sobanawartiny; Spencer, John P.; Bohache, Kevin; Boas, David A.; Magnotta, Vincent A.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an imaging technique that relies on the principle of shining near-infrared light through tissue to detect changes in hemodynamic activation. An important methodological issue encountered is the creation of optimized probe geometry for fNIRS recordings. Here, across three experiments, we describe and validate a processing pipeline designed to create an optimized, yet scalable probe geometry based on selected regions of interest (ROIs) from the functional magnetic resonance imaging (fMRI) literature. In experiment 1, we created a probe geometry optimized to record changes in activation from target ROIs important for visual working memory. Positions of the sources and detectors of the probe geometry on an adult head were digitized using a motion sensor and projected onto a generic adult atlas and a segmented head obtained from the subject's MRI scan. In experiment 2, the same probe geometry was scaled down to fit a child's head and later digitized and projected onto the generic adult atlas and a segmented volume obtained from the child's MRI scan. Using visualization tools and by quantifying the amount of intersection between target ROIs and channels, we show that out of 21 ROIs, 17 and 19 ROIs intersected with fNIRS channels from the adult and child probe geometries, respectively. Further, both the adult atlas and adult subject-specific MRI approaches yielded similar results and can be used interchangeably. However, results suggest that segmented heads obtained from MRI scans be used for registering children's data. Finally, in experiment 3, we further validated our processing pipeline by creating a different probe geometry designed to record from target ROIs involved in language and motor processing. PMID:25705757

Design of a novel instrument for active neutron interrogation of artillery shells.

PubMed

Bélanger-Champagne, Camille; Vainionpää, Hannes; Peura, Pauli; Toivonen, Harri; Eerola, Paula; Dendooven, Peter

2017-01-01

The most common explosives can be uniquely identified by measuring the elemental H/N ratio with a precision better than 10%. Monte Carlo simulations were used to design two variants of a new prompt gamma neutron activation instrument that can achieve this precision. The instrument features an intense pulsed neutron generator with precise timing. Measuring the hydrogen peak from the target explosive is especially challenging because the instrument itself contains hydrogen, which is needed for neutron moderation and shielding. By iterative design optimization, the fraction of the hydrogen peak counts coming from the explosive under interrogation increased from [Formula: see text]% to [Formula: see text]% (statistical only) for the benchmark design. In the optimized design variants, the hydrogen signal from a high-explosive shell can be measured to a statistics-only precision better than 1% in less than 30 minutes for an average neutron production yield of 109 n/s.

Design of a novel instrument for active neutron interrogation of artillery shells

PubMed Central

Vainionpää, Hannes; Peura, Pauli; Toivonen, Harri; Eerola, Paula; Dendooven, Peter

2017-01-01

The most common explosives can be uniquely identified by measuring the elemental H/N ratio with a precision better than 10%. Monte Carlo simulations were used to design two variants of a new prompt gamma neutron activation instrument that can achieve this precision. The instrument features an intense pulsed neutron generator with precise timing. Measuring the hydrogen peak from the target explosive is especially challenging because the instrument itself contains hydrogen, which is needed for neutron moderation and shielding. By iterative design optimization, the fraction of the hydrogen peak counts coming from the explosive under interrogation increased from 53-7+7% to 74-10+8% (statistical only) for the benchmark design. In the optimized design variants, the hydrogen signal from a high-explosive shell can be measured to a statistics-only precision better than 1% in less than 30 minutes for an average neutron production yield of 109 n/s. PMID:29211773

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.

Benchmarking of TALE- and CRISPR/dCas9-Based Transcriptional Regulators in Mammalian Cells for the Construction of Synthetic Genetic Circuits.

PubMed

Lebar, Tina; Jerala, Roman

2016-10-21

Transcriptional activator-like effector (TALE)- and CRISPR/Cas9-based designable recognition domains represent a technological breakthrough not only for genome editing but also for building designed genetic circuits. Both platforms are able to target rarely occurring DNA segments, even within complex genomes. TALE and dCas9 domains, genetically fused to transcriptional regulatory domains, can be used for the construction of engineered logic circuits. Here we benchmarked the performance of the two platforms, targeting the same DNA sequences, to compare their advantages for the construction of designed circuits in mammalian cells. Optimal targeting strands for repression and activation of dCas9-based designed transcription factors were identified; both platforms exhibited good orthogonality and were used to construct functionally complete NOR gates. Although the CRISPR/dCas9 system is clearly easier to construct, TALE-based activators were significantly stronger, and the TALE-based platform performed better, especially for the construction of layered circuits.

Exploratory investigation of the HIPPO gas-jet target fluid dynamic properties

NASA Astrophysics Data System (ADS)

Meisel, Zach; Shi, Ke; Jemcov, Aleksandar; Couder, Manoel

2016-08-01

In order to optimize the performance of gas-jet targets for future nuclear reaction measurements, a detailed understanding of the dependence of the gas-jet properties on experiment design parameters is required. Common methods of gas-jet characterization rely on measuring the effective thickness using nuclear elastic scattering and energy loss techniques; however, these tests are time intensive and limit the range of design modifications which can be explored to improve the properties of the jet as a nuclear reaction target. Thus, a more rapid jet-characterization method is desired. We performed the first steps towards characterizing the gas-jet density distribution of the HIPPO gas-jet target at the University of Notre Dame's Nuclear Science Laboratory by reproducing results from 20Ne(α,α)20Ne elastic scattering measurements with computational fluid dynamics (CFD) simulations performed with the state-of-the-art CFD software ANSYS Fluent. We find a strong sensitivity to experimental design parameters of the gas-jet target, such as the jet nozzle geometry and ambient pressure of the target chamber. We argue that improved predictive power will require moving to three-dimensional simulations and additional benchmarking with experimental data.

Optimization of Soft Tissue Management, Spacer Design, and Grafting Strategies for Large Segmental Bone Defects using the Chronic Caprine Tibial Defect Model

DTIC Science & Technology

2015-10-01

Several target genes such as Oct4, Sox2, TGFB, and Col1A1 were generally up-regulated in all sections. In distal sections, VWF, PDGFB, and EGFR were...TGFB, and Col1A1 in all sections. No significant main effects were found for target gene fold-change between outer or inner membrane position or distal

Performance considerations for high-definition head-mounted displays

NASA Technical Reports Server (NTRS)

Edwards, Oliver J.; Larimer, James; Gille, Jennifer

1992-01-01

Design image-optimization for helmet-mounted displays (HMDs) for military systems is presently discussed within the framework of a systems-engineering approach that encompasses (1) a description of natural targets in the field; (2) the characteristics of human visual perception; and (3) device specifications that directly relate to these ecological and human-factors parameters. Attention is given to target size and contrast and the relationship of the modulation transfer function to image resolution.

Direct Multiple Shooting Optimization with Variable Problem Parameters

NASA Technical Reports Server (NTRS)

Whitley, Ryan J.; Ocampo, Cesar A.

2009-01-01

Taking advantage of a novel approach to the design of the orbital transfer optimization problem and advanced non-linear programming algorithms, several optimal transfer trajectories are found for problems with and without known analytic solutions. This method treats the fixed known gravitational constants as optimization variables in order to reduce the need for an advanced initial guess. Complex periodic orbits are targeted with very simple guesses and the ability to find optimal transfers in spite of these bad guesses is successfully demonstrated. Impulsive transfers are considered for orbits in both the 2-body frame as well as the circular restricted three-body problem (CRTBP). The results with this new approach demonstrate the potential for increasing robustness for all types of orbit transfer problems.

Design and construction of a spectrometer facility and experiment for intermediate energy proton scattering on helium. [Wave functions, preliminary experimental techniques

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

Rolfe, R.M.

1976-12-01

The goal of the research was to investigate proton scattering on nuclei at intermediate energies and in particular to investigate proton scattering on helium. A theoretical investigation of the helium nucleus and the nature of the intermediate energy interaction, design and optimization of an energy-loss spectrometer facility for proton-nucleus scattering, and the unique superfluid helium target and experimental design are discussed.

Implementation of "Quality by Design (QbD)" Approach for the Development of 5-Fluorouracil Loaded Thermosensitive Hydrogel.

PubMed

Dalwadi, Chintan; Patel, Gayatri

2016-01-01

The purpose of this study was to investigate Quality by Design (QbD) principle for the preparation of hydrogel products to prove both practicability and utility of executing QbD concept to hydrogel based controlled release systems. Product and process understanding will help in decreasing the variability of critical material and process parameters, which give quality product output and reduce the risk. This study includes the identification of the Quality Target Product Profiles (QTPPs) and Critical Quality Attributes (CQAs) from literature or preliminary studies. To identify and control the variability in process and material attributes, two tools of QbD was utilized, Quality Risk Management (QRM) and Experimental Design. Further, it helps to identify the effect of these attributes on CQAs. Potential risk factors were identified from fishbone diagram and screened by risk assessment and optimized by 3-level 2- factor experimental design with center points in triplicate, to analyze the precision of the target process. This optimized formulation was further characterized by gelling time, gelling temperature, rheological parameters, in-vitro biodegradation and in-vitro drug release. Design space was created using experimental design tool that gives the control space and working within this controlled space reduces all the failure modes below the risk level. In conclusion, QbD approach with QRM tool provides potent and effectual pyramid to enhance the quality into the hydrogel.

Quality by design approach of a pharmaceutical gel manufacturing process, part 1: determination of the design space.

PubMed

Rosas, Juan G; Blanco, Marcel; González, Josep M; Alcalá, Manel

2011-10-01

This work was conducted in the framework of a quality by design project involving the production of a pharmaceutical gel. Preliminary work included the identification of the quality target product profiles (QTPPs) from historical values for previously manufactured batches, as well as the critical quality attributes for the process (viscosity and pH), which were used to construct a D-optimal experimental design. The experimental design comprised 13 gel batches, three of which were replicates at the domain center intended to assess the reproducibility of the target process. The viscosity and pH models established exhibited very high linearity and negligible lack of fit (LOF). Thus, R(2) was 0.996 for viscosity and 0.975 for pH, and LOF was 0.53 for the former parameter and 0.84 for the latter. The process proved reproducible at the domain center. Water content and temperature were the most influential factors for viscosity, and water content and acid neutralized fraction were the most influential factors for pH. A desirability function was used to find the best compromise to optimize the QTPPs. The body of information was used to identify and define the design space for the process. A model capable of combining the two response variables into a single one was constructed to facilitate monitoring of the process. Copyright © 2011 Wiley-Liss, Inc.

Broadband metamaterial lens antennas with special properties by controlling both refractive-index distribution and feed directivity

NASA Astrophysics Data System (ADS)

Ma, Qian; Shi, Chuan Bo; Chen, Tian Yi; Qing Qi, Mei; Li, Yun Bo; Cui, Tie Jun

2018-04-01

A new method is proposed to design gradient refractive-index metamaterial lens antennas by optimizing both the refractive-index distribution of the lens and the feed directivity. Comparing to the conventional design methods, source optimization provides a new degree of freedom to control aperture fields effectively. To demonstrate this method, two lenses with special properties based on this method are designed, to emit high-efficiency plane waves and fan-shaped beams, respectively. Both lenses have good performance and wide frequency band from 12 to 18 GHz, verifying the validity of the proposed method. The plane-wave emitting lens realized a high aperture efficiency of 75%, and the fan-beam lens achieved a high gain of 15 dB over board bandwidth. The experimental results have good agreement with the design targets and full-wave simulations.

The chemical evolution of oligonucleotide therapies of clinical utility.

PubMed

Khvorova, Anastasia; Watts, Jonathan K

2017-03-01

After nearly 40 years of development, oligonucleotide therapeutics are nearing meaningful clinical productivity. One of the key advantages of oligonucleotide drugs is that their delivery and potency are derived primarily from the chemical structure of the oligonucleotide whereas their target is defined by the base sequence. Thus, as oligonucleotides with a particular chemical design show appropriate distribution and safety profiles for clinical gene silencing in a particular tissue, this will open the door to the rapid development of additional drugs targeting other disease-associated genes in the same tissue. To achieve clinical productivity, the chemical architecture of the oligonucleotide needs to be optimized with a combination of sugar, backbone, nucleobase, and 3'- and 5'-terminal modifications. A portfolio of chemistries can be used to confer drug-like properties onto the oligonucleotide as a whole, with minor chemical changes often translating into major improvements in clinical efficacy. One outstanding challenge in oligonucleotide chemical development is the optimization of chemical architectures to ensure long-term safety. There are multiple designs that enable effective targeting of the liver, but a second challenge is to develop architectures that enable robust clinical efficacy in additional tissues.

Broadband Liner Optimization for the Source Diagnostic Test Fan

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Jones, Michael G.

2012-01-01

The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more appealing. This paper describes a broadband acoustic liner optimization study for the scale model Source Diagnostic Test fan. Specifically, in-duct attenuation predictions with a statistical fan source model are used to obtain optimum impedance spectra over a number of flow conditions for three liner locations in the bypass duct. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Typical tonal liner designs targeting single frequencies at one operating condition are first produced to provide baseline performance information. These are followed by multiple broadband design approaches culminating in a broadband liner targeting the full range of frequencies and operating conditions. The broadband liner is found to satisfy the optimum impedance objectives much better than the tonal liner designs. In addition, the broadband liner is found to provide better attenuation than the tonal designs over the full range of frequencies and operating conditions considered. Thus, the current study successfully establishes a process for the initial design and evaluation of novel broadband liner concepts for complex engine configurations.

Optimization of Time Controlled 6-mercaptopurine Delivery for Site- Specific Targeting to Colon Diseases.

PubMed

Hude, Rahul U; Jagdale, Swati C

2016-01-01

6-MP has short elimination time (<2 h) and low bioavailability (~ 50%). Present study was aimed to develop time controlled and site targeted delivery of 6-Mercaptopurine (6-MP) for treatment of colon diseases. Compression coating technique was used. 32 full factorial design was designed for optimization of the outer coat for the core tablet. For outer coat amount of Eudragit RS 100 and hydroxypropyl methylcellulose (HPMC K100) were employed as independent variables each at three levels while responses evaluated were swelling index and bursting time. Direct compression method was used for tablets formulation. 80% w/w of microcrystalline cellulose and 20% w/w of croscarmellose sodium were found to be optimum concentration for the core tablet. The outer coat of optimized batch (ED) contains 21.05% w/w Eudragit RS 100 and 78.95% w/w HPMC K100 of total polymer weight. In-vitro dissolution study indicated that combination of polymer retards the drug release in gastric region and releases ≥95% of drug in colonic region after ≥7 h. Whereas in case of in-vivo placebo x-ray imaging study had shown that the tablet reaches colonic part after 5±0.5 h providing the proof of arrival in the colon. Stability study indicated that the optimized formulation were physically and chemically stable. Present research work concluded that compression coating by Eudragit RS 100 and HPMC K100 to 6-MP core provides potential colon targeted system with advantages of reduced gastric exposure and enhanced bioavailability. Formulation can be considered as potential and promising candidate for the treatment of colon diseases.

CEM-designer: design of custom expression microarrays in the post-ENCODE Era.

PubMed

Arnold, Christian; Externbrink, Fabian; Hackermüller, Jörg; Reiche, Kristin

2014-11-10

Microarrays are widely used in gene expression studies, and custom expression microarrays are popular to monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomes uncovered recently make custom expression microarray design a non-trivial task. Pervasive transcription and alternative processing of transcripts generate a wealth of interweaved transcripts that requires well-considered probe design strategies and is largely neglected in existing approaches. We developed the web server CEM-Designer that facilitates microarray platform independent design of custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collection and generation of a set of unique target sequences from different sources and (ii) the selection of a set of sensitive and specific probes that optimally represents the target sequences. Probe design itself is left to third party software to ensure that probes meet provider-specific constraints. CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de. Copyright © 2014 Elsevier B.V. All rights reserved.

Improving Representational Competence with Concrete Models

ERIC Educational Resources Information Center

Stieff, Mike; Scopelitis, Stephanie; Lira, Matthew E.; DeSutter, Dane

2016-01-01

Representational competence is a primary contributor to student learning in science, technology, engineering, and math (STEM) disciplines and an optimal target for instruction at all educational levels. We describe the design and implementation of a learning activity that uses concrete models to improve students' representational competence and…

Analytical Quality by Design Approach in RP-HPLC Method Development for the Assay of Etofenamate in Dosage Forms

PubMed Central

Peraman, R.; Bhadraya, K.; Reddy, Y. Padmanabha; Reddy, C. Surayaprakash; Lokesh, T.

2015-01-01

By considering the current regulatory requirement for an analytical method development, a reversed phase high performance liquid chromatographic method for routine analysis of etofenamate in dosage form has been optimized using analytical quality by design approach. Unlike routine approach, the present study was initiated with understanding of quality target product profile, analytical target profile and risk assessment for method variables that affect the method response. A liquid chromatography system equipped with a C18 column (250×4.6 mm, 5 μ), a binary pump and photodiode array detector were used in this work. The experiments were conducted based on plan by central composite design, which could save time, reagents and other resources. Sigma Tech software was used to plan and analyses the experimental observations and obtain quadratic process model. The process model was used for predictive solution for retention time. The predicted data from contour diagram for retention time were verified actually and it satisfied with actual experimental data. The optimized method was achieved at 1.2 ml/min flow rate of using mobile phase composition of methanol and 0.2% triethylamine in water at 85:15, % v/v, pH adjusted to 6.5. The method was validated and verified for targeted method performances, robustness and system suitability during method transfer. PMID:26997704

Development of a polymerase chain reaction assay for the rapid detection of the oral pathogenic bacterium, Selenomonas noxia.

PubMed

Cruz, Patricia; Mehretu, Arthuro M; Buttner, Mark P; Trice, Theresa; Howard, Katherine M

2015-08-14

In recent studies, periodontal health has been linked to being overweight and/or obese. Among common oral bacteria, Selenomonas noxia has been implicated in converting periodontal health to disease, and Selenomonas species have also been found in gastric ulcers. The objective of this study was to develop and validate a quantitative polymerase chain reaction (qPCR) assay for the specific and rapid detection of S. noxia. Two oligonucleotide primer pairs and one probe were designed and tested to determine optimal amplification signal with three strains of S. noxia. The PCR assay was tested against fourteen non-target organisms, including closely related oral Selenomonads, one phylogenetically closely related bacterium, and two commonly isolated oral bacteria. One of the primer sets was more sensitive at detecting the target organism and was selected for optimization and validation experiments. The designed primers and probe amplified the target organism with 100% specificity. PCR inhibition was observed with an internal positive control, and inhibition was resolved by diluting the DNA extract. The qPCR assay designed in this study can be used to specifically detect S. noxia in the clinical setting and in future research involving the enhanced detection of S. noxia. The assay can also be used in epidemiological studies for understanding the role of S. noxia in disease processes including, but not limited to, oral health and obesity of infectious origin.

Design and physicochemical characterization of advanced spray-dried tacrolimus multifunctional particles for inhalation

PubMed Central

Wu, Xiao; Hayes, Don; Zwischenberger, Joseph B; Kuhn, Robert J; Mansour, Heidi M

2013-01-01

The aim of this study was to design, develop, and optimize respirable tacrolimus microparticles and nanoparticles and multifunctional tacrolimus lung surfactant mimic particles for targeted dry powder inhalation delivery as a pulmonary nanomedicine. Particles were rationally designed and produced at different pump rates by advanced spray-drying particle engineering design from organic solution in closed mode. In addition, multifunctional tacrolimus lung surfactant mimic dry powder particles were prepared by co-dissolving tacrolimus and lung surfactant mimic phospholipids in methanol, followed by advanced co-spray-drying particle engineering design technology in closed mode. The lung surfactant mimic phospholipids were 1,2-dipalmitoyl-sn-glycero-3-phosphocholine and 1,2-dipalmitoyl-sn-glycero-3-[phosphor-rac-1-glycerol]. Laser diffraction particle sizing indicated that the particle size distributions were suitable for pulmonary delivery, whereas scanning electron microscopy imaging indicated that these particles had both optimal particle morphology and surface morphology. Increasing the pump rate percent of tacrolimus solution resulted in a larger particle size. X-ray powder diffraction patterns and differential scanning calorimetry thermograms indicated that spray drying produced particles with higher amounts of amorphous phase. X-ray powder diffraction and differential scanning calorimetry also confirmed the preservation of the phospholipid bilayer structure in the solid state for all engineered respirable particles. Furthermore, it was observed in hot-stage micrographs that raw tacrolimus displayed a liquid crystal transition following the main phase transition, which is consistent with its interfacial properties. Water vapor uptake and lyotropic phase transitions in the solid state at varying levels of relative humidity were determined by gravimetric vapor sorption technique. Water content in the various powders was very low and well within the levels necessary for dry powder inhalation, as quantified by Karl Fisher coulometric titration. Conclusively, advanced spray-drying particle engineering design from organic solution in closed mode was successfully used to design and optimize solid-state particles in the respirable size range necessary for targeted pulmonary delivery, particularly for the deep lung. These particles were dry, stable, and had optimal properties for dry powder inhalation as a novel pulmonary nanomedicine. PMID:23403805

Detumbling control for kinematically redundant space manipulator post-grasping a rotational satellite

NASA Astrophysics Data System (ADS)

Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

2017-12-01

The objective of this paper is to establish a detumbling strategy and a coordination control scheme for a kinematically redundant space manipulator post-grasping a rotational satellite. First, the dynamics of the kinematically redundant space robot after grasping the target is presented, which lays the foundation for the coordination controller design. Subsequently, optimal detumbling and motion planning strategy for the post-capture phase is proposed based on the quartic Bézier curves and adaptive differential evolution (DE) algorithm subject to the specific constraints. Both detumbling time and control torques are taken into account for the generation of the optimal detumbling strategy. Furthermore, a coordination control scheme is presented to track the designed reference path while regulating the attitude of the chaser to a desired value, which successfully dumps the initial angular velocity of the rotational satellite and controls the base attitude synchronously. Simulation results are presented for detumbling a target with rotational motion using a 7 degree-of-freedom (DOF) redundant space manipulator, which demonstrates the effectiveness of the proposed method.

Tailoring nanoparticle designs to target cancer based on tumor pathophysiology

PubMed Central

Sykes, Edward A.; Dai, Qin; Sarsons, Christopher D.; Chen, Juan; Rocheleau, Jonathan V.; Hwang, David M.; Zheng, Gang; Cramb, David T.; Rinker, Kristina D.; Chan, Warren C. W.

2016-01-01

Nanoparticles can provide significant improvements in the diagnosis and treatment of cancer. How nanoparticle size, shape, and surface chemistry can affect their accumulation, retention, and penetration in tumors remains heavily investigated, because such findings provide guiding principles for engineering optimal nanosystems for tumor targeting. Currently, the experimental focus has been on particle design and not the biological system. Here, we varied tumor volume to determine whether cancer pathophysiology can influence tumor accumulation and penetration of different sized nanoparticles. Monte Carlo simulations were also used to model the process of nanoparticle accumulation. We discovered that changes in pathophysiology associated with tumor volume can selectively change tumor uptake of nanoparticles of varying size. We further determine that nanoparticle retention within tumors depends on the frequency of interaction of particles with the perivascular extracellular matrix for smaller nanoparticles, whereas transport of larger nanomaterials is dominated by Brownian motion. These results reveal that nanoparticles can potentially be personalized according to a patient’s disease state to achieve optimal diagnostic and therapeutic outcomes. PMID:26884153

Emerging engineering principles for yield improvement in microbial cell design.

PubMed

Comba, Santiago; Arabolaza, Ana; Gramajo, Hugo

2012-01-01

Metabolic Engineering has undertaken a rapid transformation in the last ten years making real progress towards the production of a wide range of molecules and fine chemicals using a designed cellular host. However, the maximization of product yields through pathway optimization is a constant and central challenge of this field. Traditional methods used to improve the production of target compounds from engineered biosynthetic pathways in non-native hosts include: codon usage optimization, elimination of the accumulation of toxic intermediates or byproducts, enhanced production of rate-limiting enzymes, selection of appropriate promoter and ribosome binding sites, application of directed evolution of enzymes, and chassis re-circuit. Overall, these approaches tend to be specific for each engineering project rather than a systematic practice based on a more generalizable strategy. In this mini-review, we highlight some novel and extensive approaches and tools intended to address the improvement of a target product formation, founded in sophisticated principles such as dynamic control, pathway genes modularization, and flux modeling.

