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

PubMed

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

PubMed

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

2012-05-10

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

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

PubMed Central

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 1. Evaluation and Adaptation of GastroPlus To Predict Bioavailability of Medchem Series.

PubMed

Daga, Pankaj R; Bolger, Michael B; Haworth, Ian S; Clark, Robert D; Martin, Eric J

2018-03-05

When medicinal chemists need to improve bioavailability (%F) within a chemical series during lead optimization, they synthesize new series members with systematically modified properties mainly by following experience and general rules of thumb. More quantitative models that predict %F of proposed compounds from chemical structure alone have proven elusive. Global empirical %F quantitative structure-property (QSPR) models perform poorly, and projects have too little data to train local %F QSPR models. Mechanistic oral absorption and physiologically based pharmacokinetic (PBPK) models simulate the dissolution, absorption, systemic distribution, and clearance of a drug in preclinical species and humans. Attempts to build global PBPK models based purely on calculated inputs have not achieved the <2-fold average error needed to guide lead optimization. In this work, local GastroPlus PBPK models are instead customized for individual medchem series. The key innovation was building a local QSPR for a numerically fitted effective intrinsic clearance (CL loc ). All inputs are subsequently computed from structure alone, so the models can be applied in advance of synthesis. Training CL loc on the first 15-18 rat %F measurements gave adequate predictions, with clear improvements up to about 30 measurements, and incremental improvements beyond that.

Optimal charges in lead progression: a structure-based neuraminidase case study.

PubMed

Armstrong, Kathryn A; Tidor, Bruce; Cheng, Alan C

2006-04-20

Collective experience in structure-based lead progression has found electrostatic interactions to be more difficult to optimize than shape-based ones. A major reason for this is that the net electrostatic contribution observed includes a significant nonintuitive desolvation component in addition to the more intuitive intermolecular interaction component. To investigate whether knowledge of the ligand optimal charge distribution can facilitate more intuitive design of electrostatic interactions, we took a series of small-molecule influenza neuraminidase inhibitors with known protein cocrystal structures and calculated the difference between the optimal and actual charge distributions. This difference from the electrostatic optimum correlates with the calculated electrostatic contribution to binding (r(2) = 0.94) despite small changes in binding modes caused by chemical substitutions, suggesting that the optimal charge distribution is a useful design goal. Furthermore, detailed suggestions for chemical modification generated by this approach are in many cases consistent with observed improvements in binding affinity, and the method appears to be useful despite discrete chemical constraints. Taken together, these results suggest that charge optimization is useful in facilitating generation of compound ideas in lead optimization. Our results also provide insight into design of neuraminidase inhibitors.

Tractable Pareto Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Robert; Morris, Paul; Khatib, Lina; Venable, Brent

2003-01-01

This paper focuses on temporal constraint problems where the objective is to optimize a set of local preferences for when events occur. In previous work, a subclass of these problems has been formalized as a generalization of Temporal CSPs, and a tractable strategy for optimization has been proposed, where global optimality is defined as maximizing the minimum of the component preference values. This criterion for optimality, which we call 'Weakest Link Optimization' (WLO), is known to have limited practical usefulness because solutions are compared only on the basis of their worst value; thus, there is no requirement to improve the other values. To address this limitation, we introduce a new algorithm that re-applies WLO iteratively in a way that leads to improvement of all the values. We show the value of this strategy by proving that, with suitable preference functions, the resulting solutions are Pareto Optimal.

Optimizing inhomogeneous spin ensembles for quantum memory

NASA Astrophysics Data System (ADS)

Bensky, Guy; Petrosyan, David; Majer, Johannes; Schmiedmayer, Jörg; Kurizki, Gershon

2012-07-01

We propose a method to maximize the fidelity of quantum memory implemented by a spectrally inhomogeneous spin ensemble. The method is based on preselecting the optimal spectral portion of the ensemble by judiciously designed pulses. This leads to significant improvement of the transfer and storage of quantum information encoded in the microwave or optical field.

Noninvasive, automatic optimization strategy in cardiac resynchronization therapy.

PubMed

Reumann, Matthias; Osswald, Brigitte; Doessel, Olaf

2007-07-01

Optimization of cardiac resynchronization therapy (CRT) is still unsolved. It has been shown that optimal electrode position,atrioventricular (AV) and interventricular (VV) delays improve the success of CRT and reduce the number of non-responders. However, no automatic, noninvasive optimization strategy exists to date. Cardiac resynchronization therapy was simulated on the Visible Man and a patient data-set including fiber orientation and ventricular heterogeneity. A cellular automaton was used for fast computation of ventricular excitation. An AV block and a left bundle branch block were simulated with 100%, 80% and 60% interventricular conduction velocity. A right apical and 12 left ventricular lead positions were set. Sequential optimization and optimization with the downhill simplex algorithm (DSA) were carried out. The minimal error between isochrones of the physiologic excitation and the therapy was computed automatically and leads to an optimal lead position and timing. Up to 1512 simulations were carried out per pathology per patient. One simulation took 4 minutes on an Apple Macintosh 2 GHz PowerPC G5. For each electrode pair an optimal pacemaker delay was found. The DSA reduced the number of simulations by an order of magnitude and the AV-delay and VV - delay were determined with a much higher resolution. The findings are well comparable with clinical studies. The presented computer model of CRT automatically evaluates an optimal lead position and AV-delay and VV-delay, which can be used to noninvasively plan an optimal therapy for an individual patient. The application of the DSA reduces the simulation time so that the strategy is suitable for pre-operative planning in clinical routine. Future work will focus on clinical evaluation of the computer models and integration of patient data for individualized therapy planning and optimization.

Non-optimal microbial response to antibiotics underlies suppressive drug interactions

PubMed Central

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

2010-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Development of an Optimization Methodology for the Aluminum Alloy Wheel Casting Process

NASA Astrophysics Data System (ADS)

Duan, Jianglan; Reilly, Carl; Maijer, Daan M.; Cockcroft, Steve L.; Phillion, Andre B.

2015-08-01

An optimization methodology has been developed for the aluminum alloy wheel casting process. The methodology is focused on improving the timing of cooling processes in a die to achieve improved casting quality. This methodology utilizes (1) a casting process model, which was developed within the commercial finite element package, ABAQUS™—ABAQUS is a trademark of Dassault Systèms; (2) a Python-based results extraction procedure; and (3) a numerical optimization module from the open-source Python library, Scipy. To achieve optimal casting quality, a set of constraints have been defined to ensure directional solidification, and an objective function, based on the solidification cooling rates, has been defined to either maximize, or target a specific, cooling rate. The methodology has been applied to a series of casting and die geometries with different cooling system configurations, including a 2-D axisymmetric wheel and die assembly generated from a full-scale prototype wheel. The results show that, with properly defined constraint and objective functions, solidification conditions can be improved and optimal cooling conditions can be achieved leading to process productivity and product quality improvements.

Mechanism of bandwidth improvement in passively cooled SMA position actuators

NASA Astrophysics Data System (ADS)

Gorbet, R. B.; Morris, K. A.; Chau, R. C. C.

2009-09-01

The heating of shape memory alloy (SMA) materials leads to a thermally driven phase change which can be used to do work. An SMA wire can be thermally cycled by controlling electric current through the wire, creating an electro-mechanical actuator. Such actuators are typically heated electrically and cooled through convection. The thermal time constants and lack of active cooling limit the operating frequencies. In this work, the bandwidth of a still-air-cooled SMA wire controlled with a PID controller is improved through optimization of the controller gains. Results confirm that optimization can improve the ability of the actuator to operate at a given frequency. Overshoot is observed in the optimal controllers at low frequencies. This is a result of hysteresis in the wire's contraction-temperature characteristic, since different input temperatures can achieve the same output value. The optimal controllers generate overshoot during heating, in order to cause the system to operate at a point on the hysteresis curve where faster cooling can be achieved. The optimization results in a controller which effectively takes advantage of the multi-valued nature of the hysteresis to improve performance.

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

NASA Astrophysics Data System (ADS)

Curiale, Nathanael J.

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

Non-Aqueous Primary Li-Air Flow Battery and Optimization of its Cathode through Experiment and Modeling.

PubMed

Kim, Byoungsu; Takechi, Kensuke; Ma, Sichao; Verma, Sumit; Fu, Shiqi; Desai, Amit; Pawate, Ashtamurthy S; Mizuno, Fuminori; Kenis, Paul J A

2017-09-22

A primary Li-air battery has been developed with a flowing Li-ion free ionic liquid as the recyclable electrolyte, boosting power capability by promoting superoxide diffusion and enhancing discharge capacity through separately stored discharge products. Experimental and computational tools are used to analyze the cathode properties, leading to a set of parameters that improve the discharge current density of the non-aqueous Li-air flow battery. The structure and configuration of the cathode gas diffusion layers (GDLs) are systematically modified by using different levels of hot pressing and the presence or absence of a microporous layer (MPL). These experiments reveal that the use of thinner but denser MPLs is key for performance optimization; indeed, this leads to an improvement in discharge current density. Also, computational results indicate that the extent of electrolyte immersion and porosity of the cathode can be optimized to achieve higher current density. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal Resonant Band Demodulation Based on an Improved Correlated Kurtosis and Its Application in Bearing Fault Diagnosis

PubMed Central

Chen, Xianglong; Zhang, Bingzhi; Feng, Fuzhou; Jiang, Pengcheng

2017-01-01

The kurtosis-based indexes are usually used to identify the optimal resonant frequency band. However, kurtosis can only describe the strength of transient impulses, which cannot differentiate impulse noises and repetitive transient impulses cyclically generated in bearing vibration signals. As a result, it may lead to inaccurate results in identifying resonant frequency bands, in demodulating fault features and hence in fault diagnosis. In view of those drawbacks, this manuscript redefines the correlated kurtosis based on kurtosis and auto-correlative function, puts forward an improved correlated kurtosis based on squared envelope spectrum of bearing vibration signals. Meanwhile, this manuscript proposes an optimal resonant band demodulation method, which can adaptively determine the optimal resonant frequency band and accurately demodulate transient fault features of rolling bearings, by combining the complex Morlet wavelet filter and the Particle Swarm Optimization algorithm. Analysis of both simulation data and experimental data reveal that the improved correlated kurtosis can effectively remedy the drawbacks of kurtosis-based indexes and the proposed optimal resonant band demodulation is more accurate in identifying the optimal central frequencies and bandwidth of resonant bands. Improved fault diagnosis results in experiment verified the validity and advantage of the proposed method over the traditional kurtosis-based indexes. PMID:28208820

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

PubMed

Yuan, Haidong; Fung, Chi-Hang Fred

2015-09-11

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

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

PubMed

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

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

Liu, Qiang; Chattopadhyay, Aditi

2000-06-01

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

Development of dihydropyridone indazole amides as selective Rho-kinase inhibitors.

PubMed

Goodman, Krista B; Cui, Haifeng; Dowdell, Sarah E; Gaitanopoulos, Dimitri E; Ivy, Robert L; Sehon, Clark A; Stavenger, Robert A; Wang, Gren Z; Viet, Andrew Q; Xu, Weiwei; Ye, Guosen; Semus, Simon F; Evans, Christopher; Fries, Harvey E; Jolivette, Larry J; Kirkpatrick, Robert B; Dul, Edward; Khandekar, Sanjay S; Yi, Tracey; Jung, David K; Wright, Lois L; Smith, Gary K; Behm, David J; Bentley, Ross; Doe, Christopher P; Hu, Erding; Lee, Dennis

2007-01-11

Rho kinase (ROCK1) mediates vascular smooth muscle contraction and is a potential target for the treatment of hypertension and related disorders. Indazole amide 3 was identified as a potent and selective ROCK1 inhibitor but possessed poor oral bioavailability. Optimization of this lead resulted in the discovery of a series of dihydropyridones, exemplified by 13, with improved pharmacokinetic parameters relative to the initial lead. Indazole substitution played a critical role in decreasing clearance and improving oral bioavailability.

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

NASA Astrophysics Data System (ADS)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

Wing-section optimization for supersonic viscous flow

NASA Technical Reports Server (NTRS)

Item, Cem C.; Baysal, Oktay (Editor)

1995-01-01

To improve the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating thin-layer Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wind design task, the present investigation concentrated on testing the feasibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with similar features: slightly cambered, parabolic profiles with sharp leading- and trailing-edges. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for the problem formulations which should contribute to an effective wing shape optimization.

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

PubMed

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

2012-04-01

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

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

PubMed

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

2018-03-14

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

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

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

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

2010-01-01

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

Monitoring of International Space Station Telemetry Using Shewhart Control Charts

NASA Technical Reports Server (NTRS)

Fitch, Jeffery T.; Simon, Alan L.; Gouveia, John A.; Hillin, Andrew M.; Hernandez, Steve A.

2012-01-01

Shewhart control charts have been established as an expedient method for analyzing dynamic, trending data in order to identify anomalous subsystem performance as soon as such performance would exceed a statistically established baseline. Additionally, this leading indicator tool integrates a selection methodology that reduces false positive indications, optimizes true leading indicator events, minimizes computer processor unit duty cycles, and addresses human factor concerns (i.e., the potential for flight-controller data overload). This innovation leverages statistical process control, and provides a relatively simple way to allow flight controllers to focus their attention on subtle system changes that could lead to dramatic off-nominal system performance. Finally, this capability improves response time to potential hardware damage and/or crew injury, thereby improving space flight safety. Shewhart control charts require normalized data. However, the telemetry from the ISS Early External Thermal Control System (EETCS) was not normally distributed. A method for normalizing the data was implemented, as was a means of selecting data windows, the number of standard deviations (Sigma Level), the number of consecutive points out of limits (Sequence), and direction (increasing or decreasing trend data). By varying these options, and treating them like dial settings, the number of nuisance alerts and leading indicators were optimized. The goal was to capture all leading indicators while minimizing the number of nuisances. Lean Six Sigma (L6S) design of experiment methodologies were employed. To optimize the results, Perl programming language was used to automate the massive amounts of telemetry data, control chart plots, and the data analysis.

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

PubMed

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

2017-04-01

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

The clinical benefit of cardiac resynchronization therapy optimization using a device-based hemodynamic sensor in a patient with dilated cardiomyopathy: a case report.

PubMed

Volpicelli, Mario; Covino, Gregorio; Capogrosso, Paolo

2015-12-19

Results on the evolution of the clinical status of patients undergoing cardiac resynchronization therapy with a defibrillator after automatic optimization of their cardiac resynchronization therapy are scarce. We observed a rapid and important change in the clinical status of our non-responding patient following activation of a sensor capable of weekly atrioventricular and interventricular delays' optimization. A 78-year-old Caucasian man presented with dilated cardiomyopathy, left bundle branch block, a left ventricular ejection fraction of 35 %, New York Heart Association class III/IV heart failure, and paroxysmal atrial fibrillation. Our patient was implanted with a cardiac resynchronization device with a defibrillator and the SonRtip atrial lead. Right ventricular and left ventricular leads were also implanted. Because of the recurrence of atrial fibrillation, the automatic optimization was set off at discharge. Consequently, the device did not optimize atrioventricular and interventricular delays (programming at discharge: 125 ms for the atrioventricular delay and 0 ms for the interventriculardelay). Our patient was treated with an anti-arrhythmic drug. Five months after implantation, his clinical status remained impaired (left ventricular ejection fraction = 30 %). The SonR signal amplitude had also decreased from 0.52 g to 0.29 g. Nevertheless, because our patient was no longer presenting with atrial fibrillation, the anti-arrhythmic treatment was stopped and the SonR optimization system was activated. After 2 months of automatic cardiac resynchronization therapy with defibrillator optimization, our patient's clinical status had significantly improved (left ventricular ejection fraction = 60 %, New York Heart Association class II) and the SonR signal amplitude had doubled shortly after the first weekly automatic optimization. In this non-responding patient, device-based automatic cardiac resynchronization therapy optimization was shown to significantly improve his clinical status.

The Weighted-Average Lagged Ensemble.

PubMed

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

2017-11-01

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

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.

Improvement of LOD in Fluorescence Detection with Spectrally Nonuniform Background by Optimization of Emission Filtering.

PubMed

Galievsky, Victor A; Stasheuski, Alexander S; Krylov, Sergey N

2017-10-17

The limit-of-detection (LOD) in analytical instruments with fluorescence detection can be improved by reducing noise of optical background. Efficiently reducing optical background noise in systems with spectrally nonuniform background requires complex optimization of an emission filter-the main element of spectral filtration. Here, we introduce a filter-optimization method, which utilizes an expression for the signal-to-noise ratio (SNR) as a function of (i) all noise components (dark, shot, and flicker), (ii) emission spectrum of the analyte, (iii) emission spectrum of the optical background, and (iv) transmittance spectrum of the emission filter. In essence, the noise components and the emission spectra are determined experimentally and substituted into the expression. This leaves a single variable-the transmittance spectrum of the filter-which is optimized numerically by maximizing SNR. Maximizing SNR provides an accurate way of filter optimization, while a previously used approach based on maximizing a signal-to-background ratio (SBR) is the approximation that can lead to much poorer LOD specifically in detection of fluorescently labeled biomolecules. The proposed filter-optimization method will be an indispensable tool for developing new and improving existing fluorescence-detection systems aiming at ultimately low LOD.

The key to success: Gelled-electrolyte and optimized separators for stationary lead-acid batteries

NASA Astrophysics Data System (ADS)

Toniazzo, Valérie

The lead acid technology is nowadays considered one of the best suited for stationary applications. Both gel and AGM batteries are complementary technologies and can provide reliability and efficiency due to the constant optimization of the battery design and components. However, gelled-electrolyte batteries remain the preferred technology due to a better manufacturing background and show better performance mainly at low and moderate discharge rates. Especially, using the gel technology allows to get rid of the numerous problems encountered in most AGM batteries: drainage, stratification, short circuits due to dendrites, and mostly premature capacity loss due to the release of internal cell compression. These limitations are the result of the evident lack of an optimal separation system. In gel batteries, on the contrary, highly efficient polymeric separators are nowadays available. Especially, microporous separators based on PVC and silica have shown the best efficiency for nearly 30 years all over the world, and especially in Europe, where the gel technology was born. The improved performance of these separators is explained by the unique extrusion process, which leads to excellent wettability, and optimized physical properties. Because they are the key for the battery success, continuous research and development on separators have led to improved properties, which render the separator even better adapted to the more recent gel technology: the pore size distribution has been optimized to allow good oxygen transfer while avoiding dendrite growth, the pore volume has been increased, the electrical resistance and acid displacement reduced to such an extent that the electrical output of batteries has been raised both in terms of higher capacity and longer cycle life.

Optimization of Light-Harvesting Pigment Improves Photosynthetic Efficiency.

PubMed

Jin, Honglei; Li, Mengshu; Duan, Sujuan; Fu, Mei; Dong, Xiaoxiao; Liu, Bing; Feng, Dongru; Wang, Jinfa; Wang, Hong-Bin

2016-11-01

Maximizing light capture by light-harvesting pigment optimization represents an attractive but challenging strategy to improve photosynthetic efficiency. Here, we report that loss of a previously uncharacterized gene, HIGH PHOTOSYNTHETIC EFFICIENCY1 (HPE1), optimizes light-harvesting pigments, leading to improved photosynthetic efficiency and biomass production. Arabidopsis (Arabidopsis thaliana) hpe1 mutants show faster electron transport and increased contents of carbohydrates. HPE1 encodes a chloroplast protein containing an RNA recognition motif that directly associates with and regulates the splicing of target RNAs of plastid genes. HPE1 also interacts with other plastid RNA-splicing factors, including CAF1 and OTP51, which share common targets with HPE1. Deficiency of HPE1 alters the expression of nucleus-encoded chlorophyll-related genes, probably through plastid-to-nucleus signaling, causing decreased total content of chlorophyll (a+b) in a limited range but increased chlorophyll a/b ratio. Interestingly, this adjustment of light-harvesting pigment reduces antenna size, improves light capture, decreases energy loss, mitigates photodamage, and enhances photosynthetic quantum yield during photosynthesis. Our findings suggest a novel strategy to optimize light-harvesting pigments that improves photosynthetic efficiency and biomass production in higher plants. © 2016 American Society of Plant Biologists. All Rights Reserved.

Optimization of Light-Harvesting Pigment Improves Photosynthetic Efficiency1[OPEN

PubMed Central

Jin, Honglei; Li, Mengshu; Duan, Sujuan; Fu, Mei; Dong, Xiaoxiao; Feng, Dongru; Wang, Jinfa

2016-01-01

Maximizing light capture by light-harvesting pigment optimization represents an attractive but challenging strategy to improve photosynthetic efficiency. Here, we report that loss of a previously uncharacterized gene, HIGH PHOTOSYNTHETIC EFFICIENCY1 (HPE1), optimizes light-harvesting pigments, leading to improved photosynthetic efficiency and biomass production. Arabidopsis (Arabidopsis thaliana) hpe1 mutants show faster electron transport and increased contents of carbohydrates. HPE1 encodes a chloroplast protein containing an RNA recognition motif that directly associates with and regulates the splicing of target RNAs of plastid genes. HPE1 also interacts with other plastid RNA-splicing factors, including CAF1 and OTP51, which share common targets with HPE1. Deficiency of HPE1 alters the expression of nucleus-encoded chlorophyll-related genes, probably through plastid-to-nucleus signaling, causing decreased total content of chlorophyll (a+b) in a limited range but increased chlorophyll a/b ratio. Interestingly, this adjustment of light-harvesting pigment reduces antenna size, improves light capture, decreases energy loss, mitigates photodamage, and enhances photosynthetic quantum yield during photosynthesis. Our findings suggest a novel strategy to optimize light-harvesting pigments that improves photosynthetic efficiency and biomass production in higher plants. PMID:27609860

Numerical algorithm for optimization of positive electrode in lead-acid batteries

NASA Astrophysics Data System (ADS)

Murariu, Ancuta Teodora; Buimaga-Iarinca, Luiza; Morari, Cristian

2017-12-01

The positive electrode in lead-acid batteries is one of the most sensitive parts of the whole battery, since it is affected by various aggresive chemical processes during its life. Therefore, an optimal design of the positive electrode of the battery may have as efect a dramatic improvement of the properties of the battery - such as total capacity or endurance during its life. Our efforts dedicated to this goal cover a range of rather complex tasks, from the design based on numerical analysis to statistic analysis. We present the structure of the software implementation and the results obtained for three types of positive electrodes.

Lead optimization of 2-(piperidin-3-yl)-1H-benzimidazoles: identification of 2-morpholin- and 2-thiomorpholin-2-yl-1H-benzimidazoles as selective and CNS penetrating H₁-antihistamines for insomnia.

PubMed

Ravula, Satheesh Babu; Yu, Jinghua; Tran, Joe A; Arellano, Melissa; Tucci, Fabio C; Moree, Wilna J; Li, Bin-Feng; Petroski, Robert E; Wen, Jianyun; Malany, Siobhan; Hoare, Samuel R J; Madan, Ajay; Crowe, Paul D; Beaton, Graham

2012-01-01

The structure-activity relationships of 2-(piperidin-3-yl)-1H-benzimidazoles, 2-morpholine and 2-thiomorpholin-2-yl-1H-benzimidazoles are described. In the lead optimization process, the pK(a) and/or logP of benzimidazole analogs were reduced either by attachment of polar substituents to the piperidine nitrogen or incorporation of heteroatoms into the piperidine heterocycle. Compounds 9a and 9b in the morpholine series and 10g in the thiomorpholine series demonstrated improved selectivity and CNS profiles compared to lead compound 2 and these are potential candidates for evaluation as sedative hypnotics. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed Central

2015-01-01

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

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

PubMed

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

2015-06-11

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Structure-based lead optimization to improve antiviral potency and ADMET properties of phenyl-1H-pyrrole-carboxamide entry inhibitors targeted to HIV-1 gp120.

PubMed

Curreli, Francesca; Belov, Dmitry S; Kwon, Young Do; Ramesh, Ranjith; Furimsky, Anna M; O'Loughlin, Kathleen; Byrge, Patricia C; Iyer, Lalitha V; Mirsalis, Jon C; Kurkin, Alexander V; Altieri, Andrea; Debnath, Asim K

2018-05-12

We are continuing our concerted effort to optimize our first lead entry antagonist, NBD-11021, which targets the Phe43 cavity of the HIV-1 envelope glycoprotein gp120, to improve antiviral potency and ADMET properties. In this report, we present a structure-based approach that helped us to generate working hypotheses to modify further a recently reported advanced lead entry antagonist, NBD-14107, which showed significant improvement in antiviral potency when tested in a single-cycle assay against a large panel of Env-pseudotyped viruses. We report here the synthesis of twenty-nine new compounds and evaluation of their antiviral activity in a single-cycle and multi-cycle assay to derive a comprehensive structure-activity relationship (SAR). We have selected three inhibitors with the high selectivity index for testing against a large panel of 55 Env-pseudotyped viruses representing a diverse set of clinical isolates of different subtypes. The antiviral activity of one of these potent inhibitors, 55 (NBD-14189), against some clinical isolates was as low as 63 nM. We determined the sensitivity of CD4-binding site mutated-pseudoviruses to these inhibitors to confirm that they target HIV-1 gp120. Furthermore, we assessed their ADMET properties and compared them to the clinical candidate attachment inhibitor, BMS-626529. The ADMET data indicate that some of these new inhibitors have comparable ADMET properties to BMS-626529 and can be optimized further to potential clinical candidates. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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

2015-01-01

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

Connecting the solution chemistry of PbI2 and MAI: a cyclodextrin-based supramolecular approach to the formation of hybrid halide perovskites† †Electronic supplementary information (ESI) available: Experimental section; Section 1: solution characterization; Section 2: solar cell optimization and characterization; Section 3: thin film characterization; Section 4: advanced structural characterization. See DOI: 10.1039/c7sc05095j

PubMed Central

Masi, Sofia; Aiello, Federica; Listorti, Andrea; Balzano, Federica; Altamura, Davide; Giannini, Cinzia; Caliandro, Rocco; Uccello-Barretta, Gloria

2018-01-01

The evolution from solvated precursors to hybrid halide perovskite films dictates most of the photophysical and optoelectronic properties of the final polycrystalline material. Specifically, the complex equilibria and the importantly different solubilities of lead iodide (PbI2) and methylammonium iodide (MAI) induce inhomogeneous crystal growth, often leading to a defect dense film showing non-optimal optoelectronic properties and intrinsic instability. Here, we explore a supramolecular approach based on the use of cyclodextrins (CDs) to modify the underlying solution chemistry. The peculiar phenomenon demonstrated is a tunable complexation between different CDs and MA+ cations concurrent to an out of cage PbI2 intercalation, representing the first report of a connection between the solvation equilibria of the two perovskite precursors. The optimal conditions in terms of CD cavity size and polarity translate to a neat enhancement of PbI2 solubility in the reaction media, leading to an equilibration of the availability of the precursors in solution. The macroscopic result of this is an improved nucleation process, leading to a perovskite material with higher crystallinity, better optical properties and improved moisture resistance. Remarkably, the use of CDs presents a great potential for a wide range of device-related applications, as well as for the development of tailored composite materials. PMID:29732103

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

Optimal Magnetic Sensor Vests for Cardiac Source Imaging

PubMed Central

Lau, Stephan; Petković, Bojana; Haueisen, Jens

2016-01-01

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

Pyrrolidine-constrained phenethylamines: The design of potent, selective, and pharmacologically efficacious dipeptidyl peptidase IV (DPP4) inhibitors from a lead-like screening hit.

PubMed

Backes, Bradley J; Longenecker, Kenton; Hamilton, Gregory L; Stewart, Kent; Lai, Chunqiu; Kopecka, Hana; von Geldern, Thomas W; Madar, David J; Pei, Zhonghua; Lubben, Thomas H; Zinker, Bradley A; Tian, Zhenping; Ballaron, Stephen J; Stashko, Michael A; Mika, Amanda K; Beno, David W A; Kempf-Grote, Anita J; Black-Schaefer, Candace; Sham, Hing L; Trevillyan, James M

2007-04-01

A novel series of pyrrolidine-constrained phenethylamines were developed as dipeptidyl peptidase IV (DPP4) inhibitors for the treatment of type 2 diabetes. The cyclohexene ring of lead-like screening hit 5 was replaced with a pyrrolidine to enable parallel chemistry, and protein co-crystal structural data guided the optimization of N-substituents. Employing this strategy, a >400x improvement in potency over the initial hit was realized in rapid fashion. Optimized compounds are potent and selective inhibitors with excellent pharmacokinetic profiles. Compound 30 was efficacious in vivo, lowering blood glucose in ZDF rats that were allowed to feed freely on a mixed meal.

Utilization of in vitro Caco-2 permeability and liver microsomal half-life screens in discovering BMS-488043, a novel HIV-1 attachment inhibitor with improved pharmacokinetic properties.

PubMed

Yang, Zheng; Zadjura, Lisa M; Marino, Anthony M; D'Arienzo, Celia J; Malinowski, Jacek; Gesenberg, Christoph; Lin, Pin-Fang; Colonno, Richard J; Wang, Tao; Kadow, John F; Meanwell, Nicholas A; Hansel, Steven B

2010-04-01

Optimizing pharmacokinetic properties to improve oral exposure is a common theme in modern drug discovery. In the present work, in vitro Caco-2 permeability and microsomal half-life screens were utilized in an effort to guide the structure-activity relationship in order to improve the pharmacokinetic properties of novel HIV-1 attachment inhibitors. The relevance of the in vitro screens to in vivo pharmacokinetic properties was first demonstrated with a number of program compounds at the early stage of lead optimization. The Caco-2 permeability, tested at 200 microM, was quantitatively predictive of in vivo oral absorption, with complete absorption occurring at a Caco-2 permeability of 100 nm/s or higher. The liver microsomal half-life screen, conducted at 1 microM substrate concentration, can readily differentiate low-, intermediate-, and high-clearance compounds in rats, with a nearly 1:1 correlation in 12 out of 13 program compounds tested. Among the >100 compounds evaluated, BMS-488043 emerged as a lead, exhibiting a Caco-2 permeability of 178 nm/s and a microsomal half-life predictive of a low clearance (4 mL/min/kg) in humans. These in vitro characteristics translated well to the in vivo setting. The oral bioavailability of BMS-488043 in rats, dogs, and monkeys was 90%, 57%, and 60%, respectively. The clearance was low in all three species tested, with a terminal half-life ranging from 2.4 to 4.7 h. Furthermore, the oral exposure of BMS-488043 was significantly improved (6- to 12-fold in rats and monkeys) compared to the prototype compound BMS-378806 that had a suboptimal Caco-2 permeability (51 nm/s) and microsomal half-life. More importantly, the improvements in preclinical pharmacokinetics translated well to humans, leading to a >15-fold increase in the human oral exposure of BMS-488043 than BMS-378806 and enabling a clinical proof-of-concept for this novel class of anti-HIV agents. The current studies demonstrated the valuable role of in vitro ADME screens in improving oral pharmacokinetics at the lead optimization stage. 2009 Wiley-Liss, Inc. and the American Pharmacists Association

Connecting the solution chemistry of PbI2 and MAI: a cyclodextrin-based supramolecular approach to the formation of hybrid halide perovskites.

PubMed

Masi, Sofia; Aiello, Federica; Listorti, Andrea; Balzano, Federica; Altamura, Davide; Giannini, Cinzia; Caliandro, Rocco; Uccello-Barretta, Gloria; Rizzo, Aurora; Colella, Silvia

2018-03-28

The evolution from solvated precursors to hybrid halide perovskite films dictates most of the photophysical and optoelectronic properties of the final polycrystalline material. Specifically, the complex equilibria and the importantly different solubilities of lead iodide (PbI 2 ) and methylammonium iodide (MAI) induce inhomogeneous crystal growth, often leading to a defect dense film showing non-optimal optoelectronic properties and intrinsic instability. Here, we explore a supramolecular approach based on the use of cyclodextrins (CDs) to modify the underlying solution chemistry. The peculiar phenomenon demonstrated is a tunable complexation between different CDs and MA + cations concurrent to an out of cage PbI 2 intercalation, representing the first report of a connection between the solvation equilibria of the two perovskite precursors. The optimal conditions in terms of CD cavity size and polarity translate to a neat enhancement of PbI 2 solubility in the reaction media, leading to an equilibration of the availability of the precursors in solution. The macroscopic result of this is an improved nucleation process, leading to a perovskite material with higher crystallinity, better optical properties and improved moisture resistance. Remarkably, the use of CDs presents a great potential for a wide range of device-related applications, as well as for the development of tailored composite materials.

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

NASA Astrophysics Data System (ADS)

Duraccio, Vincenzo; Elia, Valerio; Forcina, Antonio

2016-06-01

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

High-Intensity Interval Training After Stroke: An Opportunity to Promote Functional Recovery, Cardiovascular Health, and Neuroplasticity.

PubMed

Crozier, Jennifer; Roig, Marc; Eng, Janice J; MacKay-Lyons, Marilyn; Fung, Joyce; Ploughman, Michelle; Bailey, Damian M; Sweet, Shane N; Giacomantonio, Nicholas; Thiel, Alexander; Trivino, Michael; Tang, Ada

2018-04-01

Stroke is the leading cause of adult disability. Individuals poststroke possess less than half of the cardiorespiratory fitness (CRF) as their nonstroke counterparts, leading to inactivity, deconditioning, and an increased risk of cardiovascular events. Preserving cardiovascular health is critical to lower stroke risk; however, stroke rehabilitation typically provides limited opportunity for cardiovascular exercise. Optimal cardiovascular training parameters to maximize recovery in stroke survivors also remains unknown. While stroke rehabilitation recommendations suggest the use of moderate-intensity continuous exercise (MICE) to improve CRF, neither is it routinely implemented in clinical practice, nor is the intensity always sufficient to elicit a training effect. High-intensity interval training (HIIT) has emerged as a potentially effective alternative that encompasses brief high-intensity bursts of exercise interspersed with bouts of recovery, aiming to maximize cardiovascular exercise intensity in a time-efficient manner. HIIT may provide an alternative exercise intervention and invoke more pronounced benefits poststroke. To provide an updated review of HIIT poststroke through ( a) synthesizing current evidence; ( b) proposing preliminary considerations of HIIT parameters to optimize benefit; ( c) discussing potential mechanisms underlying changes in function, cardiovascular health, and neuroplasticity following HIIT; and ( d) discussing clinical implications and directions for future research. Preliminary evidence from 10 studies report HIIT-associated improvements in functional, cardiovascular, and neuroplastic outcomes poststroke; however, optimal HIIT parameters remain unknown. Larger randomized controlled trials are necessary to establish ( a) effectiveness, safety, and optimal training parameters within more heterogeneous poststroke populations; (b) potential mechanisms of HIIT-associated improvements; and ( c) adherence and psychosocial outcomes.

MACHINE COOLANT WASTE REDUCTION BY OPTIMIZING COOLANT LIFE

EPA Science Inventory

Machine shops use coolants to improve the life and function of machine tools. hese coolants become contaminated with oils with use, and this contamination can lead to growth of anaerobic bacteria and shortened coolant life. his project investigated methods to extend coolant life ...

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

DOE PAGES

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

2014-10-15

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

A continuous quality improvement project to improve the quality of cervical Papanicolaou smears.

PubMed

Burkman, R T; Ward, R; Balchandani, K; Kini, S

1994-09-01

To improve the quality of cervical Papanicolaou smears by continuous quality improvement techniques. The study used a Papanicolaou smear data base of over 200,000 specimens collected between June 1988 and December 1992. A team approach employing techniques such as process flow-charting, cause and effect diagrams, run charts, and a randomized trial of collection methods was used to evaluate potential causes of Papanicolaou smear reports with the notation "inadequate" or "less than optimal" due to too few or absent endocervical cells. Once a key process variable (method of collection) was identified, the proportion of Papanicolaou smears with inadequate or absent endocervical cells was determined before and after employment of a collection technique using a spatula and Cytobrush. We measured the rate of less than optimal Papanicolaou smears due to too few or absent endocervical cells. Before implementing the new collection technique fully by June 1990, the overall rate of less than optimal cervical Papanicolaou smears ranged from 20-25%; by December 1993, it had stabilized at about 10%. Continuous quality improvement can be used successfully to study a clinical process and implement change that will lead to improvement.

Improvement of forecast skill for severe weather by merging radar-based extrapolation and storm-scale NWP corrected forecast

NASA Astrophysics Data System (ADS)

Wang, Gaili; Wong, Wai-Kin; Hong, Yang; Liu, Liping; Dong, Jili; Xue, Ming

2015-03-01

The primary objective of this study is to improve the performance of deterministic high resolution rainfall forecasts caused by severe storms by merging an extrapolation radar-based scheme with a storm-scale Numerical Weather Prediction (NWP) model. Effectiveness of Multi-scale Tracking and Forecasting Radar Echoes (MTaRE) model was compared with that of a storm-scale NWP model named Advanced Regional Prediction System (ARPS) for forecasting a violent tornado event that developed over parts of western and much of central Oklahoma on May 24, 2011. Then the bias corrections were performed to improve the forecast accuracy of ARPS forecasts. Finally, the corrected ARPS forecast and radar-based extrapolation were optimally merged by using a hyperbolic tangent weight scheme. The comparison of forecast skill between MTaRE and ARPS in high spatial resolution of 0.01° × 0.01° and high temporal resolution of 5 min showed that MTaRE outperformed ARPS in terms of index of agreement and mean absolute error (MAE). MTaRE had a better Critical Success Index (CSI) for less than 20-min lead times and was comparable to ARPS for 20- to 50-min lead times, while ARPS had a better CSI for more than 50-min lead times. Bias correction significantly improved ARPS forecasts in terms of MAE and index of agreement, although the CSI of corrected ARPS forecasts was similar to that of the uncorrected ARPS forecasts. Moreover, optimally merging results using hyperbolic tangent weight scheme further improved the forecast accuracy and became more stable.

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

PubMed

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

2017-10-26

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

Cardiopulmonary resuscitation quality and beyond: the need to improve real-time feedback and physiologic monitoring.

PubMed

Lin, Steve; Scales, Damon C

2016-06-28

High-quality cardiopulmonary resuscitation (CPR) has been shown to improve survival outcomes after cardiac arrest. The current standard in studies evaluating CPR quality is to measure CPR process measures-for example, chest compression rate, depth, and fraction. Published studies evaluating CPR feedback devices have yielded mixed results. Newer approaches that seek to optimize CPR by measuring physiological endpoints during the resuscitation may lead to individualized patient care and improved patient outcomes.

Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning

PubMed Central

Brković, Milenko; Simić, Mirjana

2014-01-01

Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443

Guiding lead optimization with GPCR structure modeling and molecular dynamics.

PubMed

Heifetz, Alexander; James, Tim; Morao, Inaki; Bodkin, Michael J; Biggin, Philip C

2016-10-01

G-protein coupled receptor (GPCR) modeling approaches are widely used in the hit-to-lead and lead optimization stages of drug discovery. Modern protocols that involve molecular dynamics simulation can address key issues such as the free energy of binding (affinity), ligand-induced GPCR flexibility, ligand binding kinetics, conserved water positions and their role in ligand binding and the effects of mutations. The goals of these calculations are to predict the structures of the complexes between existing ligands and their receptors, to understand the key interactions and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this review we present a brief survey of various computational approaches illustrated through a hierarchical GPCR modeling protocol and its prospective application in three industrial drug discovery projects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multidisciplinary lung cancer meetings: improving the practice of radiation oncology and facing future challenges.