Emerging engineering principles for yield improvement in microbial cell design

PubMed Central

Comba, Santiago; Arabolaza, Ana; Gramajo, Hugo

2012-01-01

Metabolic Engineering has undertaken a rapid transformation in the last ten years making real progress towards the production of a wide range of molecules and fine chemicals using a designed cellular host. However, the maximization of product yields through pathway optimization is a constant and central challenge of this field. Traditional methods used to improve the production of target compounds from engineered biosynthetic pathways in non-native hosts include: codon usage optimization, elimination of the accumulation of toxic intermediates or byproducts, enhanced production of rate-limiting enzymes, selection of appropriate promoter and ribosome binding sites, application of directed evolution of enzymes, and chassis re-circuit. Overall, these approaches tend to be specific for each engineering project rather than a systematic practice based on a more generalizable strategy. In this mini-review, we highlight some novel and extensive approaches and tools intended to address the improvement of a target product formation, founded in sophisticated principles such as dynamic control, pathway genes modularization, and flux modeling. PMID:24688676

The Development of CK2 Inhibitors: From Traditional Pharmacology to in Silico Rational Drug Design

PubMed Central

Cozza, Giorgio

2017-01-01

Casein kinase II (CK2) is an ubiquitous and pleiotropic serine/threonine protein kinase able to phosphorylate hundreds of substrates. Being implicated in several human diseases, from neurodegeneration to cancer, the biological roles of CK2 have been intensively studied. Upregulation of CK2 has been shown to be critical to tumor progression, making this kinase an attractive target for cancer therapy. Several CK2 inhibitors have been developed so far, the first being discovered by “trial and error testing”. In the last decade, the development of in silico rational drug design has prompted the discovery, de novo design and optimization of several CK2 inhibitors, active in the low nanomolar range. The screening of big chemical libraries and the optimization of hit compounds by Structure Based Drug Design (SBDD) provide telling examples of a fruitful application of rational drug design to the development of CK2 inhibitors. Ligand Based Drug Design (LBDD) models have been also applied to CK2 drug discovery, however they were mainly focused on methodology improvements rather than being critical for de novo design and optimization. This manuscript provides detailed description of in silico methodologies whose applications to the design and development of CK2 inhibitors proved successful and promising. PMID:28230762

Targeted therapy using nanotechnology: focus on cancer

PubMed Central

Sanna, Vanna; Pala, Nicolino; Sechi, Mario

2014-01-01

Recent advances in nanotechnology and biotechnology have contributed to the development of engineered nanoscale materials as innovative prototypes to be used for biomedical applications and optimized therapy. Due to their unique features, including a large surface area, structural properties, and a long circulation time in blood compared with small molecules, a plethora of nanomaterials has been developed, with the potential to revolutionize the diagnosis and treatment of several diseases, in particular by improving the sensitivity and recognition ability of imaging contrast agents and by selectively directing bioactive agents to biological targets. Focusing on cancer, promising nanoprototypes have been designed to overcome the lack of specificity of conventional chemotherapeutic agents, as well as for early detection of precancerous and malignant lesions. However, several obstacles, including difficulty in achieving the optimal combination of physicochemical parameters for tumor targeting, evading particle clearance mechanisms, and controlling drug release, prevent the translation of nanomedicines into therapy. In spite of this, recent efforts have been focused on developing functionalized nanoparticles for delivery of therapeutic agents to specific molecular targets overexpressed on different cancer cells. In particular, the combination of targeted and controlled-release polymer nanotechnologies has resulted in a new programmable nanotherapeutic formulation of docetaxel, namely BIND-014, which recently entered Phase II clinical testing for patients with solid tumors. BIND-014 has been developed to overcome the limitations facing delivery of nanoparticles to many neoplasms, and represents a validated example of targeted nanosystems with the optimal biophysicochemical properties needed for successful tumor eradication. PMID:24531078

Optimization of personalized therapies for anticancer treatment.

PubMed

Vazquez, Alexei

2013-04-12

As today, there are hundreds of targeted therapies for the treatment of cancer, many of which have companion biomarkers that are in use to inform treatment decisions. If we would consider this whole arsenal of targeted therapies as a treatment option for every patient, very soon we will reach a scenario where each patient is positive for several markers suggesting their treatment with several targeted therapies. Given the documented side effects of anticancer drugs, it is clear that such a strategy is unfeasible. Here, we propose a strategy that optimizes the design of combinatorial therapies to achieve the best response rates with the minimal toxicity. In this methodology markers are assigned to drugs such that we achieve a high overall response rate while using personalized combinations of minimal size. We tested this methodology in an in silico cancer patient cohort, constructed from in vitro data for 714 cell lines and 138 drugs reported by the Sanger Institute. Our analysis indicates that, even in the context of personalized medicine, combinations of three or more drugs are required to achieve high response rates. Furthermore, patient-to-patient variations in pharmacokinetics have a significant impact in the overall response rate. A 10 fold increase in the pharmacokinetics variations resulted in a significant drop the overall response rate. The design of optimal combinatorial therapy for anticancer treatment requires a transition from the one-drug/one-biomarker approach to global strategies that simultaneously assign makers to a catalog of drugs. The methodology reported here provides a framework to achieve this transition.

Interplanetary Trajectory Design for the Asteroid Robotic Redirect Mission Alternate Approach Trade Study

NASA Technical Reports Server (NTRS)

Merrill, Raymond Gabriel; Qu, Min; Vavrina, Matthew A.; Englander, Jacob A.; Jones, Christopher A.

2014-01-01

This paper presents mission performance analysis methods and results for the Asteroid Robotic Redirect Mission (ARRM) option to capture a free standing boulder on the surface of a 100 m or larger NEA. It details the optimization and design of heliocentric low-thrust trajectories to asteroid targets for the ARRM solar electric propulsion spacecraft. Extensive searches were conducted to determine asteroid targets with large pick-up mass potential and potential observation opportunities. Interplanetary trajectory approximations were developed in method based tools for Itokawa, Bennu, 1999 JU3, and 2008 EV5 and were validated by end-to-end integrated trajectories.

Photoaffinity labeling in target- and binding-site identification

PubMed Central

Smith, Ewan; Collins, Ian

2015-01-01

Photoaffinity labeling (PAL) using a chemical probe to covalently bind its target in response to activation by light has become a frequently used tool in drug discovery for identifying new drug targets and molecular interactions, and for probing the location and structure of binding sites. Methods to identify the specific target proteins of hit molecules from phenotypic screens are highly valuable in early drug discovery. In this review, we summarize the principles of PAL including probe design and experimental techniques for in vitro and live cell investigations. We emphasize the need to optimize and validate probes and highlight examples of the successful application of PAL across multiple disease areas. PMID:25686004

Optimization of a binding fragment targeting the "enlarged methionine pocket" leads to potent Trypanosoma brucei methionyl-tRNA synthetase inhibitors.

PubMed

Huang, Wenlin; Zhang, Zhongsheng; Ranade, Ranae M; Gillespie, J Robert; Barros-Álvarez, Ximena; Creason, Sharon A; Shibata, Sayaka; Verlinde, Christophe L M J; Hol, Wim G J; Buckner, Frederick S; Fan, Erkang

2017-06-15

Potent inhibitors of Trypanosoma brucei methionyl-tRNA synthetase were previously designed using a structure-guided approach. Compounds 1 and 2 were the most active compounds in the cyclic and linear linker series, respectively. To further improve cellular potency, SAR investigation of a binding fragment targeting the "enlarged methionine pocket" (EMP) was performed. The optimization led to the identification of a 6,8-dichloro-tetrahydroquinoline ring as a favorable fragment to bind the EMP. Replacement of 3,5-dichloro-benzyl group (the EMP binding fragment) of inhibitor 2 using this tetrahydroquinoline fragment resulted in compound 13, that exhibited an EC 50 of 4nM. Copyright © 2017 Elsevier Ltd. All rights reserved.

A high-efficiency low-voltage class-E PA for IoT applications in sub-1 GHz frequency range

NASA Astrophysics Data System (ADS)

Zhou, Chenyi; Lu, Zhenghao; Gu, Jiangmin; Yu, Xiaopeng

2017-10-01

We present and propose a complete and iterative integrated-circuit and electro-magnetic (EM) co-design methodology and procedure for a low-voltage sub-1 GHz class-E PA. The presented class-E PA consists of the on-chip power transistor, the on-chip gate driving circuits, the off-chip tunable LC load network and the off-chip LC ladder low pass filter. The design methodology includes an explicit design equation based circuit components values' analysis and numerical derivation, output power targeted transistor size and low pass filter design, and power efficiency oriented design optimization. The proposed design procedure includes the power efficiency oriented LC network tuning, the detailed circuit/EM co-simulation plan on integrated circuit level, package level and PCB level to ensure an accurate simulation to measurement match and first pass design success. The proposed PA is targeted to achieve more than 15 dBm output power delivery and 40% power efficiency at 433 MHz frequency band with 1.5 V low voltage supply. The LC load network is designed to be off-chip for the purpose of easy tuning and optimization. The same circuit can be extended to all sub-1 GHz applications with the same tuning and optimization on the load network at different frequencies. The amplifier is implemented in 0.13 μm CMOS technology with a core area occupation of 400 μm by 300 μm. Measurement results showed that it provided power delivery of 16.42 dBm at antenna with efficiency of 40.6%. A harmonics suppression of 44 dBc is achieved, making it suitable for massive deployment of IoT devices. Project supported by the National Natural Science Foundation of China (No. 61574125) and the Industry Innovation Project of Suzhou City of China (No. SYG201641).

Designing manufacturable filters for a 16-band plenoptic camera using differential evolution

NASA Astrophysics Data System (ADS)

Doster, Timothy; Olson, Colin C.; Fleet, Erin; Yetzbacher, Michael; Kanaev, Andrey; Lebow, Paul; Leathers, Robert

2017-05-01

A 16-band plenoptic camera allows for the rapid exchange of filter sets via a 4x4 filter array on the lens's front aperture. This ability to change out filters allows for an operator to quickly adapt to different locales or threat intelligence. Typically, such a system incorporates a default set of 16 equally spaced at-topped filters. Knowing the operating theater or the likely targets of interest it becomes advantageous to tune the filters. We propose using a modified beta distribution to parameterize the different possible filters and differential evolution (DE) to search over the space of possible filter designs. The modified beta distribution allows us to jointly optimize the width, taper and wavelength center of each single- or multi-pass filter in the set over a number of evolutionary steps. Further, by constraining the function parameters we can develop solutions which are not just theoretical but manufacturable. We examine two independent tasks: general spectral sensing and target detection. In the general spectral sensing task we utilize the theory of compressive sensing (CS) and find filters that generate codings which minimize the CS reconstruction error based on a fixed spectral dictionary of endmembers. For the target detection task and a set of known targets, we train the filters to optimize the separation of the background and target signature. We compare our results to the default 16 at-topped non-overlapping filter set which comes with the plenoptic camera and full hyperspectral resolution data which was previously acquired.

Structure Guided Development of Novel Thymidine Mimetics targeting Pseudomonas aeruginosa Thymidylate Kinase: from Hit to Lead Generation

PubMed Central

Choi, Jun Yong; Plummer, Mark S.; Starr, Jeremy; Desbonnet, Charlene R.; Soutter, Holly; Chang, Jeanne; Miller, J. Richard; Dillman, Keith; Miller, Alita A.; Roush, William R.

2012-01-01

Thymidylate kinase (TMK) is a potential chemotherapeutic target because it is directly involved in the synthesis of an essential component, thymidine triphosphate, in DNA replication. All reported TMK inhibitors are thymidine analogs, which might retard their development as potent therapeutics due to cell permeability and off-target activity against human TMK. A small molecule hit (1, IC50 = 58 μM), which has reasonable inhibition potency against Pseudomonas aeruginosa TMK (PaTMK), was identified by the analysis of the binding mode of thymidine or TP5A in a PaTMK homology model. This hit (1) was co-crystallized with PaTMK, and several potent PaTMK inhibitors (leads, 46, 47, 48, and 56, IC50 = 100–200 nM) were synthesized using computer aided design approaches including virtual synthesis/screening, which was used to guide the design of inhibitors. The binding mode of the optimized leads in PaTMK overlaps with that of other bacterial TMKs, but not with human TMK which shares few common features with the bacterial enzymes. Therefore, the optimized TMK inhibitors described here should be useful for the development of antibacterial agents targeting TMK without undesired off-target effects. In addition, an inhibition mechanism associated with the LID loop, which mimics the process of phosphate transfer from ATP to dTMP, was proposed based on X-ray co-crystal structures, homology models, and SAR results. PMID:22243413

Aerodynamic shape optimization of a HSCT type configuration with improved surface definition

NASA Technical Reports Server (NTRS)

Thomas, Almuttil M.; Tiwari, Surendra N.

1994-01-01

Two distinct parametrization procedures of generating free-form surfaces to represent aerospace vehicles are presented. The first procedure is the representation using spline functions such as nonuniform rational b-splines (NURBS) and the second is a novel (geometrical) parametrization using solutions to a suitably chosen partial differential equation. The main idea is to develop a surface which is more versatile and can be used in an optimization process. Unstructured volume grid is generated by an advancing front algorithm and solutions obtained using an Euler solver. Grid sensitivity with respect to surface design parameters and aerodynamic sensitivity coefficients based on potential flow is obtained using an automatic differentiator precompiler software tool. Aerodynamic shape optimization of a complete aircraft with twenty four design variables is performed. High speed civil transport aircraft (HSCT) configurations are targeted to demonstrate the process.

Optimal design of damping layers in SMA/GFRP laminated hybrid composites

NASA Astrophysics Data System (ADS)

Haghdoust, P.; Cinquemani, S.; Lo Conte, A.; Lecis, N.

2017-10-01

This work describes the optimization of the shape profiles for shape memory alloys (SMA) sheets in hybrid layered composite structures, i.e. slender beams or thinner plates, designed for the passive attenuation of flexural vibrations. The paper starts with the description of the material and architecture of the investigated hybrid layered composite. An analytical method, for evaluating the energy dissipation inside a vibrating cantilever beam is developed. The analytical solution is then followed by a shape profile optimization of the inserts, using a genetic algorithm to minimize the SMA material layer usage, while maintaining target level of structural damping. Delamination problem at SMA/glass fiber reinforced polymer interface is discussed. At the end, the proposed methodology has been applied to study the hybridization of a wind turbine layered structure blade with SMA material, in order to increase its passive damping.

Feasibility study on the use of uranium in photoneutron target and BSA optimization for Linac based BNCT

NASA Astrophysics Data System (ADS)

Rahmani, Faezeh; Shahriari, Majid; Minoochehr, Abdolhamid; Nedaie, Hasan

2011-06-01

A hybrid photoneutron target including natural uranium has been studied for a 20 MeV linear electron accelerator (Linac) based Boron Neutron Capture Therapy (BNCT) facility. In this study the possibility of using uranium to increase the neutron intensity has been investigated by focusing on the time dependence behavior of the build-up and decay of the delayed gamma rays from fission fragments and activation products through photo-fission reactions in the BSA (Beam Shaping Assembly) configuration design. Delayed components of neutrons and photons were calculated. The obtained BSA parameters are in agreement with the IAEA recommendation and compared to the hybrid photoneutron target without U. The epithermal flux in the suggested design is 2.67E9 (n/cm 2s/mA).

Design, modeling and simulations of a Cabinet Safe System for a linear particle accelerator of intermediate-low energy by optimization of the beam optics

NASA Astrophysics Data System (ADS)

Maidana, Carlos Omar

As part of an accelerator based Cargo Inspection System, studies were made to develop a Cabinet Safe System by Optimization of the Beam Optics of Microwave Linear Accelerators of the IAC-Varian series working on the S-band and standing wave pi/2 mode. Measurements, modeling and simulations of the main subsystems were done and a Multiple Solenoidal System was designed. This Cabinet Safe System based on a Multiple Solenoidal System minimizes the radiation field generated by the low efficiency of the microwave accelerators by optimizing the RF waveguide system and by also trapping secondaries generated in the accelerator head. These secondaries are generated mainly due to instabilities in the exit window region and particles backscattered from the target. The electron gun was also studied and software for its right mechanical design and for its optimization was developed as well. Besides the standard design method, an optimization of the injection process is accomplished by slightly modifying the gun configuration and by placing a solenoid on the waist position while avoiding threading the cathode with the magnetic flux generated. The Multiple Solenoidal System and the electron gun optimization are the backbone of a Cabinet Safe System that could be applied not only to the 25 MeV IAC-Varian microwave accelerators but, by extension, to machines of different manufacturers as well. Thus, they constitute the main topic of this dissertation.

3D reconstruction of laser projective point with projection invariant generated from five points on 2D target.

PubMed

Xu, Guan; Yuan, Jing; Li, Xiaotao; Su, Jian

2017-08-01

Vision measurement on the basis of structured light plays a significant role in the optical inspection research. The 2D target fixed with a line laser projector is designed to realize the transformations among the world coordinate system, the camera coordinate system and the image coordinate system. The laser projective point and five non-collinear points that are randomly selected from the target are adopted to construct a projection invariant. The closed form solutions of the 3D laser points are solved by the homogeneous linear equations generated from the projection invariants. The optimization function is created by the parameterized re-projection errors of the laser points and the target points in the image coordinate system. Furthermore, the nonlinear optimization solutions of the world coordinates of the projection points, the camera parameters and the lens distortion coefficients are contributed by minimizing the optimization function. The accuracy of the 3D reconstruction is evaluated by comparing the displacements of the reconstructed laser points with the actual displacements. The effects of the image quantity, the lens distortion and the noises are investigated in the experiments, which demonstrate that the reconstruction approach is effective to contribute the accurate test in the measurement system.

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

PubMed

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

2014-09-01

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

Application of optimal control theory to the design of broadband excitation pulses for high-resolution NMR.

PubMed

Skinner, Thomas E; Reiss, Timo O; Luy, Burkhard; Khaneja, Navin; Glaser, Steffen J

2003-07-01

Optimal control theory is considered as a methodology for pulse sequence design in NMR. It provides the flexibility for systematically imposing desirable constraints on spin system evolution and therefore has a wealth of applications. We have chosen an elementary example to illustrate the capabilities of the optimal control formalism: broadband, constant phase excitation which tolerates miscalibration of RF power and variations in RF homogeneity relevant for standard high-resolution probes. The chosen design criteria were transformation of I(z)-->I(x) over resonance offsets of +/- 20 kHz and RF variability of +/-5%, with a pulse length of 2 ms. Simulations of the resulting pulse transform I(z)-->0.995I(x) over the target ranges in resonance offset and RF variability. Acceptably uniform excitation is obtained over a much larger range of RF variability (approximately 45%) than the strict design limits. The pulse performs well in simulations that include homonuclear and heteronuclear J-couplings. Experimental spectra obtained from 100% 13C-labeled lysine show only minimal coupling effects, in excellent agreement with the simulations. By increasing pulse power and reducing pulse length, we demonstrate experimental excitation of 1H over +/-32 kHz, with phase variations in the spectra <8 degrees and peak amplitudes >93% of maximum. Further improvements in broadband excitation by optimized pulses (BEBOP) may be possible by applying more sophisticated implementations of the optimal control formalism.

Optimal rates for phylogenetic inference and experimental design in the era of genome-scale datasets.

PubMed

Dornburg, Alex; Su, Zhuo; Townsend, Jeffrey P

2018-06-25

With the rise of genome- scale datasets there has been a call for increased data scrutiny and careful selection of loci appropriate for attempting the resolution of a phylogenetic problem. Such loci are desired to maximize phylogenetic information content while minimizing the risk of homoplasy. Theory posits the existence of characters that evolve under such an optimum rate, and efforts to determine optimal rates of inference have been a cornerstone of phylogenetic experimental design for over two decades. However, both theoretical and empirical investigations of optimal rates have varied dramatically in their conclusions: spanning no relationship to a tight relationship between the rate of change and phylogenetic utility. Here we synthesize these apparently contradictory views, demonstrating both empirical and theoretical conditions under which each is correct. We find that optimal rates of characters-not genes-are generally robust to most experimental design decisions. Moreover, consideration of site rate heterogeneity within a given locus is critical to accurate predictions of utility. Factors such as taxon sampling or the targeted number of characters providing support for a topology are additionally critical to the predictions of phylogenetic utility based on the rate of character change. Further, optimality of rates and predictions of phylogenetic utility are not equivalent, demonstrating the need for further development of comprehensive theory of phylogenetic experimental design.

Proceedings of the Open Sessions of the Workshop on Imaging Trackers and Autonomous Acquisition Applications for Missile Guidance Held at Redstone Arsenal, Alabama on 19-20 November 1979

DTIC Science & Technology

1979-11-01

a generalized cooccurrence matrix. Describing image texture is an important problem in the design of image understanding systems . Applications as...display system design optimization and video signal processing. Based on a study by Southern Research Institute , a number of options were identified...Specification for Target Acquisition Designation System (U), RFP # AMC-DP-AAH-H4020, i2 Apr 77. 4. Terminal Homing Applications of Solid State Image

[Computational chemistry in structure-based drug design].

PubMed

Cao, Ran; Li, Wei; Sun, Han-Zi; Zhou, Yu; Huang, Niu

2013-07-01

Today, the understanding of the sequence and structure of biologically relevant targets is growing rapidly and researchers from many disciplines, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. However, it remains challenging to rationally design small molecular ligands with desired biological characteristics based on the structural information of the drug targets, which demands more accurate calculation of ligand binding free-energy. With the rapid advances in computer power and extensive efforts in algorithm development, physics-based computational chemistry approaches have played more important roles in structure-based drug design. Here we reviewed the newly developed computational chemistry methods in structure-based drug design as well as the elegant applications, including binding-site druggability assessment, large scale virtual screening of chemical database, and lead compound optimization. Importantly, here we address the current bottlenecks and propose practical solutions.

Slotted rotatable target assembly and systematic error analysis for a search for long range spin dependent interactions from exotic vector boson exchange using neutron spin rotation

NASA Astrophysics Data System (ADS)

Haddock, C.; Crawford, B.; Fox, W.; Francis, I.; Holley, A.; Magers, S.; Sarsour, M.; Snow, W. M.; Vanderwerp, J.

2018-03-01

We discuss the design and construction of a novel target array of nonmagnetic test masses used in a neutron polarimetry measurement made in search for new possible exotic spin dependent neutron-atominteractions of Nature at sub-mm length scales. This target was designed to accept and efficiently transmit a transversely polarized slow neutron beam through a series of long open parallel slots bounded by flat rectangular plates. These openings possessed equal atom density gradients normal to the slots from the flat test masses with dimensions optimized to achieve maximum sensitivity to an exotic spin-dependent interaction from vector boson exchanges with ranges in the mm - μm regime. The parallel slots were oriented differently in four quadrants that can be rotated about the neutron beam axis in discrete 90°increments using a Geneva drive. The spin rotation signals from the 4 quadrants were measured using a segmented neutron ion chamber to suppress possible systematic errors from stray magnetic fields in the target region. We discuss the per-neutron sensitivity of the target to the exotic interaction, the design constraints, the potential sources of systematic errors which could be present in this design, and our estimate of the achievable sensitivity using this method.

Assessment, design and control strategy development of a fuel cell hybrid electric vehicle for CSU's EcoCAR

NASA Astrophysics Data System (ADS)

Fox, Matthew D.

Advanced automotive technology assessment and powertrain design are increasingly performed through modeling, simulation, and optimization. But technology assessments usually target many competing criteria making any individual optimization challenging and arbitrary. Further, independent design simulations and optimizations take considerable time to execute, and design constraints and objectives change throughout the design process. Changes in design considerations usually require re-processing of simulations and more time. In this thesis, these challenges are confronted through CSU's participation in the EcoCAR2 hybrid vehicle design competition. The complexity of the competition's design objectives leveraged development of a decision support system tool to aid in multi-criteria decision making across technologies and to perform powertrain optimization. To make the decision support system interactive, and bypass the problem of long simulation times, a new approach was taken. The result of this research is CSU's architecture selection and component sizing, which optimizes a composite objective function representing the competition score. The selected architecture is an electric vehicle with an onboard range extending hydrogen fuel cell system. The vehicle has a 145kW traction motor, 18.9kWh of lithium ion battery, a 15kW fuel cell system, and 5kg of hydrogen storage capacity. Finally, a control strategy was developed that improves the vehicles performance throughout the driving range under variable driving conditions. In conclusion, the design process used in this research is reviewed and evaluated against other common design methodologies. I conclude, through the highlighted case studies, that the approach is more comprehensive than other popular design methodologies and is likely to lead to a higher quality product. The upfront modeling work and decision support system formulation will pay off in superior and timely knowledge transfer and more informed design decisions. The hypothesis is supported by the three case studies examined in this thesis.

An optimal controller for an electric ventricular-assist device: theory, implementation, and testing.

PubMed

Klute, G K; Tasch, U; Geselowitz, D B

1992-04-01

This paper addresses the development and testing of an optimal position feedback controller for the Penn State electric ventricular-assist device (EVAD). The control law is designed to minimize the expected value of the EVAD's power consumption for a targeted patient population. The closed-loop control law is implemented on an Intel 8096 microprocessor and in vitro test runs show that this controller improves the EVAD's efficiency by 15-21%, when compared with the performance of the currently used feedforward control scheme.

Optimization of a chemical identification algorithm

NASA Astrophysics Data System (ADS)

Chyba, Thomas H.; Fisk, Brian; Gunning, Christin; Farley, Kevin; Polizzi, Amber; Baughman, David; Simpson, Steven; Slamani, Mohamed-Adel; Almassy, Robert; Da Re, Ryan; Li, Eunice; MacDonald, Steve; Slamani, Ahmed; Mitchell, Scott A.; Pendell-Jones, Jay; Reed, Timothy L.; Emge, Darren

2010-04-01

A procedure to evaluate and optimize the performance of a chemical identification algorithm is presented. The Joint Contaminated Surface Detector (JCSD) employs Raman spectroscopy to detect and identify surface chemical contamination. JCSD measurements of chemical warfare agents, simulants, toxic industrial chemicals, interferents and bare surface backgrounds were made in the laboratory and under realistic field conditions. A test data suite, developed from these measurements, is used to benchmark algorithm performance throughout the improvement process. In any one measurement, one of many possible targets can be present along with interferents and surfaces. The detection results are expressed as a 2-category classification problem so that Receiver Operating Characteristic (ROC) techniques can be applied. The limitations of applying this framework to chemical detection problems are discussed along with means to mitigate them. Algorithmic performance is optimized globally using robust Design of Experiments and Taguchi techniques. These methods require figures of merit to trade off between false alarms and detection probability. Several figures of merit, including the Matthews Correlation Coefficient and the Taguchi Signal-to-Noise Ratio are compared. Following the optimization of global parameters which govern the algorithm behavior across all target chemicals, ROC techniques are employed to optimize chemical-specific parameters to further improve performance.

Progress Toward Efficient Laminar Flow Analysis and Design

NASA Technical Reports Server (NTRS)

Campbell, Richard L.; Campbell, Matthew L.; Streit, Thomas

2011-01-01

A multi-fidelity system of computer codes for the analysis and design of vehicles having extensive areas of laminar flow is under development at the NASA Langley Research Center. The overall approach consists of the loose coupling of a flow solver, a transition prediction method and a design module using shell scripts, along with interface modules to prepare the input for each method. This approach allows the user to select the flow solver and transition prediction module, as well as run mode for each code, based on the fidelity most compatible with the problem and available resources. The design module can be any method that designs to a specified target pressure distribution. In addition to the interface modules, two new components have been developed: 1) an efficient, empirical transition prediction module (MATTC) that provides n-factor growth distributions without requiring boundary layer information; and 2) an automated target pressure generation code (ATPG) that develops a target pressure distribution that meets a variety of flow and geometry constraints. The ATPG code also includes empirical estimates of several drag components to allow the optimization of the target pressure distribution. The current system has been developed for the design of subsonic and transonic airfoils and wings, but may be extendable to other speed ranges and components. Several analysis and design examples are included to demonstrate the current capabilities of the system.

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

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm

NASA Astrophysics Data System (ADS)

Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui

2017-05-01

The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.

HYBRID NEURAL NETWORK AND SUPPORT VECTOR MACHINE METHOD FOR OPTIMIZATION

NASA Technical Reports Server (NTRS)

Rai, Man Mohan (Inventor)

2005-01-01

System and method for optimization of a design associated with a response function, using a hybrid neural net and support vector machine (NN/SVM) analysis to minimize or maximize an objective function, optionally subject to one or more constraints. As a first example, the NN/SVM analysis is applied iteratively to design of an aerodynamic component, such as an airfoil shape, where the objective function measures deviation from a target pressure distribution on the perimeter of the aerodynamic component. As a second example, the NN/SVM analysis is applied to data classification of a sequence of data points in a multidimensional space. The NN/SVM analysis is also applied to data regression.

Hybrid Neural Network and Support Vector Machine Method for Optimization

NASA Technical Reports Server (NTRS)

Rai, Man Mohan (Inventor)

2007-01-01

System and method for optimization of a design associated with a response function, using a hybrid neural net and support vector machine (NN/SVM) analysis to minimize or maximize an objective function, optionally subject to one or more constraints. As a first example, the NN/SVM analysis is applied iteratively to design of an aerodynamic component, such as an airfoil shape, where the objective function measures deviation from a target pressure distribution on the perimeter of the aerodynamic component. As a second example, the NN/SVM analysis is applied to data classification of a sequence of data points in a multidimensional space. The NN/SVM analysis is also applied to data regression.

Multi-objective optimization of a low specific speed centrifugal pump using an evolutionary algorithm

NASA Astrophysics Data System (ADS)

An, Zhao; Zhounian, Lai; Peng, Wu; Linlin, Cao; Dazhuan, Wu

2016-07-01

This paper describes the shape optimization of a low specific speed centrifugal pump at the design point. The target pump has already been manually modified on the basis of empirical knowledge. A genetic algorithm (NSGA-II) with certain enhancements is adopted to improve its performance further with respect to two goals. In order to limit the number of design variables without losing geometric information, the impeller is parametrized using the Bézier curve and a B-spline. Numerical simulation based on a Reynolds averaged Navier-Stokes (RANS) turbulent model is done in parallel to evaluate the flow field. A back-propagating neural network is constructed as a surrogate for performance prediction to save computing time, while initial samples are selected according to an orthogonal array. Then global Pareto-optimal solutions are obtained and analysed. The results manifest that unexpected flow structures, such as the secondary flow on the meridian plane, have diminished or vanished in the optimized pump.

A Summary Description of a Computer Program Concept for the Design and Simulation of Solar Pond Electric Power Generation Systems

NASA Technical Reports Server (NTRS)

1984-01-01

A solar pond electric power generation subsystem, an electric power transformer and switch yard, a large solar pond, a water treatment plant, and numerous storage and evaporation ponds. Because a solar pond stores thermal energy over a long period of time, plant operation at any point in time is dependent upon past operation and future perceived generation plans. This time or past history factor introduces a new dimension in the design process. The design optimization of a plant must go beyond examination of operational state points and consider the seasonal variations in solar, solar pond energy storage, and desired plant annual duty-cycle profile. Models or design tools will be required to optimize a plant design. These models should be developed in order to include a proper but not excessive level of detail. The model should be targeted to a specific objective and not conceived as a do everything analysis tool, i.e., system design and not gradient-zone stability.

Multi-Objective Hybrid Optimal Control for Multiple-Flyby Interplanetary Mission Design Using Chemical Propulsion

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Vavrina, Matthew A.

2015-01-01

Preliminary design of high-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys and the bodies at which those flybys are performed. For some missions, such as surveys of small bodies, the mission designer also contributes to target selection. In addition, real-valued decision variables, such as launch epoch, flight times, maneuver and flyby epochs, and flyby altitudes must be chosen. There are often many thousands of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the impulsive mission design problem as a multiobjective hybrid optimal control problem. The method is demonstrated on several real-world problems.

Enhancing the branching ratios in the dissociation channels for O{sup 16}O{sup 16}O{sup 18} molecule by designing optimum laser pulses: A study using stochastic optimization

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

Talukder, Srijeeta; Chaudhury, Pinaki, E-mail: pinakc@rediffmail.com; Sen, Shrabani

We propose a strategy of using a stochastic optimization technique, namely, simulated annealing to design optimum laser pulses (both IR and UV) to achieve greater fluxes along the two dissociating channels (O{sup 18} + O{sup 16}O{sup 16} and O{sup 16} + O{sup 16}O{sup 18}) in O{sup 16}O{sup 16}O{sup 18} molecule. We show that the integrated fluxes obtained along the targeted dissociating channel is larger with the optimized pulse than with the unoptimized one. The flux ratios are also more impressive with the optimized pulse than with the unoptimized one. We also look at the evolution contours of the wavefunctions alongmore » the two channels with time after the actions of both the IR and UV pulses and compare the profiles for unoptimized (initial) and optimized fields for better understanding the results that we achieve. We also report the pulse parameters obtained as well as the final shapes they take.« less

Analytical optimal pulse shapes obtained with the aid of genetic algorithms

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

Guerrero, Rubén D., E-mail: rdguerrerom@unal.edu.co; Arango, Carlos A.; Reyes, Andrés

2015-09-28

We propose a methodology to design optimal pulses for achieving quantum optimal control on molecular systems. Our approach constrains pulse shapes to linear combinations of a fixed number of experimentally relevant pulse functions. Quantum optimal control is obtained by maximizing a multi-target fitness function using genetic algorithms. As a first application of the methodology, we generated an optimal pulse that successfully maximized the yield on a selected dissociation channel of a diatomic molecule. Our pulse is obtained as a linear combination of linearly chirped pulse functions. Data recorded along the evolution of the genetic algorithm contained important information regarding themore » interplay between radiative and diabatic processes. We performed a principal component analysis on these data to retrieve the most relevant processes along the optimal path. Our proposed methodology could be useful for performing quantum optimal control on more complex systems by employing a wider variety of pulse shape functions.« less

Photoacoustic design parameter optimization for deep tissue imaging by numerical simulation

NASA Astrophysics Data System (ADS)

Wang, Zhaohui; Ha, Seunghan; Kim, Kang

2012-02-01

A new design of light illumination scheme for deep tissue photoacoustic (PA) imaging, a light catcher, is proposed and evaluated by in silico simulation. Finite element (FE)-based numerical simulation model was developed for photoacoustic (PA) imaging in soft tissues. In this in silico simulation using a commercially available FE simulation package (COMSOL MultiphysicsTM, COMSOL Inc., USA), a short-pulsed laser point source (pulse length of 5 ns) was placed in water on the tissue surface. Overall, four sets of simulation models were integrated together to describe the physical principles of PA imaging. Light energy transmission through background tissues from the laser source to the target tissue or contrast agent was described by diffusion equation. The absorption of light energy and its conversion to heat by target tissue or contrast agent was modeled using bio-heat equation. The heat then causes the stress and strain change, and the resulting displacement of the target surface produces acoustic pressure. The created wide-band acoustic pressure will propagate through background tissues to the ultrasound detector, which is governed by acoustic wave equation. Both optical and acoustical parameters in soft tissues such as scattering, absorption, and attenuation are incorporated in tissue models. PA imaging performance with different design parameters of the laser source and energy delivery scheme was investigated. The laser light illumination into the deep tissues can be significantly improved by up to 134.8% increase of fluence rate by introducing a designed compact light catcher with highly reflecting inner surface surrounding the light source. The optimized parameters through this simulation will guide the design of PA system for deep tissue imaging, and help to form the base protocols of experimental evaluations in vitro and in vivo.

Preparation, Characterization, and Optimization of Folic Acid-Chitosan-Methotrexate Core-Shell Nanoparticles by Box-Behnken Design for Tumor-Targeted Drug Delivery.

PubMed

Naghibi Beidokhti, Hamid Reza; Ghaffarzadegan, Reza; Mirzakhanlouei, Sasan; Ghazizadeh, Leila; Dorkoosh, Farid Abedin

2017-01-01

The objective of this study was to investigate the combined influence of independent variables in the preparation of folic acid-chitosan-methotrexate nanoparticles (FA-Chi-MTX NPs). These NPs were designed and prepared for targeted drug delivery in tumor. The NPs of each batch were prepared by coaxial electrospray atomization method and evaluated for particle size (PS) and particle size distribution (PSD). The independent variables were selected to be concentration of FA-chitosan, ratio of shell solution flow rate to core solution flow rate, and applied voltage. The process design of experiments (DOE) was obtained with three factors in three levels by Design expert software. Box-Behnken design was used to select 15 batches of experiments randomly. The chemical structure of FA-chitosan was examined by FTIR. The NPs of each batch were collected separately, and morphologies of NPs were investigated by field emission scanning electron microscope (FE-SEM). The captured pictures of all batches were analyzed by ImageJ software. Mean PS and PSD were calculated for each batch. Polynomial equation was produced for each response. The FE-SEM results showed the mean diameter of the core-shell NPs was around 304 nm, and nearly 30% of the produced NPs are in the desirable range. Optimum formulations were selected. The validation of DOE optimization results showed errors around 2.5 and 2.3% for PS and PSD, respectively. Moreover, the feasibility of using prepared NPs to target tumor extracellular pH was shown, as drug release was greater in the pH of endosome (acidic medium). Finally, our results proved that FA-Chi-MTX NPs were active against the human epithelial cervical cancer (HeLa) cells.

Tabu Search enhances network robustness under targeted attacks

NASA Astrophysics Data System (ADS)

Sun, Shi-wen; Ma, Yi-lin; Li, Rui-qi; Wang, Li; Xia, Cheng-yi

2016-03-01

We focus on the optimization of network robustness with respect to intentional attacks on high-degree nodes. Given an existing network, this problem can be considered as a typical single-objective combinatorial optimization problem. Based on the heuristic Tabu Search optimization algorithm, a link-rewiring method is applied to reconstruct the network while keeping the degree of every node unchanged. Through numerical simulations, BA scale-free network and two real-world networks are investigated to verify the effectiveness of the proposed optimization method. Meanwhile, we analyze how the optimization affects other topological properties of the networks, including natural connectivity, clustering coefficient and degree-degree correlation. The current results can help to improve the robustness of existing complex real-world systems, as well as to provide some insights into the design of robust networks.

Identifying members of the domain Archaea with rRNA-targeted oligonucleotide probes.

PubMed

Burggraf, S; Mayer, T; Amann, R; Schadhauser, S; Woese, C R; Stetter, K O

1994-09-01

Two 16S rRNA-targeted oligonucleotide probes were designed for the archaeal kingdoms Euryachaeota and Crenarchaeota. Probe specificities were evaluated by nonradioactive dot blot hybridization against selected reference organisms. The successful application of fluorescent-probe derivatives for whole-cell hybridization required organism-specific optimizations of fixation and hybridization conditions to assure probe penetration and morphological integrity of the cells. The probes allowed preliminary grouping of three new hyperthermophilic isolates. Together with other group-specific rRNA-targeted oligonucleotide probes, these probes will facilitate rapid in situ monitoring of the populations present in hydrothermal systems and support cultivation attempts.

Evolution of Magnetized Liner Inertial Fusion (MagLIF) Targets

DOE PAGES

Fooks, J. A.; Carlson, L. C.; Fitzsimmons, P.; ...

2017-12-19

Here, the magnetized liner inertial fusion (MagLIF) experimental campaign conducted at the University of Rochester’s Laboratory for Laser Energetics (LLE) has evolved significantly since its start in 2014. Scientific requirements and OMEGA EP system technology both have progressed, resulting in necessary and available updates to the target design. These include, but are not limited to: optimizing target dimensions and aspect ratios to maximize survival at desired pressures; coating target components to enhance physics diagnosis; precision-machining diagnostic windows along the axis of the target; improving fiducial placement reproducibility and reducing subsequent assembly time by 50%; and implementing gas-pressure transducers on themore » targets. In addition, target fabrication techniques have changed and improved, allowing for simpler target reproducibility and decreased assembly time. To date, eleven variations of targets have been fabricated, with successful target fielding ranging from 1 to 20atm internal pressure and a maximum survivability of 33atm.« less

Evolution of Magnetized Liner Inertial Fusion (MagLIF) Targets

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

Fooks, J. A.; Carlson, L. C.; Fitzsimmons, P.

Here, the magnetized liner inertial fusion (MagLIF) experimental campaign conducted at the University of Rochester’s Laboratory for Laser Energetics (LLE) has evolved significantly since its start in 2014. Scientific requirements and OMEGA EP system technology both have progressed, resulting in necessary and available updates to the target design. These include, but are not limited to: optimizing target dimensions and aspect ratios to maximize survival at desired pressures; coating target components to enhance physics diagnosis; precision-machining diagnostic windows along the axis of the target; improving fiducial placement reproducibility and reducing subsequent assembly time by 50%; and implementing gas-pressure transducers on themore » targets. In addition, target fabrication techniques have changed and improved, allowing for simpler target reproducibility and decreased assembly time. To date, eleven variations of targets have been fabricated, with successful target fielding ranging from 1 to 20atm internal pressure and a maximum survivability of 33atm.« less

Formulation and optimization of doxorubicin loaded polymeric nanoparticles using Box-Behnken design: ex-vivo stability and in-vitro activity.

PubMed

Shaikh, Muhammad Vaseem; Kala, Manika; Nivsarkar, Manish

2017-03-30

Biodegradable nanoparticles (NPs) have gained tremendous interest for targeting chemotherapeutic drugs to the tumor environment. Inspite of several advances sufficient encapsulation along with the controlled release and desired size range have remained as considerable challenges. Hence, the present study examines the formulation optimization of doxorubicin loaded PLGA NPs (DOX-PLGA-NPs), prepared by single emulsion method for cancer targeting. Critical process parameters (CPP) were selected by initial screening. Later, Box-Behnken design (BBD) was used for analyzing the effect of the selected CPP on critical quality attributes (CQA) and to generate a design space. The optimized formulation was stabilized by lyophilization and was used for in-vitro drug release and in-vitro activity on A549 cell line. Moreover, colloidal stability of the NPs in the biological milieu was assessed. Amount of PLGA and PVA, oil:water ratio and sonication time were the selected independent factors for BBD. The statistical data showed that a quadratic model was fitted to the data obtained. Additionally, the lack of fit values for the models was not significant. The delivery system showed sustained release behavior over a period of 120h and was governed by Fickian diffusion. The multipoint analysis at 24, 48 and 72h showed gradual reduction in IC50 value of DOX-PLGA-NPs (p<0.05, Fig. 9). DOX-PLGA-NPs were found to be stable in the biological fluids indicating their in-vivo applicability. In conclusion, optimization of the DOX-PLGA-NPs by BBD yielded in a promising drug carrier for doxorubicin that could provide a novel treatment modality for cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

A framework for accelerated phototrophic bioprocess development: integration of parallelized microscale cultivation, laboratory automation and Kriging-assisted experimental design.

PubMed

Morschett, Holger; Freier, Lars; Rohde, Jannis; Wiechert, Wolfgang; von Lieres, Eric; Oldiges, Marco

2017-01-01

Even though microalgae-derived biodiesel has regained interest within the last decade, industrial production is still challenging for economic reasons. Besides reactor design, as well as value chain and strain engineering, laborious and slow early-stage parameter optimization represents a major drawback. The present study introduces a framework for the accelerated development of phototrophic bioprocesses. A state-of-the-art micro-photobioreactor supported by a liquid-handling robot for automated medium preparation and product quantification was used. To take full advantage of the technology's experimental capacity, Kriging-assisted experimental design was integrated to enable highly efficient execution of screening applications. The resulting platform was used for medium optimization of a lipid production process using Chlorella vulgaris toward maximum volumetric productivity. Within only four experimental rounds, lipid production was increased approximately threefold to 212 ± 11 mg L -1  d -1 . Besides nitrogen availability as a key parameter, magnesium, calcium and various trace elements were shown to be of crucial importance. Here, synergistic multi-parameter interactions as revealed by the experimental design introduced significant further optimization potential. The integration of parallelized microscale cultivation, laboratory automation and Kriging-assisted experimental design proved to be a fruitful tool for the accelerated development of phototrophic bioprocesses. By means of the proposed technology, the targeted optimization task was conducted in a very timely and material-efficient manner.

Numerical optimization of perturbative coils for tokamaks

NASA Astrophysics Data System (ADS)

Lazerson, Samuel; Park, Jong-Kyu; Logan, Nikolas; Boozer, Allen; NSTX-U Research Team

2014-10-01

Numerical optimization of coils which apply three dimensional (3D) perturbative fields to tokamaks is presented. The application of perturbative 3D magnetic fields in tokamaks is now commonplace for control of error fields, resistive wall modes, resonant field drive, and neoclassical toroidal viscosity (NTV) torques. The design of such systems has focused on control of toroidal mode number, with coil shapes based on simple window-pane designs. In this work, a numerical optimization suite based on the STELLOPT 3D equilibrium optimization code is presented. The new code, IPECOPT, replaces the VMEC equilibrium code with the IPEC perturbed equilibrium code, and targets NTV torque by coupling to the PENT code. Fixed boundary optimizations of the 3D fields for the NSTX-U experiment are underway. Initial results suggest NTV torques can be driven by normal field spectrums which are not pitch-resonant with the magnetic field lines. Work has focused on driving core torque with n = 1 and edge torques with n = 3 fields. Optimizations of the coil currents for the planned NSTX-U NCC coils highlight the code's free boundary capability. This manuscript has been authored by Princeton University under Contract Number DE-AC02-09CH11466 with the U.S. Department of Energy.

Fragment informatics and computational fragment-based drug design: an overview and update.

PubMed

Sheng, Chunquan; Zhang, Wannian

2013-05-01

Fragment-based drug design (FBDD) is a promising approach for the discovery and optimization of lead compounds. Despite its successes, FBDD also faces some internal limitations and challenges. FBDD requires a high quality of target protein and good solubility of fragments. Biophysical techniques for fragment screening necessitate expensive detection equipment and the strategies for evolving fragment hits to leads remain to be improved. Regardless, FBDD is necessary for investigating larger chemical space and can be applied to challenging biological targets. In this scenario, cheminformatics and computational chemistry can be used as alternative approaches that can significantly improve the efficiency and success rate of lead discovery and optimization. Cheminformatics and computational tools assist FBDD in a very flexible manner. Computational FBDD can be used independently or in parallel with experimental FBDD for efficiently generating and optimizing leads. Computational FBDD can also be integrated into each step of experimental FBDD and help to play a synergistic role by maximizing its performance. This review will provide critical analysis of the complementarity between computational and experimental FBDD and highlight recent advances in new algorithms and successful examples of their applications. In particular, fragment-based cheminformatics tools, high-throughput fragment docking, and fragment-based de novo drug design will provide the focus of this review. We will also discuss the advantages and limitations of different methods and the trends in new developments that should inspire future research. © 2012 Wiley Periodicals, Inc.

Optimization of a Diaphragm for a Micro-Shock Tube-Based Drug Delivery Method

PubMed Central

Rathod, Vivek T.; Mahapatra, Debiprosad Roy

2017-01-01

This paper presents the design optimization of diaphragms for a micro-shock tube-based drug delivery device. The function of the diaphragm is to impart the required velocity and direction to the loosely held drug particles on the diaphragm through van der Waals interaction. The finite element model-based studies involved diaphragms made up of copper, brass and aluminium. The study of the influence of material and geometric parameters serves as a vital tool in optimizing the magnitude and direction of velocity distribution on the diaphragm surface. Experiments carried out using a micro-shock tube validate the final deformed shape of the diaphragms determined from the finite element simulation. The diaphragm yields a maximum velocity of 335 m/s for which the maximum deviation of the velocity vector is 0.62°. Drug particles that travel to the destination target tissue are simulated using the estimated velocity distribution and angular deviation. Further, a theoretical model of penetration helps in the prediction of the drug particle penetration in the skin tissue like a target, which is found to be 0.126 mm. The design and calibration procedure of a micro-shock tube device to alter drug particle penetration considering the skin thickness and property are presented. PMID:28952503

Optimization of a magnetic capture RT-LAMP assay for fast and real-time detection of potato virus Y and differentiation of N and O serotypes.

PubMed

Treder, Krzysztof; Chołuj, Joanna; Zacharzewska, Bogumiła; Babujee, Lavanya; Mielczarek, Mateusz; Burzyński, Adam; Rakotondrafara, Aurélie M

2018-02-01

Potato virus Y (PVY) infection has been a global challenge for potato production and the leading cause of downgrading and rejection of seed crops for certification. Accurate and timely diagnosis is a key for effective disease control. Here, we have optimized a reverse transcription loop-mediated amplification (RT-LAMP) assay to differentiate the PVY O and N serotypes. The RT-LAMP assay is based on isothermal autocyclic strand displacement during DNA synthesis. The high specificity of this method relies heavily on the primer sets designed for the amplification of the targeted regions. We designed specific primer sets targeting a region within the coat protein gene that contains nucleotide signatures typical for O and N coat protein types, and these primers differ in their annealing temperature. Combining this assay with total RNA extraction by magnetic capture, we have established a highly sensitive, simplified and shortened RT-LAMP procedure as an alternative to conventional nucleic acid assays for diagnosis. This optimized procedure for virus detection may be used as a preliminary test for identifying the viral serotype prior to investing time and effort in multiplex RT-PCR tests when a specific strain is needed.

Soft computing model for optimized siRNA design by identifying off target possibilities using artificial neural network model.

PubMed

Murali, Reena; John, Philips George; Peter S, David

2015-05-15

The ability of small interfering RNA (siRNA) to do posttranscriptional gene regulation by knocking down targeted genes is an important research topic in functional genomics, biomedical research and in cancer therapeutics. Many tools had been developed to design exogenous siRNA with high experimental inhibition. Even though considerable amount of work has been done in designing exogenous siRNA, design of effective siRNA sequences is still a challenging work because the target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. In some cases, siRNAs may tolerate mismatches with the target mRNA, but knockdown of genes other than the intended target could make serious consequences. Hence to design siRNAs, two important concepts must be considered: the ability in knocking down target genes and the off target possibility on any nontarget genes. So before doing gene silencing by siRNAs, it is essential to analyze their off target effects in addition to their inhibition efficacy against a particular target. Only a few methods have been developed by considering both efficacy and off target possibility of siRNA against a gene. In this paper we present a new design of neural network model with whole stacking energy (ΔG) that enables to identify the efficacy and off target effect of siRNAs against target genes. The tool lists all siRNAs against a particular target with their inhibition efficacy and number of matches or sequence similarity with other genes in the database. We could achieve an excellent performance of Pearson Correlation Coefficient (R=0. 74) and Area Under Curve (AUC=0.906) when the threshold of whole stacking energy is ≥-34.6 kcal/mol. To the best of the author's knowledge, this is one of the best score while considering the "combined efficacy and off target possibility" of siRNA for silencing a gene. The proposed model shall be useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in the area of bioinformatics. The software is developed as a desktop application and available at http://opsid.in/opsid/. Copyright © 2015 Elsevier B.V. All rights reserved.

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind.

PubMed

Luo, He; Liang, Zhengzheng; Zhu, Moning; Hu, Xiaoxuan; Wang, Guoqiang

2018-01-01

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided.

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind

PubMed Central

Liang, Zhengzheng; Zhu, Moning; Hu, Xiaoxuan; Wang, Guoqiang

2018-01-01

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided. PMID:29561888

Optimization of Insertion Cost for Transfer Trajectories to Libration Point Orbits

NASA Technical Reports Server (NTRS)

Howell, K. C.; Wilson, R. S.; Lo, M. W.