PubMed

Campbell, Belinda A; Ball, David; Mornex, Françoise

2015-02-01

Clinical guidelines widely recognize the importance of multidisciplinary meetings (MDM) in the optimal care of lung cancer patients. The published literature suggest that dedicated Lung Cancer MDM lead to increased treatment utilization rates and improved survival outcomes for patients with lung cancer. For radiation oncologists, Lung Cancer MDM have been proven to support evidence-based practice and improve the utilization of radiotherapy. Lung Cancer MDM also allow for education and promotion of specialty radiotherapy services. The fast pace of modern medicine is also presenting new challenges for the multidisciplinary lung cancer team, and technological advances are likely to lead to new changes in the structure of traditional Lung Cancer MDM. © 2015 Asian Pacific Society of Respirology.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Optimized mid-infrared thermal emitters for applications in aircraft countermeasures

NASA Astrophysics Data System (ADS)

Lorenzo, Simón G.; You, Chenglong; Granier, Christopher H.; Veronis, Georgios; Dowling, Jonathan P.

2017-12-01

We introduce an optimized aperiodic multilayer structure capable of broad angle and high temperature thermal emission over the 3 μm to 5 μm atmospheric transmission band. This aperiodic multilayer structure composed of alternating layers of silicon carbide and graphite on top of a tungsten substrate exhibits near maximal emittance in a 2 μm wavelength range centered in the mid-wavelength infrared band traditionally utilized for atmospheric transmission. We optimize the layer thicknesses using a hybrid optimization algorithm coupled to a transfer matrix code to maximize the power emitted in this mid-infrared range normal to the structure's surface. We investigate possible applications for these structures in mimicking 800-1000 K aircraft engine thermal emission signatures and in improving countermeasure effectiveness against hyperspectral imagers. We find these structures capable of matching the Planck blackbody curve in the selected infrared range with relatively sharp cutoffs on either side, leading to increased overall efficiency of the structures. Appropriately optimized multilayer structures with this design could lead to matching a variety of mid-infrared thermal emissions. For aircraft countermeasure applications, this method could yield a flare design capable of mimicking engine spectra and breaking the lock of hyperspectral imaging systems.

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

DOE PAGES

Castillo, Anya; Gayme, Dennice

2017-03-27

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

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

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

Duraccio, Vincenzo; Elia, Valerio; Forcina, Antonio

2016-06-08

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

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

Unkelbach, J; Perko, Z; Wolfgang, J

Purpose: Stereotactic body radiotherapy (SBRT) has become an established treatment option for liver cancer. For patients with large tumors, the prescription dose is often limited by constraints on the mean liver dose, leading to tumor recurrence. In this work, we demonstrate that spatiotemporal fractionation schemes, ie delivering distinct dose distributions in different fractions, may allow for a 10% increase in biologically effective dose (BED) in the tumor compared to current practice where each fraction delivers the same dose distribution. Methods: We consider rotation therapy delivered with x-ray beams. Treatment plan optimization is performed using objective functions evaluated for the cumulativemore » BED delivered at the end of treatment. This allows for simultaneously optimizing multiple distinct treatment plans for different fractions. Results: The treatment that optimally exploits fractionation effects is designed such that each fraction delivers a similar dose bath to the uninvolved liver while delivering high single fraction doses to complementary parts of the target volume. Thereby, partial hypofractionation in the tumor is achieved along with near uniform fractionation in the surrounding liver - leading to an improvement in the therapeutic ratio. The benefit of such spatiotemporal fractionation schemes depends on tumor geometry and location as well as the number of fractions. For 5-fraction treatments (allowing for 5 distinct dose distributions) an improvement in the order of 10% is observed. Conclusion: Delivering distinct dose distributions in different fractions, purely motivated by fractionation effects rather than geometric changes, may improve the therapeutic ratio. For treatment sites where the prescriptions dose is limited by mean dose constraints in the surrounding organ, such as liver cancer, this approach may facilitate biological dose escalation and improved cure rates.« less

In Situ Passivation for Efficient PbS Quantum Dot Solar Cells by Precursor Engineering.

PubMed

Wang, Yongjie; Lu, Kunyuan; Han, Lu; Liu, Zeke; Shi, Guozheng; Fang, Honghua; Chen, Si; Wu, Tian; Yang, Fan; Gu, Mengfan; Zhou, Sijie; Ling, Xufeng; Tang, Xun; Zheng, Jiawei; Loi, Maria Antonietta; Ma, Wanli

2018-04-01

Current efforts on lead sulfide quantum dot (PbS QD) solar cells are mostly paid to the device architecture engineering and postsynthetic surface modification, while very rare work regarding the optimization of PbS synthesis is reported. Here, PbS QDs are successfully synthesized using PbO and PbAc 2  · 3H 2 O as the lead sources. QD solar cells based on PbAc-PbS have demonstrated a high power conversion efficiency (PCE) of 10.82% (and independently certificated values of 10.62%), which is significantly higher than the PCE of 9.39% for PbO-PbS QD based ones. For the first time, systematic investigations are carried out on the effect of lead precursor engineering on the device performance. It is revealed that acetate can act as an efficient capping ligands together with oleic acid, providing better surface coverage and replace some of the harmful hydroxyl (OH) ligands during the synthesis. Then the acetate on the surface can be exchanged by iodide and lead to desired passivation. This work demonstrates that the precursor engineering has great potential in performance improvement. It is also pointed out that the initial synthesis is an often neglected but critical stage and has abundant room for optimization to further improve the quality of the resultant QDs, leading to breakthrough efficiency. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2016-07-01

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

Abdomen disease diagnosis in CT images using flexiscale curvelet transform and improved genetic algorithm.

PubMed

Sethi, Gaurav; Saini, B S

2015-12-01

This paper presents an abdomen disease diagnostic system based on the flexi-scale curvelet transform, which uses different optimal scales for extracting features from computed tomography (CT) images. To optimize the scale of the flexi-scale curvelet transform, we propose an improved genetic algorithm. The conventional genetic algorithm assumes that fit parents will likely produce the healthiest offspring that leads to the least fit parents accumulating at the bottom of the population, reducing the fitness of subsequent populations and delaying the optimal solution search. In our improved genetic algorithm, combining the chromosomes of a low-fitness and a high-fitness individual increases the probability of producing high-fitness offspring. Thereby, all of the least fit parent chromosomes are combined with high fit parent to produce offspring for the next population. In this way, the leftover weak chromosomes cannot damage the fitness of subsequent populations. To further facilitate the search for the optimal solution, our improved genetic algorithm adopts modified elitism. The proposed method was applied to 120 CT abdominal images; 30 images each of normal subjects, cysts, tumors and stones. The features extracted by the flexi-scale curvelet transform were more discriminative than conventional methods, demonstrating the potential of our method as a diagnostic tool for abdomen diseases.

Decision-Making Strategies for College Students

ERIC Educational Resources Information Center

Morey, Janis T.; Dansereau, Donald F.

2010-01-01

College students' decision making is often less than optimal and sometimes leads to negative consequences. The effectiveness of two strategies for improving student decision making--node-link mapping and social perspective taking (SPT)--are examined. Participants using SPT were significantly better able to evaluate decision options and develop…

Optimizing airport capacity utilization in air traffic flow management subject to constraints at arrival and departure fixes

DOT National Transportation Integrated Search

1997-09-01

This paper formulates a new approach for improvement : of air traffic flow management at airports, which leads to : more efficient utilization of existing airport capacity to alleviate : the consequences of congestion. A new model is presented, : whi...

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

PubMed

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

2015-12-01

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

A review on fracture prevention of stent in femoropopliteal artery

NASA Astrophysics Data System (ADS)

Atan, Bainun Akmal Mohd; Ismail, Al Emran; Taib, Ishkrizat; Lazim, Zulfaqih

2017-01-01

Heavily calcific lesions, total occlusions, tortuous blood vessels, variable lengths of arteries, various dynamic loads and deformations in the femoropopliteal (FP) arterial segment make stenosis treatments are complicated. The dynamic forces in FP artery including bending, torsion and radial compression may lead to stent fracture (SF) and eventually to in-stent restenosis (ISR). Stent design specifically geometrical configurations are a major factor need to be improved to optimize stent expansion and flexibility both bending and torsion during stent deployment into the diseased FP artery. Previous studies discovered the influence of various stent geometrical designs resulted different structural behaviour. Optimizing stent design can improve stent performances: flexibility and radial strength to prevent SF in FP arterial segment

Magnetic recording performance of keepered media

NASA Astrophysics Data System (ADS)

Coughlin, T. M.; Tang, Y. S.; Velu, E. M. T.; Lairson, B.

1997-04-01

Using low flying and proximity inductive heads, keepered media show improved on- and off-track performance leading us to conclude that a greater than 20% areal density improvement is possible with a keeper layer over the magnetic storage layer. For Sendust keeper layers there is an optimal range of thickness and an optimal bias point for best performance. There are both amplitude and timing asymmetries that are functions of the read-back bias. For a peak detect channel the best performance corresponds to the minimum timing asymmetry although this is not the point where the pulses are narrowest. Keepered media may have an advantage in total jitter and partial erasure. NLTS is almost identical for keepered versus unkeepered media.

Coronary Sinus Lead Positioning.

PubMed

Roka, Attila; Borgquist, Rasmus; Singh, Jagmeet

2015-12-01

Although cardiac resynchronization therapy improves morbidity and mortality in patients with cardiomyopathy, heart failure, and electrical dyssynchrony, the rate of nonresponders using standard indications and implant techniques is still high. Optimal coronary sinus lead positioning is important to increase the chance of successful resynchronization. Patient factors such as cause of heart failure, type of dyssynchrony, scar burden, coronary sinus anatomy, and phrenic nerve capture may affect the efficacy of the therapy. Several modalities are under investigation. Alternative left ventricular lead implantation strategies are occasionally required when the transvenous route is not feasible or would result in a suboptimal lead position. Copyright © 2015 Elsevier Inc. All rights reserved.

Coronary Sinus Lead Positioning.

PubMed

Roka, Attila; Borgquist, Rasmus; Singh, Jagmeet

2017-01-01

Although cardiac resynchronization therapy improves morbidity and mortality in patients with cardiomyopathy, heart failure, and electrical dyssynchrony, the rate of nonresponders using standard indications and implant techniques is still high. Optimal coronary sinus lead positioning is important to increase the chance of successful resynchronization. Patient factors such as cause of heart failure, type of dyssynchrony, scar burden, coronary sinus anatomy, and phrenic nerve capture may affect the efficacy of the therapy. Several modalities are under investigation. Alternative left ventricular lead implantation strategies are occasionally required when the transvenous route is not feasible or would result in a suboptimal lead position. Copyright © 2016 Elsevier Inc. All rights reserved.

A new optimized GA-RBF neural network algorithm.

PubMed

Jia, Weikuan; Zhao, Dean; Shen, Tian; Su, Chunyang; Hu, Chanli; Zhao, Yuyan

2014-01-01

When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this problem, we propose a new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm), which uses genetic algorithm to optimize the weights and structure of RBF neural network; it chooses new ways of hybrid encoding and optimizing simultaneously. Using the binary encoding encodes the number of the hidden layer's neurons and using real encoding encodes the connection weights. Hidden layer neurons number and connection weights are optimized simultaneously in the new algorithm. However, the connection weights optimization is not complete; we need to use least mean square (LMS) algorithm for further leaning, and finally get a new algorithm model. Using two UCI standard data sets to test the new algorithm, the results show that the new algorithm improves the operating efficiency in dealing with complex problems and also improves the recognition precision, which proves that the new algorithm is valid.

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

PubMed

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

2018-06-14

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

In Silico Design of DNP Polarizing Agents: Can Current Dinitroxides Be Improved?

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

Perras, Frédéric A.; Sadow, Aaron; Pruski, Marek

Numerical calculations of enhancement factors offered by dynamic nuclear polarization in solids under magic angle spinning (DNP-MAS) were performed to determine the optimal EPR parameters for a dinitroxide polarizing agent. We found that the DNP performance of a biradical is more tolerant to the relative orientation of the two nitroxide moieties than previously thought. In general, any condition in which the gyy tensor components of both radicals are perpendicular to one another is expected to have near-optimal DNP performance. These results highlight the important role of the exchange coupling, which can lessen the sensitivity of DNP performance to the inter-radicalmore » distance, but also lead to lower enhancements when the number of atoms in the linker becomes less than three. Finally, the calculations showed that the electron T1e value should be near 500μs to yield optimal performance. Importantly, the newest polarizing agents already feature all of the qualities of the optimal polarizing agent, leaving little room for further improvement. Further research into DNP polarizing agents should then target non-nitroxide radicals, as well as improvements in sample formulations to advance high-temperature DNP and limit quenching and reactivity.« less

In Silico Design of DNP Polarizing Agents: Can Current Dinitroxides Be Improved?

DOE PAGES

Perras, Frédéric A.; Sadow, Aaron; Pruski, Marek

2017-06-09

Numerical calculations of enhancement factors offered by dynamic nuclear polarization in solids under magic angle spinning (DNP-MAS) were performed to determine the optimal EPR parameters for a dinitroxide polarizing agent. We found that the DNP performance of a biradical is more tolerant to the relative orientation of the two nitroxide moieties than previously thought. In general, any condition in which the gyy tensor components of both radicals are perpendicular to one another is expected to have near-optimal DNP performance. These results highlight the important role of the exchange coupling, which can lessen the sensitivity of DNP performance to the inter-radicalmore » distance, but also lead to lower enhancements when the number of atoms in the linker becomes less than three. Finally, the calculations showed that the electron T1e value should be near 500μs to yield optimal performance. Importantly, the newest polarizing agents already feature all of the qualities of the optimal polarizing agent, leaving little room for further improvement. Further research into DNP polarizing agents should then target non-nitroxide radicals, as well as improvements in sample formulations to advance high-temperature DNP and limit quenching and reactivity.« less

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.

Optimized tomography of continuous variable systems using excitation counting

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Simultaneous beam sampling and aperture shape optimization for SPORT.

PubMed

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

2015-02-01

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

Simultaneous beam sampling and aperture shape optimization for SPORT

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

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

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

Disorder-assisted quantum transport in suboptimal decoherence regimes

PubMed Central

Novo, Leonardo; Mohseni, Masoud; Omar, Yasser

2016-01-01

We investigate quantum transport in binary tree structures and in hypercubes for the disordered Frenkel-exciton Hamiltonian under pure dephasing noise. We compute the energy transport efficiency as a function of disorder and dephasing rates. We demonstrate that dephasing improves transport efficiency not only in the disordered case, but also in the ordered one. The maximal transport efficiency is obtained when the dephasing timescale matches the hopping timescale, which represent new examples of the Goldilocks principle at the quantum scale. Remarkably, we find that in weak dephasing regimes, away from optimal levels of environmental fluctuations, the average effect of increasing disorder is to improve the transport efficiency until an optimal value for disorder is reached. Our results suggest that rational design of the site energies statistical distributions could lead to better performances in transport systems at nanoscale when their natural environments are far from the optimal dephasing regime. PMID:26726133

Fabrication and Characterization of Three Dimensional Photonic Crystals Generated by Multibeam Interference Lithography

ERIC Educational Resources Information Center

Chen, Ying-Chieh

2009-01-01

Multibeam interference lithography is investigated as a manufacturing technique for three-dimensional photonic crystal templates. In this research, optimization of the optical setup and the photoresist initiation system leads to a significant improvement of the optical quality of the crystal, as characterized by normal incidence optical…

Rapid in vitro shoot multiplication of the recalcitrant species Juglans nigra L.

Treesearch

Micah E. Stevens; Paula M. Pijut

2018-01-01

Black walnut (Juglans nigra L.) has long been prized for its timber, leading to commercial cultivation and significant breeding efforts for improving marketable traits. Vegetative and in vitro black walnut propagation techniques, however, are variable and highly genotype dependent. Optimizing plant growth regulator type and...

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

PubMed

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

2015-04-01

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

Nuclear Electric Vehicle Optimization Toolset (NEVOT)

NASA Technical Reports Server (NTRS)

Tinker, Michael L.; Steincamp, James W.; Stewart, Eric T.; Patton, Bruce W.; Pannell, William P.; Newby, Ronald L.; Coffman, Mark E.; Kos, Larry D.; Qualls, A. Lou; Greene, Sherrell

2004-01-01

The Nuclear Electric Vehicle Optimization Toolset (NEVOT) optimizes the design of all major nuclear electric propulsion (NEP) vehicle subsystems for a defined mission within constraints and optimization parameters chosen by a user. The tool uses a genetic algorithm (GA) search technique to combine subsystem designs and evaluate the fitness of the integrated design to fulfill a mission. The fitness of an individual is used within the GA to determine its probability of survival through successive generations in which the designs with low fitness are eliminated and replaced with combinations or mutations of designs with higher fitness. The program can find optimal solutions for different sets of fitness metrics without modification and can create and evaluate vehicle designs that might never be considered through traditional design techniques. It is anticipated that the flexible optimization methodology will expand present knowledge of the design trade-offs inherent in designing nuclear powered space vehicles and lead to improved NEP designs.

Optimal back-to-front airplane boarding.

PubMed

Bachmat, Eitan; Khachaturov, Vassilii; Kuperman, Ran

2013-06-01

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

Design, synthesis and optimization of bis-amide derivatives as CSF1R inhibitors.

PubMed

Ramachandran, Sreekanth A; Jadhavar, Pradeep S; Miglani, Sandeep K; Singh, Manvendra P; Kalane, Deepak P; Agarwal, Anil K; Sathe, Balaji D; Mukherjee, Kakoli; Gupta, Ashu; Haldar, Srijan; Raja, Mohd; Singh, Siddhartha; Pham, Son M; Chakravarty, Sarvajit; Quinn, Kevin; Belmar, Sebastian; Alfaro, Ivan E; Higgs, Christopher; Bernales, Sebastian; Herrera, Francisco J; Rai, Roopa

2017-05-15

Signaling via the receptor tyrosine kinase CSF1R is thought to play an important role in recruitment and differentiation of tumor-associated macrophages (TAMs). TAMs play pro-tumorigenic roles, including the suppression of anti-tumor immune response, promotion of angiogenesis and tumor cell metastasis. Because of the role of this signaling pathway in the tumor microenvironment, several small molecule CSF1R kinase inhibitors are undergoing clinical evaluation for cancer therapy, either as a single agent or in combination with other cancer therapies, including immune checkpoint inhibitors. Herein we describe our lead optimization effort that resulted in the identification of a potent, cellular active and orally bioavailable bis-amide CSF1R inhibitor. Docking and biochemical analysis allowed the removal of a metabolically labile and poorly permeable methyl piperazine group from an early lead compound. Optimization led to improved metabolic stability and Caco2 permeability, which in turn resulted in good oral bioavailability in mice. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discovery of the Highly Potent PI3K/mTOR Dual Inhibitor PF-04979064 through Structure-Based Drug Design

PubMed Central

2012-01-01

PI3K, AKT, and mTOR are key kinases from PI3K signaling pathway being extensively pursued to treat a variety of cancers in oncology. To search for a structurally differentiated back-up candidate to PF-04691502, which is currently in phase I/II clinical trials for treating solid tumors, a lead optimization effort was carried out with a tricyclic imidazo[1,5]naphthyridine series. Integration of structure-based drug design and physical properties-based optimization yielded a potent and selective PI3K/mTOR dual kinase inhibitor PF-04979064. This manuscript discusses the lead optimization for the tricyclic series, which both improved the in vitro potency and addressed a number of ADMET issues including high metabolic clearance mediated by both P450 and aldehyde oxidase (AO), poor permeability, and poor solubility. An empirical scaling tool was developed to predict human clearance from in vitro human liver S9 assay data for tricyclic derivatives that were AO substrates. PMID:24900568

Development and Testing of an Algorithm for Efficient Resource Positioning in Pre-hospital Emergency Care

PubMed Central

Saini, Devashish; Mazza, Giovanni; Shah, Najaf; Mirza, Muzna; Gori, Mandar M; Nandigam, Hari Krishna; Orthner, Helmuth F

2006-01-01

Response times for pre-hospital emergency care may be improved with the use of algorithms that analyzes historical patterns in incident location and suggests optimal places for prepositioning of emergency response units. We will develop such an algorithm based on cluster analysis and test whether it leads to significant improvement in mileage when compared to actual historical data of dispatching based on fixed stations. PMID:17238702

Development and testing of an algorithm for efficient resource positioning in pre-hospital emergency care.

PubMed

Saini, Devashish; Mazza, Giovanni; Shah, Najaf; Mirza, Muzna; Gori, Mandar M; Nandigam, Hari Krishna; Orthner, Helmuth F

2006-01-01

Response times for pre-hospital emergency care may be improved with the use of algorithms that analyzes historical patterns in incident location and suggests optimal places for pre-positioning of emergency response units. We will develop such an algorithm based on cluster analysis and test whether it leads to significant improvement in mileage when compared to actual historical data of dispatching based on fixed stations.

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

NASA Astrophysics Data System (ADS)

Watkins, Edward Francis

1995-01-01

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

Chemical behavior of residential lead in urban yards in the United States.

PubMed

Elless, M P; Bray, C A; Blaylock, M J

2007-07-01

Long after federal regulations banned the use of lead-based paints and leaded gasoline, residential lead remains a persistent challenge. Soil lead is a significant contributor to this hazard and an improved understanding of physicochemical properties is likely to be useful for in situ abatement techniques such as phytoremediation and chemical stabilization. A laboratory characterization of high-lead soils collected from across the United States shows that the lead contaminants were concentrating in the silt and clay fractions, in the form of discrete particles of lead, as observed by scanning electron microscopy coupled with energy dispersive X-ray analysis. Soil lead varied widely in its solubility behavior as assessed by sequential and chelate extractions. Because site-specific factors (e.g., soil pH, texture, etc.) are believed to govern the solubility of the lead, understanding the variability in these characteristics at each site is necessary to optimize in situ remediation or abatement of these soils.

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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

PubMed

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

2014-11-24

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

Improving the photovoltaic performance of perovskite solar cells with acetate

PubMed Central

Zhao, Qian; Li, G. R.; Song, Jian; Zhao, Yulong; Qiang, Yinghuai; Gao, X. P.

2016-01-01

In an all-solid-state perovskite solar cell, methylammonium lead halide film is in charge of generating photo-excited electrons, thus its quality can directly influence the final photovoltaic performance of the solar cell. This paper accentuates a very simple chemical approach to improving the quality of a perovskite film with a suitable amount of acetic acid. With introduction of acetate ions, a homogeneous, continual and hole-free perovskite film comprised of high-crystallinity grains is obtained. UV-visible spectra, steady-state and time-resolved photoluminescence (PL) spectra reveal that the obtained perovskite film under the optimized conditions shows a higher light absorption, more efficient electron transport, and faster electron extraction to the adjoining electron transport layer. The features result in the optimized perovskite film can provide an improved short-circuit current. The corresponding solar cells with a planar configuration achieves an improved power conversion efficiency of 13.80%, and the highest power conversion efficiency in the photovoltaic measurements is up to 14.71%. The results not only provide a simple approach to optimizing perovskite films but also present a novel angle of view on fabricating high-performance perovskite solar cells. PMID:27934924

Improving the photovoltaic performance of perovskite solar cells with acetate.

PubMed

Zhao, Qian; Li, G R; Song, Jian; Zhao, Yulong; Qiang, Yinghuai; Gao, X P

2016-12-09

In an all-solid-state perovskite solar cell, methylammonium lead halide film is in charge of generating photo-excited electrons, thus its quality can directly influence the final photovoltaic performance of the solar cell. This paper accentuates a very simple chemical approach to improving the quality of a perovskite film with a suitable amount of acetic acid. With introduction of acetate ions, a homogeneous, continual and hole-free perovskite film comprised of high-crystallinity grains is obtained. UV-visible spectra, steady-state and time-resolved photoluminescence (PL) spectra reveal that the obtained perovskite film under the optimized conditions shows a higher light absorption, more efficient electron transport, and faster electron extraction to the adjoining electron transport layer. The features result in the optimized perovskite film can provide an improved short-circuit current. The corresponding solar cells with a planar configuration achieves an improved power conversion efficiency of 13.80%, and the highest power conversion efficiency in the photovoltaic measurements is up to 14.71%. The results not only provide a simple approach to optimizing perovskite films but also present a novel angle of view on fabricating high-performance perovskite solar cells.

Simplification of the time-dependent generalized self-interaction correction method using two sets of orbitals: Application of the optimized effective potential formalism

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

Messud, J.; Dinh, P. M.; Suraud, Eric

2009-10-15

We propose a simplification of the time-dependent self-interaction correction (TD-SIC) method using two sets of orbitals, applying the optimized effective potential (OEP) method. The resulting scheme is called time-dependent 'generalized SIC-OEP'. A straightforward approximation, using the spatial localization of one set of orbitals, leads to the 'generalized SIC-Slater' formalism. We show that it represents a great improvement compared to the traditional SIC-Slater and Krieger-Li-Iafrate formalisms.

Simplification of the time-dependent generalized self-interaction correction method using two sets of orbitals: Application of the optimized effective potential formalism

NASA Astrophysics Data System (ADS)

Messud, J.; Dinh, P. M.; Reinhard, P.-G.; Suraud, Eric

2009-10-01

We propose a simplification of the time-dependent self-interaction correction (TD-SIC) method using two sets of orbitals, applying the optimized effective potential (OEP) method. The resulting scheme is called time-dependent “generalized SIC-OEP.” A straightforward approximation, using the spatial localization of one set of orbitals, leads to the “generalized SIC-Slater” formalism. We show that it represents a great improvement compared to the traditional SIC-Slater and Krieger-Li-Iafrate formalisms.

Heimdall System for MSSS Sensor Tasking

NASA Astrophysics Data System (ADS)

Herz, A.; Jones, B.; Herz, E.; George, D.; Axelrad, P.; Gehly, S.

In Norse Mythology, Heimdall uses his foreknowledge and keen eyesight to keep watch for disaster from his home near the Rainbow Bridge. Orbit Logic and the Colorado Center for Astrodynamics Research (CCAR) at the University of Colorado (CU) have developed the Heimdall System to schedule observations of known and uncharacterized objects and search for new objects from the Maui Space Surveillance Site. Heimdall addresses the current need for automated and optimized SSA sensor tasking driven by factors associated with improved space object catalog maintenance. Orbit Logic and CU developed an initial baseline prototype SSA sensor tasking capability for select sensors at the Maui Space Surveillance Site (MSSS) using STK and STK Scheduler, and then added a new Track Prioritization Component for FiSST-inspired computations for predicted Information Gain and Probability of Detection, and a new SSA-specific Figure-of-Merit (FOM) for optimized SSA sensor tasking. While the baseline prototype addresses automation and some of the multi-sensor tasking optimization, the SSA-improved prototype addresses all of the key elements required for improved tasking leading to enhanced object catalog maintenance. The Heimdall proof-of-concept was demonstrated for MSSS SSA sensor tasking for a 24 hour period to attempt observations of all operational satellites in the unclassified NORAD catalog, observe a small set of high priority GEO targets every 30 minutes, make a sky survey of the GEO belt region accessible to MSSS sensors, and observe particular GEO regions that have a high probability of finding new objects with any excess sensor time. This Heimdall prototype software paves the way for further R&D that will integrate this technology into the MSSS systems for operational scheduling, improve the software's scalability, and further tune and enhance schedule optimization. The Heimdall software for SSA sensor tasking provides greatly improved performance over manual tasking, improved coordinated sensor usage, and tasking schedules driven by catalog improvement goals (reduced overall covariance, etc.). The improved performance also enables more responsive sensor tasking to address external events, newly detected objects, newly detected object activity, and sensor anomalies. Instead of having to wait until the next day's scheduling phase, events can be addressed with new tasking schedules immediately (within seconds or minutes). Perhaps the most important benefit is improved SSA based on an overall improvement to the quality of the space catalog. By driving sensor tasking and scheduling based on predicted Information Gain and other relevant factors, better decisions are made in the application of available sensor resources, leading to an improved catalog and better information about the objects of most interest. The Heimdall software solution provides a configurable, automated system to improve sensor tasking efficiency and responsiveness for SSA applications. The FISST algorithms for Track Prioritization, SSA specific task and resource attributes, Scheduler algorithms, and configurable SSA-specific Figure-of-Merit together provide optimized and tunable scheduling for the Maui Space Surveillance Site and possibly other sites and organizations across the U.S. military and for allies around the world.

NREL, SPI Solar and Trimark Optimize Parabolic Trough Receiver Performance

Science.gov Websites

(CSP) plants. Photo of parabolic trough receiver equipment in a laboratory Photo by Dennis Schroeder Receivers in CSP plants take a lot of abuse, from dramatic temperature changes to numerous mechanical conditions can lead to big improvements in the overall efficiency of CSP plants

Transonic airfoil design for helicopter rotor applications

NASA Technical Reports Server (NTRS)

Hassan, Ahmed A.; Jackson, B.

1989-01-01

Despite the fact that the flow over a rotor blade is strongly influenced by locally three-dimensional and unsteady effects, practical experience has always demonstrated that substantial improvements in the aerodynamic performance can be gained by improving the steady two-dimensional charateristics of the airfoil(s) employed. The two phenomena known to have great impact on the overall rotor performance are: (1) retreating blade stall with the associated large pressure drag, and (2) compressibility effects on the advancing blade leading to shock formation and the associated wave drag and boundary-layer separation losses. It was concluded that: optimization routines are a powerful tool for finding solutions to multiple design point problems; the optimization process must be guided by the judicious choice of geometric and aerodynamic constraints; optimization routines should be appropriately coupled to viscous, not inviscid, transonic flow solvers; hybrid design procedures in conjunction with optimization routines represent the most efficient approach for rotor airfroil design; unsteady effects resulting in the delay of lift and moment stall should be modeled using simple empirical relations; and inflight optimization of aerodynamic loads (e.g., use of variable rate blowing, flaps, etc.) can satisfy any number of requirements at design and off-design conditions.

Bi-level Optimization Method of Air-conditioning System Based on Office Building Energy Storage Characteristics

NASA Astrophysics Data System (ADS)

Wang, Qingze; Chen, Xingying; Ji, Li; Liao, Yingchen; Yu, Kun

2017-05-01

The air-conditioning system of office building is a large power consumption terminal equipment, whose unreasonable operation mode leads to low energy efficiency. Realizing the optimization of the air-conditioning system has become one of the important research contents of the electric power demand response. In this paper, in order to save electricity cost and improve energy efficiency, bi-level optimization method of air-conditioning system based on TOU price is put forward by using the energy storage characteristics of the office building itself. In the upper level, the operation mode of the air-conditioning system is optimized in order to minimize the uses’ electricity cost in the premise of ensuring user’ comfort according to the information of outdoor temperature and TOU price, and the cooling load of the air-conditioning is output to the lower level; In the lower level, the distribution mode of cooling load among the multi chillers is optimized in order to maximize the energy efficiency according to the characteristics of each chiller. Finally, the experimental results under different modes demonstrate that the strategy can improve the energy efficiency of chillers and save the electricity cost for users.

Cell wall-bound silicon optimizes ammonium uptake and metabolism in rice cells.

PubMed

Sheng, Huachun; Ma, Jie; Pu, Junbao; Wang, Lijun

2018-05-16

Turgor-driven plant cell growth depends on cell wall structure and mechanics. Strengthening of cell walls on the basis of an association and interaction with silicon (Si) could lead to improved nutrient uptake and optimized growth and metabolism in rice (Oryza sativa). However, the structural basis and physiological mechanisms of nutrient uptake and metabolism optimization under Si assistance remain obscure. Single-cell level biophysical measurements, including in situ non-invasive micro-testing (NMT) of NH4+ ion fluxes, atomic force microscopy (AFM) of cell walls, and electrolyte leakage and membrane potential, as well as whole-cell proteomics using isobaric tags for relative and absolute quantification (iTRAQ), were performed. The altered cell wall structure increases the uptake rate of the main nutrient NH4+ in Si-accumulating cells, whereas the rate is only half in Si-deprived counterparts. Rigid cell walls enhanced by a wall-bound form of Si as the structural basis stabilize cell membranes. This, in turn, optimizes nutrient uptake of the cells in the same growth phase without any requirement for up-regulation of transmembrane ammonium transporters. Optimization of cellular nutrient acquisition strategies can substantially improve performance in terms of growth, metabolism and stress resistance.

Analysis of signal to noise enhancement using a highly selective modulation tracking filter

NASA Technical Reports Server (NTRS)

Haden, C. R.; Alworth, C. W.

1972-01-01

Experiments are reported which utilize photodielectric effects in semiconductor loaded superconducting resonant circuits for suppressing noise in RF communication systems. The superconducting tunable cavity acts as a narrow band tracking filter for detecting conventional RF signals. Analytical techniques were developed which lead to prediction of signal-to-noise improvements. Progress is reported in optimization of the experimental variables. These include improved Q, new semiconductors, improved optics, and simplification of the electronics. Information bearing signals were passed through the system, and noise was introduced into the computer model.

Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution

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

Dall-Anese, Emiliano; Zhao, Changhong; Zamzam, Admed S.

This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successivemore » convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.« less

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

Optimism and Cause-Specific Mortality: A Prospective Cohort Study

PubMed Central

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

2017-01-01

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2013-01-01

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

Gaussian mass optimization for kernel PCA parameters

NASA Astrophysics Data System (ADS)

Liu, Yong; Wang, Zulin

2011-10-01

This paper proposes a novel kernel parameter optimization method based on Gaussian mass, which aims to overcome the current brute force parameter optimization method in a heuristic way. Generally speaking, the choice of kernel parameter should be tightly related to the target objects while the variance between the samples, the most commonly used kernel parameter, doesn't possess much features of the target, which gives birth to Gaussian mass. Gaussian mass defined in this paper has the property of the invariance of rotation and translation and is capable of depicting the edge, topology and shape information. Simulation results show that Gaussian mass leads a promising heuristic optimization boost up for kernel method. In MNIST handwriting database, the recognition rate improves by 1.6% compared with common kernel method without Gaussian mass optimization. Several promising other directions which Gaussian mass might help are also proposed at the end of the paper.

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

NASA Astrophysics Data System (ADS)

Morley, Joshua

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

Full Wave Function Optimization with Quantum Monte Carlo and Its Effect on the Dissociation Energy of FeS.

PubMed

Haghighi Mood, Kaveh; Lüchow, Arne

2017-08-17

Diffusion quantum Monte Carlo calculations with partial and full optimization of the guide function are carried out for the dissociation of the FeS molecule. For the first time, quantum Monte Carlo orbital optimization for transition metal compounds is performed. It is demonstrated that energy optimization of the orbitals of a complete active space wave function in the presence of a Jastrow correlation function is required to obtain agreement with the experimental dissociation energy. Furthermore, it is shown that orbital optimization leads to a 5 Δ ground state, in agreement with experiments but in disagreement with other high-level ab initio wave function calculations which all predict a 5 Σ + ground state. The role of the Jastrow factor in DMC calculations with pseudopotentials is investigated. The results suggest that a large Jastrow factor may improve the DMC accuracy substantially at small additional cost.

The importance of hydration thermodynamics in fragment-to-lead optimization.

PubMed

Ichihara, Osamu; Shimada, Yuzo; Yoshidome, Daisuke

2014-12-01

Using a computational approach to assess changes in solvation thermodynamics upon ligand binding, we investigated the effects of water molecules on the binding energetics of over 20 fragment hits and their corresponding optimized lead compounds. Binding activity and X-ray crystallographic data of published fragment-to-lead optimization studies from various therapeutically relevant targets were studied. The analysis reveals a distinct difference between the thermodynamic profile of water molecules displaced by fragment hits and those displaced by the corresponding optimized lead compounds. Specifically, fragment hits tend to displace water molecules with notably unfavorable excess entropies-configurationally constrained water molecules-relative to those displaced by the newly added moieties of the lead compound during the course of fragment-to-lead optimization. Herein we describe the details of this analysis with the goal of providing practical guidelines for exploiting thermodynamic signatures of binding site water molecules in the context of fragment-to-lead optimization. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of the protocols for the use of contrast agents in PET/CT studies.

PubMed

Pelegrí Martínez, L; Kohan, A A; Vercher Conejero, J L

The introduction of PET/CT scanners in clinical practice in 1998 has improved care for oncologic patients throughout the clinical pathway, from the initial diagnosis of disease through the evaluation of the response to treatment to screening for possible recurrence. The CT component of a PET/CT study is used to correct the attenuation of PET studies; CT also provides anatomic information about the distribution of the radiotracer. CT is especially useful in situations where PET alone can lead to false positives and false negatives, and CT thereby improves the diagnostic performance of PET. The use of intravenous or oral contrast agents and optimal CT protocols have improved the detection and characterization of lesions. However, there are circumstances in which the systematic use of contrast agents is not justified. The standard acquisition in PET/CT scanners is the whole body protocol, but this can lead to artifacts due to the position of patients and respiratory movements between the CT and PET acquisitions. This article discusses these aspects from a constructive perspective with the aim of maximizing the diagnostic potential of PET/CT and providing better care for patients. Copyright © 2016 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Reducing the metabolic cost of walking with an ankle exoskeleton: interaction between actuation timing and power.

PubMed

Galle, Samuel; Malcolm, Philippe; Collins, Steven Hartley; De Clercq, Dirk

2017-04-27

Powered ankle-foot exoskeletons can reduce the metabolic cost of human walking to below normal levels, but optimal assistance properties remain unclear. The purpose of this study was to test the effects of different assistance timing and power characteristics in an experiment with a tethered ankle-foot exoskeleton. Ten healthy female subjects walked on a treadmill with bilateral ankle-foot exoskeletons in 10 different assistance conditions. Artificial pneumatic muscles assisted plantarflexion during ankle push-off using one of four actuation onset timings (36, 42, 48 and 54% of the stride) and three power levels (average positive exoskeleton power over a stride, summed for both legs, of 0.2, 0.4 and 0.5 W∙kg -1 ). We compared metabolic rate, kinematics and electromyography (EMG) between conditions. Optimal assistance was achieved with an onset of 42% stride and average power of 0.4 W∙kg -1 , leading to 21% reduction in metabolic cost compared to walking with the exoskeleton deactivated and 12% reduction compared to normal walking without the exoskeleton. With suboptimal timing or power, the exoskeleton still reduced metabolic cost, but substantially less so. The relationship between timing, power and metabolic rate was well-characterized by a two-dimensional quadratic function. The assistive mechanisms leading to these improvements included reducing muscular activity in the ankle plantarflexors and assisting leg swing initiation. These results emphasize the importance of optimizing exoskeleton actuation properties when assisting or augmenting human locomotion. Our optimal assistance onset timing and average power levels could be used for other exoskeletons to improve assistance and resulting benefits.

Accurate Binding Free Energy Predictions in Fragment Optimization.