1999-01-01

The objective of this work is the development of efficient techniques to optimize the cost associated with transfer trajectories to libration point orbits in the Sun-Earth-Moon four body problem, that may include lunar gravity assists. Initially, dynamical systems theory is used to determine invariant manifolds associated with the desired libration point orbit. These manifolds are employed to produce an initial approximation to the transfer trajectory. Specific trajectory requirements such as, transfer injection constraints, inclusion of phasing loops, and targeting of a specified state on the manifold are then incorporated into the design of the transfer trajectory. A two level differential corrections process is used to produce a fully continuous trajectory that satisfies the design constraints, and includes appropriate lunar and solar gravitational models. Based on this methodology, and using the manifold structure from dynamical systems theory, a technique is presented to optimize the cost associated with insertion onto a specified libration point orbit.

Design and analysis of reflector for uniform light-emitting diode illuminance.

PubMed

Tsai, Chung-Yu

2013-05-01

A light-emitting diode (LED) projection system is proposed, composed of an LED chip and a variable-focus-parabolic (VFP) reflector, in which the focal length varies as a function of the vertical displacement of the incidence point relative to the horizontal centerline of the LED chip. The light-ray paths within the projection system are analyzed using an exact analytical model and a skew-ray tracing approach. The profile of the proposed VFP reflector and the position of the LED chip are then optimized in such a way as to enhance the uniformity of the illuminance distribution on the target region of the image plane. The validity of the optimized design is demonstrated by means of ZEMAX simulations. It is shown that the optimized VFP projector system yields a significant improvement in illuminance uniformity compared to conventional spherical and parabolic projectors and therefore minimizes the glare effect.

Control theory based airfoil design for potential flow and a finite volume discretization

NASA Technical Reports Server (NTRS)

Reuther, J.; Jameson, A.

1994-01-01

This paper describes the implementation of optimization techniques based on control theory for airfoil design. In previous studies it was shown that control theory could be used to devise an effective optimization procedure for two-dimensional profiles in which the shape is determined by a conformal transformation from a unit circle, and the control is the mapping function. The goal of our present work is to develop a method which does not depend on conformal mapping, so that it can be extended to treat three-dimensional problems. Therefore, we have developed a method which can address arbitrary geometric shapes through the use of a finite volume method to discretize the potential flow equation. Here the control law serves to provide computationally inexpensive gradient information to a standard numerical optimization method. Results are presented, where both target speed distributions and minimum drag are used as objective functions.

Numerical simulation and optimal design of Segmented Planar Imaging Detector for Electro-Optical Reconnaissance

NASA Astrophysics Data System (ADS)

Chu, Qiuhui; Shen, Yijie; Yuan, Meng; Gong, Mali

2017-12-01

Segmented Planar Imaging Detector for Electro-Optical Reconnaissance (SPIDER) is a cutting-edge electro-optical imaging technology to realize miniaturization and complanation of imaging systems. In this paper, the principle of SPIDER has been numerically demonstrated based on the partially coherent light theory, and a novel concept of adjustable baseline pairing SPIDER system has further been proposed. Based on the results of simulation, it is verified that the imaging quality could be effectively improved by adjusting the Nyquist sampling density, optimizing the baseline pairing method and increasing the spectral channel of demultiplexer. Therefore, an adjustable baseline pairing algorithm is established for further enhancing the image quality, and the optimal design procedure in SPIDER for arbitrary targets is also summarized. The SPIDER system with adjustable baseline pairing method can broaden its application and reduce cost under the same imaging quality.

Overview of field gamma spectrometries based on Si-photomultiplier

NASA Astrophysics Data System (ADS)

Denisov, Viktor; Korotaev, Valery; Titov, Aleksandr; Blokhina, Anastasia; Kleshchenok, Maksim

2017-05-01

Design of optical-electronic devices and systems involves the selection of such technical patterns that under given initial requirements and conditions are optimal according to certain criteria. The original characteristic of the OES for any purpose, defining its most important feature ability is a threshold detection. Based on this property, will be achieved the required functional quality of the device or system. Therefore, the original criteria and optimization methods have to subordinate to the idea of a better detectability. Generally reduces to the problem of optimal selection of the expected (predetermined) signals in the predetermined observation conditions. Thus the main purpose of optimization of the system when calculating its detectability is the choice of circuits and components that provide the most effective selection of a target.

“Addition” and “Subtraction”: Selectivity Design for Type II Maternal Embryonic Leucine Zipper Kinase Inhibitors

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

Chen, Xin; Giraldes, John; Sprague, Elizabeth R.

2017-02-17

While adding the structural features that are more favored by on-target activity is the more common strategy in selectivity optimization, the opposite strategy of subtracting the structural features that contribute more to off-target activity can also be very effective. Reported here is our successful effort of improving the kinase selectivity of type II maternal embryonic leucine zipper kinase inhibitors by applying these two complementary approaches together, which clearly demonstrates the powerful synergy between them.

Lujan Center Mark-IV Target Neutronics Design Internal Review Report

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

Lisowski, Paul W.; Gallmeier, Franz; Guber, Klaus

The 1L Target Moderator Reflector System (TMRS) at the Lujan Center will need to be replaced before the CY 2020 operating cycle. A Physics Division design team investigated options for improving the overall target performance for nuclear science research with minimal reduction in performance for materials science. This review concluded that devoting an optimized arrangement of the Lujan TMRS upper tier to nuclear science and using the lower tier for materials science can achieve those goals. This would open the opportunity for enhanced nuclear science research in an important neutron energy range for NNSA. There will be no other facilitymore » in the US that will compete in the keV energy range provided flight paths and instrumentation are developed to take advantage of the neutron flux and resolution.« less

Methamphetamine Vaccines: Improvement through Hapten Design.

PubMed

Collins, Karen C; Schlosburg, Joel E; Bremer, Paul T; Janda, Kim D

2016-04-28

Methamphetamine (MA) addiction is a serious public health problem, and current methods to abate addiction and relapse are currently ineffective for mitigating this growing global epidemic. Development of a vaccine targeting MA would provide a complementary strategy to existing behavioral therapies, but this has proven challenging. Herein, we describe optimization of both hapten design and formulation, identifying a vaccine that elicited a robust anti-MA immune response in mice, decreasing methamphetamine-induced locomotor activity.

Selection of a turbine cooling system applying multi-disciplinary design considerations.

PubMed

Glezer, B

2001-05-01

The presented paper describes a multi-disciplinary cooling selection approach applied to major gas turbine engine hot section components, including turbine nozzles, blades, discs, combustors and support structures, which maintain blade tip clearances. The paper demonstrates benefits of close interaction between participating disciplines starting from early phases of the hot section development. The approach targets advancements in engine performance and cost by optimizing the design process, often requiring compromises within individual disciplines.

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2005-07-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A Framework to Design and Optimize Chemical Flooding Processes

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2006-08-31

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2004-11-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

Development and optimization of transferrin-conjugated nanostructured lipid carriers for brain delivery of paclitaxel using Box-Behnken design.

PubMed

Emami, Jaber; Rezazadeh, Mahboubeh; Sadeghi, Hojjat; Khadivar, Khashayar

2017-05-01

The treatment of brain cancer remains one of the most difficult challenges in oncology. The purpose of this study was to develop transferrin-conjugated nanostructured lipid carriers (Tf-NLCs) for brain delivery of paclitaxel (PTX). PTX-loaded NLCs (PTX-NLCs) were prepared using solvent evaporation method and the impact of various formulation variables were assessed using Box-Behnken design. Optimized PTX-NLC was coupled with transferrin as targeting ligand and in vitro cytotoxicity of it was investigated against U-87 brain cancer cell line. As a result, 14.1 mg of cholesterol, 18.5 mg of triolein, and 0.5% poloxamer were used to prepare the optimal formulation. Mean particle size (PS), zeta potential (ZP), entrapment efficiency (EE), drug loading (DL), mean release time (MRT) of adopted formulation were confirmed to be 205.4 ± 11 nm, 25.7 ± 6.22 mV, 91.8 ± 0.5%, 5.38 ± 0.03% and 29.3 h, respectively. Following conjugation of optimized PTX-NLCs with transferrin, coupling efficiency was 21.3 mg transferrin per mmol of stearylamine; PS and MRT were increased while ZP, EE and DL decreased non-significantly. Tf-PTX-NLCs showed higher cytotoxic activity compared to non-targeted NLCs and free drug. These results indicated that the Tf-PTX-NLCs could potentially be exploited as a delivery system in brain cancer cells.

Engineering of small interfering RNA-loaded lipidoid-poly(DL-lactic-co-glycolic acid) hybrid nanoparticles for highly efficient and safe gene silencing: A quality by design-based approach.

PubMed

Thanki, Kaushik; Zeng, Xianghui; Justesen, Sarah; Tejlmann, Sarah; Falkenberg, Emily; Van Driessche, Elize; Mørck Nielsen, Hanne; Franzyk, Henrik; Foged, Camilla

2017-11-01

Safety and efficacy of therapeutics based on RNA interference, e.g., small interfering RNA (siRNA), are dependent on the optimal engineering of the delivery technology, which is used for intracellular delivery of siRNA to the cytosol of target cells. We investigated the hypothesis that commonly used and poorly tolerated cationic lipids might be replaced with more efficacious and safe lipidoids as the lipid component of siRNA-loaded lipid-polymer hybrid nanoparticles (LPNs) for achieving more efficient gene silencing at lower and safer doses. However, formulation design of such a complex formulation is highly challenging due to a strong interplay between several contributing factors. Hence, critical formulation variables, i.e. the lipidoid content and siRNA:lipidoid ratio, were initially identified, followed by a systematic quality-by-design approach to define the optimal operating space (OOS), eventually resulting in the identification of a robust, highly efficacious and safe formulation. A 17-run design of experiment with an I-optimal approach was performed to systematically assess the effect of selected variables on critical quality attributes (CQAs), i.e. physicochemical properties (hydrodynamic size, zeta potential, siRNA encapsulation/loading) and the biological performance (in vitro gene silencing and cell viability). Model fitting of the obtained data to construct predictive models revealed non-linear relationships for all CQAs, which can be readily overlooked in one-factor-at-a-time optimization approaches. The response surface methodology further enabled the identification of an OOS that met the desired quality target product profile. The optimized lipidoid-modified LPNs revealed more than 50-fold higher in vitro gene silencing at well-tolerated doses and approx. a twofold increase in siRNA loading as compared to reference LPNs modified with the commonly used cationic lipid dioleyltrimethylammonium propane (DOTAP). Thus, lipidoid-modified LPNs show highly promising prospects for efficient and safe intracellular delivery of siRNA. Copyright © 2017 Elsevier B.V. All rights reserved.

Direct measurements of anode/cathode gap plasma in cylindrically imploding loads on the Z machine

NASA Astrophysics Data System (ADS)

Porwitzky, A.; Dolan, D. H.; Martin, M. R.; Laity, G.; Lemke, R. W.; Mattsson, T. R.

2018-06-01

By deploying a photon Doppler velocimetry based plasma diagnostic, we have directly observed low density plasma in the load anode/cathode gap of cylindrically converging pulsed power targets. The arrival of this plasma is temporally correlated with gross current loss and subtle power flow differences between the anode and the cathode. The density is in the range where Hall terms in the electromagnetic equations are relevant, but this physics is lacking in the magnetohydrodynamics codes commonly used to design, analyze, and optimize pulsed power experiments. The present work presents evidence of the importance of physics beyond traditional resistive magnetohydrodynamics for the design of pulsed power targets and drivers.

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.

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.

A quantitative framework for the forward design of synthetic miRNA circuits.

PubMed

Bloom, Ryan J; Winkler, Sally M; Smolke, Christina D

2014-11-01

Synthetic genetic circuits incorporating regulatory components based on RNA interference (RNAi) have been used in a variety of systems. A comprehensive understanding of the parameters that determine the relationship between microRNA (miRNA) and target expression levels is lacking. We describe a quantitative framework supporting the forward engineering of gene circuits that incorporate RNAi-based regulatory components in mammalian cells. We developed a model that captures the quantitative relationship between miRNA and target gene expression levels as a function of parameters, including mRNA half-life and miRNA target-site number. We extended the model to synthetic circuits that incorporate protein-responsive miRNA switches and designed an optimized miRNA-based protein concentration detector circuit that noninvasively measures small changes in the nuclear concentration of β-catenin owing to induction of the Wnt signaling pathway. Our results highlight the importance of methods for guiding the quantitative design of genetic circuits to achieve robust, reliable and predictable behaviors in mammalian cells.

Design and evaluation of online arithmetic for signal processing applications on FPGAs

NASA Astrophysics Data System (ADS)

Galli, Reto; Tenca, Alexandre F.

2001-11-01

This paper shows the design and the evaluation of on-line arithmetic modules for the most common operators used in DSP applications, using FPGAs as the target technology. The designs are highly optimized for the target technology and the common range of precision in DSP. The results are based on experimental data collected using CAD tools. All designs are synthesized for the same type of devices (Xilinx XC4000) for comparison, avoiding rough estimates of the system performance, and generating a more reliable and detailed comparison of on-line signal processing solutions with other state of the art approaches, such as distributed arithmetic. We show that on-line designs have a hard stand for basic DSP applications that use only addition and multiplication. However, we also show that on-line designs are able to overtake other approaches as the applications become more sophisticated, e.g. when data dependencies exist, or when non constant multiplicands restrict the use of other approaches.

Design of a Low-Energy FARAD Thruster

NASA Technical Reports Server (NTRS)

Polzin, K. A.; Rose, M. F.; Miller, R.; Best, S.; Owens, T.; Dankanich, J.

2007-01-01

The design of an electrodeless thruster that relies on a pulsed, rf-assisted discharge and electromagnetic acceleration using an inductive coil is presented. The thruster design is optimized using known performance,scaling parameters, and experimentally-determined design rules, with design targets for discharge energy, plasma exhaust velocity; and thrust efficiency of 100 J/pulse, 25 km/s, and 50%, respectively. Propellant is injected using a high-speed gas valve and preionized by a pulsed-RF signal supplied by a vector inversion generator, allowing for current sheet formation at lower discharge voltages and energies relative to pulsed inductive accelerators that do not employ preionization. The acceleration coil is designed to possess an inductance of at least 700 nH while the target stray (non-coil) inductance in the circuit is 70 nH. A Bernardes and Merryman pulsed power train or a pulse compression power train provide current to the acceleration coil and solid-state components are used to switch both powertrains.

Adnectin-Based Design of Chimeric Antigen Receptor for T Cell Engineering.

PubMed

Han, Xiaolu; Cinay, Gunce E; Zhao, Yifan; Guo, Yunfei; Zhang, Xiaoyang; Wang, Pin

2017-11-01

Although chimeric antigen receptor (CAR)-engineered T cell therapy has achieved encouraging clinical trial results for treating hematological cancers, further optimization can likely expand this therapeutic success to more patients and other cancer types. Most CAR constructs used in clinical trials incorporate single chain variable fragment (scFv) as the extracellular antigen recognition domain. The immunogenicity of nonhuman scFv could cause host rejection against CAR T cells and compromise their persistence and efficacy. The limited availability of scFvs and slow discovery of new monoclonal antibodies also limit the development of novel CAR constructs. Adnectin, a class of affinity molecules derived from the tenth type III domain of human fibronectin, can be an alternative to scFv as an antigen-binding moiety in the design of CAR molecules. We constructed adnectin-based CARs targeting epithelial growth factor receptor (EGFR) and found that compared to scFv-based CAR, T cells engineered with adnectin-based CARs exhibited equivalent cell-killing activity against target H292 lung cancer cells in vitro and had comparable antitumor efficacy in xenograft tumor-bearing mice in vivo. In addition, with optimal affinity tuning, adnectin-based CAR showed higher selectivity on target cells with high EGFR expression than on those with low expression. This new design of adnectin CARs can potentially facilitate the development of T cell immunotherapy for cancer and other diseases. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

Optimized Design and Synthesis of Cell Permeable Biarsenical Cyanine Probe for Imaging Tagged Cytosolic Bacterial Proteins

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

Fu, Na; Xiong, Yijia; Squier, Thomas C.

2013-01-21

To optimize cellular delivery and specific labeling of tagged cytosolic proteins by biarsenical fluorescent probes build around a cyanine dye scaffold, we have systematically varied the polarity of the hydrophobic tails (i.e., 4-5 methylene groups appended by a sulfonate or methoxy ester moiety) and arsenic capping reagent (ethanedithiol versus benzenedithiol). Targeted labeling of the cytosolic proteins SlyD and the alpha subunit of RNA polymerase engineered with a tetracysteine tagging sequences demonstrate the utility of the newly synthesized probes for live-cell visualization, albeit with varying efficiencies and background intensities. Optimal routine labeling and visualization is apparent using the ethanedithiol capping reagentmore » with the uncharged methoxy ester functionalized acyl chains. These measurements demonstrate the general utility of this class of photostable and highly fluorescent biarsenical reagents based on the cyanine scaffold for in vivo targeting of tagged cellular proteins for live cell measurements of protein dynamics.« less

Dimension reduction: additional benefit of an optimal filter for independent component analysis to extract event-related potentials.

PubMed

Cong, Fengyu; Leppänen, Paavo H T; Astikainen, Piia; Hämäläinen, Jarmo; Hietanen, Jari K; Ristaniemi, Tapani

2011-09-30

The present study addresses benefits of a linear optimal filter (OF) for independent component analysis (ICA) in extracting brain event-related potentials (ERPs). A filter such as the digital filter is usually considered as a denoising tool. Actually, in filtering ERP recordings by an OF, the ERP' topography should not be changed by the filter, and the output should also be able to be modeled by the linear transformation. Moreover, an OF designed for a specific ERP source or component may remove noise, as well as reduce the overlap of sources and even reject some non-targeted sources in the ERP recordings. The OF can thus accomplish both the denoising and dimension reduction (reducing the number of sources) simultaneously. We demonstrated these effects using two datasets, one containing visual and the other auditory ERPs. The results showed that the method including OF and ICA extracted much more reliable components than the sole ICA without OF did, and that OF removed some non-targeted sources and made the underdetermined model of EEG recordings approach to the determined one. Thus, we suggest designing an OF based on the properties of an ERP to filter recordings before using ICA decomposition to extract the targeted ERP component. Copyright © 2011 Elsevier B.V. All rights reserved.

Evolution-guided optimization of biosynthetic pathways.

PubMed

Raman, Srivatsan; Rogers, Jameson K; Taylor, Noah D; Church, George M

2014-12-16

Engineering biosynthetic pathways for chemical production requires extensive optimization of the host cellular metabolic machinery. Because it is challenging to specify a priori an optimal design, metabolic engineers often need to construct and evaluate a large number of variants of the pathway. We report a general strategy that combines targeted genome-wide mutagenesis to generate pathway variants with evolution to enrich for rare high producers. We convert the intracellular presence of the target chemical into a fitness advantage for the cell by using a sensor domain responsive to the chemical to control a reporter gene necessary for survival under selective conditions. Because artificial selection tends to amplify unproductive cheaters, we devised a negative selection scheme to eliminate cheaters while preserving library diversity. This scheme allows us to perform multiple rounds of evolution (addressing ∼10(9) cells per round) with minimal carryover of cheaters after each round. Based on candidate genes identified by flux balance analysis, we used targeted genome-wide mutagenesis to vary the expression of pathway genes involved in the production of naringenin and glucaric acid. Through up to four rounds of evolution, we increased production of naringenin and glucaric acid by 36- and 22-fold, respectively. Naringenin production (61 mg/L) from glucose was more than double the previous highest titer reported. Whole-genome sequencing of evolved strains revealed additional untargeted mutations that likely benefit production, suggesting new routes for optimization.

Recombinant expression, purification, and crystallization of the glutaminyl-tRNA synthetase from Toxoplasma gondii.

PubMed

van Rooyen, Jason M; Hakimi, Mohamed-Ali; Belrhali, Hassan

2015-06-01

Aminoacyl tRNA synthetases play a critical role in protein synthesis by providing precursor transfer-RNA molecules correctly charged with their cognate amino-acids. The essential nature of these enzymes make them attractive targets for designing new drugs against important pathogenic protozoans like Toxoplasma. Because no structural data currently exists for a protozoan glutaminyl-tRNA synthetase (QRS), an understanding of its potential as a drug target and its function in the assembly of the Toxoplasma multi-aminoacyl tRNA (MARS) complex is therefore lacking. Here we describe the optimization of expression and purification conditions that permitted the recovery and crystallization of both domains of the Toxoplasma QRS enzyme from a heterologous Escherichia coli expression system. Expression of full-length QRS was only achieved after the addition of an N-terminal histidine affinity tag and the isolated protein was active on both cellular and in vitro produced Toxoplasma tRNA. Taking advantage of the proteolytic susceptibility of QRS to cleavage into component domains, N-terminal glutathione S-transferase (GST) motif-containing domain fragments were isolated and crystallization conditions discovered. Isolation of the C-terminal catalytic domain was accomplished after subcloning the domain and optimizing expression conditions. Purified catalytic domain survived cryogenic storage and yielded large diffraction-quality crystals over-night after optimization of screening conditions. This work will form the basis of future structural studies into structural-functional relationships of both domains including potential targeted drug-design studies and investigations into the assembly of the Toxoplasma MARS complex. Copyright © 2015 Elsevier Inc. All rights reserved.

Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review

PubMed Central

Csermely, Peter; Korcsmáros, Tamás; Kiss, Huba J.M.; London, Gábor; Nussinov, Ruth

2013-01-01

Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only gives a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The “central hit strategy” selectively targets central node/edges of the flexible networks of infectious agents or cancer cells to kill them. The “network influence strategy” works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach. PMID:23384594

Designing the X-Ray Microcalorimeter Spectrometer for Optimal Science Return

NASA Technical Reports Server (NTRS)

Ptak, Andrew; Bandler, Simon R.; Bookbinder, Jay; Kelley, Richard L.; Petre, Robert; Smith, Randall K.; Smith, Stephen

2013-01-01

Recent advances in X-ray microcalorimeters enable a wide range of possible focal plane designs for the X-ray Microcalorimeter Spectrometer (XMS) instrument on the future Advanced X-ray Spectroscopic Imaging Observatory (AXSIO) or X-ray Astrophysics Probe (XAP). Small pixel designs (75 microns) oversample a 5-10" PSF by a factor of 3-6 for a 10 m focal length, enabling observations at both high count rates and high energy resolution. Pixel designs utilizing multiple absorbers attached to single transition-edge sensors can extend the focal plane to cover a significantly larger field of view, albeit at a cost in maximum count rate and energy resolution. Optimizing the science return for a given cost and/or complexity is therefore a non-trivial calculation that includes consideration of issues such as the mission science drivers, likely targets, mirror size, and observing efficiency. We present a range of possible designs taking these factors into account and their impacts on the science return of future large effective-area X-ray spectroscopic missions.

A polymer dataset for accelerated property prediction and design

DOE PAGES

Huan, Tran Doan; Mannodi-Kanakkithodi, Arun; Kim, Chiho; ...

2016-03-01

Emerging computation- and data-driven approaches are particularly useful for rationally designing materials with targeted properties. Generally, these approaches rely on identifying structure-property relationships by learning from a dataset of sufficiently large number of relevant materials. The learned information can then be used to predict the properties of materials not already in the dataset, thus accelerating the materials design. Herein, we develop a dataset of 1,073 polymers and related materials and make it available at http://khazana.uconn.edu/. This dataset is uniformly prepared using first-principles calculations with structures obtained either from other sources or by using structure search methods. Because the immediate targetmore » of this work is to assist the design of high dielectric constant polymers, it is initially designed to include the optimized structures, atomization energies, band gaps, and dielectric constants. As a result, it will be progressively expanded by accumulating new materials and including additional properties calculated for the optimized structures provided.« less

Physics-model-based nonlinear actuator trajectory optimization and safety factor profile feedback control for advanced scenario development in DIII-D

DOE PAGES

Barton, Justin E.; Boyer, Mark D.; Shi, Wenyu; ...