PubMed

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

2015-11-23

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

Optical absorption enhancement in NH2CH=NH2PbI3 lead halide perovskite solar cells with nanotextures

NASA Astrophysics Data System (ADS)

Xie, Ziang; Sun, Shuren; Xie, Xixi; Hou, Ruixiang; Xu, Wanjin; Li, Yanping; Qin, G. G.

2018-01-01

This article reports, for the first time to our knowledge, that the power conversion efficiencies (PCEs) of planar NH2CH=NH2PbI3 (FAPbI3) lead halide perovskite solar cells (SCs) can be largely improved by fabricating nanotextures on the SC surface. Four kinds of nanotextures are investigated and compared with each other: column hollow (CLH) nanoarrays, cone hollow (CNH) nanoarrays, square prism hollow (SPH) nanoarrays, and pyramid hollow (PYH) nanoarrays. Compared with the PCEs of the planar SCs with the same layer depth d, it is found that when d is in the range of 125-500 nm and when the array period, as well as the filling fraction of the nanotexture, are optimized, the ultimate efficiency increased 29%-50% for the CLH and SPH textured FAPbI3 SCs relative to the planar ones, and 20%-41% for the CNH and PYH textured FAPbI3 SCs relative to the planar ones. When d < 250 nm, the optimized ultimate efficiencies of the CLH and SPH textured FAPbI3 SCs with optimized nanotextures are higher than those of the CNH and PYH ones, and vice versa. The reasons why fabricating nanotextures on SC surfaces can largely improve the PCE of the FAPbI3 SCs are discussed.

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

PubMed Central

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

2018-01-01

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

Firefly as a novel swarm intelligence variable selection method in spectroscopy.

PubMed

Goodarzi, Mohammad; dos Santos Coelho, Leandro

2014-12-10

A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle. This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models. The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same. Copyright © 2014. Published by Elsevier B.V.

Optimized mixed Markov models for motif identification

PubMed Central

Huang, Weichun; Umbach, David M; Ohler, Uwe; Li, Leping

2006-01-01

Background Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challenging issue, largely due to limited availability of training samples. Results We introduce a novel and flexible model, the Optimized Mixture Markov model (OMiMa), and related methods to allow adjustment of model complexity for different motifs. In comparison with other leading methods, OMiMa can incorporate more than the NNSplice's pairwise dependencies; OMiMa avoids model over-fitting better than the Permuted Variable Length Markov Model (PVLMM); and OMiMa requires smaller training samples than the Maximum Entropy Model (MEM). Testing on both simulated and actual data (regulatory cis-elements and splice sites), we found OMiMa's performance superior to the other leading methods in terms of prediction accuracy, required size of training data or computational time. Our OMiMa system, to our knowledge, is the only motif finding tool that incorporates automatic selection of the best model. OMiMa is freely available at [1]. Conclusion Our optimized mixture of Markov models represents an alternative to the existing methods for modeling dependent structures within a biological motif. Our model is conceptually simple and effective, and can improve prediction accuracy and/or computational speed over other leading methods. PMID:16749929

Approximate approach for optimization space flights with a low thrust on the basis of sufficient optimality conditions

NASA Astrophysics Data System (ADS)

Salmin, Vadim V.

2017-01-01

Flight mechanics with a low-thrust is a new chapter of mechanics of space flight, considered plurality of all problems trajectory optimization and movement control laws and the design parameters of spacecraft. Thus tasks associated with taking into account the additional factors in mathematical models of the motion of spacecraft becomes increasingly important, as well as additional restrictions on the possibilities of the thrust vector control. The complication of the mathematical models of controlled motion leads to difficulties in solving optimization problems. Author proposed methods of finding approximate optimal control and evaluating their optimality based on analytical solutions. These methods are based on the principle of extending the class of admissible states and controls and sufficient conditions for the absolute minimum. Developed procedures of the estimation enabling to determine how close to the optimal founded solution, and indicate ways to improve them. Authors describes procedures of estimate for approximately optimal control laws for space flight mechanics problems, in particular for optimization flight low-thrust between the circular non-coplanar orbits, optimization the control angle and trajectory movement of the spacecraft during interorbital flights, optimization flights with low-thrust between arbitrary elliptical orbits Earth satellites.

Communication between nurses and physicians: strategies to surviving in the emergency department trenches.

PubMed

Abourbih, Daniel; Armstrong, Sherry; Nixon, Kirsty; Ackery, Alun D

2015-02-01

The emergency department (ED) is a challenging and stressful work environment where communication lapses can lead to negative health outcomes. This article offers strategies to Emergency Medicine residents, nurses and staff physicians on how to improve communication to optimize patient care. © 2014 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

An Efficient Approach to Improve the Usability of e-Learning Resources: The Role of Heuristic Evaluation

ERIC Educational Resources Information Center

Davids, Mogamat Razeen; Chikte, Usuf M. E.; Halperin, Mitchell L.

2013-01-01

Optimizing the usability of e-learning materials is necessary to maximize their potential educational impact, but this is often neglected when time and other resources are limited, leading to the release of materials that cannot deliver the desired learning outcomes. As clinician-teachers in a resource-constrained environment, we investigated…

Optimal Contrast: Competition between Two Referents Improves Word Learning

ERIC Educational Resources Information Center

Zosh, Jennifer M.; Brinster, Meredith; Halberda, Justin

2013-01-01

Does making an inference lead to better learning than being instructed directly? Two experiments evaluated preschoolers' ability to learn new words, comparing their memory for words learned via inference or instruction. On Inference trials, one familiar and one novel object was presented and children were asked to "Point at the [object name (i.e.,…

ZT Optimization: An Application Focus

PubMed Central

Tuley, Richard; Simpson, Kevin

2017-01-01

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

Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks.

PubMed

Dilkina, Bistra; Houtman, Rachel; Gomes, Carla P; Montgomery, Claire A; McKelvey, Kevin S; Kendall, Katherine; Graves, Tabitha A; Bernstein, Richard; Schwartz, Michael K

2017-02-01

Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs and by allowing derived corridors to more closely reflect conservation priorities. © 2016 Society for Conservation Biology.

Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks

USGS Publications Warehouse

Dilkina, Bistra; Houtman, Rachel; Gomes, Carla P.; Montgomery, Claire A.; McKelvey, Kevin; Kendall, Katherine; Graves, Tabitha A.; Bernstein, Richard; Schwartz, Michael K.

2017-01-01

Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs and by allowing derived corridors to more closely reflect conservation priorities.

Behavior-aware cache hierarchy optimization for low-power multi-core embedded systems

NASA Astrophysics Data System (ADS)

Zhao, Huatao; Luo, Xiao; Zhu, Chen; Watanabe, Takahiro; Zhu, Tianbo

2017-07-01

In modern embedded systems, the increasing number of cores requires efficient cache hierarchies to ensure data throughput, but such cache hierarchies are restricted by their tumid size and interference accesses which leads to both performance degradation and wasted energy. In this paper, we firstly propose a behavior-aware cache hierarchy (BACH) which can optimally allocate the multi-level cache resources to many cores and highly improved the efficiency of cache hierarchy, resulting in low energy consumption. The BACH takes full advantage of the explored application behaviors and runtime cache resource demands as the cache allocation bases, so that we can optimally configure the cache hierarchy to meet the runtime demand. The BACH was implemented on the GEM5 simulator. The experimental results show that energy consumption of a three-level cache hierarchy can be saved from 5.29% up to 27.94% compared with other key approaches while the performance of the multi-core system even has a slight improvement counting in hardware overhead.

Ranked set sampling: cost and optimal set size.

PubMed

Nahhas, Ramzi W; Wolfe, Douglas A; Chen, Haiying

2002-12-01

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.

Nuclear Electric Vehicle Optimization Toolset (NEVOT): Integrated System Design Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Tinker, Michael L.; Steincamp, James W.; Stewart, Eric T.; Patton, Bruce W.; Pannell, William P.; Newby, Ronald L.; Coffman, Mark E.; Qualls, A. L.; Bancroft, S.; Molvik, Greg

2003-01-01

The Nuclear Electric Vehicle Optimization Toolset (NEVOT) optimizes the design of all major Nuclear Electric Propulsion (NEP) vehicle subsystems for a defined mission within constraints and optimization parameters chosen by a user. The tool uses a Genetic Algorithm (GA) search technique to combine subsystem designs and evaluate the fitness of the integrated design to fulfill a mission. The fitness of an individual is used within the GA to determine its probability of survival through successive generations in which the designs with low fitness are eliminated and replaced with combinations or mutations of designs with higher fitness. The program can find optimal solutions for different sets of fitness metrics without modification and can create and evaluate vehicle designs that might never be conceived of through traditional design techniques. It is anticipated that the flexible optimization methodology will expand present knowledge of the design trade-offs inherent in designing nuclear powered space vehicles and lead to improved NEP designs.

Improving Societal Resilience Through Enhanced Reconnection Speed of Damaged Networks

NASA Astrophysics Data System (ADS)

Vodák, Rostislav; Bíl, Michal

2017-04-01

Road networks rank among the foundations of civilization. They enable people, services and goods to be transported to arbitrary places at any time. Its functioning can be impacted by various events, not only by natural hazards and their combinations. This can lead to the concurrent interruption of a number of roads and even cut-off parts of the network from vital services. The impact of these events can be reduced by various measures, but cannot be fully eliminated. We are aware of the fact that extreme events which result in road network break up will occur regardless of the ongoing process of hazard reduction using, for example, the improvement of the structural robustness of roads. The next problem is that many of the events are unpredictable and thus the needed costs of the improvement can easily spiral out of control. We therefore focus on the speed of the recovery process which can be optimized. This means that the time during which the damaged network is reconnected again will be as short as possible. The result of the optimization procedure is a sequence of road links which represent the routes of the repair units. The optimization process is, however, highly nontrivial because of the large number of possible routes for repair units. This prevents anyone from finding an optimal solution. We consequently introduce an approach based on the Ant Colony Optimization algorithm which is able to suggest an almost optimal solution under various constraints which can be established by the administrator of the network. We will also demonstrate its results and variability with several case examples.

Modeling and optimization aspects of radiation induced grafting of 4-vinylpyridene onto partially fluorinated films

NASA Astrophysics Data System (ADS)

Nasef, Mohamed Mahmoud; Ahmad Ali, Amgad; Saidi, Hamdani; Ahmad, Arshad

2014-01-01

Modeling and optimization aspects of radiation induced grafting (RIG) of 4-vinylpyridine (4-VP) onto partially fluorinated polymers such as poly(ethylene-co-tetrafluoroethene) (ETFE) and poly(vinylidene fluoride) (PVDF) films were comparatively investigated using response surface method (RSM). The effects of independent parameters: absorbed dose, monomer concentration, grafting time and reaction temperature on the response, grafting yield (GY) were correlated through two quadratic models. The results of this work confirm that RSM is a reliable tool not only for optimization of the reaction parameters and prediction of GY in RIG processes, but also for the reduction of the number of the experiments, monomer consumption and absorbed dose leading to an improvement of the overall reaction cost.

Adjuvant radiation therapy for pancreatic cancer: a review of the old and the new.

PubMed

Boyle, John; Czito, Brian; Willett, Christopher; Palta, Manisha

2015-08-01

Surgery represents the only potential curative treatment option for patients diagnosed with pancreatic adenocarcinoma. Despite aggressive surgical management for patients deemed to be resectable, rates of local recurrence and/or distant metastases remain high, resulting in poor long-term outcomes. In an effort to reduce recurrence rates and improve survival for patients having undergone resection, adjuvant therapies (ATs) including chemotherapy and chemoradiation therapy (CRT) have been explored. While adjuvant chemotherapy has been shown to consistently improve outcomes, the data regarding adjuvant radiation therapy (RT) is mixed. Although the ability of radiation to improve local control has been demonstrated, it has not always led to improved survival outcomes for patients. Early trials are flawed in their utilization of sub-optimal radiation techniques, limiting their generalizability. Recent and ongoing trials incorporate more optimized RT approaches and seek to clarify its role in treatment strategies. At the same time novel radiation techniques such as intensity modulated RT (IMRT) and stereotactic body RT (SBRT) are under active investigation. It is hoped that these efforts will lead to improved disease-related outcomes while reducing toxicity rates.

Adjuvant radiation therapy for pancreatic cancer: a review of the old and the new

PubMed Central

Boyle, John; Czito, Brian; Willett, Christopher

2015-01-01

Surgery represents the only potential curative treatment option for patients diagnosed with pancreatic adenocarcinoma. Despite aggressive surgical management for patients deemed to be resectable, rates of local recurrence and/or distant metastases remain high, resulting in poor long-term outcomes. In an effort to reduce recurrence rates and improve survival for patients having undergone resection, adjuvant therapies (ATs) including chemotherapy and chemoradiation therapy (CRT) have been explored. While adjuvant chemotherapy has been shown to consistently improve outcomes, the data regarding adjuvant radiation therapy (RT) is mixed. Although the ability of radiation to improve local control has been demonstrated, it has not always led to improved survival outcomes for patients. Early trials are flawed in their utilization of sub-optimal radiation techniques, limiting their generalizability. Recent and ongoing trials incorporate more optimized RT approaches and seek to clarify its role in treatment strategies. At the same time novel radiation techniques such as intensity modulated RT (IMRT) and stereotactic body RT (SBRT) are under active investigation. It is hoped that these efforts will lead to improved disease-related outcomes while reducing toxicity rates. PMID:26261730

Protein homology model refinement by large-scale energy optimization.

PubMed

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

Non-Markovian optimal sideband cooling

NASA Astrophysics Data System (ADS)

Triana, Johan F.; Pachon, Leonardo A.

2018-04-01

Optimal control theory is applied to sideband cooling of nano-mechanical resonators. The formulation described here makes use of exact results derived by means of the path-integral approach of quantum dynamics, so that no approximation is invoked. It is demonstrated that the intricate interplay between time-dependent fields and structured thermal bath may lead to improve results of the sideband cooling by an order of magnitude. Cooling is quantified by means of the mean number of phonons of the mechanical modes as well as by the von Neumann entropy. Potencial extension to non-linear systems, by means of semiclassical methods, is briefly discussed.

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.

Analysis of neighborhood behavior in lead optimization and array design.

PubMed

Papadatos, George; Cooper, Anthony W J; Kadirkamanathan, Visakan; Macdonald, Simon J F; McLay, Iain M; Pickett, Stephen D; Pritchard, John M; Willett, Peter; Gillet, Valerie J

2009-02-01

Neighborhood behavior describes the extent to which small structural changes defined by a molecular descriptor are likely to lead to small property changes. This study evaluates two methods for the quantification of neighborhood behavior: the optimal diagonal method of Patterson et al. and the optimality criterion method of Horvath and Jeandenans. The methods are evaluated using twelve different types of fingerprint (both 2D and 3D) with screening data derived from several lead optimization projects at GlaxoSmithKline. The principal focus of the work is the design of chemical arrays during lead optimization, and the study hence considers not only biological activity but also important drug properties such as metabolic stability, permeability, and lipophilicity. Evidence is provided to suggest that the optimality criterion method may provide a better quantitative description of neighborhood behavior than the optimal diagonal method.

Optimizing Requirements Decisions with KEYS

NASA Technical Reports Server (NTRS)

Jalali, Omid; Menzies, Tim; Feather, Martin

2008-01-01

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

Innovating for quality and value: Utilizing national quality improvement programs to identify opportunities for responsible surgical innovation.

PubMed

Woo, Russell K; Skarsgard, Erik D

2015-06-01

Innovation in surgical techniques, technology, and care processes are essential for improving the care and outcomes of surgical patients, including children. The time and cost associated with surgical innovation can be significant, and unless it leads to improvements in outcome at equivalent or lower costs, it adds little or no value from the perspective of the patients, and decreases the overall resources available to our already financially constrained healthcare system. The emergence of a safety and quality mandate in surgery, and the development of the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) allow needs-based surgical care innovation which leads to value-based improvement in care. In addition to general and procedure-specific clinical outcomes, surgeons should consider the measurement of quality from the patients' perspective. To this end, the integration of validated Patient Reported Outcome Measures (PROMs) into actionable, benchmarked institutional outcomes reporting has the potential to facilitate quality improvement in process, treatment and technology that optimizes value for our patients and health system. Copyright © 2015 Elsevier Inc. All rights reserved.

Iterative Refinement of a Binding Pocket Model: Active Computational Steering of Lead Optimization

PubMed Central

2012-01-01

Computational approaches for binding affinity prediction are most frequently demonstrated through cross-validation within a series of molecules or through performance shown on a blinded test set. Here, we show how such a system performs in an iterative, temporal lead optimization exercise. A series of gyrase inhibitors with known synthetic order formed the set of molecules that could be selected for “synthesis.” Beginning with a small number of molecules, based only on structures and activities, a model was constructed. Compound selection was done computationally, each time making five selections based on confident predictions of high activity and five selections based on a quantitative measure of three-dimensional structural novelty. Compound selection was followed by model refinement using the new data. Iterative computational candidate selection produced rapid improvements in selected compound activity, and incorporation of explicitly novel compounds uncovered much more diverse active inhibitors than strategies lacking active novelty selection. PMID:23046104

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

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

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

2015-05-01

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

Optimal design study of high efficiency indium phosphide space solar cells

NASA Technical Reports Server (NTRS)

Jain, Raj K.; Flood, Dennis J.

1990-01-01

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

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

PubMed

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

2015-05-01

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

Finite-difference simulation and visualization of elastodynamics in time-evolving generalized curvilinear coordinates

NASA Technical Reports Server (NTRS)

Kaul, Upender K. (Inventor)

2009-01-01

Modeling and simulation of free and forced structural vibrations is essential to an overall structural health monitoring capability. In the various embodiments, a first principles finite-difference approach is adopted in modeling a structural subsystem such as a mechanical gear by solving elastodynamic equations in generalized curvilinear coordinates. Such a capability to generate a dynamic structural response is widely applicable in a variety of structural health monitoring systems. This capability (1) will lead to an understanding of the dynamic behavior of a structural system and hence its improved design, (2) will generate a sufficiently large space of normal and damage solutions that can be used by machine learning algorithms to detect anomalous system behavior and achieve a system design optimization and (3) will lead to an optimal sensor placement strategy, based on the identification of local stress maxima all over the domain.

Case study: technology initiative led to advanced lead optimization screening processes at Bristol-Myers Squibb, 2004-2009.

PubMed

Zhang, Litao; Cvijic, Mary Ellen; Lippy, Jonathan; Myslik, James; Brenner, Stephen L; Binnie, Alastair; Houston, John G

2012-07-01

In this paper, we review the key solutions that enabled evolution of the lead optimization screening support process at Bristol-Myers Squibb (BMS) between 2004 and 2009. During this time, technology infrastructure investment and scientific expertise integration laid the foundations to build and tailor lead optimization screening support models across all therapeutic groups at BMS. Together, harnessing advanced screening technology platforms and expanding panel screening strategy led to a paradigm shift at BMS in supporting lead optimization screening capability. Parallel SAR and structure liability relationship (SLR) screening approaches were first and broadly introduced to empower more-rapid and -informed decisions about chemical synthesis strategy and to broaden options for identifying high-quality drug candidates during lead optimization. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-12-01

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

A Program to Improve the Triangulated Surface Mesh Quality Along Aircraft Component Intersections

NASA Technical Reports Server (NTRS)

Cliff, Susan E.

2005-01-01

A computer program has been developed for improving the quality of unstructured triangulated surface meshes in the vicinity of component intersections. The method relies solely on point removal and edge swapping for improving the triangulations. It can be applied to any lifting surface component such as a wing, canard or horizontal tail component intersected with a fuselage, or it can be applied to a pylon that is intersected with a wing, fuselage or nacelle. The lifting surfaces or pylon are assumed to be aligned in the axial direction with closed trailing edges. The method currently maintains salient edges only at leading and trailing edges of the wing or pylon component. This method should work well for any shape of fuselage that is free of salient edges at the intersection. The method has been successfully demonstrated on a total of 125 different test cases that include both blunt and sharp wing leading edges. The code is targeted for use in the automated environment of numerical optimization where geometric perturbations to individual components can be critical to the aerodynamic performance of a vehicle. Histograms of triangle aspect ratios are reported to assess the quality of the triangles attached to the intersection curves before and after application of the program. Large improvements to the quality of the triangulations were obtained for the 125 test cases; the quality was sufficient for use with an automated tetrahedral mesh generation program that is used as part of an aerodynamic shape optimization method.

Application of controller partitioning optimization procedure to integrated flight/propulsion control design for a STOVL aircraft

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Schmidt, Phillip H.

1993-01-01

A parameter optimization framework has earlier been developed to solve the problem of partitioning a centralized controller into a decentralized, hierarchical structure suitable for integrated flight/propulsion control implementation. This paper presents results from the application of the controller partitioning optimization procedure to IFPC design for a Short Take-Off and Vertical Landing (STOVL) aircraft in transition flight. The controller partitioning problem and the parameter optimization algorithm are briefly described. Insight is provided into choosing various 'user' selected parameters in the optimization cost function such that the resulting optimized subcontrollers will meet the characteristics of the centralized controller that are crucial to achieving the desired closed-loop performance and robustness, while maintaining the desired subcontroller structure constraints that are crucial for IFPC implementation. The optimization procedure is shown to improve upon the initial partitioned subcontrollers and lead to performance comparable to that achieved with the centralized controller. This application also provides insight into the issues that should be addressed at the centralized control design level in order to obtain implementable partitioned subcontrollers.

An Examination of the Professional Development of Experienced Principals and Aspiring Principals in Long Island, New York Public Schools

ERIC Educational Resources Information Center

Bullock, Gay

2012-01-01

Principals are being asked to create optimal learning conditions that will "lead to improved results for students, long-term gains in school system capacity, and increased productivity and effectiveness" (RTTT, 2009). The purpose of this study was to examine the professional development offered to and sought by experienced principals and…

Computer-Aided Lead Optimization: Improved Small-Molecule Inhibitor of the Zinc Endopeptidase of Botulinum Neurotoxin Serotype A

DTIC Science & Technology

2007-08-01

doi:10.1371/journal.pone.0000761.s004 (1.33 MB TIF) ACKNOWLEDGMENTS The authors thank Steve Whiting and Seth Swaii for their assistance in preparing...clinical and epidemiologic review. Ann Intern Med 129: 221–228. 2. Kessler KR, Benecke R (1997) Botulinum toxin—from poison to remedy. Neurotoxicology 18

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

PubMed

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

2012-04-24

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

Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

NASA Astrophysics Data System (ADS)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright

From Maximization to Optimization: A Paradigm Shift in Rice Production in Thailand to Improve Overall Quality of Life of Stakeholders

PubMed Central

Doi, Ryoichi; Pitiwut, Supachai

2014-01-01

The concept of crop yield maximization has been widely supported. In practice, however, yield maximization does not necessarily lead to maximum socioeconomic welfare. Optimization is therefore necessary to ensure quality of life of farmers and other stakeholders. In Thailand, a rice farmers' network has adopted a promising agricultural system aimed at the optimization of rice farming. Various feasible techniques were flexibly combined. The new system offers technical strengths and minimizes certain difficulties with which the rice farmers once struggled. It has resulted in fairly good yields of up to 8.75 t ha−1 or yield increases of up to 57% (from 4.38 to 6.88 t ha−1). Under the optimization paradigm, the farmers have established diversified sustainable relationships with the paddy fields in terms of ecosystem management through their own self-motivated scientific observations. The system has resulted in good health conditions for the farmers and villagers, financial security, availability of extra time, and additional opportunities and freedom and hence in the improvement of their overall quality of life. The underlying technical and social mechanisms are discussed herein. PMID:25089294

On combining multi-normalization and ancillary measures for the optimal score level fusion of fingerprint and voice biometrics

NASA Astrophysics Data System (ADS)

Mohammed Anzar, Sharafudeen Thaha; Sathidevi, Puthumangalathu Savithri

2014-12-01

In this paper, we have considered the utility of multi-normalization and ancillary measures, for the optimal score level fusion of fingerprint and voice biometrics. An efficient matching score preprocessing technique based on multi-normalization is employed for improving the performance of the multimodal system, under various noise conditions. Ancillary measures derived from the feature space and the score space are used in addition to the matching score vectors, for weighing the modalities, based on their relative degradation. Reliability (dispersion) and the separability (inter-/intra-class distance and d-prime statistics) measures under various noise conditions are estimated from the individual modalities, during the training/validation stage. The `best integration weights' are then computed by algebraically combining these measures using the weighted sum rule. The computed integration weights are then optimized against the recognition accuracy using techniques such as grid search, genetic algorithm and particle swarm optimization. The experimental results show that, the proposed biometric solution leads to considerable improvement in the recognition performance even under low signal-to-noise ratio (SNR) conditions and reduces the false acceptance rate (FAR) and false rejection rate (FRR), making the system useful for security as well as forensic applications.

The economics of optimal urban groundwater management in southwestern USA

NASA Astrophysics Data System (ADS)

Hansen, Jason K.

2012-08-01

Groundwater serves as the primary water source for approximately 80% of public water systems in the United States, and for many more as a secondary source. Traditionally management relies on groundwater to meet rising demand by increasing supply, but climate uncertainty and population growth require more judicious management to achieve efficiency and sustainability. Over-pumping leads to groundwater overdraft and jeopardizes the ability of future users to depend on the resource. Optimal urban groundwater pumping can play a role in solving this conundrum. This paper investigates to what extent and under what circumstances controlled pumping improves social welfare. It considers management in a hydro-economic framework and finds the optimal pumping path and the optimal price path. These allow for the identification of the social benefit of controlled pumping, and the scarcity rent, which is one tool to sustainably manage groundwater resources. The model is numerically illustrated with a case study from Albuquerque, New Mexico (USA). The Albuquerque results indicate that, in the presence of strong demand growth, controlled pumping improves social welfare by 22%, extends use of the resource, and provides planners with a mechanism to advance the economic sustainability of groundwater.

Continuous Adaptive Population Reduction (CAPR) for Differential Evolution Optimization.

PubMed

Wong, Ieong; Liu, Wenjia; Ho, Chih-Ming; Ding, Xianting

2017-06-01

Differential evolution (DE) has been applied extensively in drug combination optimization studies in the past decade. It allows for identification of desired drug combinations with minimal experimental effort. This article proposes an adaptive population-sizing method for the DE algorithm. Our new method presents improvements in terms of efficiency and convergence over the original DE algorithm and constant stepwise population reduction-based DE algorithm, which would lead to a reduced number of cells and animals required to identify an optimal drug combination. The method continuously adjusts the reduction of the population size in accordance with the stage of the optimization process. Our adaptive scheme limits the population reduction to occur only at the exploitation stage. We believe that continuously adjusting for a more effective population size during the evolutionary process is the major reason for the significant improvement in the convergence speed of the DE algorithm. The performance of the method is evaluated through a set of unimodal and multimodal benchmark functions. In combining with self-adaptive schemes for mutation and crossover constants, this adaptive population reduction method can help shed light on the future direction of a completely parameter tune-free self-adaptive DE algorithm.

Conservative strategy-based ensemble surrogate model for optimal groundwater remediation design at DNAPLs-contaminated sites

NASA Astrophysics Data System (ADS)

Ouyang, Qi; Lu, Wenxi; Lin, Jin; Deng, Wenbing; Cheng, Weiguo

2017-08-01

The surrogate-based simulation-optimization techniques are frequently used for optimal groundwater remediation design. When this technique is used, surrogate errors caused by surrogate-modeling uncertainty may lead to generation of infeasible designs. In this paper, a conservative strategy that pushes the optimal design into the feasible region was used to address surrogate-modeling uncertainty. In addition, chance-constrained programming (CCP) was adopted to compare with the conservative strategy in addressing this uncertainty. Three methods, multi-gene genetic programming (MGGP), Kriging (KRG) and support vector regression (SVR), were used to construct surrogate models for a time-consuming multi-phase flow model. To improve the performance of the surrogate model, ensemble surrogates were constructed based on combinations of different stand-alone surrogate models. The results show that: (1) the surrogate-modeling uncertainty was successfully addressed by the conservative strategy, which means that this method is promising for addressing surrogate-modeling uncertainty. (2) The ensemble surrogate model that combines MGGP with KRG showed the most favorable performance, which indicates that this ensemble surrogate can utilize both stand-alone surrogate models to improve the performance of the surrogate model.

An improved real time image detection system for elephant intrusion along the forest border areas.

PubMed

Sugumar, S J; Jayaparvathy, R

2014-01-01

Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Nomenclature and guideline to express the amount of a membrane protein synthesized in animal cells in view of bioprocess optimization and production monitoring.

PubMed

Augusto, Elisabeth F P; Moraes, Angela M; Piccoli, Rosane A M; Barral, Manuel F; Suazo, Cláudio A T; Tonso, Aldo; Pereira, Carlos A

2010-01-01

Studies of a bioprocess optimization and monitoring for protein synthesis in animal cells face a challenge on how to express in quantitative terms the system performance. It is possible to have a panel of calculated variables that fits more or less appropriately the intended goal. Each mathematical expression approach translates different quantitative aspects. We can basically separate them into two categories: those used for the evaluation of cell physiology in terms of product synthesis, which can be for bioprocess improvement or optimization, and those used for production unit sizing and for bioprocess operation. With these perspectives and based on our own data of kinetic S2 cells growth and metabolism, as well as on their synthesis of the transmembrane recombinant rabies virus glycoprotein, here indicated as P, we show and discuss the main characteristics of calculated variables and their recommended use. Mainly applied to a bioprocess improvement/optimization and that mainly used for operation definition and to design the production unit, we expect these definitions/recommendations would improve the quality of data produced in this field and lead to more standardized procedures. In turn, it would allow a better and easier comprehension of scientific and technological communications for specialized readers. Copyright 2009 The International Association for Biologicals. Published by Elsevier Ltd. All rights reserved.

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

Marquez, Andres; Manzano Franco, Joseph B.; Song, Shuaiwen

With Exascale performance and its challenges in mind, one ubiquitous concern among architects is energy efficiency. Petascale systems projected to Exascale systems are unsustainable at current power consumption rates. One major contributor to system-wide power consumption is the number of memory operations leading to data movement and management techniques applied by the runtime system. To address this problem, we present the concept of the Architected Composite Data Types (ACDT) framework. The framework is made aware of data composites, assigning them a specific layout, transformations and operators. Data manipulation overhead is amortized over a larger number of elements and program performancemore » and power efficiency can be significantly improved. We developed the fundamentals of an ACDT framework on a massively multithreaded adaptive runtime system geared towards Exascale clusters. Showcasing the capability of ACDT, we exercised the framework with two representative processing kernels - Matrix Vector Multiply and the Cholesky Decomposition – applied to sparse matrices. As transformation modules, we applied optimized compress/decompress engines and configured invariant operators for maximum energy/performance efficiency. Additionally, we explored two different approaches based on transformation opaqueness in relation to the application. Under the first approach, the application is agnostic to compression and decompression activity. Such approach entails minimal changes to the original application code, but leaves out potential applicationspecific optimizations. The second approach exposes the decompression process to the application, hereby exposing optimization opportunities that can only be exploited with application knowledge. The experimental results show that the two approaches have their strengths in HW and SW respectively, where the SW approach can yield performance and power improvements that are an order of magnitude better than ACDT-oblivious, hand-optimized implementations.We consider the ACDT runtime framework an important component of compute nodes that will lead towards power efficient Exascale clusters.« less

Genome-scale biological models for industrial microbial systems.

PubMed

Xu, Nan; Ye, Chao; Liu, Liming

2018-04-01

The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

Supercritical tests of a self-optimizing, variable-Camber wind tunnel model

NASA Technical Reports Server (NTRS)

Levinsky, E. S.; Palko, R. L.

1979-01-01

A testing procedure was used in a 16-foot Transonic Propulsion Wind Tunnel which leads to optimum wing airfoil sections without stopping the tunnel for model changes. Being experimental, the optimum shapes obtained incorporate various three-dimensional and nonlinear viscous and transonic effects not included in analytical optimization methods. The method is a closed-loop, computer-controlled, interactive procedure and employs a Self-Optimizing Flexible Technology wing semispan model that conformally adapts the airfoil section at two spanwise control stations to maximize or minimize various prescribed merit functions subject to both equality and inequality constraints. The model, which employed twelve independent hydraulic actuator systems and flexible skins, was also used for conventional testing. Although six of seven optimizations attempted were at least partially convergent, further improvements in model skin smoothness and hydraulic reliability are required to make the technique fully operational.

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

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

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

Co-Optimization of Internal Combustion Engines and Biofuels

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

McCormick, Robert L.

2016-03-08

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

Spatio-temporal modeling and optimization of a deformable-grating compressor for short high-energy laser pulses

DOE PAGES

Qiao, Jie; Papa, J.; Liu, X.

2015-09-24

Monolithic large-scale diffraction gratings are desired to improve the performance of high-energy laser systems and scale them to higher energy, but the surface deformation of these diffraction gratings induce spatio-temporal coupling that is detrimental to the focusability and compressibility of the output pulse. A new deformable-grating-based pulse compressor architecture with optimized actuator positions has been designed to correct the spatial and temporal aberrations induced by grating wavefront errors. An integrated optical model has been built to analyze the effect of grating wavefront errors on the spatio-temporal performance of a compressor based on four deformable gratings. Moreover, a 1.5-meter deformable gratingmore » has been optimized using an integrated finite-element-analysis and genetic-optimization model, leading to spatio-temporal performance similar to the baseline design with ideal gratings.« less

3D sensor placement strategy using the full-range pheromone ant colony system

NASA Astrophysics Data System (ADS)

Shuo, Feng; Jingqing, Jia

2016-07-01

An optimized sensor placement strategy will be extremely beneficial to ensure the safety and cost reduction considerations of structural health monitoring (SHM) systems. The sensors must be placed such that important dynamic information is obtained and the number of sensors is minimized. The practice is to select individual sensor directions by several 1D sensor methods and the triaxial sensors are placed in these directions for monitoring. However, this may lead to non-optimal placement of many triaxial sensors. In this paper, a new method, called FRPACS, is proposed based on the ant colony system (ACS) to solve the optimal placement of triaxial sensors. The triaxial sensors are placed as single units in an optimal fashion. And then the new method is compared with other algorithms using Dalian North Bridge. The computational precision and iteration efficiency of the FRPACS has been greatly improved compared with the original ACS and EFI method.

Application of da Vinci(®) Robot in simple or radical hysterectomy: Tips and tricks.

PubMed

Iavazzo, Christos; Gkegkes, Ioannis D

2016-01-01

The first robotic simple hysterectomy was performed more than 10 years ago. These days, robotic-assisted hysterectomy is accepted as an alternative surgical approach and is applied both in benign and malignant surgical entities. The two important points that should be taken into account to optimize postoperative outcomes in the early period of a surgeon's training are how to achieve optimal oncological and functional results. Overcoming any technical challenge, as with any innovative surgical method, leads to an improved surgical operation timewise as well as for patients' safety. The standardization of the technique and recognition of critical anatomical landmarks are essential for optimal oncological and clinical outcomes on both simple and radical robotic-assisted hysterectomy. Based on our experience, our intention is to present user-friendly tips and tricks to optimize the application of a da Vinci® robot in simple or radical hysterectomies.

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

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

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

Improved power control using optimal adjustable coefficients for three-phase photovoltaic inverter under unbalanced grid voltage.

PubMed

Wang, Qianggang; Zhou, Niancheng; Lou, Xiaoxuan; Chen, Xu

2014-01-01

Unbalanced grid faults will lead to several drawbacks in the output power quality of photovoltaic generation (PV) converters, such as power fluctuation, current amplitude swell, and a large quantity of harmonics. The aim of this paper is to propose a flexible AC current generation method by selecting coefficients to overcome these problems in an optimal way. Three coefficients are brought in to tune the output current reference within the required limits of the power quality (the current harmonic distortion, the AC current peak, the power fluctuation, and the DC voltage fluctuation). Through the optimization algorithm, the coefficients can be determined aiming to generate the minimum integrated amplitudes of the active and reactive power references with the constraints of the inverter current and DC voltage fluctuation. Dead-beat controller is utilized to track the optimal current reference in a short period. The method has been verified in PSCAD/EMTDC software.

Improved Power Control Using Optimal Adjustable Coefficients for Three-Phase Photovoltaic Inverter under Unbalanced Grid Voltage

PubMed Central

Wang, Qianggang; Zhou, Niancheng; Lou, Xiaoxuan; Chen, Xu

2014-01-01

Unbalanced grid faults will lead to several drawbacks in the output power quality of photovoltaic generation (PV) converters, such as power fluctuation, current amplitude swell, and a large quantity of harmonics. The aim of this paper is to propose a flexible AC current generation method by selecting coefficients to overcome these problems in an optimal way. Three coefficients are brought in to tune the output current reference within the required limits of the power quality (the current harmonic distortion, the AC current peak, the power fluctuation, and the DC voltage fluctuation). Through the optimization algorithm, the coefficients can be determined aiming to generate the minimum integrated amplitudes of the active and reactive power references with the constraints of the inverter current and DC voltage fluctuation. Dead-beat controller is utilized to track the optimal current reference in a short period. The method has been verified in PSCAD/EMTDC software. PMID:25243215

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

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

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

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

PubMed

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

2011-01-01

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

Improving the machinability of leaded free cutting steel through process optimization

NASA Astrophysics Data System (ADS)

Sathyamurthy, P.; Vetrivelmurugan, R.; Sooryaprakash, J.

2018-02-01

Free cutting steel grades are high sulphur grades which can be classified under two categories as Leaded and Non-Leaded. These grades are used for manufacturing components like Nuts, bolts, studs, hydraulic fittings, brake pistons where higher machining is required to get intricate shape. Machinability of these grades are affected by hard oxide inclusions and highly deformed manganese sulphide inclusions. At JSW, machinability of leaded free cutting steel is improved by various process modifications namely deoxidation through carbon and manganese, Tellurium (Rare earth element) addition and maintaining the oxygen level at 80- 120ppm. Former one avoids the formation of hard SiO2 and Al2O3 compounds, Tellurium addition forms PbTe compound at the tail of MnS inclusions which resists the deformation of MnS inclusions and increased oxygen level favours the formation of less deformable oxy- sulphide inclusions. Above process modifications have resulted in achieving the low silicate content, better aspect ratio of MnS inclusions in the final rolled product. They are assessed by the characteristics of chip formation and surface roughness of machined part.

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

PubMed Central

Chatterjee, Arnab K; Yeung, Bryan KS

2012-01-01

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

Magnetostrictive materials and method for improving AC characteristics in same

DOEpatents

Pulvirenti, Patricia P.; Jiles, David C.

2001-08-14

The present invention provides Terfenol-D alloys ("doped" Terfenol) having optimized performances under the condition of time-dependent magnetic fields. In one embodiment, performance is optimized by lowering the conductivity of Terfenol, thereby improving the frequency response. This can be achieved through addition of Group III or IV elements, such as Si and Al. Addition of these types of elements provides scattering sites for conduction electrons, thereby increasing resistivity by 125% which leads to an average increase in penetration depth of 80% at 1 kHz and an increase in energy conversion efficiency of 55%. The permeability of doped Terfenol remains constant over a wider frequency range as compared with undoped Terfenol. These results demonstrate that adding impurities, such as Si and Al, are effective in improving the ac characteristics of Terfenol. A magnetoelastic Gruneisen parameter, .gamma..sub.me, has also been derived from the thermodynamic equations of state, and provides another means by which to characterize the coupling efficiency in magnetostrictive materials on a more fundamental basis.