2015-07-30

DIII-D experimental results are reported to demonstrate the potential of physics-model-based safety factor profile control for robust and reproducible sustainment of advanced scenarios. In the absence of feedback control, variability in wall conditions and plasma impurities, as well as drifts due to external disturbances, can limit the reproducibility of discharges with simple pre-programmed scenario trajectories. The control architecture utilized is a feedforward + feedback scheme where the feedforward commands are computed off-line and the feedback commands are computed on-line. In this work, firstly a first-principles-driven (FPD), physics-based model of the q profile and normalized beta (β N) dynamics is embeddedmore » into a numerical optimization algorithm to design feedforward actuator trajectories that sheer the plasma through the tokamak operating space to reach a desired stationary target state that is characterized by the achieved q profile and β N. Good agreement between experimental results and simulations demonstrates the accuracy of the models employed for physics-model-based control design. Secondly, a feedback algorithm for q profile control is designed following a FPD approach, and the ability of the controller to achieve and maintain a target q profile evolution is tested in DIII-D high confinement (H-mode) experiments. The controller is shown to be able to effectively control the q profile when β N is relatively close to the target, indicating the need for integrated q profile and β N control to further enhance the ability to achieve robust scenario execution. Furthermore, the ability of an integrated q profile + β N feedback controller to track a desired target is demonstrated through simulation.« less

Role of step size and max dwell time in anatomy based inverse optimization for prostate implants

PubMed Central

Manikandan, Arjunan; Sarkar, Biplab; Rajendran, Vivek Thirupathur; King, Paul R.; Sresty, N.V. Madhusudhana; Holla, Ragavendra; Kotur, Sachin; Nadendla, Sujatha

2013-01-01

In high dose rate (HDR) brachytherapy, the source dwell times and dwell positions are vital parameters in achieving a desirable implant dose distribution. Inverse treatment planning requires an optimal choice of these parameters to achieve the desired target coverage with the lowest achievable dose to the organs at risk (OAR). This study was designed to evaluate the optimum source step size and maximum source dwell time for prostate brachytherapy implants using an Ir-192 source. In total, one hundred inverse treatment plans were generated for the four patients included in this study. Twenty-five treatment plans were created for each patient by varying the step size and maximum source dwell time during anatomy-based, inverse-planned optimization. Other relevant treatment planning parameters were kept constant, including the dose constraints and source dwell positions. Each plan was evaluated for target coverage, urethral and rectal dose sparing, treatment time, relative target dose homogeneity, and nonuniformity ratio. The plans with 0.5 cm step size were seen to have clinically acceptable tumor coverage, minimal normal structure doses, and minimum treatment time as compared with the other step sizes. The target coverage for this step size is 87% of the prescription dose, while the urethral and maximum rectal doses were 107.3 and 68.7%, respectively. No appreciable difference in plan quality was observed with variation in maximum source dwell time. The step size plays a significant role in plan optimization for prostate implants. Our study supports use of a 0.5 cm step size for prostate implants. PMID:24049323

A "Reverse-Schur" Approach to Optimization With Linear PDE Constraints: Application to Biomolecule Analysis and Design.

PubMed

Bardhan, Jaydeep P; Altman, Michael D; Tidor, B; White, Jacob K

2009-01-01

We present a partial-differential-equation (PDE)-constrained approach for optimizing a molecule's electrostatic interactions with a target molecule. The approach, which we call reverse-Schur co-optimization, can be more than two orders of magnitude faster than the traditional approach to electrostatic optimization. The efficiency of the co-optimization approach may enhance the value of electrostatic optimization for ligand-design efforts-in such projects, it is often desirable to screen many candidate ligands for their viability, and the optimization of electrostatic interactions can improve ligand binding affinity and specificity. The theoretical basis for electrostatic optimization derives from linear-response theory, most commonly continuum models, and simple assumptions about molecular binding processes. Although the theory has been used successfully to study a wide variety of molecular binding events, its implications have not yet been fully explored, in part due to the computational expense associated with the optimization. The co-optimization algorithm achieves improved performance by solving the optimization and electrostatic simulation problems simultaneously, and is applicable to both unconstrained and constrained optimization problems. Reverse-Schur co-optimization resembles other well-known techniques for solving optimization problems with PDE constraints. Model problems as well as realistic examples validate the reverse-Schur method, and demonstrate that our technique and alternative PDE-constrained methods scale very favorably compared to the standard approach. Regularization, which ordinarily requires an explicit representation of the objective function, can be included using an approximate Hessian calculated using the new BIBEE/P (boundary-integral-based electrostatics estimation by preconditioning) method.

A “Reverse-Schur” Approach to Optimization With Linear PDE Constraints: Application to Biomolecule Analysis and Design

PubMed Central

Bardhan, Jaydeep P.; Altman, Michael D.

2009-01-01

We present a partial-differential-equation (PDE)-constrained approach for optimizing a molecule’s electrostatic interactions with a target molecule. The approach, which we call reverse-Schur co-optimization, can be more than two orders of magnitude faster than the traditional approach to electrostatic optimization. The efficiency of the co-optimization approach may enhance the value of electrostatic optimization for ligand-design efforts–in such projects, it is often desirable to screen many candidate ligands for their viability, and the optimization of electrostatic interactions can improve ligand binding affinity and specificity. The theoretical basis for electrostatic optimization derives from linear-response theory, most commonly continuum models, and simple assumptions about molecular binding processes. Although the theory has been used successfully to study a wide variety of molecular binding events, its implications have not yet been fully explored, in part due to the computational expense associated with the optimization. The co-optimization algorithm achieves improved performance by solving the optimization and electrostatic simulation problems simultaneously, and is applicable to both unconstrained and constrained optimization problems. Reverse-Schur co-optimization resembles other well-known techniques for solving optimization problems with PDE constraints. Model problems as well as realistic examples validate the reverse-Schur method, and demonstrate that our technique and alternative PDE-constrained methods scale very favorably compared to the standard approach. Regularization, which ordinarily requires an explicit representation of the objective function, can be included using an approximate Hessian calculated using the new BIBEE/P (boundary-integral-based electrostatics estimation by preconditioning) method. PMID:23055839

Bayesian Optimal Interval Design: A Simple and Well-Performing Design for Phase I Oncology Trials

PubMed Central

Yuan, Ying; Hess, Kenneth R.; Hilsenbeck, Susan G.; Gilbert, Mark R.

2016-01-01

Despite more than two decades of publications that offer more innovative model-based designs, the classical 3+3 design remains the most dominant phase I trial design in practice. In this article, we introduce a new trial design, the Bayesian optimal interval (BOIN) design. The BOIN design is easy to implement in a way similar to the 3+3 design, but is more flexible for choosing the target toxicity rate and cohort size and yields a substantially better performance that is comparable to that of more complex model-based designs. The BOIN design contains the 3+3 design and the accelerated titration design as special cases, thus linking it to established phase I approaches. A numerical study shows that the BOIN design generally outperforms the 3+3 design and the modified toxicity probability interval (mTPI) design. The BOIN design is more likely than the 3+3 design to correctly select the maximum tolerated dose (MTD) and allocate more patients to the MTD. Compared to the mTPI design, the BOIN design has a substantially lower risk of overdosing patients and generally a higher probability of correctly selecting the MTD. User-friendly software is freely available to facilitate the application of the BOIN design. PMID:27407096

Engineered Peptides for Applications in Cancer-Targeted Drug Delivery and Tumor Detection.

PubMed

Soudy, R; Byeon, N; Raghuwanshi, Y; Ahmed, S; Lavasanifar, A; Kaur, K

2017-01-01

Cancer-targeting peptides as ligands for targeted delivery of anticancer drugs or drug carriers have the potential to significantly enhance the selectivity and the therapeutic benefit of current chemotherapeutic agents. Identification of tumor-specific biomarkers like integrins, aminopeptidase N, and epidermal growth factor receptor as well as the popularity of phage display techniques along with synthetic combinatorial methods used for peptide design and structure optimization have fueled the advancement and application of peptide ligands for targeted drug delivery and tumor detection in cancer treatment, detection and guided therapy. Although considerable preclinical data have shown remarkable success in the use of tumor targeting peptides, peptides generally suffer from poor pharmacokinetics, enzymatic instability, and weak receptor affinity, and they need further structural modification before successful translation to clinics is possible. The current review gives an overview of the different engineering strategies that have been developed for peptide structure optimization to confer selectivity and stability. We also provide an update on the methods used for peptide ligand identification, and peptide- receptor interactions. Additionally, some applications for the use of peptides in targeted delivery of chemotherapeutics and diagnostics over the past 5 years are summarized. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Adaptive ISAR Imaging of Maneuvering Targets Based on a Modified Fourier Transform.

PubMed

Wang, Binbin; Xu, Shiyou; Wu, Wenzhen; Hu, Pengjiang; Chen, Zengping

2018-04-27

Focusing on the inverse synthetic aperture radar (ISAR) imaging of maneuvering targets, this paper presents a new imaging method which works well when the target's maneuvering is not too severe. After translational motion compensation, we describe the equivalent rotation of maneuvering targets by two variables-the relative chirp rate of the linear frequency modulated (LFM) signal and the Doppler focus shift. The first variable indicates the target's motion status, and the second one represents the possible residual error of the translational motion compensation. With them, a modified Fourier transform matrix is constructed and then used for cross-range compression. Consequently, the imaging of maneuvering is converted into a two-dimensional parameter optimization problem in which a stable and clear ISAR image is guaranteed. A gradient descent optimization scheme is employed to obtain the accurate relative chirp rate and Doppler focus shift. Moreover, we designed an efficient and robust initialization process for the gradient descent method, thus, the well-focused ISAR images of maneuvering targets can be achieved adaptively. Human intervention is not needed, and it is quite convenient for practical ISAR imaging systems. Compared to precedent imaging methods, the new method achieves better imaging quality under reasonable computational cost. Simulation results are provided to validate the effectiveness and advantages of the proposed method.

Engineering of an inhalable DDA/TDB liposomal adjuvant: a quality-by-design approach towards optimization of the spray drying process.

PubMed

Ingvarsson, Pall Thor; Yang, Mingshi; Mulvad, Helle; Nielsen, Hanne Mørck; Rantanen, Jukka; Foged, Camilla

2013-11-01

The purpose of this study was to identify and optimize spray drying parameters of importance for the design of an inhalable powder formulation of a cationic liposomal adjuvant composed of dimethyldioctadecylammonium (DDA) bromide and trehalose-6,6'-dibehenate (TDB). A quality by design (QbD) approach was applied to identify and link critical process parameters (CPPs) of the spray drying process to critical quality attributes (CQAs) using risk assessment and design of experiments (DoE), followed by identification of an optimal operating space (OOS). A central composite face-centered design was carried out followed by multiple linear regression analysis. Four CQAs were identified; the mass median aerodynamic diameter (MMAD), the liposome stability (size) during processing, the moisture content and the yield. Five CPPs (drying airflow, feed flow rate, feedstock concentration, atomizing airflow and outlet temperature) were identified and tested in a systematic way. The MMAD and the yield were successfully modeled. For the liposome size stability, the ratio between the size after and before spray drying was modeled successfully. The model for the residual moisture content was poor, although, the moisture content was below 3% in the entire design space. Finally, the OOS was drafted from the constructed models for the spray drying of trehalose stabilized DDA/TDB liposomes. The QbD approach for the spray drying process should include a careful consideration of the quality target product profile. This approach implementing risk assessment and DoE was successfully applied to optimize the spray drying of an inhalable DDA/TDB liposomal adjuvant designed for pulmonary vaccination.

Self-esteem and optimism in rural youth: gender differences.

PubMed

Puskar, Kathryn R; Bernardo, Lisa Marie; Ren, Dianxu; Haley, Tammy M; Tark, Kirsti Hetager; Switala, Joann; Siemon, Linda

2010-01-01

To identify and describe gender-related differences in the self-esteem and optimism levels of rural adolescents. Self-esteem and optimism have been broadly examined and are associated with health-practices, social interaction, attachment, resiliency, and personal identity. Information describing the relationship of self-esteem and optimism as it relates to gender is limited. Using a cross-sectional survey design, students (N = 193) from three high-schools in rural Pennsylvania, USA completed the Rosenberg Self-Esteem Scale and the Optimism Scale-Life Orientation Test-Revised as part of a National Institute of Health, National Institute of Nursing Research funded study. Both instruments' mean scores were in the range of average for this population, with females scoring lower than males in both self-esteem (p < 0.0001) and optimism (p < 0.0001). The results of this study have nursing implications for evidenced based interventions that target self-esteem and optimism. Attention to self-esteem and optimism in female youth is recommended.

Design of a high-performance rotary stratified-charge research aircraft engine

NASA Technical Reports Server (NTRS)

Jones, C.; Mount, R. E.

1984-01-01

The power section for an advanced rotary stratified-charge general aviation engine has been designed under contract to NASA. The single-rotor research engine of 40 cubic-inches displacement (RCI-40), now being procured for test initiation this summer, is targeted for 320 T.O. horse-power in a two-rotor production engine. The research engine is designed for operating on jet-fuel, gasoline or diesel fuel and will be used to explore applicable advanced technologies and to optimize high output performance variables. Design of major components of the engine is described in this paper.

Atlas IIAS ascent trajectory design for the SOHO mission

NASA Technical Reports Server (NTRS)

Willen, Robert E.; Rude, Bradley J.

1993-01-01

In 1995, an Atlas IIAS launch vehicle will loft the Solar and Heliospheric Observatory (SOHO) as part of the International Solar and Terrestrial Physics program. The operational phase of the SOHO mission will be conducted from a `halo orbit' about the Sun-Earth interior libration point. Depending on the time of the year of launch, the optimal transfer requires a parking orbit of variable duration to satisfy widely varying inertial targets. A simulation capability has been developed that optimizes the launch vehicle ascent and spacecraft transfer phases of flight together, subject to both launch vehicle and spacecraft constraints. It will be shown that this `ground-up' simulation removes the need for an intermediate target vector at Centaur upper stage/spacecraft separation. Although providing only a modest gain in deliverable satellite mass, this capability substantially improves the mission integration process by removing the strict reliance on near-Earth target vectors. Trajectory data from several cases are presented and future applications of this capability are also discussed.

Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches.

PubMed

Luo, Yao; Wang, Ling

2017-11-16

The mammalian target of rapamycin (mTOR) is a central controller of cell growth, proliferation, metabolism, and angiogenesis. This protein is an attractive target for new anticancer drug development. Significant progress has been made in hit discovery, lead optimization, drug candidate development and determination of the three-dimensional (3D) structure of mTOR. Computational methods have been applied to accelerate the discovery and development of mTOR inhibitors helping to model the structure of mTOR, screen compound databases, uncover structure-activity relationship (SAR) and optimize the hits, mine the privileged fragments and design focused libraries. Besides, computational approaches were also applied to study protein-ligand interactions mechanisms and in natural product-driven drug discovery. Herein, we survey the most recent progress on the application of computational approaches to advance the discovery and development of compounds targeting mTOR. Future directions in the discovery of new mTOR inhibitors using computational methods are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Driving personalized medicine: capturing maximum net present value and optimal return on investment.

PubMed

Roth, Mollie; Keeling, Peter; Smart, Dave

2010-01-01

In order for personalized medicine to meet its potential future promise, a closer focus on the work being carried out today and the foundation it will provide for that future is imperative. While big picture perspectives of this still nascent shift in the drug-development process are important, it is more important that today's work on the first wave of targeted therapies is used to build specific benchmarking and financial models against which further such therapies may be more effectively developed. Today's drug-development teams need a robust tool to identify the exact drivers that will ensure the successful launch and rapid adoption of targeted therapies, and financial metrics to determine the appropriate resource levels to power those drivers. This special report will describe one such benchmarking and financial model that is specifically designed for the personalized medicine field and will explain how the use of this or similar models can help to capture the maximum net present value of targeted therapies and help to realize optimal return on investment.

Mapping algorithm for freeform construction using non-ideal light sources

NASA Astrophysics Data System (ADS)

Li, Chen; Michaelis, D.; Schreiber, P.; Dick, L.; Bräuer, A.

2015-09-01

Using conventional mapping algorithms for the construction of illumination freeform optics' arbitrary target pattern can be obtained for idealized sources, e.g. collimated light or point sources. Each freeform surface element generates an image point at the target and the light intensity of an image point is corresponding to the area of the freeform surface element who generates the image point. For sources with a pronounced extension and ray divergence, e.g. an LED with a small source-freeform-distance, the image points are blurred and the blurred patterns might be different between different points. Besides, due to Fresnel losses and vignetting, the relationship between light intensity of image points and area of freeform surface elements becomes complicated. These individual light distributions of each freeform element are taken into account in a mapping algorithm. To this end the method of steepest decent procedures are used to adapt the mapping goal. A structured target pattern for a optics system with an ideal source is computed applying corresponding linear optimization matrices. Special weighting factor and smoothing factor are included in the procedures to achieve certain edge conditions and to ensure the manufacturability of the freefrom surface. The corresponding linear optimization matrices, which are the lighting distribution patterns of each of the freeform surface elements, are gained by conventional raytracing with a realistic source. Nontrivial source geometries, like LED-irregularities due to bonding or source fine structures, and a complex ray divergence behavior can be easily considered. Additionally, Fresnel losses, vignetting and even stray light are taken into account. After optimization iterations, with a realistic source, the initial mapping goal can be achieved by the optics system providing a structured target pattern with an ideal source. The algorithm is applied to several design examples. A few simple tasks are presented to discussed the ability and limitation of the this mothed. It is also presented that a homogeneous LED-illumination system design, in where, with a strongly tilted incident direction, a homogeneous distribution is achieved with a rather compact optics system and short working distance applying a relatively large LED source. It is shown that the lighting distribution patterns from the freeform surface elements can be significantly different from the others. The generation of a structured target pattern, applying weighting factor and smoothing factor, are discussed. Finally, freeform designs for much more complex sources like clusters of LED-sources are presented.

Identifying Synergies in Multilevel Interventions: The Convergence Strategy

ERIC Educational Resources Information Center

Lewis, Megan A.; Fitzgerald, Tania M.; Zulkiewicz, Brittany; Peinado, Susana; Williams, Pamela A.

2017-01-01

Social ecological models of health often describe multiple levels of influence that interact to influence health. However, it is still common for interventions to target only one or two of these levels, perhaps owing in part to a lack of guidance on how to design multilevel interventions to achieve optimal impact. The convergence strategy…

Airfoil Design Using a Coupled Euler and Integral Boundary Layer Method with Adjoint Based Sensitivities

NASA Technical Reports Server (NTRS)

Edwards, S.; Reuther, J.; Chattot, J. J.

1997-01-01

The objective of this paper is to present a control theory approach for the design of airfoils in the presence of viscous compressible flows. A coupled system of the integral boundary layer and the Euler equations is solved to provide rapid flow simulations. An adjunct approach consistent with the complete coupled state equations is employed to obtain the sensitivities needed to drive a numerical optimization algorithm. Design to target pressure distribution is demonstrated on an RAE 2822 airfoil at transonic speed.

Identification of small-molecule antagonists of the Pseudomonas aeruginosa transcriptional regulator PqsR: biophysically guided hit discovery and optimization.

PubMed

Klein, Tobias; Henn, Claudia; de Jong, Johannes C; Zimmer, Christina; Kirsch, Benjamin; Maurer, Christine K; Pistorius, Dominik; Müller, Rolf; Steinbach, Anke; Hartmann, Rolf W

2012-09-21

The Gram-negative pathogen Pseudomonas aeruginosa produces an intercellular alkyl quinolone signaling molecule, the Pseudomonas quinolone signal. The pqs quorum sensing communication system that is characteristic for P. aeruginosa regulates the production of virulence factors. Therefore, we consider the pqs system a novel target to limit P. aeruginosa pathogenicity. Here, we present small molecules targeting a key player of the pqs system, PqsR. A rational design strategy in combination with surface plasmon resonance biosensor analysis led to the identification of PqsR binders. Determination of thermodynamic binding signatures and functional characterization in E. coli guided the hit optimization, resulting in the potent hydroxamic acid derived PqsR antagonist 11 (IC(50) = 12.5 μM). Remarkably it displayed a comparable potency in P. aeruginosa (IC(50) = 23.6 μM) and reduced the production of the virulence factor pyocyanin. Beyond this, site-directed mutagenesis together with thermodynamic analysis provided insights into the energetic characteristics of protein-ligand interactions. Thus the identified PqsR antagonists are promising scaffolds for further drug design efforts against this important pathogen.

Approach range and velocity determination using laser sensors and retroreflector targets

NASA Technical Reports Server (NTRS)

Donovan, William J.

1991-01-01

A laser docking sensor study is currently in the third year of development. The design concept is considered to be validated. The concept is based on using standard radar techniques to provide range, velocity, and bearing information. Multiple targets are utilized to provide relative attitude data. The design requirements were to utilize existing space-qualifiable technology and require low system power, weight, and size yet, operate from 0.3 to 150 meters with a range accuracy greater than 3 millimeters and a range rate accuracy greater than 3 mm per second. The field of regard for the system is +/- 20 deg. The transmitter and receiver design features a diode laser, microlens beam steering, and power control as a function of range. The target design consists of five target sets, each having seven 3-inch retroreflectors, arranged around the docking port. The target map is stored in the sensor memory. Phase detection is used for ranging, with the frequency range-optimized. Coarse bearing measurement is provided by the scanning system (one set of binary optics) angle. Fine bearing measurement is provided by a quad detector. A MIL-STD-1750 A/B computer is used for processing. Initial test results indicate a probability of detection greater than 99 percent and a probability of false alarm less than 0.0001. The functional system is currently at the MIT/Lincoln Lab for demonstration.

Mixed oxidizer hybrid propulsion system optimization under uncertainty using applied response surface methodology and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Whitehead, James Joshua

The analysis documented herein provides an integrated approach for the conduct of optimization under uncertainty (OUU) using Monte Carlo Simulation (MCS) techniques coupled with response surface-based methods for characterization of mixture-dependent variables. This novel methodology provides an innovative means of conducting optimization studies under uncertainty in propulsion system design. Analytic inputs are based upon empirical regression rate information obtained from design of experiments (DOE) mixture studies utilizing a mixed oxidizer hybrid rocket concept. Hybrid fuel regression rate was selected as the target response variable for optimization under uncertainty, with maximization of regression rate chosen as the driving objective. Characteristic operational conditions and propellant mixture compositions from experimental efforts conducted during previous foundational work were combined with elemental uncertainty estimates as input variables. Response surfaces for mixture-dependent variables and their associated uncertainty levels were developed using quadratic response equations incorporating single and two-factor interactions. These analysis inputs, response surface equations and associated uncertainty contributions were applied to a probabilistic MCS to develop dispersed regression rates as a function of operational and mixture input conditions within design space. Illustrative case scenarios were developed and assessed using this analytic approach including fully and partially constrained operational condition sets over all of design mixture space. In addition, optimization sets were performed across an operationally representative region in operational space and across all investigated mixture combinations. These scenarios were selected as representative examples relevant to propulsion system optimization, particularly for hybrid and solid rocket platforms. Ternary diagrams, including contour and surface plots, were developed and utilized to aid in visualization. The concept of Expanded-Durov diagrams was also adopted and adapted to this study to aid in visualization of uncertainty bounds. Regions of maximum regression rate and associated uncertainties were determined for each set of case scenarios. Application of response surface methodology coupled with probabilistic-based MCS allowed for flexible and comprehensive interrogation of mixture and operating design space during optimization cases. Analyses were also conducted to assess sensitivity of uncertainty to variations in key elemental uncertainty estimates. The methodology developed during this research provides an innovative optimization tool for future propulsion design efforts.

The Storage Cell for the Tri-Experiment at COSY-JÜLICH

NASA Astrophysics Data System (ADS)

Felden, O.; Gebel, R.; Glende, M.; Lehrach, A.; Maier, R.; Prasuhn, D.; von Rossen, P.; Bisplinghoff, J.; Eversheim, P. D.; Hinterberger, F.

2002-04-01

At the EDDA experiment in the cooler synchrotron COSY in Jülich an atomic beam target is used which provides the designed polarization and density distribution. To increase the target density significantly a storage cell has been developed and implemented. This will contribute to a higher accuracy for the test of Time Reversal Invariance (TRI) which will be performed at the EDDA target place. To obtain the higher luminosity the target density and the transmission of the COSY beam through the cell were determined in their dependence on the cell aperture. Low storage cell apertures increase the target density in the cell but reduce the transmission of the circulating proton beam. To find the optimal cell design the transmission of the COSY beam was measured with movable scrapers and tested with an aperture at EDDA simulating the storage cell. The target density was calculated by Monte Carlo simulations for several cell geometries. An additional gain in target density is achieved by cooling the cell. A Teflon coating of the cell reduces depolarization of the target gas. First measurements with the EDDA detector have shown that the target density as well as the polarization are within the range of the expected values.

Optimization and evaluation of clarithromycin floating tablets using experimental mixture design.

PubMed

Uğurlu, Timucin; Karaçiçek, Uğur; Rayaman, Erkan

2014-01-01

The purpose of the study was to prepare and evaluate clarithromycin (CLA) floating tablets using experimental mixture design for treatment of Helicobacter pylori provided by prolonged gastric residence time and controlled plasma level. Ten different formulations were generated based on different molecular weight of hypromellose (HPMC K100, K4M, K15M) by using simplex lattice design (a sub-class of mixture design) with Minitab 16 software. Sodium bicarbonate and anhydrous citric acid were used as gas generating agents. Tablets were prepared by wet granulation technique. All of the process variables were fixed. Results of cumulative drug release at 8th h (CDR 8th) were statistically analyzed to get optimized formulation (OF). Optimized formulation, which gave floating lag time lower than 15 s and total floating time more than 10 h, was analyzed and compared with target for CDR 8th (80%). A good agreement was shown between predicted and actual values of CDR 8th with a variation lower than 1%. The activity of clarithromycin contained optimizedformula against H. pylori were quantified using well diffusion agar assay. Diameters of inhibition zones vs. log10 clarithromycin concentrations were plotted in order to obtain a standard curve and clarithromycin activity.

Cold flow simulation of an internal combustion engine with vertical valves using layering approach

NASA Astrophysics Data System (ADS)

Martinas, G.; Cupsa, O. S.; Stan, L. C.; Arsenie, A.