Continuum topology optimization considering uncertainties in load locations based on the cloud model

NASA Astrophysics Data System (ADS)

Liu, Jie; Wen, Guilin

2018-06-01

Few researchers have paid attention to designing structures in consideration of uncertainties in the loading locations, which may significantly influence the structural performance. In this work, cloud models are employed to depict the uncertainties in the loading locations. A robust algorithm is developed in the context of minimizing the expectation of the structural compliance, while conforming to a material volume constraint. To guarantee optimal solutions, sufficient cloud drops are used, which in turn leads to low efficiency. An innovative strategy is then implemented to enormously improve the computational efficiency. A modified soft-kill bi-directional evolutionary structural optimization method using derived sensitivity numbers is used to output the robust novel configurations. Several numerical examples are presented to demonstrate the effectiveness and efficiency of the proposed algorithm.

A multi-group firefly algorithm for numerical optimization

NASA Astrophysics Data System (ADS)

Tong, Nan; Fu, Qiang; Zhong, Caiming; Wang, Pengjun

2017-08-01

To solve the problem of premature convergence of firefly algorithm (FA), this paper analyzes the evolution mechanism of the algorithm, and proposes an improved Firefly algorithm based on modified evolution model and multi-group learning mechanism (IMGFA). A Firefly colony is divided into several subgroups with different model parameters. Within each subgroup, the optimal firefly is responsible for leading the others fireflies to implement the early global evolution, and establish the information mutual system among the fireflies. And then, each firefly achieves local search by following the brighter firefly in its neighbors. At the same time, learning mechanism among the best fireflies in various subgroups to exchange information can help the population to obtain global optimization goals more effectively. Experimental results verify the effectiveness of the proposed algorithm.

Radiation shielding evaluation of the BNCT treatment room at THOR: a TORT-coupled MCNP Monte Carlo simulation study.

PubMed

Chen, A Y; Liu, Y-W H; Sheu, R J

2008-01-01

This study investigates the radiation shielding design of the treatment room for boron neutron capture therapy at Tsing Hua Open-pool Reactor using "TORT-coupled MCNP" method. With this method, the computational efficiency is improved significantly by two to three orders of magnitude compared to the analog Monte Carlo MCNP calculation. This makes the calculation feasible using a single CPU in less than 1 day. Further optimization of the photon weight windows leads to additional 50-75% improvement in the overall computational efficiency.

Improved Weather and Power Forecasts for Energy Operations - the German Research Project EWeLiNE

NASA Astrophysics Data System (ADS)

Lundgren, Kristina; Siefert, Malte; Hagedorn, Renate; Majewski, Detlev

2014-05-01

The German energy system is going through a fundamental change. Based on the energy plans of the German federal government, the share of electrical power production from renewables should increase to 35% by 2020. This means that, in the near future at certain times renewable energies will provide a major part of Germany's power production. Operating a power supply system with a large share of weather-dependent power sources in a secure way requires improved power forecasts. One of the most promising strategies to improve the existing wind power and PV power forecasts is to optimize the underlying weather forecasts and to enhance the collaboration between the meteorology and energy sectors. Deutscher Wetterdienst addresses these challenges in collaboration with Fraunhofer IWES within the research project EWeLiNE. The overarching goal of the project is to improve the wind and PV power forecasts by combining improved power forecast models and optimized weather forecasts. During the project, the numerical weather prediction models COSMO-DE and COSMO-DE-EPS (Ensemble Prediction System) by Deutscher Wetterdienst will be generally optimized towards improved wind power and PV forecasts. For instance, it will be investigated whether the assimilation of new types of data, e.g. power production data, can lead to improved weather forecasts. With regard to the probabilistic forecasts, the focus is on the generation of ensembles and ensemble calibration. One important aspect of the project is to integrate the probabilistic information into decision making processes by developing user-specified products. In this paper we give an overview of the project and present first results.

Improving stability and strength characteristics of framed structures with nonlinear behavior

NASA Technical Reports Server (NTRS)

Pezeshk, Shahram

1990-01-01

In this paper an optimal design procedure is introduced to improve the overall performance of nonlinear framed structures. The design methodology presented here is a multiple-objective optimization procedure whose objective functions involve the buckling eigenvalues and eigenvectors of the structure. A constant volume with bounds on the design variables is used in conjunction with an optimality criterion approach. The method provides a general tool for solving complex design problems and generally leads to structures with better limit strength and stability. Many algorithms have been developed to improve the limit strength of structures. In most applications geometrically linear analysis is employed with the consequence that overall strength of the design is overestimated. Directly optimizing the limit load of the structure would require a full nonlinear analysis at each iteration which would be prohibitively expensive. The objective of this paper is to develop an algorithm that can improve the limit-load of geometrically nonlinear framed structures while avoiding the nonlinear analysis. One of the novelties of the new design methodology is its ability to efficiently model and design structures under multiple loading conditions. These loading conditions can be different factored loads or any kind of loads that can be applied to the structure simultaneously or independently. Attention is focused on optimal design of space framed structures. Three-dimensional design problems are more complicated to carry out, but they yield insight into real behavior of the structure and can help avoiding some of the problems that might appear in planar design procedure such as the need for out-of-plane buckling constraint. Although researchers in the field of structural engineering generally agree that optimum design of three-dimension building frames especially in the seismic regions would be beneficial, methods have been slow to emerge. Most of the research in this area has dealt with the optimization of truss and plane frame structures.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks.

PubMed

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-04-19

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs. However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks

PubMed Central

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-01-01

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs). However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%. PMID:28422062

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

PubMed

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

2017-01-01

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

Enhanced performance of Zn(II)-doped lead-acid batteries with electrochemical active carbon in negative mass

NASA Astrophysics Data System (ADS)

Xiang, Jiayuan; Hu, Chen; Chen, Liying; Zhang, Dong; Ding, Ping; Chen, Dong; Liu, Hao; Chen, Jian; Wu, Xianzhang; Lai, Xiaokang

2016-10-01

The effect and mechanism of Zn(II) on improving the performances of lead-acid cell with electrochemical active carbon (EAC) in negative mass is investigated. The hydrogen evolution of the cell is significantly reduced due to the deposition of Zn on carbon surface and the increased porosity of negative mass. Zn(II) additives can also improve the low-temperature and high-rate capacities of the cell with EAC in negative mass, which ascribes to the formation of Zn on lead and carbon surface that constructs a conductive bridge among the active mass. Under the co-contribution of EAC and Zn(II), the partial-state-of-charge cycle life is greatly prolonged. EAC optimizes the NAM structure and porosity to enhance the charge acceptance and retard the lead sulfate accumulation. Zn(II) additive reduces the hydrogen evolution during charge process and improves the electric conductivity of the negative electrode. The cell with 0.6 wt% EAC and 0.006 wt% ZnO in negative mass exhibits 90% reversible capacity of the initial capacity after 2100 cycles. In contrast, the cell with 0.6 wt% EAC exhibits 84% reversible capacity after 2100 cycles and the control cell with no EAC and Zn(II) exhibits less than 80% reversible capacity after 1350 cycles.

Left ventricular assist device management in patients chronically supported for advanced heart failure.

PubMed

Cowger, Jennifer; Romano, Matthew A; Stulak, John; Pagani, Francis D; Aaronson, Keith D

2011-03-01

This review summarizes management strategies to reduce morbidity and mortality in heart failure patients supported chronically with implantable left ventricular assist devices (LVADs). As the population of patients supported with long-term LVADs has grown, patient selection, operative technique, and patient management strategies have been refined, leading to improved outcomes. This review summarizes recent findings on LVAD candidate selection, and discusses outpatient strategies to optimize device performance and heart failure management. It also reviews important device complications that warrant close outpatient monitoring. Managing patients on chronic LVAD support requires regular patient follow-up, multidisciplinary care teams, and frequent laboratory and echocardiographic surveillance to ensure optimal outcomes.

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

PubMed

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

2012-12-15

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

Engineering an Antibiotic to Fight Cancer: Optimization of the Novobiocin Scaffold to Produce Anti-Proliferative Agents

PubMed Central

Zhao, Huiping; Donnelly, Alison C.; Kusuma, Bhaskar R.; Brandt, Gary E. L.; Brown, Douglas; Rajewski, Roger A.; Vielhauer, George; Holzbeierlein, Jeffrey; Cohen, Mark S.; Blagg, Brian S. J.

2011-01-01

Development of the DNA gyrase inhibitor, novobiocin, into a selective Hsp90 inhibitor was accomplished through structural modifications to the amide side chain, coumarin ring, and sugar moiety. These species exhibit ~700-fold improved anti-proliferative activity versus the natural product as evaluated by cellular efficacies against breast, colon, prostate, lung, and other cancer cell lines. Utilization of structure–activity relationships established for three novobiocin synthons produced optimized scaffolds, which manifest mid-nanomolar activity against a panel of cancer cell lines and serve as lead compounds that manifest their activities through Hsp90 inhibition. PMID:21553822

High-Energy QCD Asymptotics of Photon-Photon Collisions

NASA Astrophysics Data System (ADS)

Brodsky, S. J.; Fadin, V. S.; Kim, V. T.; Lipatov, L. N.; Pivovarov, G. B.

2002-07-01

The high-energy behaviour of the total cross section for highly virtual photons, as predicted by the BFKL equation at next-to-leading order (NLO) in QCD, is discussed. The NLO BFKL predictions, improved by the BLM optimal scale setting, are in good agreement with recent OPAL and L3 data at CERN LEP2. NLO BFKL predictions for future linear colliders are presented.

Optimization of orally bioavailable alkyl amine renin inhibitors

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

Xu, Zhenrong; Cacatian, Salvacion; Yuan, Jing

2010-09-17

Structure-guided drug design led to new alkylamine renin inhibitors with improved in vitro and in vivo potency. Lead compound 21a, has an IC{sub 50} of 0.83 nM for the inhibition of human renin in plasma (PRA). Oral administration of 21a at 10 mg/kg resulted in >20 h reduction of blood pressure in a double transgenic rat model of hypertension.

Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

PubMed

Yaeli, Steve; Meir, Ron

2010-01-01

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

Optimization and surgical design for applications in pediatric cardiology

NASA Astrophysics Data System (ADS)

Marsden, Alison; Bernstein, Adam; Taylor, Charles; Feinstein, Jeffrey

2007-11-01

The coupling of shape optimization to cardiovascular blood flow simulations has potential to improve the design of current surgeries and to eventually allow for optimization of surgical designs for individual patients. This is particularly true in pediatric cardiology, where geometries vary dramatically between patients, and unusual geometries can lead to unfavorable hemodynamic conditions. Interfacing shape optimization to three-dimensional, time-dependent fluid mechanics problems is particularly challenging because of the large computational cost and the difficulty in computing objective function gradients. In this work a derivative-free optimization algorithm is coupled to a three-dimensional Navier-Stokes solver that has been tailored for cardiovascular applications. The optimization code employs mesh adaptive direct search in conjunction with a Kriging surrogate. This framework is successfully demonstrated on several geometries representative of cardiovascular surgical applications. We will discuss issues of cost function choice for surgical applications, including energy loss and wall shear stress distribution. In particular, we will discuss the creation of new designs for the Fontan procedure, a surgery done in pediatric cardiology to treat single ventricle heart defects.

An optimized treatment for algorithmic differentiation of an important glaciological fixed-point problem

DOE PAGES

Goldberg, Daniel N.; Narayanan, Sri Hari Krishna; Hascoet, Laurent; ...

2016-05-20

We apply an optimized method to the adjoint generation of a time-evolving land ice model through algorithmic differentiation (AD). The optimization involves a special treatment of the fixed-point iteration required to solve the nonlinear stress balance, which differs from a straightforward application of AD software, and leads to smaller memory requirements and in some cases shorter computation times of the adjoint. The optimization is done via implementation of the algorithm of Christianson (1994) for reverse accumulation of fixed-point problems, with the AD tool OpenAD. For test problems, the optimized adjoint is shown to have far lower memory requirements, potentially enablingmore » larger problem sizes on memory-limited machines. In the case of the land ice model, implementation of the algorithm allows further optimization by having the adjoint model solve a sequence of linear systems with identical (as opposed to varying) matrices, greatly improving performance. Finally, the methods introduced here will be of value to other efforts applying AD tools to ice models, particularly ones which solve a hybrid shallow ice/shallow shelf approximation to the Stokes equations.« less

Modeling of lead air pollution. [Baton Rouge, Louisiana

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

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

1982-05-01

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

A new lead alloy for automotive batteries operating under high-temperature conditions

NASA Astrophysics Data System (ADS)

Albert, L.; Goguelin, A.; Jullian, E.

The operating conditions of automotive and some industrial batteries are involving increasingly higher temperatures and heavier duty cycles. These place stress on the positive-grid materials which are presently not sufficiently resistant to corrosion and to creep. Conventional lead-calcium-tin-aluminium alloys can usually be optimized by a proper choice of calcium and tin contents for each specific manufacturing technology. With the new requirements of customers and the typical behaviour of these conventional alloys, however, there is no more room for improvement without searching for additional alloying elements. The work reported here shows how the doping of conventional lead-calcium-tin-aluminium alloys with barium improves mechanical properties (tensile strength and creep resistance) and increases corrosion resistance at temperatures between 50 and 75°C. Grid materials prepared by two manufacturing technologies (gravity cast; continuous cast followed by expansion) are investigated. Both the mechanical properties and the corrosion behaviour of the resulting grids are evaluated.

Application of dynamic programming to control khuzestan water resources system

USGS Publications Warehouse

Jamshidi, M.; Heidari, M.

1977-01-01

An approximate optimization technique based on discrete dynamic programming called discrete differential dynamic programming (DDDP), is employed to obtain the near optimal operation policies of a water resources system in the Khuzestan Province of Iran. The technique makes use of an initial nominal state trajectory for each state variable, and forms corridors around the trajectories. These corridors represent a set of subdomains of the entire feasible domain. Starting with such a set of nominal state trajectories, improvements in objective function are sought within the corridors formed around them. This leads to a set of new nominal trajectories upon which more improvements may be sought. Since optimization is confined to a set of subdomains, considerable savings in memory and computer time are achieved over that of conventional dynamic programming. The Kuzestan water resources system considered in this study is located in southwest Iran, and consists of two rivers, three reservoirs, three hydropower plants, and three irrigable areas. Data and cost benefit functions for the analysis were obtained either from the historical records or from similar studies. ?? 1977.

Are people excessive or judicious in their egocentrism? A modeling approach to understanding bias and accuracy in people's optimism.

PubMed

Windschitl, Paul D; Rose, Jason P; Stalkfleet, Michael T; Smith, Andrew R

2008-08-01

People are often egocentric when judging their likelihood of success in competitions, leading to overoptimism about winning when circumstances are generally easy and to overpessimism when the circumstances are difficult. Yet, egocentrism might be grounded in a rational tendency to favor highly reliable information (about the self) more so than less reliable information (about others). A general theory of probability called extended support theory was used to conceptualize and assess the role of egocentrism and its consequences for the accuracy of people's optimism in 3 competitions (Studies 1-3, respectively). Also, instructions were manipulated to test whether people who were urged to avoid egocentrism would show improved or worsened accuracy in their likelihood judgments. Egocentrism was found to have a potentially helpful effect on one form of accuracy, but people generally showed too much egocentrism. Debias instructions improved one form of accuracy but had no impact on another. The advantages of using the EST framework for studying optimism and other types of judgments (e.g., comparative ability judgments) are discussed. (c) 2008 APA, all rights reserved

Optimization of L-shaped tunneling field-effect transistor for ambipolar current suppression and Analog/RF performance enhancement

NASA Astrophysics Data System (ADS)

Li, Cong; Zhao, Xiaolong; Zhuang, Yiqi; Yan, Zhirui; Guo, Jiaming; Han, Ru

2018-03-01

L-shaped tunneling field-effect transistor (LTFET) has larger tunnel area than planar TFET, which leads to enhanced on-current ION . However, LTFET suffers from severe ambipolar behavior, which needs to be further optimized for low power and high-frequency applications. In this paper, both hetero-gate-dielectric (HGD) and lightly doped drain (LDD) structures are introduced into LTFET for suppression of ambipolarity and improvement of analog/RF performance of LTFET. Current-voltage characteristics, the variation of energy band diagrams, distribution of band-to-band tunneling (BTBT) generation and distribution of electric field are analyzed for our proposed HGD-LDD-LTFET. In addition, the effect of LDD on the ambipolar behavior of LTFET is investigated, the length and doping concentration of LDD is also optimized for better suppression of ambipolar current. Finally, analog/RF performance of HGD-LDD-LTFET are studied in terms of gate-source capacitance, gate-drain capacitance, cut-off frequency, and gain bandwidth production. TCAD simulation results show that HGD-LDD-LTFET not only drastically suppresses ambipolar current but also improves analog/RF performance compared with conventional LTFET.

Knowledge-based system for detailed blade design of turbines

NASA Astrophysics Data System (ADS)

Goel, Sanjay; Lamson, Scott

1994-03-01

A design optimization methodology that couples optimization techniques to CFD analysis for design of airfoils is presented. This technique optimizes 2D airfoil sections of a blade by minimizing the deviation of the actual Mach number distribution on the blade surface from a smooth fit of the distribution. The airfoil is not reverse engineered by specification of a precise distribution of the desired Mach number plot, only general desired characteristics of the distribution are specified for the design. Since the Mach number distribution is very complex, and cannot be conveniently represented by a single polynomial, it is partitioned into segments, each of which is characterized by a different order polynomial. The sum of the deviation of all the segments is minimized during optimization. To make intelligent changes to the airfoil geometry, it needs to be associated with features observed in the Mach number distribution. Associating the geometry parameters with independent features of the distribution is a fairly complex task. Also, for different optimization techniques to work efficiently the airfoil geometry needs to be parameterized into independent parameters, with enough degrees of freedom for adequate geometry manipulation. A high-pressure, low reaction steam turbine blade section was optimized using this methodology. The Mach number distribution was partitioned into pressure and suction surfaces and the suction surface distribution was further subdivided into leading edge, mid section and trailing edge sections. Two different airfoil representation schemes were used for defining the design variables of the optimization problem. The optimization was performed by using a combination of heuristic search and numerical optimization. The optimization results for the two schemes are discussed in the paper. The results are also compared to a manual design improvement study conducted independently by an experienced airfoil designer. The turbine blade optimization system (TBOS) is developed using the described methodology of coupling knowledge engineering with multiple search techniques for blade shape optimization. TBOS removes a major bottleneck in the design cycle by performing multiple design optimizations in parallel, and improves design quality at the same time. TBOS not only improves the design but also the designers' quality of work by taking the mundane repetitive task of design iterations away and leaving them more time for innovative design.