2015-11-01

Complying with emission requirements and fuel consumption efficiency are the points which drive any development of internal combustion engine. Refinement of the process of combustion and mixture formation, together with in-cylinder flow refinement, is a requirement, valves and piston bowl and intake exhaust port design optimization is essential. In order to reduce the time for design optimization cycle it is used Computational Fluid Dynamics (CFD). Being time consuming and highly costly caring out of experiment using flow bench testing this methods start to become less utilized. Air motion inside the intake manifold is one of the important factors, which govern the engine performance and emission of multi-cylinder diesel engines. Any cold flow study on IC is targeting the process of identifying and improving the fluid flow inside the ports and the combustion chamber. This is only the base for an optimization process targeting to increase the volume of air accessing the combustion space and to increase the turbulence of the air at the end of the compression stage. One of the first conclusions will be that the valve diameter is a fine tradeoff between the need for a bigger diameter involving a greater mass of air filling the cylinder, and the need of a smaller diameter in order to reduce the blind zone. Here there is room for optimization studies. The relative pressure indicates a suction effect coming from the moving piston. The more the shape of the inlet port is smoother and the diameter of the piston is bigger, the aerodynamic resistance of the geometry will be smaller so that the difference of inlet port pressure and the pressure near to piston face will be smaller. Here again there is enough room for more optimization studies.

Assessment of Laser-Driven Pulsed Neutron Sources for Poolside Neutron-based Advanced NDE – A Pathway to LANSCE-like Characterization at INL

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

Roth, Markus; Vogel, Sven C.; Bourke, Mark Andrew M.

A variety of opportunities for characterization of fresh nuclear fuels using thermal (~25meV) and epithermal (~10eV) neutrons have been documented at Los Alamos National Laboratory. They include spatially resolved non-destructive characterization of features, isotopic enrichment, chemical heterogeneity and stoichiometry. The LANSCE spallation neutron source is well suited in neutron fluence and temporal characteristics for studies of fuels. However, recent advances in high power short pulse lasers suggest that compact neutron sources might, over the next decade, become viable at a price point that would permit their consideration for poolside characterization on site at irradiation facilities. In a laser-driven neutron sourcemore » the laser is used to accelerate deuterium ions into a beryllium target where neutrons are produced. At this time, the technology is new and their total neutron production is approximately four orders of magnitude less than a facility like LANSCE. However, recent measurements on a sub-optimized system demonstrated >10 10 neutrons in sub-nanosecond pulses in predominantly forward direction. The compactness of the target system compared to a spallation target may allow exchanging the target during a measurement to e.g. characterize a highly radioactive sample with thermal, epithermal, and fast neutrons as well as hard X-rays, thus avoiding sample handling. At this time several groups are working on laser-driven neutron production and are advancing concepts for lasers, laser targets, and optimized neutron target/moderator systems. Advances in performance sufficient to enable poolside fuels characterization with LANSCE-like fluence on sample within a decade may be possible. This report describes the underlying physics and state-of-the-art of the laser-driven neutron production process from the perspective of the DOE/NE mission. It also discusses the development and understanding that will be necessary to provide customized capability for characterization of irradiated fuels. Potential operational advantages compared to a spallation neutron source include reduced shielding complexity, reduced energy requirements, and a production target free of fission products. Contributors to this report include experts in laser-driven neutron production (Roth, Fernandez), laser design (Haefner, Siders, Leemans), laser target design (Glenzer), spallation target/moderator design (Mocko), neutron instrumentation and characterization applications (Vogel, Bourke).« less

Optimization of coronagraph design for segmented aperture telescopes

NASA Astrophysics Data System (ADS)

Jewell, Jeffrey; Ruane, Garreth; Shaklan, Stuart; Mawet, Dimitri; Redding, Dave

2017-09-01

The goal of directly imaging Earth-like planets in the habitable zone of other stars has motivated the design of coronagraphs for use with large segmented aperture space telescopes. In order to achieve an optimal trade-off between planet light throughput and diffracted starlight suppression, we consider coronagraphs comprised of a stage of phase control implemented with deformable mirrors (or other optical elements), pupil plane apodization masks (gray scale or complex valued), and focal plane masks (either amplitude only or complex-valued, including phase only such as the vector vortex coronagraph). The optimization of these optical elements, with the goal of achieving 10 or more orders of magnitude in the suppression of on-axis (starlight) diffracted light, represents a challenging non-convex optimization problem with a nonlinear dependence on control degrees of freedom. We develop a new algorithmic approach to the design optimization problem, which we call the "Auxiliary Field Optimization" (AFO) algorithm. The central idea of the algorithm is to embed the original optimization problem, for either phase or amplitude (apodization) in various planes of the coronagraph, into a problem containing additional degrees of freedom, specifically fictitious "auxiliary" electric fields which serve as targets to inform the variation of our phase or amplitude parameters leading to good feasible designs. We present the algorithm, discuss details of its numerical implementation, and prove convergence to local minima of the objective function (here taken to be the intensity of the on-axis source in a "dark hole" region in the science focal plane). Finally, we present results showing application of the algorithm to both unobscured off-axis and obscured on-axis segmented telescope aperture designs. The application of the AFO algorithm to the coronagraph design problem has produced solutions which are capable of directly imaging planets in the habitable zone, provided end-to-end telescope system stability requirements can be met. Ongoing work includes advances of the AFO algorithm reported here to design in additional robustness to a resolved star, and other phase or amplitude aberrations to be encountered in a real segmented aperture space telescope.

Energy Efficient Waste Heat Recovery from an Engine Exhaust System

DTIC Science & Technology

2016-12-01

targets. Since solar panels and wind turbines will not work for ships; the energy savings must come from making the existing power generation...achieve an approximate solution to the problem . The research for this thesis involved design by analysis of heat exchange in a gas turbine exhaust...effectiveness of a new style of heat exchanger for waste heat recovery. The new design sought to optimize heat recovery from a gas turbine engine exhaust as

Joint Waveform Optimization and Adaptive Processing for Random-Phase Radar Signals

DTIC Science & Technology

2014-01-01

extended targets,” IEEE Journal of Selected Topics in Signal Processing, vol. 1, no. 1, pp. 42– 55, June 2007. [2] S. Sen and A. Nehorai, “ OFDM mimo ...radar compared to traditional waveforms. I. INTRODUCTION There has been much recent interest in waveform design for multiple-input, multiple-output ( MIMO ...amplitude. When the resolution capability of the MIMO radar system is of interest, the transmit waveform can be designed to sharpen the radar ambiguity

Human Mars Ascent Vehicle Performance Sensitivities

NASA Technical Reports Server (NTRS)

Polsgrove, Tara P.; Thomas, Herbert D.

2016-01-01

Human Mars mission architecture studies have shown that the ascent vehicle mass drives performance requirements for the descent and in-space transportation elements. Understanding the sensitivity of Mars ascent vehicle (MAV) mass to various mission and vehicle design choices enables overall transportation system optimization. This paper presents the results of a variety of sensitivity trades affecting MAV performance including: landing site latitude, target orbit, initial thrust to weight ratio, staging options, specific impulse, propellant type and engine design.

United States Air Force Graduate Student Summer Support Program (1987). Program Management Report.

DTIC Science & Technology

1987-12-01

were briefed on the benefits and research opportunities of the SFRP. The targeted groups within the University community were faculty of the...Effects on Fine Mary C. Robinson Motor Skill and Decoding Tasks 78 Design of a Mechanism to Control Wind Filiberto Santiago Tunnel Turbulence 79 Low...Systems 81 The Integration of Decision Support Jon A. Shupe Problems into Feature Modeling Based Design 89 r 0 82 Optimal Control of the Wing

Quantitative structure-activity relationship: promising advances in drug discovery platforms.

PubMed

Wang, Tao; Wu, Mian-Bin; Lin, Jian-Ping; Yang, Li-Rong

2015-12-01

Quantitative structure-activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced. In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization. QSAR should intentionally be used as a powerful tool for fragment-based drug design platforms in the field of drug discovery and design. Although there have been an increasing number of experimentally determined protein structures in recent years, a great number of protein structures cannot be easily obtained (i.e., membrane transport proteins and G-protein coupled receptors). Fragment-based drug discovery, such as QSAR, could be applied further and have a significant role in dealing with these problems. Moreover, along with the development of computer software and hardware, it is believed that QSAR will be increasingly important.

An integrated, quality by design (QbD) approach for design, development and optimization of orally disintegrating tablet formulation of carbamazepine.

PubMed

Mishra, Saurabh M; Rohera, Bhagwan D

2017-11-01

The objective of the present study was to design and develop a formulation for orally disintegrating tablets (ODTs) of carbamazepine using quality by design principles. The target product profile (TPP) and quality target product profile (QTPP) of ODTs were identified. Risk assessment was carried out by leveraging prior knowledge and experience to define the criticality of factors based on their impact by Ishikawa fishbone diagram and preliminary hazard analysis tool. Box-Behnken response surface methodology was used to study the effect of critical factors on various attributes of ODTs. The independent factors selected were compression pressure (X 1 ), concentration of sublimating agent (volatile material) (X 2 ), disintegrant concentration (X 3 ) and the responses were tablet crushing strength, tablet porosity, disintegration time, water absorption time, tablet friability and drug dissolution. ANOVA and lack of fit test illustrated that selected independent variables had significant effect on the response variables, and excellent correlation was observed between actual and predicted values. Optimization by desirability function indicated that compression pressure, X 1 (1534 lbs), ammonium bicarbonate concentration, X 2 (7.68%) and Kollidon ® CL-SF concentration, X 3 (6%) were optimum to prepare ODT formulation of carbamazepine of desired attributes complying with QTPP. Thus, in the present study, a high level of assurance was established for ODT product quality and performance.

REBL: design progress toward 16 nm half-pitch maskless projection electron beam lithography

NASA Astrophysics Data System (ADS)

McCord, Mark A.; Petric, Paul; Ummethala, Upendra; Carroll, Allen; Kojima, Shinichi; Grella, Luca; Shriyan, Sameet; Rettner, Charles T.; Bevis, Chris F.

2012-03-01

REBL (Reflective Electron Beam Lithography) is a novel concept for high speed maskless projection electron beam lithography. Originally targeting 45 nm HP (half pitch) under a DARPA funded contract, we are now working on optimizing the optics and architecture for the commercial silicon integrated circuit fabrication market at the equivalent of 16 nm HP. The shift to smaller features requires innovation in most major subsystems of the tool, including optics, stage, and metrology. We also require better simulation and understanding of the exposure process. In order to meet blur requirements for 16 nm lithography, we are both shrinking the pixel size and reducing the beam current. Throughput will be maintained by increasing the number of columns as well as other design optimizations. In consequence, the maximum stage speed required to meet wafer throughput targets at 16 nm will be much less than originally planned for at 45 nm. As a result, we are changing the stage architecture from a rotary design to a linear design that can still meet the throughput requirements but with more conventional technology that entails less technical risk. The linear concept also allows for simplifications in the datapath, primarily from being able to reuse pattern data across dies and columns. Finally, we are now able to demonstrate working dynamic pattern generator (DPG) chips, CMOS chips with microfabricated lenslets on top to prevent crosstalk between pixels.

Rational design based synthetic polyepitope DNA vaccine for eliciting HIV-specific CD8+ T cell responses.

PubMed

Bazhan, S I; Karpenko, L I; Ilyicheva, T N; Belavin, P A; Seregin, S V; Danilyuk, N K; Antonets, D V; Ilyichev, A A

2010-04-01

Advances in defining HIV-1 CD8+ T cell epitopes and understanding endogenous MHC class I antigen processing enable the rational design of polyepitope vaccines for eliciting broadly targeted CD8+ T cell responses to HIV-1. Here we describe the construction and comparison of experimental DNA vaccines consisting of ten selected HLA-A2 epitopes from the major HIV-1 antigens Env, Gag, Pol, Nef, and Vpr. The immunogenicity of designed gene constructs was assessed after double DNA prime, single vaccinia virus boost immunization of HLA-A2 transgenic mice. We compared a number of parameters including different strategies for fusing ubiquitin to the polyepitope and including spacer sequences between epitopes to optimize proteasome liberation and TAP transport. It was demonstrated that the vaccine construct that induced in vitro the largest number of [peptide-MHC class I] complexes was also the most immunogenic in the animal experiments. This most immunogenic vaccine construct contained the N-terminal ubiquitin for targeting the polyepitope to the proteasome and included both proteasome liberation and TAP transport optimized spacer sequences that flanked the epitopes within the polyepitope construct. The immunogenicity of determinants was strictly related to their affinities for HLA-A2. Our finding supports the concept of rational vaccine design based on detailed knowledge of antigen processing. Copyright 2010 Elsevier Ltd. All rights reserved.

Progress Toward Attractive Stellarators

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

Neilson, G H; Brown, T G; Gates, D A

The quasi-axisymmetric stellarator (QAS) concept offers a promising path to a more compact stellarator reactor, closer in linear dimensions to tokamak reactors than previous stellarator designs. Concept improvements are needed, however, to make it more maintainable and more compatible with high plant availability. Using the ARIES-CS design as a starting point, compact stellarator designs with improved maintenance characteristics have been developed. While the ARIES-CS features a through-the-port maintenance scheme, we have investigated configuration changes to enable a sector-maintenance approach, as envisioned for example in ARIES AT. Three approaches are reported. The first is to make tradeoffs within the QAS designmore » space, giving greater emphasis to maintainability criteria. The second approach is to improve the optimization tools to more accurately and efficiently target the physics properties of importance. The third is to employ a hybrid coil topology, so that the plasma shaping functions of the main coils are shared more optimally, either with passive conductors made of high-temperature superconductor or with local compensation coils, allowing the main coils to become simpler. Optimization tools are being improved to test these approaches.« less

Radar correlated imaging for extended target by the combination of negative exponential restraint and total variation

NASA Astrophysics Data System (ADS)

Qian, Tingting; Wang, Lianlian; Lu, Guanghua

2017-07-01

Radar correlated imaging (RCI) introduces the optical correlated imaging technology to traditional microwave imaging, which has raised widespread concern recently. Conventional RCI methods neglect the structural information of complex extended target, which makes the quality of recovery result not really perfect, thus a novel combination of negative exponential restraint and total variation (NER-TV) algorithm for extended target imaging is proposed in this paper. The sparsity is measured by a sequential order one negative exponential function, then the 2D total variation technique is introduced to design a novel optimization problem for extended target imaging. And the proven alternating direction method of multipliers is applied to solve the new problem. Experimental results show that the proposed algorithm could realize high resolution imaging efficiently for extended target.

Selectivity on-target of bromodomain chemical probes by structure-guided medicinal chemistry and chemical biology

PubMed Central

Galdeano, Carles; Ciulli, Alessio

2017-01-01

Targeting epigenetic proteins is a rapidly growing area for medicinal chemistry and drug discovery. Recent years have seen an explosion of interest in developing small molecules binding to bromodomains, the readers of acetyl-lysine modifications. A plethora of co-crystal structures has motivated focused fragment-based design and optimization programs within both industry and academia. These efforts have yielded several compounds entering the clinic, and many more are increasingly being used as chemical probes to interrogate bromodomain biology. High selectivity of chemical probes is necessary to ensure biological activity is due to an on-target effect. Here, we review the state-of-the-art of bromodomain-targeting compounds, focusing on the structural basis for their on-target selectivity or lack thereof. We also highlight chemical biology approaches to enhance on-target selectivity. PMID:27193077

More complete gene silencing by fewer siRNAs: transparent optimized design and biophysical signature

PubMed Central

Ladunga, Istvan

2007-01-01

Highly accurate knockdown functional analyses based on RNA interference (RNAi) require the possible most complete hydrolysis of the targeted mRNA while avoiding the degradation of untargeted genes (off-target effects). This in turn requires significant improvements to target selection for two reasons. First, the average silencing activity of randomly selected siRNAs is as low as 62%. Second, applying more than five different siRNAs may lead to saturation of the RNA-induced silencing complex (RISC) and to the degradation of untargeted genes. Therefore, selecting a small number of highly active siRNAs is critical for maximizing knockdown and minimizing off-target effects. To satisfy these needs, a publicly available and transparent machine learning tool is presented that ranks all possible siRNAs for each targeted gene. Support vector machines (SVMs) with polynomial kernels and constrained optimization models select and utilize the most predictive effective combinations from 572 sequence, thermodynamic, accessibility and self-hairpin features over 2200 published siRNAs. This tool reaches an accuracy of 92.3% in cross-validation experiments. We fully present the underlying biophysical signature that involves free energy, accessibility and dinucleotide characteristics. We show that while complete silencing is possible at certain structured target sites, accessibility information improves the prediction of the 90% active siRNA target sites. Fast siRNA activity predictions can be performed on our web server at . PMID:17169992

Enabling Quantitative Optical Imaging for In-die-capable Critical Dimension Targets

PubMed Central

Barnes, B.M.; Henn, M.-A.; Sohn, M. Y.; Zhou, H.; Silver, R. M.

2017-01-01

Dimensional scaling trends will eventually bring semiconductor critical dimensions (CDs) down to only a few atoms in width. New optical techniques are required to address the measurement and variability for these CDs using sufficiently small in-die metrology targets. Recently, Qin et al. [Light Sci Appl, 5, e16038 (2016)] demonstrated quantitative model-based measurements of finite sets of lines with features as small as 16 nm using 450 nm wavelength light. This paper uses simulation studies, augmented with experiments at 193 nm wavelength, to adapt and optimize the finite sets of features that work as in-die-capable metrology targets with minimal increases in parametric uncertainty. A finite element based solver for time-harmonic Maxwell's equations yields two- and three-dimensional simulations of the electromagnetic scattering for optimizing the design of such targets as functions of reduced line lengths, fewer number of lines, fewer focal positions, smaller critical dimensions, and shorter illumination wavelength. Metrology targets that exceeded performance requirements are as short as 3 μm for 193 nm light, feature as few as eight lines, and are extensible to sub-10 nm CDs. Target areas measured at 193 nm can be fifteen times smaller in area than current state-of-the-art scatterometry targets described in the literature. This new methodology is demonstrated to be a promising alternative for optical model-based in-die CD metrology. PMID:28757674

Frequency Tuning of Vibration Absorber Using Topology Optimization

NASA Astrophysics Data System (ADS)

Harel, Swapnil Subhash

A tuned mass absorber is a system for reducing the amplitude in one oscillator by coupling it to a second oscillator. If tuned correctly, the maximum amplitude of the first oscillator in response to a periodic driver will be lowered, and much of the vibration will be 'transferred' to the second oscillator. The tuned vibration absorber (TVA) has been utilized for vibration control purposes in many sectors of Civil/Automotive/Aerospace Engineering for many decades since its inception. Time and again we come across a situation in which a vibratory system is required to run near resonance. In the past, approaches have been made to design such auxiliary spring mass tuned absorbers for the safety of the structures. This research focuses on the development and optimization of continuously tuned mass absorbers as a substitute to the discretely tuned mass absorbers (spring- mass system). After conducting the study of structural behavior, the boundary condition and frequency to which the absorber is to be tuned are determined. The Modal analysis approach is used to determine mode shapes and frequencies. The absorber is designed and optimized using the topology optimization tool, which simultaneously designs, optimizes and tunes the absorber to the desired frequency. The tuned, optimized absorber, after post processing, is attached to the target structure. The number of the absorbers are increased to amplify bandwidth and thereby upgrade the safety of structure for a wide range of frequency. The frequency response analysis is carried out using various combinations of structure and number of absorber cell.

Biolayer modeling and optimization for the SPARROW biosensor

NASA Astrophysics Data System (ADS)

Feng, Ke

2007-12-01

Biosensor direct detection of molecular binding events is of significant interest in applications from molecular screening for cancer drug design to bioagent detection for homeland security and defense. The Stacked Planar Affinity Regulated Resonant Optical Waveguide (SPARROW) structure based on coupled waveguides was recently developed to achieve increased sensitivity within a fieldable biosensor device configuration. Under ideal operating conditions, modification of the effective propagation constant of the structure's sensing waveguide through selective attachment of specific targets to probes on the waveguide surface results in a change in the coupling characteristics of the guide over a specifically designed interaction length with the analyte. Monitoring the relative power in each waveguide after interaction enables 'recognition' of those targets which have selectively bound to the surface. However, fabrication tolerances, waveguide interface roughness, biolayer surface roughness and biolayer partial coverage have an effect on biosensor behavior and achievable limit of detection (LOD). In addition to these influences which play a role in device optimization, the influence of the spatially random surface loading of molecular binding events has to be considered, especially for low surface coverage. In this dissertation an analytic model is established for the SPARROW biosensor which accounts for these nonidealities with which the design of the biosensor can be guided and optimized. For the idealized case of uniform waveguide transducer layers and biolayer, both theoretical simulation (analytical expression) and computer simulation (numerical calculation) are completed. For the nonideal case of an inhomogeneous transducer with nonideal waveguide and biolayer surfaces, device output power is affected by such physical influences as surface scattering, coupling length, absorption, and percent coverage of binding events. Using grating and perturbation techniques we explore the influence of imperfect surfaces and random surface loading on scattering loss and coupling length. Results provide a range of achievable limits of detection in the SPARROW device for a given target size, surface loading, and detectable optical power.

Quality by design case study 1: Design of 5-fluorouracil loaded lipid nanoparticles by the W/O/W double emulsion - Solvent evaporation method.

PubMed

Amasya, Gulin; Badilli, Ulya; Aksu, Buket; Tarimci, Nilufer

2016-03-10

With Quality by Design (QbD), a systematic approach involving design and development of all production processes to achieve the final product with a predetermined quality, you work within a design space that determines the critical formulation and process parameters. Verification of the quality of the final product is no longer necessary. In the current study, the QbD approach was used in the preparation of lipid nanoparticle formulations to improve skin penetration of 5-Fluorouracil, a widely-used compound for treating non-melanoma skin cancer. 5-Fluorouracil-loaded lipid nanoparticles were prepared by the W/O/W double emulsion - solvent evaporation method. Artificial neural network software was used to evaluate the data obtained from the lipid nanoparticle formulations, to establish the design space, and to optimize the formulations. Two different artificial neural network models were developed. The limit values of the design space of the inputs and outputs obtained by both models were found to be within the knowledge space. The optimal formulations recommended by the models were prepared and the critical quality attributes belonging to those formulations were assigned. The experimental results remained within the design space limit values. Consequently, optimal formulations with the critical quality attributes determined to achieve the Quality Target Product Profile were successfully obtained within the design space by following the QbD steps. Copyright © 2016 Elsevier B.V. All rights reserved.

Spacecraft Mission Design for the Mitigation of the 2017 PDC Hypothetical Asteroid Threat

NASA Technical Reports Server (NTRS)

Barbee, Brent W.; Sarli, Bruno V.; Lyzhoft, Josh; Chodas, Paul W.; Englander, Jacob A.

2017-01-01

This paper presents a detailed mission design analysis results for the 2017 Planetary Defense Conference (PDC) Hypothetical Asteroid Impact Scenario, documented at https:cneos.jpl.nasa.govpdcspdc17. The mission design includes campaigns for both reconnaissance (flyby or rendezvous) of the asteroid (to characterize it and the nature of the threat it poses to Earth) and mitigation of the asteroid, via kinetic impactor deflection, nuclear explosive device (NED) deflection, or NED disruption. Relevant scenario parameters are varied to assess the sensitivity of the design outcome, such as asteroid bulk density, asteroid diameter, momentum enhancement factor, spacecraft launch vehicle, and mitigation system type. Different trajectory types are evaluated in the mission design process from purely ballistic to those involving optimal midcourse maneuvers, planetary gravity assists, and/or low-thrust solar electric propulsion. The trajectory optimization is targeted around peak deflection points that were found through a novel linear numerical technique method. The optimization process includes constrain parameters, such as Earth departure date, launch declination, spacecraft, asteroid relative velocity and solar phase angle, spacecraft dry mass, minimum/maximum spacecraft distances from Sun and Earth, and Earth-spacecraft communications line of sight. Results show that one of the best options for the 2017 PDC deflection is solar electric propelled rendezvous mission with a single spacecraft using NED for the deflection.

Optimal design of near-Earth asteroid sample-return trajectories in the Sun-Earth-Moon system

NASA Astrophysics Data System (ADS)

He, Shengmao; Zhu, Zhengfan; Peng, Chao; Ma, Jian; Zhu, Xiaolong; Gao, Yang

2016-08-01

In the 6th edition of the Chinese Space Trajectory Design Competition held in 2014, a near-Earth asteroid sample-return trajectory design problem was released, in which the motion of the spacecraft is modeled in multi-body dynamics, considering the gravitational forces of the Sun, Earth, and Moon. It is proposed that an electric-propulsion spacecraft initially parking in a circular 200-km-altitude low Earth orbit is expected to rendezvous with an asteroid and carry as much sample as possible back to the Earth in a 10-year time frame. The team from the Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences has reported a solution with an asteroid sample mass of 328 tons, which is ranked first in the competition. In this article, we will present our design and optimization methods, primarily including overall analysis, target selection, escape from and capture by the Earth-Moon system, and optimization of impulsive and low-thrust trajectories that are modeled in multi-body dynamics. The orbital resonance concept and lunar gravity assists are considered key techniques employed for trajectory design. The reported solution, preliminarily revealing the feasibility of returning a hundreds-of-tons asteroid or asteroid sample, envisions future space missions relating to near-Earth asteroid exploration.

Design of complex bone internal structure using topology optimization with perimeter control.

PubMed

Park, Jaejong; Sutradhar, Alok; Shah, Jami J; Paulino, Glaucio H

2018-03-01

Large facial bone loss usually requires patient-specific bone implants to restore the structural integrity and functionality that also affects the appearance of each patient. Titanium alloys (e.g., Ti-6Al-4V) are typically used in the interfacial porous coatings between the implant and the surrounding bone to promote stability. There exists a property mismatch between the two that in general leads to complications such as stress-shielding. This biomechanical discrepancy is a hurdle in the design of bone replacements. To alleviate the mismatch, the internal structure of the bone replacements should match that of the bone. Topology optimization has proven to be a good technique for designing bone replacements. However, the complex internal structure of the bone is difficult to mimic using conventional topology optimization methods without additional restrictions. In this work, the complex bone internal structure is recovered using a perimeter control based topology optimization approach. By restricting the solution space by means of the perimeter, the intricate design complexity of bones can be achieved. Three different bone regions with well-known physiological loadings are selected to illustrate the method. Additionally, we found that the target perimeter value and the pattern of the initial distribution play a vital role in obtaining the natural curvatures in the bone internal structures as well as avoiding excessive island patterns. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization of Soluble Expression and Purification of Recombinant Human Rhinovirus Type-14 3C Protease Using Statistically Designed Experiments: Isolation and Characterization of the Enzyme.

PubMed

Antoniou, Georgia; Papakyriacou, Irineos; Papaneophytou, Christos

2017-10-01

Human rhinovirus (HRV) 3C protease is widely used in recombinant protein production for various applications such as biochemical characterization and structural biology projects to separate recombinant fusion proteins from their affinity tags in order to prevent interference between these tags and the target proteins. Herein, we report the optimization of expression and purification conditions of glutathione S-transferase (GST)-tagged HRV 3C protease by statistically designed experiments. Soluble expression of GST-HRV 3C protease was initially optimized by response surface methodology (RSM), and a 5.5-fold increase in enzyme yield was achieved. Subsequently, we developed a new incomplete factorial (IF) design that examines four variables (bacterial strain, expression temperature, induction time, and inducer concentration) in a single experiment. The new design called Incomplete Factorial-Strain/Temperature/Time/Inducer (IF-STTI) was validated using three GST-tagged proteins. In all cases, IF-STTI resulted in only 10% lower expression yields than those obtained by RSM. Purification of GST-HRV 3C was optimized by an IF design that examines simultaneously the effect of the amount of resin, incubation time of cell lysate with resin, and glycerol and DTT concentration in buffers, and a further 15% increase in protease recovery was achieved. Purified GST-HRV 3C protease was active at both 4 and 25 °C in a variety of buffers.

Design of siRNA Therapeutics from the Molecular Scale

PubMed Central

Angart, Phillip; Vocelle, Daniel; Chan, Christina; Walton, S. Patrick

2013-01-01

While protein-based therapeutics is well-established in the market, development of nucleic acid therapeutics has lagged. Short interfering RNAs (siRNAs) represent an exciting new direction for the pharmaceutical industry. These small, chemically synthesized RNAs can knock down the expression of target genes through the use of a native eukaryotic pathway called RNA interference (RNAi). Though siRNAs are routinely used in research studies of eukaryotic biological processes, transitioning the technology to the clinic has proven challenging. Early efforts to design an siRNA therapeutic have demonstrated the difficulties in generating a highly-active siRNA with good specificity and a delivery vehicle that can protect the siRNA as it is transported to a specific tissue. In this review article, we discuss design considerations for siRNA therapeutics, identifying criteria for choosing therapeutic targets, producing highly-active siRNA sequences, and designing an optimized delivery vehicle. Taken together, these design considerations provide logical guidelines for generating novel siRNA therapeutics. PMID:23976875

Quantum mechanical design of enzyme active sites.

PubMed

Zhang, Xiyun; DeChancie, Jason; Gunaydin, Hakan; Chowdry, Arnab B; Clemente, Fernando R; Smith, Adam J T; Handel, T M; Houk, K N

2008-02-01

The design of active sites has been carried out using quantum mechanical calculations to predict the rate-determining transition state of a desired reaction in presence of the optimal arrangement of catalytic functional groups (theozyme). Eleven versatile reaction targets were chosen, including hydrolysis, dehydration, isomerization, aldol, and Diels-Alder reactions. For each of the targets, the predicted mechanism and the rate-determining transition state (TS) of the uncatalyzed reaction in water is presented. For the rate-determining TS, a catalytic site was designed using naturalistic catalytic units followed by an estimation of the rate acceleration provided by a reoptimization of the catalytic site. Finally, the geometries of the sites were compared to the X-ray structures of related natural enzymes. Recent advances in computational algorithms and power, coupled with successes in computational protein design, have provided a powerful context for undertaking such an endeavor. We propose that theozymes are excellent candidates to serve as the active site models for design processes.

An experimental sample of the field gamma-spectrometer based on solid state Si-photomultiplier

NASA Astrophysics Data System (ADS)

Denisov, Viktor; Korotaev, Valery; Titov, Aleksandr; Blokhina, Anastasia; Kleshchenok, Maksim

2017-05-01

Design of optical-electronic devices and systems involves the selection of such technical patterns that under given initial requirements and conditions are optimal according to certain criteria. The original characteristic of the OES for any purpose, defining its most important feature ability is a threshold detection. Based on this property, will be achieved the required functional quality of the device or system. Therefore, the original criteria and optimization methods have to subordinate to the idea of a better detectability. Generally reduces to the problem of optimal selection of the expected (predetermined) signals in the predetermined observation conditions. Thus the main purpose of optimization of the system when calculating its detectability is the choice of circuits and components that provide the most effective selection of a target.

Rational Design of Plasmonic Nanoparticles for Enhanced Cavitation and Cell Perforation.

PubMed

Lachaine, Rémi; Boutopoulos, Christos; Lajoie, Pierre-Yves; Boulais, Étienne; Meunier, Michel

2016-05-11

Metallic nanoparticles are routinely used as nanoscale antenna capable of absorbing and converting photon energy with subwavelength resolution. Many applications, notably in nanomedicine and nanobiotechnology, benefit from the enhanced optical properties of these materials, which can be exploited to image, damage, or destroy targeted cells and subcellular structures with unprecedented precision. Modern inorganic chemistry enables the synthesis of a large library of nanoparticles with an increasing variety of shapes, composition, and optical characteristic. However, identifying and tailoring nanoparticles morphology to specific applications remains challenging and limits the development of efficient nanoplasmonic technologies. In this work, we report a strategy for the rational design of gold plasmonic nanoshells (AuNS) for the efficient ultrafast laser-based nanoscale bubble generation and cell membrane perforation, which constitute one of the most crucial challenges toward the development of effective gene therapy treatments. We design an in silico rational design framework that we use to tune AuNS morphology to simultaneously optimize for the reduction of the cavitation threshold while preserving the particle structural integrity. Our optimization procedure yields optimal AuNS that are slightly detuned compared to their plasmonic resonance conditions with an optical breakdown threshold 30% lower than randomly selected AuNS and 13% lower compared to similarly optimized gold nanoparticles (AuNP). This design strategy is validated using time-resolved bubble spectroscopy, shadowgraphy imaging and electron microscopy that confirm the particle structural integrity and a reduction of 51% of the cavitation threshold relative to optimal AuNP. Rationally designed AuNS are finally used to perforate cancer cells with an efficiency of 61%, using 33% less energy compared to AuNP, which demonstrate that our rational design framework is readily transferable to a cell environment. The methodology developed here thus provides a general strategy for the systematic design of nanoparticles for nanomedical applications and should be broadly applicable to bioimaging and cell nanosurgery.

Targeted drug delivery and enhanced intracellular release using functionalized liposomes

NASA Astrophysics Data System (ADS)

Garg, Ashish

The ability to target cancer cells using an appropriate drug delivery system can significantly reduce the associated side effects from cancer therapies and can help in improving the overall quality of life, post cancer survival. Integrin alpha5beta1 is expressed on several types of cancer cells, including colon cancer and plays an important role in tumor growth and metastasis. Thus, the ability to target the integrin alpha 5beta1 using an appropriate drug delivery nano-vector can significantly help in inhibiting tumor growth and reducing tumor metastasis. The work in this thesis focuses on designing and optimizing, functionalized stealth liposomes (liposomes covered with polyethylene glycol (PEG)) that specifically target the integrin alpha5beta1. The PEG provides a steric barrier allowing the liposomes to circulate in the blood for longer duration and the functionalizing moiety, PR_b peptide specifically recognizes and binds to integrin alpha5beta1 expressing cells. The work demonstrates that by optimizing the amount of PEG and PR_b on the liposomal interface, nano-vectors can be engineered that bind to CT26.WT colon cancer cells in a specific manner and internalize through alpha 5beta1-mediated endocytosis. To further improve the efficacy of the system, PR_b functionalized pH-sensitive stealth liposomes that exhibit triggered release under mild acidic conditions present in endocytotic vesicles were designed. The study showed that PR_b functionalized pH-sensitive stealth liposomes, undergo destabilization under mildly acidic conditions and incorporation of the PR_b peptide does not significantly affect the pH-sensitivity of the liposomes. PR_b functionalized pH-sensitive stealth liposomes bind to CT26.WT colon carcinoma cells that express integrin alpha5beta 1, undergo cellular internalization, and release their load intracellularly in a short period of time as compared to other formulations. PR_b-targeted pH-sensitive stealth liposomes encapsulating 5-fluorouracil (5-FU) show significantly higher cytotoxicity than the PR_b-targeted inert stealth liposomes and the non-targeted stealth liposomes (both pH-sensitive and inert). The studies demonstrated that optimized PR_b functionalized pH sensitive liposomes have the potential to deliver a payload, such as chemotherapeutic agents, directly to colon cancer cells in an efficient and specific manner.

DARPin-targeting of Measles Virus: Unique Bispecificity, Effective Oncolysis, and Enhanced Safety

PubMed Central

Friedrich, Katrin; Hanauer, Jan RH; Prüfer, Steffen; Münch, Robert C; Völker, Iris; Filippis, Christodoulos; Jost, Christian; Hanschmann, Kay-Martin; Cattaneo, Roberto; Peng, Kah-Whye; Plückthun, Andreas; Buchholz, Christian J; Cichutek, Klaus; Mühlebach, Michael D

2013-01-01

Oncolytic virotherapy is an emerging treatment modality that uses replication-competent viruses to destroy cancers. Many naturally occurring viruses have a preferential, although nonexclusive, tropism for tumors and tumor cells. In addition, specific targeting of cancer cells can be achieved at the virus entry level. We optimized retargeting of cell entry by elongating the measles virus attachment protein with designed ankyrin repeat proteins (DARPins), while simultaneously ablating entry through the natural receptors. DARPin-targeted viruses were strongly attenuated in off-target tissue, thereby enhancing safety, but completely eliminated tumor xenografts. Taking advantage of the unique properties of DARPins of being fused without generating folding problems, we generated a virus simultaneous targeting two different tumor markers. The bispecific virus retained the original oncolytic efficacy, while providing proof of concept for a strategy to counteract issues of resistance development. Thus, DARPin-targeting opens new prospects for the development of personalized, targeted therapeutics. PMID:23380817

Design of a family of ring-core fibers for OAM transmission studies.

PubMed

Brunet, Charles; Ung, Bora; Wang, Lixian; Messaddeq, Younès; LaRochelle, Sophie; Rusch, Leslie A

2015-04-20

We propose a family of ring-core fibers, designed for the transmission of OAM modes, that can be fabricated by drawing five different fibers from a single preform. This novel technique allows us to experimentally sweep design parameters and speed up the fiber design optimization process. Such a family of fibers could be used to examine system performance, but also facilitate understanding of parameter impact in the transition from design to fabrication. We present design parameters characterizing our fiber, and enumerate criteria to be satisfied. We determine targeted fiber dimensions and explain our strategy for examining a design family rather than a single fiber design. We simulate modal properties of the designed fibers, and compare the results with measurements performed on fabricated fibers.

A functional gene array for detection of bacterial virulence elements

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

Jaing, C

2007-11-01

We report our development of the first of a series of microarrays designed to detect pathogens with known mechanisms of virulence and antibiotic resistance. By targeting virulence gene families as well as genes unique to specific biothreat agents, these arrays will provide important data about the pathogenic potential and drug resistance profiles of unknown organisms in environmental samples. To validate our approach, we developed a first generation array targeting genes from Escherichia coli strains K12 and CFT073, Enterococcus faecalis and Staphylococcus aureus. We determined optimal probe design parameters for microorganism detection and discrimination, measured the required target concentration, and assessedmore » tolerance for mismatches between probe and target sequences. Mismatch tolerance is a priority for this application, due to DNA sequence variability among members of gene families. Arrays were created using the NimbleGen Maskless Array Synthesizer at Lawrence Livermore National Laboratory. Purified genomic DNA from combinations of one or more of the four target organisms, pure cultures of four related organisms, and environmental aerosol samples with spiked-in genomic DNA were hybridized to the arrays. Based on the success of this prototype, we plan to design further arrays in this series, with the goal of detecting all known virulence and antibiotic resistance gene families in a greatly expanded set of organisms.« less

A preliminary study for the development and optimization by experimental design of an in vitro method for prediction of drug buccal absorption.

PubMed

Mura, Paola; Orlandini, Serena; Cirri, Marzia; Maestrelli, Francesca; Mennini, Natascia; Casella, Giada; Furlanetto, Sandra

2018-06-15

The work was aimed at developing an in vitro method able to provide rapid and reliable evaluation of drug absorption through buccal mucosa. Absorption simulator apparatus endowed with an artificial membrane was purposely developed by experimental design. The apparent permeation coefficient (P app ) through excised porcine buccal mucosa of naproxen, selected as model drug, was the target value to obtain with the artificial membrane. The multivariate approach enabled systematic evaluation of the effect on the response (P app ) of simultaneous variations of the variables (kind of lipid components for support impregnation and relative amounts). A screening phase followed by a response-surface study allowed optimization of the lipid-mixture composition to obtain the desired P app value, and definition of a design space where all mixture components combinations fulfilled the desired target at a fixed probability level. The method offers a useful tool for a quick screening in the early stages of drug discovery and/or in preformulation studies, improving efficiency and chance of success in the development of buccal delivery systems. Further studies with other model drugs are planned to confirm the buccal absorption predictive capacity of the developed membrane. Copyright © 2018 Elsevier B.V. All rights reserved.

A combinatorial approach to the design of vaccines.

PubMed

Martínez, Luis; Milanič, Martin; Legarreta, Leire; Medvedev, Paul; Malaina, Iker; de la Fuente, Ildefonso M

2015-05-01

We present two new problems of combinatorial optimization and discuss their applications to the computational design of vaccines. In the shortest λ-superstring problem, given a family S1,...,S(k) of strings over a finite alphabet, a set Τ of "target" strings over that alphabet, and an integer λ, the task is to find a string of minimum length containing, for each i, at least λ target strings as substrings of S(i). In the shortest λ-cover superstring problem, given a collection X1,...,X(n) of finite sets of strings over a finite alphabet and an integer λ, the task is to find a string of minimum length containing, for each i, at least λ elements of X(i) as substrings. The two problems are polynomially equivalent, and the shortest λ-cover superstring problem is a common generalization of two well known combinatorial optimization problems, the shortest common superstring problem and the set cover problem. We present two approaches to obtain exact or approximate solutions to the shortest λ-superstring and λ-cover superstring problems: one based on integer programming, and a hill-climbing algorithm. An application is given to the computational design of vaccines and the algorithms are applied to experimental data taken from patients infected by H5N1 and HIV-1.

A novel orbiter mission concept for venus with the EnVision proposal

NASA Astrophysics Data System (ADS)

de Oliveira, Marta R. R.; Gil, Paulo J. S.; Ghail, Richard

2018-07-01

In space exploration, planetary orbiter missions are essential to gain insight into planets as a whole, and to help uncover unanswered scientific questions. In particular, the planets closest to the Earth have been a privileged target of the world's leading space agencies. EnVision is a mission proposal designed for Venus and competing for ESA's next launch opportunity with the objective of studying Earth's closest neighbor. The main goal is to study geological and atmospheric processes, namely surface processes, interior dynamics and atmosphere, to determine the reasons behind Venus and Earth's radically different evolution despite the planets' similarities. To achieve these goals, the operational orbit selection is a fundamental element of the mission design process. The design of an orbit around Venus faces specific challenges, such as the impossibility of choosing Sun-synchronous orbits. In this paper, an innovative genetic algorithm optimization was applied to select the optimal orbit based on the parameters with more influence in the mission planning, in particular the mission duration and the coverage of sites of interest on the Venusian surface. The solution obtained is a near-polar circular orbit with an altitude of 259 km that enables the coverage of all priority targets almost two times faster than with the parameters considered before this study.

The Earth Phenomena Observing System: Intelligent Autonomy for Satellite Operations

NASA Technical Reports Server (NTRS)

Ricard, Michael; Abramson, Mark; Carter, David; Kolitz, Stephan

2003-01-01

Earth monitoring systems of the future may include large numbers of inexpensive small satellites, tasked in a coordinated fashion to observe both long term and transient targets. For best performance, a tool which helps operators optimally assign targets to satellites will be required. We present the design of algorithms developed for real-time optimized autonomous planning of large numbers of small single-sensor Earth observation satellites. The algorithms will reduce requirements on the human operators of such a system of satellites, ensure good utilization of system resources, and provide the capability to dynamically respond to temporal terrestrial phenomena. Our initial real-time system model consists of approximately 100 satellites and large number of points of interest on Earth (e.g., hurricanes, volcanoes, and forest fires) with the objective to maximize the total science value of observations over time. Several options for calculating the science value of observations include the following: 1) total observation time, 2) number of observations, and the 3) quality (a function of e.g., sensor type, range, slant angle) of the observations. An integrated approach using integer programming, optimization and astrodynamics is used to calculate optimized observation and sensor tasking plans.

Local search heuristic for the discrete leader-follower problem with multiple follower objectives

NASA Astrophysics Data System (ADS)

Kochetov, Yury; Alekseeva, Ekaterina; Mezmaz, Mohand

2016-10-01

We study a discrete bilevel problem, called as well as leader-follower problem, with multiple objectives at the lower level. It is assumed that constraints at the upper level can include variables of both levels. For such ill-posed problem we define feasible and optimal solutions for pessimistic case. A central point of this work is a two stage method to get a feasible solution under the pessimistic case, given a leader decision. The target of the first stage is a follower solution that violates the leader constraints. The target of the second stage is a pessimistic feasible solution. Each stage calls a heuristic and a solver for a series of particular mixed integer programs. The method is integrated inside a local search based heuristic that is designed to find near-optimal leader solutions.

Semantic wireless localization of WiFi terminals in smart buildings

NASA Astrophysics Data System (ADS)

Ahmadi, H.; Polo, A.; Moriyama, T.; Salucci, M.; Viani, F.

2016-06-01

The wireless localization of mobile terminals in indoor scenarios by means of a semantic interpretation of the environment is addressed in this work. A training-less approach based on the real-time calibration of a simple path loss model is proposed which combines (i) the received signal strength information measured by the wireless terminal and (ii) the topological features of the localization domain. A customized evolutionary optimization technique has been designed to estimate the optimal target position that fits the complex wireless indoor propagation and the semantic target-environment relation, as well. The proposed approach is experimentally validated in a real building area where the available WiFi network is opportunistically exploited for data collection. The presented results point out a reduction of the localization error obtained with the introduction of a very simple semantic interpretation of the considered scenario.

Modeling of endoluminal and interstitial ultrasound hyperthermia and thermal ablation: applications to device design, feedback control, and treatment planning

PubMed Central

Prakash, Punit; Salgaonkar, Vasant A.; Diederich, Chris J.

2014-01-01

Endoluminal and catheter-based ultrasound applicators are currently under development and are in clinical use for minimally invasive hyperthermia and thermal ablation of various tissue targets. Computational models play a critical role in in device design and optimization, assessment of therapeutic feasibility and safety, devising treatment monitoring and feedback control strategies, and performing patient-specific treatment planning with this technology. The critical aspects of theoretical modeling, applied specifically to endoluminal and interstitial ultrasound thermotherapy, are reviewed. Principles and practical techniques for modeling acoustic energy deposition, bioheat transfer, thermal tissue damage, and dynamic changes in the physical and physiological state of tissue are reviewed. The integration of these models and applications of simulation techniques in identification of device design parameters, development of real time feedback-control platforms, assessing the quality and safety of treatment delivery strategies, and optimization of inverse treatment plans are presented. PMID:23738697

Optimizing Parking Orbits for Roundtrip Mars Missions

NASA Technical Reports Server (NTRS)

Qu, Min; Merill, Raymond G.; Chai, Patrick; Komar, David R.

2017-01-01

A roundtrip Mars mission presents many challenges to the design of a transportation system and requires a series of orbital maneuvers within Mars vicinity to capture, reorient, and then return the spacecraft back to Earth. The selection of a Mars parking orbit is crucial to the mission design; not only can the parking or-bit choice drastically impact the ?V requirements of these maneuvers but also it must be properly aligned to target desired surface or orbital destinations. This paper presents a method that can optimize the Mars parking orbits given the arrival and departure conditions from heliocentric trajectories, and it can also en-force constraints on the parking orbits to satisfy other architecture design requirements such as co-planar subperiapsis descent to planned landing sites, due east or co-planar ascent back to the parking orbit, or low cost transfers to and from Phobos and Deimos.

GA-optimized feedforward-PID tracking control for a rugged electrohydraulic system design.

PubMed

Sarkar, B K; Mandal, P; Saha, R; Mookherjee, S; Sanyal, D

2013-11-01

Rugged electrohydraulic systems are preferred for remote and harsh applications. Despite the low bandwidth, large deadband and flow nonlinearities in proportional valves valve and highly nonlinear friction in industry-grade cylinders that comprise rugged systems, their maintenance are much easier than very sophisticated and delicate servocontrol and servocylinder systems. With the target of making the easily maintainable system to perform comparably to a servosystem, a feedforward control has been designed here for compensating the nonlinearities. A PID feedback of the piston displacement has been employed in tandem for absorbing the unmodeled effects. All the controller parameters have been optimized by a real-coded genetic algorithm. The agreement between the achieved real-time responses for step and sinusoidal demands with those achieved by modern servosystems clearly establishes the acceptability of the controller design. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Status of Low Thrust Work at JSC

NASA Technical Reports Server (NTRS)

Condon, Gerald L.

2004-01-01

High performance low thrust (solar electric, nuclear electric, variable specific impulse magnetoplasma rocket) propulsion offers a significant benefit to NASA missions beyond low Earth orbit. As NASA (e.g., Prometheus Project) endeavors to develop these propulsion systems and associated power supplies, it becomes necessary to develop a refined trajectory design capability that will allow engineers to develop future robotic and human mission designs that take advantage of this new technology. This ongoing work addresses development of a trajectory design and optimization tool for assessing low thrust (and other types) trajectories. This work targets to advance the state of the art, enable future NASA missions, enable science drivers, and enhance education. This presentation provides a summary of the low thrust-related JSC activities under the ISP program and specifically, provides a look at a new release of a multi-gravity, multispacecraft trajectory optimization tool (Copernicus) along with analysis performed using this tool over the past year.

Optimal distribution of borehole geophones for monitoring CO2-injection-induced seismicity

NASA Astrophysics Data System (ADS)

Huang, L.; Chen, T.; Foxall, W.; Wagoner, J. L.

2016-12-01

The U.S. DOE initiative, National Risk Assessment Partnership (NRAP), aims to develop quantitative risk assessment methodologies for carbon capture, utilization and storage (CCUS). As part of tasks of the Strategic Monitoring Group of NRAP, we develop a tool for optimal design of a borehole geophones distribution for monitoring CO2-injection-induced seismicity. The tool consists of a number of steps, including building a geophysical model for a given CO2 injection site, defining target monitoring regions within CO2-injection/migration zones, generating synthetic seismic data, giving acceptable uncertainties in input data, and determining the optimal distribution of borehole geophones. We use a synthetic geophysical model as an example to demonstrate the capability our new tool to design an optimal/cost-effective passive seismic monitoring network using borehole geophones. The model is built based on the geologic features found at the Kimberlina CCUS pilot site located in southern San Joaquin Valley, California. This tool can provide CCUS operators with a guideline for cost-effective microseismic monitoring of geologic carbon storage and utilization.

Finding the sweet spots of inhibition: understanding the targets of a functional antibody against Plasmodium vivax Duffy binding protein

PubMed Central

Ntumngia, Francis B.; King, Christopher L.; Adams, John H.

2014-01-01

Plasmodium vivax Duffy binding protein region II (DBPII) is an essential ligand for reticulocyte invasion, thereby making this molecule an attractive vaccine candidate against asexual blood-stage P. vivax. Similar to other Plasmodium blood-stage vaccine candidates, strain-specific immunity due to DBPII allelic variation may complicate vaccine efficacy. Targeting immune responses to more conserved epitopes that are potential targets of strain-transcending neutralizing immunity is necessary to avoid induction of strain-specific responses to dominant variant epitopes. In this article, we focus on different approaches to optimize the design of DBP immunogenicity to target conserved epitopes, which is important for developing a broadly effective vaccine against P. vivax. PMID:23068913

Target discovery focused approaches to overcome bottlenecks in the exploitation of antimycobacterial natural products.

PubMed

Baptista, Rafael; Bhowmick, Sumana; Nash, Robert J; Baillie, Les; Mur, Luis Aj

2018-04-01

Tuberculosis is a major global health hazard. The search for new antimycobacterials has focused on such as screening combinational chemistry libraries or designing chemicals to target predefined pockets of essential bacterial proteins. The relative ineffectiveness of these has led to a reappraisal of natural products for new antimycobacterial drug leads. However, progress has been limited, we suggest through a failure in many cases to define the drug target and optimize the hits using this information. We highlight methods of target discovery needed to develop a drug into a candidate for clinical trials. We incorporate these into suggested analysis pipelines which could inform the research strategies to accelerate the development of new drug leads from natural products.

Flexible CRISPR library construction using parallel oligonucleotide retrieval

PubMed Central

Read, Abigail; Gao, Shaojian; Batchelor, Eric

2017-01-01

Abstract CRISPR/Cas9-based gene knockout libraries have emerged as a powerful tool for functional screens. We present here a set of pre-designed human and mouse sgRNA sequences that are optimized for both high on-target potency and low off-target effect. To maximize the chance of target gene inactivation, sgRNAs were curated to target both 5΄ constitutive exons and exons that encode conserved protein domains. We describe here a robust and cost-effective method to construct multiple small sized CRISPR library from a single oligo pool generated by array synthesis using parallel oligonucleotide retrieval. Together, these resources provide a convenient means for individual labs to generate customized CRISPR libraries of variable size and coverage depth for functional genomics application. PMID:28334828

Integration of fragment screening and library design.

PubMed

Siegal, Gregg; Ab, Eiso; Schultz, Jan

2007-12-01

With more than 10 years of practical experience and theoretical analysis, fragment-based drug discovery (FBDD) has entered the mainstream of the pharmaceutical and biotech industries. An array of biophysical techniques has been used to detect the weak interaction between a fragment and the target. Each technique presents its own requirements regarding the fragment collection and the target; therefore, in order to optimize the potential of FBDD, the nature of the target should be a driving factor for simultaneous development of both the library and the screening technology. A roadmap is now available to guide fragment-to-lead evolution when structural information is available. The next challenge is to apply FBDD to targets for which high-resolution structural information is not available.

GLRS-R 2-colour retroreflector target design and predicted performance

NASA Technical Reports Server (NTRS)

Lund, Glenn

1993-01-01

This paper reports on the retroreflector ground-target design for the GLRS-R spaceborne dual-wavelength laser ranging system. The described passive design flows down from the requirements of high station autonomy, high global FOV (up to 60 degrees zenith angle), little or no multiple pulse returns, and adequate optical cross section for most ranging geometries. The proposed solution makes use of 5 hollow cube-corner retroreflectors of which one points to the zenith and the remaining four are inclined from the vertical at uniform azimuthal spacings. The need for fairly large (is approximately 10 cm) retroreflectors is expected (within turbulence limitations) to generate quite narrow diffraction lobes, thus placing non-trivial requirements on the vectorial accuracy of velocity aberration corrections. A good compromise solution is found by appropriately spoiling just one of the retroreflector dihedral angles from 90 degrees, thus generating two symmetrically oriented diffraction lobes in the return beam. The required spoil angles are found to have little dependence on ground target latitude. Various link budget analyses are presented, showing the influence of such factors as point-ahead optimization, turbulence, ranging angle, atmospheric visibility and ground target thermal deformations.

GLRS-R 2-colour retroreflector target design and predicted performance

NASA Astrophysics Data System (ADS)

Lund, Glenn

1993-06-01

This paper reports on the retroreflector ground-target design for the GLRS-R spaceborne dual-wavelength laser ranging system. The described passive design flows down from the requirements of high station autonomy, high global FOV (up to 60 degrees zenith angle), little or no multiple pulse returns, and adequate optical cross section for most ranging geometries. The proposed solution makes use of 5 hollow cube-corner retroreflectors of which one points to the zenith and the remaining four are inclined from the vertical at uniform azimuthal spacings. The need for fairly large (is approximately 10 cm) retroreflectors is expected (within turbulence limitations) to generate quite narrow diffraction lobes, thus placing non-trivial requirements on the vectorial accuracy of velocity aberration corrections. A good compromise solution is found by appropriately spoiling just one of the retroreflector dihedral angles from 90 degrees, thus generating two symmetrically oriented diffraction lobes in the return beam. The required spoil angles are found to have little dependence on ground target latitude. Various link budget analyses are presented, showing the influence of such factors as point-ahead optimization, turbulence, ranging angle, atmospheric visibility and ground target thermal deformations.

Diverse ways of perturbing the human arachidonic acid metabolic network to control inflammation.

PubMed

Meng, Hu; Liu, Ying; Lai, Luhua

2015-08-18

Inflammation and other common disorders including diabetes, cardiovascular disease, and cancer are often the result of several molecular abnormalities and are not likely to be resolved by a traditional single-target drug discovery approach. Though inflammation is a normal bodily reaction, uncontrolled and misdirected inflammation can cause inflammatory diseases such as rheumatoid arthritis and asthma. Nonsteroidal anti-inflammatory drugs including aspirin, ibuprofen, naproxen, or celecoxib are commonly used to relieve aches and pains, but often these drugs have undesirable and sometimes even fatal side effects. To facilitate safer and more effective anti-inflammatory drug discovery, a balanced treatment strategy should be developed at the biological network level. In this Account, we focus on our recent progress in modeling the inflammation-related arachidonic acid (AA) metabolic network and subsequent multiple drug design. We first constructed a mathematical model of inflammation based on experimental data and then applied the model to simulate the effects of commonly used anti-inflammatory drugs. Our results indicated that the model correctly reproduced the established bleeding and cardiovascular side effects. Multitarget optimal intervention (MTOI), a Monte Carlo simulated annealing based computational scheme, was then developed to identify key targets and optimal solutions for controlling inflammation. A number of optimal multitarget strategies were discovered that were both effective and safe and had minimal associated side effects. Experimental studies were performed to evaluate these multitarget control solutions further using different combinations of inhibitors to perturb the network. Consequently, simultaneous control of cyclooxygenase-1 and -2 and leukotriene A4 hydrolase, as well as 5-lipoxygenase and prostaglandin E2 synthase were found to be among the best solutions. A single compound that can bind multiple targets presents advantages including low risk of drug-drug interactions and robustness regarding concentration fluctuations. Thus, we developed strategies for multiple-target drug design and successfully discovered several series of multiple-target inhibitors. Optimal solutions for a disease network often involve mild but simultaneous interventions of multiple targets, which is in accord with the philosophy of traditional Chinese medicine (TCM). To this end, our AA network model can aptly explain TCM anti-inflammatory herbs and formulas at the molecular level. We also aimed to identify activators for several enzymes that appeared to have increased activity based on MTOI outcomes. Strategies were then developed to predict potential allosteric sites and to discover enzyme activators based on our hypothesis that combined treatment with the projected activators and inhibitors could balance different AA network pathways, control inflammation, and reduce associated adverse effects. Our work demonstrates that the integration of network modeling and drug discovery can provide novel solutions for disease control, which also calls for new developments in drug design concepts and methodologies. With the rapid accumulation of quantitative data and knowledge of the molecular networks of disease, we can expect an increase in the development and use of quantitative disease models to facilitate efficient and safe drug discovery.

Design and optimization of a series of 1-sulfonylpyrazolo[4,3-b]pyridines as selective c-Met inhibitors.

PubMed

Ma, Yuchi; Sun, Guangqiang; Chen, Danqi; Peng, Xia; Chen, Yue-Lei; Su, Yi; Ji, Yinchun; Liang, Jin; Wang, Xin; Chen, Lin; Ding, Jian; Xiong, Bing; Ai, Jing; Geng, Meiyu; Shen, Jingkang

2015-03-12

c-Met has emerged as an attractive target for targeted cancer therapy because of its abnormal activation in many cancer cells. To identify high potent and selective c-Met inhibitors, we started with profiling the potency and in vitro metabolic stability of a reported hit 7. By rational design, a novel sulfonylpyrazolo[4,3-b]pyridine 9 with improved DMPK properties was discovered. Further elaboration of π-π stacking interactions and solvent accessible polar moieties led to a series of highly potent and selective type I c-Met inhibitors. On the basis of in vitro and in vivo pharmacological and pharmacokinetics studies, compound 46 was selected as a preclinical candidate for further anticancer drug development.

Surveillance theory applied to virus detection: a case for targeted discovery

USGS Publications Warehouse

Bogich, Tiffany L.; Anthony, Simon J.; Nichols, James D.

2013-01-01

Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.

COMPUTER-AIDED DRUG DISCOVERY AND DEVELOPMENT (CADDD): in silico-chemico-biological approach

PubMed Central

Kapetanovic, I.M.

2008-01-01

It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415

Visualization for Hyper-Heuristics. Front-End Graphical User Interface

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

Kroenung, Lauren

Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. While such automated design has great advantages, it can often be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address thesemore » issues of usability by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics to support practitioners, as well as scientific visualization of the produced automated designs. My contributions to this project are exhibited in the user-facing portion of the developed system and the detailed scientific visualizations created from back-end data.« less

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

PubMed

Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E

2015-09-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.

Template-based de novo design for type II kinase inhibitors and its extented application to acetylcholinesterase inhibitors.

PubMed

Su, Bo-Han; Huang, Yi-Syuan; Chang, Chia-Yun; Tu, Yi-Shu; Tseng, Yufeng J

2013-10-31

There is a compelling need to discover type II inhibitors targeting the unique DFG-out inactive kinase conformation since they are likely to possess greater potency and selectivity relative to traditional type I inhibitors. Using a known inhibitor, such as a currently available and approved drug or inhibitor, as a template to design new drugs via computational de novo design is helpful when working with known ligand-receptor interactions. This study proposes a new template-based de novo design protocol to discover new inhibitors that preserve and also optimize the binding interactions of the type II kinase template. First, sorafenib (Nexavar) and nilotinib (Tasigna), two type II inhibitors with different ligand-receptor interactions, were selected as the template compounds. The five-step protocol can reassemble each drug from a large fragment library. Our procedure demonstrates that the selected template compounds can be successfully reassembled while the key ligand-receptor interactions are preserved. Furthermore, to demonstrate that the algorithm is able to construct more potent compounds, we considered kinase inhibitors and other protein dataset, acetylcholinesterase (AChE) inhibitors. The de novo optimization was initiated using a template compound possessing a less than optimal activity from a series of aminoisoquinoline and TAK-285 inhibiting type II kinases, and E2020 derivatives inhibiting AChE respectively. Three compounds with greater potency than the template compound were discovered that were also included in the original congeneric series. This template-based lead optimization protocol with the fragment library can help to design compounds with preferred binding interactions of known inhibitors automatically and further optimize the compounds in the binding pockets.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty

PubMed Central

Mdluli, Thembi; Buzzard, Gregery T.; Rundell, Ann E.

2015-01-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm’s scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements. PMID:26379275

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

Optimal Policy of Cross-Layer Design for Channel Access and Transmission Rate Adaptation in Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

He, Hao; Wang, Jun; Zhu, Jiang; Li, Shaoqian

2010-12-01

In this paper, we investigate the cross-layer design of joint channel access and transmission rate adaptation in CR networks with multiple channels for both centralized and decentralized cases. Our target is to maximize the throughput of CR network under transmission power constraint by taking spectrum sensing errors into account. In centralized case, this problem is formulated as a special constrained Markov decision process (CMDP), which can be solved by standard linear programming (LP) method. As the complexity of finding the optimal policy by LP increases exponentially with the size of action space and state space, we further apply action set reduction and state aggregation to reduce the complexity without loss of optimality. Meanwhile, for the convenience of implementation, we also consider the pure policy design and analyze the corresponding characteristics. In decentralized case, where only local information is available and there is no coordination among the CR users, we prove the existence of the constrained Nash equilibrium and obtain the optimal decentralized policy. Finally, in the case that the traffic load parameters of the licensed users are unknown for the CR users, we propose two methods to estimate the parameters for two different cases. Numerical results validate the theoretic analysis.

Computationally efficient optimization of radiation drives

NASA Astrophysics Data System (ADS)

Zimmerman, George; Swift, Damian

2017-06-01

For many applications of pulsed radiation, the temporal pulse shape is designed to induce a desired time-history of conditions. This optimization is normally performed using multi-physics simulations of the system, adjusting the shape until the desired response is induced. These simulations may be computationally intensive, and iterative forward optimization is then expensive and slow. In principle, a simulation program could be modified to adjust the radiation drive automatically until the desired instantaneous response is achieved, but this may be impracticable in a complicated multi-physics program. However, the computational time increment is typically much shorter than the time scale of changes in the desired response, so the radiation intensity can be adjusted so that the response tends toward the desired value. This relaxed in-situ optimization method can give an adequate design for a pulse shape in a single forward simulation, giving a typical gain in computational efficiency of tens to thousands. This approach was demonstrated for the design of laser pulse shapes to induce ramp loading to high pressure in target assemblies where different components had significantly different mechanical impedance, requiring careful pulse shaping. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

Selection of optimal oligonucleotide probes for microarrays usingmultiple criteria, global alignment and parameter estimation.

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

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 onmore » 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.« less

Ultrasound effects on brain-targeting mannosylated liposomes: in vitro and blood-brain barrier transport investigations.

PubMed

Zidan, Ahmed S; Aldawsari, Hibah

2015-01-01

Delivering drugs to intracerebral regions can be accomplished by improving the capacity of transport through blood-brain barrier. Using sertraline as model drug for brain targeting, the current study aimed at modifying its liposomal vesicles with mannopyranoside. Box-Behnken design was employed to statistically optimize the ultrasound parameters, namely ultrasound amplitude, time, and temperature, for maximum mannosylation capacity, sertraline entrapment, and surface charge while minimizing vesicular size. Moreover, in vitro blood-brain barrier transport model was established to assess the transendothelial capacity of the optimized mannosylated vesicles. Results showed a dependence of vesicular size, mannosylation capacity, and sertraline entrapment on cavitation and bubble implosion events that were related to ultrasound power amplitude, temperature. However, short ultrasound duration was required to achieve >90% mannosylation with nanosized vesicles (<200 nm) of narrow size distribution. Optimized ultrasound parameters of 65°C, 27%, and 59 seconds for ultrasound temperature, amplitude, and time were elucidated to produce 81.1%, 46.6 nm, and 77.6% sertraline entrapment, vesicular size, and mannosylation capacity, respectively. Moreover, the transendothelial ability was significantly increased by 2.5-fold by mannosylation through binding with glucose transporters. Hence, mannosylated liposomes processed by ultrasound could be a promising approach for manufacturing and scale-up of brain-targeting liposomes.

Aptamer-loaded Gold Nanoconstructs for Targeted Cancer Therapy

NASA Astrophysics Data System (ADS)

Dam, Duncan Hieu Minh

Traditional cancer treatments, including chemotherapy, often cause severe side effects in patients. Targeted therapy where tumor cells are targeted via biomarkers overexpressed on the cell surface has been shown to reduce such adverse effects. Monoclonal antibodies (mAbs) are currently the most common chemotherapeutic agents that bind with high affinity to these cancer markers. However, poor intratumoral uptake of mAb and release of drugs from mAb carriers have been the biggest challenge for this delivery method. As a result, recent work has focused on other strategies to improve the efficacy of drug delivery in targeted therapy. Among potential carriers for drug delivery, gold nanoparticles (AuNPs) have emerged as one of the most promising vehicles. This thesis describes the development of a drug delivery nanoconstruct that can both target cancer cells and induce therapeutic effects. The nanoconstructs are composed of gold nanostars (AuNS) as delivery vehicles loaded with the DNA aptamer AS1411 that can target the ubiquitous shuttle protein nucleolin (NCL) in various cancer cell types. The gold nanocarrier stabilizes the oligonucleotides for intracellular delivery and promotes high loading densities of the oligonucleotide drugs. We have investigated the interactions of the nanoconstruct with different subcellular compartments of the cancer cells. This physical phenomenon has shown to correlate with the biological activities such as apoptosis and cell death that happen in the cancer cells after incubation with the nanoconstructs. A thorough screening of the nanoconstructs in 13 different cancer cell lines is conducted to narrow down the potential targets for in vivo study. Before testing the in vivo efficacy, we evaluate the toxicity of the nanoconstructs in non-tumor animals, which confirms its safety for further in vivo applications. The accumulation of the nanoconstructs in two different cancerous tumors, however, suggests that further optimization of the design is required. Thus, we introduced an improved nanoconstruct with higher loading of AS1411 on the surface of AuNS. The significant enhancement in the loading of the Apt increases the cellular uptake as well as the in vitro efficacy of the nanoconstruct in both fibrosarcoma and pancreatic cancer cells. To further optimize the design of the nanoconstruct, we create a conjugation method in which the loading of AS1411 can be effectively controlled at various pH conditions. This method can potentially be applied for any DNA or RNA; however, the stability of oligonucleotides is unknown as a function of pH. Therefore, we also evaluate how pH conditions can affect the loading densities and structural integrity of a range of different oligonucleotides (single stranded DNA, hairpin DNA, duplexes, quadruplexes) on AuNS. The ultimate goal of this process is to identify a set of design principles to optimize oligonucleotide loading based on the local chemical environment around the nanoparticle.

Method and apparatus for decoupled thermo-catalytic pollution control

DOEpatents

Tabatabaie-Raissi, Ali; Muradov, Nazim Z.; Martin, Eric

2006-07-11

A new method for design and scale-up of thermocatalytic processes is disclosed. The method is based on optimizing process energetics by decoupling of the process energetics from the DRE for target contaminants. The technique is applicable to high temperature thermocatalytic reactor design and scale-up. The method is based on the implementation of polymeric and other low-pressure drop support for thermocatalytic media as well as the multifunctional catalytic media in conjunction with a novel rotating fluidized particle bed reactor.

Site Targeted Press Coated Delivery of Methylprednisolone Using Eudragit RS 100 and Chitosan for Treatment of Colitis.

PubMed

Jagdale, Swati; Chandekar, Apoorva

2016-01-01

Inflammatory bowel disease (IBD) is one of the five most prevalent gastrointestinal disease burdens which commonly require lifetime care. Worldwide incidence rate of ulcerative colitis and Crohn's disease is about 16.8% and 13.4% respectively. Colitis is an inflammation of the colon. Colon targeted drug delivery will direct the drug to the colon. The drug will reach at the site of action and hence its side effects as well as dose can be reduced. Recent patent describes treatment of ulcerative colitis using anti CD3 antibodies, with nicotine and anti-depressant drugs, budesonide foam etc. Present study deals with optimization of site targeted methylprednisolone delivery for treatment of colitis. Chitosan and Eudragit RS 100 were used as coating polymers. Tablets were prepared by press coated technology. The core tablets contain drug, avicel as binder, croscarmellose sodium as super disintegrant and dicalcium phosphate as diluent. Drug excipient compatibility was carried out using FTIR, UV and DSC. Design of experiment was used to optimize the formulation. Tablets were evaluated for thickness, weight variation, hardness, swelling index, in-vitro drug release and release of drug in simulated media. Optimized batch (B2) contained chitosan 40% and eudragit RS 100 17.5%. B2 showed in-vitro drug release 85.65 ± 7.6% in 6.8 pH phosphate buffer and 96.7 ±9.1% in simulated media after 7.5 hours. In-vivo x-ray placebo study for formulation B2 had shown that the tablet reached to the ascending colon after 5 hours. This indicated a potential site targeted delivery of optimized batch B2.

MIMO radar waveform design with peak and sum power constraints

NASA Astrophysics Data System (ADS)

Arulraj, Merline; Jeyaraman, Thiruvengadam S.

2013-12-01

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

Simulation study of electric-guided delivery of 0.4µm monodisperse and polydisperse aerosols to the ostiomeatal complex.

PubMed

Xi, Jinxiang; Yuan, Jiayao Eddie; Si, Xiuhua April

2016-05-01

Despite the high prevalence of rhinosinusitis, current inhalation therapy shows limited efficacy due to extremely low drug delivery efficiency to the paranasal sinuses. Novel intranasal delivery systems are needed to enhance targeted delivery to the sinus with therapeutic dosages. An optimization framework for intranasal drug delivery was developed to target polydisperse charged aerosols to the ostiomeatal complex (OMC) with electric guidance. The delivery efficiency of a group of charged aerosols recently reported in the literature was numerically assessed and optimized in an anatomically accurate nose-sinus model. Key design variables included particle charge number, particle size and distribution, electrode strength, and inhalation velocity. Both monodisperse and polydisperse aerosol profiles were considered. Results showed that the OMC delivery efficiency was highly sensitive to the applied electric field and electrostatic charges carried by the particles. Through the synthesis of electric-guidance and point drug release, focused deposition with significantly enhanced dosage in the OMC can be achieved. For 0.4 µm charged aerosols, an OMC delivery efficiency of 51.6% was predicted for monodisperse aerosols and 34.4% for polydisperse aerosols. This difference suggested that the aerosol profile exerted a notable effect on intranasal deliveries. Sensitivity analysis indicated that the OMC deposition fraction was highly sensitive to the charge and size of particles and was less sensitive to the inhalation velocity considered in this study. Experimental studies are needed to validate the numerically optimized designs. Further studies are warranted to investigate the targeted OMC delivery with both electric and acoustics controls, the latter of which has the potential to further deliver the drug particles into the sinus cavity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

PubMed

Podlewska, Sabina; Czarnecki, Wojciech M; Kafel, Rafał; Bojarski, Andrzej J

2017-02-27

The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most often, the source of such molecules consists of commercially available compound databases, but they can also be searched for within the libraries of structures generated in silico from existing ligands. Various computational combinatorial approaches are based solely on the chemical structure of compounds, using different types of substitutions for new molecules formation. In this study, the starting point for combinatorial library generation was the fingerprint referring to the optimal substructural composition in terms of the activity toward a considered target, which was obtained using a machine learning-based optimization procedure. The systematic enumeration of all possible connections between preferred substructures resulted in the formation of target-focused libraries of new potential ligands. The compounds were initially assessed by machine learning methods using a hashed fingerprint to represent molecules; the distribution of their physicochemical properties was also investigated, as well as their synthetic accessibility. The examination of various fingerprints and machine learning algorithms indicated that the Klekota-Roth fingerprint and support vector machine were an optimal combination for such experiments. This study was performed for 8 protein targets, and the obtained compound sets and their characterization are publically available at http://skandal.if-pan.krakow.pl/comb_lib/ .

Quality by design approach for developing chitosan-Ca-alginate microspheres for colon delivery of celecoxib-hydroxypropyl-β-cyclodextrin-PVP complex.

PubMed

Mennini, N; Furlanetto, S; Cirri, M; Mura, P

2012-01-01

The aim of the present work was to develop a new multiparticulate system, designed for colon-specific delivery of celecoxib for both systemic (in chronotherapic treatment of arthritis) and local (in prophylaxis of colon carcinogenesis) therapy. The system simultaneously benefits from ternary complexation with hydroxypropyl-β-cyclodextrin and PVP (polyvinylpyrrolidone), to increase drug solubility, and vectorization in chitosan-Ca-alginate microspheres, to exploit the colon-specific carrier properties of these polymers. Statistical experimental design was employed to investigate the combined effect of four formulation variables, i.e., % of alginate, CaCl₂, and chitosan and time of cross-linking on microsphere entrapment efficiency (EE%) and drug amount released after 4h in colonic medium, considered as the responses to be optimized. Design of experiment was used in the context of Quality by Design, which requires a multivariate approach for understanding the multifactorial relationships among formulation parameters. Doehlert design allowed for defining a design space, which revealed that variations of the considered factors had in most cases an opposite influence on the responses. Desirability function was used to attain simultaneous optimization of both responses. The desired goals were achieved for both systemic and local use of celecoxib. Experimental values obtained from the optimized formulations were in both cases very close to the predicted values, thus confirming the validity of the generated mathematical model. These results demonstrated the effectiveness of the proposed jointed use of drug cyclodextrin complexation and chitosan-Ca-alginate microsphere vectorization, as well as the usefulness of the multivariate approach for the preparation of colon-targeted celecoxib microspheres with optimized properties. Copyright © 2011 Elsevier B.V. All rights reserved.

Overview on the target fabrication facilities at ELI-NP and ongoing strategies

NASA Astrophysics Data System (ADS)

Gheorghiu, C. C.; Leca, V.; Popa, D.; Cernaianu, M. O.; Stutman, D.

2016-10-01

Along with the development of petawatt class laser systems, the interaction between high power lasers and matter flourished an extensive research, with high-interest applications like: laser nuclear physics, proton radiography or cancer therapy. The new ELI-NP (Extreme Light Infrastructure - Nuclear Physics) petawatt laser facility, with 10PW and ~ 1023W/cm2 beam intensity, is one of the innovative projects that will provide novel research of fundamental processes during light-matter interaction. As part of the ELI-NP facility, Targets Laboratory will provide the means for in-house manufacturing and characterization of the required targets (mainly solid ones) for the experiments, in addition to the research activity carried out in order to develop novel target designs with improved performances. A description of the Targets Laboratory with the main pieces of equipment and their specifications are presented. Moreover, in view of the latest progress in the target design, one of the proposed strategies for the forthcoming experiments at ELI-NP is also described, namely: ultra-thin patterned foil of diamond-like carbon (DLC) coated with a carbon-based ultra-low density layer. The carbon foam which behaves as a near-critical density plasma, will allow the controlled-shaping of the laser pulse before the main interaction with the solid foil. Particular emphasis will be directed towards the target's design optimization, by simulation tests and tuning the key-properties (thickness/length, spacing, density foam, depth, periodicity etc.) which are expected to have a crucial effect on the laser-matter interaction process.