Effectiveness of an Individualized Training Based on Force-Velocity Profiling during Jumping

PubMed Central

Jiménez-Reyes, Pedro; Samozino, Pierre; Brughelli, Matt; Morin, Jean-Benoît

2017-01-01

Ballistic performances are determined by both the maximal lower limb power output (Pmax) and their individual force-velocity (F-v) mechanical profile, especially the F-v imbalance (FVimb): difference between the athlete's actual and optimal profile. An optimized training should aim to increase Pmax and/or reduce FVimb. The aim of this study was to test whether an individualized training program based on the individual F-v profile would decrease subjects' individual FVimb and in turn improve vertical jump performance. FVimb was used as the reference to assign participants to different training intervention groups. Eighty four subjects were assigned to three groups: an “optimized” group divided into velocity-deficit, force-deficit, and well-balanced sub-groups based on subjects' FVimb, a “non-optimized” group for which the training program was not specifically based on FVimb and a control group. All subjects underwent a 9-week specific resistance training program. The programs were designed to reduce FVimb for the optimized groups (with specific programs for sub-groups based on individual FVimb values), while the non-optimized group followed a classical program exactly similar for all subjects. All subjects in the three optimized training sub-groups (velocity-deficit, force-deficit, and well-balanced) increased their jumping performance (12.7 ± 5.7% ES = 0.93 ± 0.09, 14.2 ± 7.3% ES = 1.00 ± 0.17, and 7.2 ± 4.5% ES = 0.70 ± 0.36, respectively) with jump height improvement for all subjects, whereas the results were much more variable and unclear in the non-optimized group. This greater change in jump height was associated with a markedly reduced FVimb for both force-deficit (57.9 ± 34.7% decrease in FVimb) and velocity-deficit (20.1 ± 4.3%) subjects, and unclear or small changes in Pmax (−0.40 ± 8.4% and +10.5 ± 5.2%, respectively). An individualized training program specifically based on FVimb (gap between the actual and optimal F-v profiles of each individual) was more efficient at improving jumping performance (i.e., unloaded squat jump height) than a traditional resistance training common to all subjects regardless of their FVimb. Although improving both FVimb and Pmax has to be considered to improve ballistic performance, the present results showed that reducing FVimb without even increasing Pmax lead to clearly beneficial jump performance changes. Thus, FVimb could be considered as a potentially useful variable for prescribing optimal resistance training to improve ballistic performance. PMID:28119624

Acetate Salts as Nonhalogen Additives To Improve Perovskite Film Morphology for High-Efficiency Solar Cells.

PubMed

Wu, Qiliang; Zhou, Pengcheng; Zhou, Weiran; Wei, Xiangfeng; Chen, Tao; Yang, Shangfeng

2016-06-22

A two-step method has been popularly adopted to fabricate a perovskite film of planar heterojunction organo-lead halide perovskite solar cells (PSCs). However, this method often generates uncontrollable film morphology with poor coverage. Herein, we report a facile method to improve perovskite film morphology by incorporating a small amount of acetate (CH3COO(-), Ac(-)) salts (NH4Ac, NaAc) as nonhalogen additives in CH3NH3I solution used for immersing PbI2 film, resulting in improved CH3NH3PbI3 film morphology. Under the optimized NH4Ac additive concentration of 10 wt %, the best power conversion efficiency (PCE) reaches 17.02%, which is enhanced by ∼23.2% relative to that of the pristine device without additive, whereas the NaAc additive does not lead to an efficiency enhancement despite the improvement of the CH3NH3PbI3 film morphology. SEM study reveals that NH4Ac and NaAc additives can both effectively improve perovskite film morphology by increasing the surface coverage via diminishing pinholes. The improvement on CH3NH3PbI3 film morphology is beneficial for increasing the optical absorption of perovskite film and improving the interfacial contact at the perovskite/spiro-OMeTAD interface, leading to the increase of short-circuit current and consequently efficiency enhancement of the PSC device for NH4Ac additive only.

Effects of annealing temperature on the H2-sensing properties of Pd-decorated WO3 nanorods

NASA Astrophysics Data System (ADS)

Lee, Sangmin; Lee, Woo Seok; Lee, Jae Kyung; Hyun, Soong Keun; Lee, Chongmu; Choi, Seungbok

2018-03-01

The temperature of the post-annealing treatment carried out after noble metal deposition onto semiconducting metal oxides (SMOs) must be carefully optimized to maximize the sensing performance of the metal-decorated SMO sensors. WO3 nanorods were synthesized by thermal evaporation of WO3 powders and decorated with Pd nanoparticles using a sol-gel method, followed by an annealing process. The effects of the annealing temperature on the hydrogen gas-sensing properties of the Pd-decorated WO3 nanorods were then examined; the optimal annealing temperature, leading to the highest response of the WO3 nanorod sensor to H2, was determined to be 600 °C. Post-annealing at 600 °C resulted in nanorods with the highest surface area-to-volume ratio, as well as in the optimal size and the largest number of deposited Pd nanoparticles, leading to the highest response and the shortest response/recovery times toward H2. The improved H2-sensing performance of the Pd-decorated WO3 nanorod sensor, compared to a sensor based on pristine WO3 nanorods, is attributed to the enhanced catalytic activity, increased surface area-to-volume ratio, and higher amounts of surface defects.

Optimal digital filtering for tremor suppression.

PubMed

Gonzalez, J G; Heredia, E A; Rahman, T; Barner, K E; Arce, G R

2000-05-01

Remote manually operated tasks such as those found in teleoperation, virtual reality, or joystick-based computer access, require the generation of an intermediate electrical signal which is transmitted to the controlled subsystem (robot arm, virtual environment, or a cursor in a computer screen). When human movements are distorted, for instance, by tremor, performance can be improved by digitally filtering the intermediate signal before it reaches the controlled device. This paper introduces a novel tremor filtering framework in which digital equalizers are optimally designed through pursuit tracking task experiments. Due to inherent properties of the man-machine system, the design of tremor suppression equalizers presents two serious problems: 1) performance criteria leading to optimizations that minimize mean-squared error are not efficient for tremor elimination and 2) movement signals show ill-conditioned autocorrelation matrices, which often result in useless or unstable solutions. To address these problems, a new performance indicator in the context of tremor is introduced, and the optimal equalizer according to this new criterion is developed. Ill-conditioning of the autocorrelation matrix is overcome using a novel method which we call pulled-optimization. Experiments performed with artificially induced vibrations and a subject with Parkinson's disease show significant improvement in performance. Additional results, along with MATLAB source code of the algorithms, and a customizable demo for PC joysticks, are available on the Internet at http:¿tremor-suppression.com.

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

PubMed

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

2014-05-01

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

Improving the efficiency of branch-and-bound complete-search NMR assignment using the symmetry of molecules and spectra

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

Bernal, Andrés; Patiny, Luc; Castillo, Andrés M.

2015-02-21

Nuclear magnetic resonance (NMR) assignment of small molecules is presented as a typical example of a combinatorial optimization problem in chemical physics. Three strategies that help improve the efficiency of solution search by the branch and bound method are presented: 1. reduction of the size of the solution space by resort to a condensed structure formula, wherein symmetric nuclei are grouped together; 2. partitioning of the solution space based on symmetry, that becomes the basis for an efficient branching procedure; and 3. a criterion of selection of input restrictions that leads to increased gaps between branches and thus faster pruningmore » of non-viable solutions. Although the examples chosen to illustrate this work focus on small-molecule NMR assignment, the results are generic and might help solving other combinatorial optimization problems.« less

Anodal right ventricular capture during left ventricular stimulation in CRT-implantable cardioverter defibrillators.

PubMed

Thibault, Bernard; Roy, Denis; Guerra, Peter G; Macle, Laurent; Dubuc, Marc; Gagné, Pierre; Greiss, Isabelle; Novak, Paul; Furlani, Aldo; Talajic, Mario

2005-07-01

Cardiac resynchronization therapy (CRT) has been shown to improve symptoms of patients with moderate to severe heart failure. Optimal CRT involves biventricular or left ventricular (LV) stimulation alone, atrio-ventricular (AV) delay optimization, and possibly interventricular timing adjustment. Recently, anodal capture of the right ventricle (RV) has been described for patients with CRT-pacemakers. It is unknown whether the same phenomenon exists in CRT systems associated with defibrillators (CRT-ICD). The RV leads used in these systems are different from pacemaker leads: they have a larger diameter and shocking coils, which may affect the occurrence of anodal capture. We looked for anodal RV capture during LV stimulation in 11 consecutive patients who received a CRT-ICD system with RV leads with a true bipolar design. Fifteen patients who had RV leads with an integrated design were used as controls. Anodal RV and LV thresholds were determined at pulse width (pw) durations of 0.2, 0.5, and 1.0 ms. RV anodal capture during LV pacing was found in 11/11 patients at some output with true bipolar RV leads versus 0/15 patients with RV leads with an integrated bipolar design. Anodal RV capture threshold was more affected by changes in pw duration than LV capture threshold. In CRT-ICD systems, RV leads with a true bipolar design with the proximal ring also used as the anode for LV pacing are associated with a high incidence of anodal RV capture during LV pacing. This may affect the clinical response to alternative resynchronization methods using single LV stimulation or interventricular delay programming.

An improved hybrid of particle swarm optimization and the gravitational search algorithm to produce a kinetic parameter estimation of aspartate biochemical pathways.

PubMed

Ismail, Ahmad Muhaimin; Mohamad, Mohd Saberi; Abdul Majid, Hairudin; Abas, Khairul Hamimah; Deris, Safaai; Zaki, Nazar; Mohd Hashim, Siti Zaiton; Ibrahim, Zuwairie; Remli, Muhammad Akmal

2017-12-01

Mathematical modelling is fundamental to understand the dynamic behavior and regulation of the biochemical metabolisms and pathways that are found in biological systems. Pathways are used to describe complex processes that involve many parameters. It is important to have an accurate and complete set of parameters that describe the characteristics of a given model. However, measuring these parameters is typically difficult and even impossible in some cases. Furthermore, the experimental data are often incomplete and also suffer from experimental noise. These shortcomings make it challenging to identify the best-fit parameters that can represent the actual biological processes involved in biological systems. Computational approaches are required to estimate these parameters. The estimation is converted into multimodal optimization problems that require a global optimization algorithm that can avoid local solutions. These local solutions can lead to a bad fit when calibrating with a model. Although the model itself can potentially match a set of experimental data, a high-performance estimation algorithm is required to improve the quality of the solutions. This paper describes an improved hybrid of particle swarm optimization and the gravitational search algorithm (IPSOGSA) to improve the efficiency of a global optimum (the best set of kinetic parameter values) search. The findings suggest that the proposed algorithm is capable of narrowing down the search space by exploiting the feasible solution areas. Hence, the proposed algorithm is able to achieve a near-optimal set of parameters at a fast convergence speed. The proposed algorithm was tested and evaluated based on two aspartate pathways that were obtained from the BioModels Database. The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. Nevertheless, the proposed algorithm is only expected to work well in small scale systems. In addition, the results of this study can be used to estimate kinetic parameter values in the stage of model selection for different experimental conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal nonimaging integrated evacuated solar collector

NASA Astrophysics Data System (ADS)

Garrison, John D.; Duff, W. S.; O'Gallagher, Joseph J.; Winston, Roland

1993-11-01

A non imaging integrated evacuated solar collector for solar thermal energy collection is discussed which has the lower portion of the tubular glass vacuum enveloped shaped and inside surface mirrored to optimally concentrate sunlight onto an absorber tube in the vacuum. This design uses vacuum to eliminate heat loss from the absorber surface by conduction and convection of air, soda lime glass for the vacuum envelope material to lower cost, optimal non imaging concentration integrated with the glass vacuum envelope to lower cost and improve solar energy collection, and a selective absorber for the absorbing surface which has high absorptance and low emittance to lower heat loss by radiation and improve energy collection efficiency. This leads to a very low heat loss collector with high optical collection efficiency, which can operate at temperatures up to the order of 250 degree(s)C with good efficiency while being lower in cost than current evacuated solar collectors. Cost estimates are presented which indicate a cost for this solar collector system which can be competitive with the cost of fossil fuel heat energy sources when the collector system is produced in sufficient volume. Non imaging concentration, which reduces cost while improving performance, and which allows efficient solar energy collection without tracking the sun, is a key element in this solar collector design.

Lead optimization in the nondrug-like space.

PubMed

Zhao, Hongyu

2011-02-01

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

The criteria of optimization of training specialists for the nuclear power industry and its implementation in the educational process

NASA Astrophysics Data System (ADS)

Lavrinenko, S. V.; Polikarpov, P. I.

2017-11-01

The nuclear industry is one of the most important and high-tech spheres of human activity in Russia. The main cause of accidents in the nuclear industry is the human factor. In this connection, the need to constantly analyze the system of training of specialists and its optimization in order to improve safety at nuclear industry enterprises. To do this, you must analyze the international experience in the field of training in the field of nuclear energy leading countries. Based on the analysis criteria have been formulated to optimize the educational process of training specialists for the nuclear power industry and test their effectiveness. The most effective and promising is the introduction of modern information technologies of training of students, such as real-time simulators, electronic educational resources, etc.

Analyse et design aerodynamique haute-fidelite de l'integration moteur sur un avion BWB

NASA Astrophysics Data System (ADS)

Mirzaei Amirabad, Mojtaba

BWB (Blended Wing Body) is an innovative type of aircraft based on the flying wing concept. In this configuration, the wing and the fuselage are blended together smoothly. BWB offers economical and environmental advantages by reducing fuel consumption through improving aerodynamic performance. In this project, the goal is to improve the aerodynamic performance by optimizing the main body of BWB that comes from conceptual design. The high fidelity methods applied in this project have been less frequently addressed in the literature. This research develops an automatic optimization procedure in order to reduce the drag force on the main body. The optimization is carried out in two main stages: before and after engine installation. Our objective is to minimize the drag by taking into account several constraints in high fidelity optimization. The commercial software, Isight is chosen as an optimizer in which MATLAB software is called to start the optimization process. Geometry is generated using ANSYS-DesignModeler, unstructured mesh is created by ANSYS-Mesh and CFD calculations are done with the help of ANSYS-Fluent. All of these software are coupled together in ANSYS-Workbench environment which is called by MATLAB. The high fidelity methods are used during optimization by solving Navier-Stokes equations. For verifying the results, a finer structured mesh is created by ICEM software to be used in each stage of optimization. The first stage includes a 3D optimization on the surface of the main body, before adding the engine. The optimized case is then used as an input for the second stage in which the nacelle is added. It could be concluded that this study leads us to obtain appropriate reduction in drag coefficient for BWB without nacelle. In the second stage (adding the nacelle) a drag minimization is also achieved by performing a local optimization. Furthermore, the flow separation, created in the main body-nacelle zone, is reduced.

Quantum Adiabatic Brachistochrone

NASA Astrophysics Data System (ADS)

Rezakhani, A. T.; Kuo, W.-J.; Hamma, A.; Lidar, D. A.; Zanardi, P.

2009-08-01

We formulate a time-optimal approach to adiabatic quantum computation (AQC). A corresponding natural Riemannian metric is also derived, through which AQC can be understood as the problem of finding a geodesic on the manifold of control parameters. This geometrization of AQC is demonstrated through two examples, where we show that it leads to improved performance of AQC, and sheds light on the roles of entanglement and curvature of the control manifold in algorithmic performance.

Quantum adiabatic brachistochrone.

PubMed

Rezakhani, A T; Kuo, W-J; Hamma, A; Lidar, D A; Zanardi, P

2009-08-21

We formulate a time-optimal approach to adiabatic quantum computation (AQC). A corresponding natural Riemannian metric is also derived, through which AQC can be understood as the problem of finding a geodesic on the manifold of control parameters. This geometrization of AQC is demonstrated through two examples, where we show that it leads to improved performance of AQC, and sheds light on the roles of entanglement and curvature of the control manifold in algorithmic performance.

Annual Research Review: New Frontiers in Developmental Neuropharmacology--Can Long-Term Therapeutic Effects of Drugs Be Optimized through Carefully Timed Early Intervention?

ERIC Educational Resources Information Center

Andersen, Susan L.; Navalta, Carryl P.

2011-01-01

Our aim is to present a working model that may serve as a valuable heuristic to predict enduring effects of drugs when administered during development. Our primary tenet is that a greater understanding of neurodevelopment can lead to improved treatment that intervenes early in the progression of a given disorder and prevents symptoms from…

Optimal superdense coding over memory channels

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

Shadman, Z.; Kampermann, H.; Bruss, D.

2011-10-15

We study the superdense coding capacity in the presence of quantum channels with correlated noise. We investigate both the cases of unitary and nonunitary encoding. Pauli channels for arbitrary dimensions are treated explicitly. The superdense coding capacity for some special channels and resource states is derived for unitary encoding. We also provide an example of a memory channel where nonunitary encoding leads to an improvement in the superdense coding capacity.

Fast and accurate denoising method applied to very high resolution optical remote sensing images

NASA Astrophysics Data System (ADS)

Masse, Antoine; Lefèvre, Sébastien; Binet, Renaud; Artigues, Stéphanie; Lassalle, Pierre; Blanchet, Gwendoline; Baillarin, Simon

2017-10-01

Restoration of Very High Resolution (VHR) optical Remote Sensing Image (RSI) is critical and leads to the problem of removing instrumental noise while keeping integrity of relevant information. Improving denoising in an image processing chain implies increasing image quality and improving performance of all following tasks operated by experts (photo-interpretation, cartography, etc.) or by algorithms (land cover mapping, change detection, 3D reconstruction, etc.). In a context of large industrial VHR image production, the selected denoising method should optimized accuracy and robustness with relevant information and saliency conservation, and rapidity due to the huge amount of data acquired and/or archived. Very recent research in image processing leads to a fast and accurate algorithm called Non Local Bayes (NLB) that we propose to adapt and optimize for VHR RSIs. This method is well suited for mass production thanks to its best trade-off between accuracy and computational complexity compared to other state-of-the-art methods. NLB is based on a simple principle: similar structures in an image have similar noise distribution and thus can be denoised with the same noise estimation. In this paper, we describe in details algorithm operations and performances, and analyze parameter sensibilities on various typical real areas observed in VHR RSIs.

Adaptive Swarm Balancing Algorithms for rare-event prediction in imbalanced healthcare data

PubMed Central

Wong, Raymond K.; Mohammed, Sabah; Fiaidhi, Jinan; Sung, Yunsick

2017-01-01

Clinical data analysis and forecasting have made substantial contributions to disease control, prevention and detection. However, such data usually suffer from highly imbalanced samples in class distributions. In this paper, we aim to formulate effective methods to rebalance binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat algorithm, and apply them to empower the effects of synthetic minority over-sampling technique (SMOTE) for pre-processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reported in this paper reveal that the performance improvements obtained by the former methods are not scalable to larger data scales. The latter methods, which we call Adaptive Swarm Balancing Algorithms, lead to significant efficiency and effectiveness improvements on large datasets while the first method is invalid. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. The proposed methods lead to more credible performances of the classifier, and shortening the run time compared to brute-force method. PMID:28753613

Optimization of a biomimetic bone cement: role of DCPD.

PubMed

Panzavolta, Silvia; Bracci, Barbara; Rubini, Katia; Bigi, Adriana

2011-08-01

We previously proposed a biomimetic α-tricalcium phosphate (α-TCP) bone cement where gelatin controls the transformation of α-TCP into calcium deficient hydroxyapatite (CDHA), leading to improved mechanical properties. In this study we investigated the setting and hardening processes of biomimetic cements containing increasing amounts of CaHPO(4)·2H2O (DCPD) (0, 2.5, 5, 10, 15 wt.%), with the aim to optimize composition. Both initial and final setting times increased significantly when DCPD content accounts for 10 wt.%, whereas cements containing 15 wt.% DCPD did not set at all. Differential scanning calorimetry (DSC), X-ray diffraction (XRD), thermogravimetry (TG) and scanning electron microscopy (SEM) investigations were performed on samples maintained in physiological solution for different times. DCPD dissolution starts soon after cement preparation, but the rate of transformation decreases on increasing DCPD initial content in the samples. The rate of α-TCP to CDHA conversion during hardening decreases on increasing DCPD initial content. Moreover, the presence of DCPD prevents gelatin release during hardening. The combined effects of gelatin and DCPD on the rate of CDHA formation and porosity lead to significantly improved mechanical properties, with the best composition displaying a compressive strength of 35 MPa and a Young modulus of 1600 MPa. Copyright © 2011 Elsevier Inc. All rights reserved.

Assessing the sustainability of lead utilization in China.

PubMed

Sun, Lingyu; Zhang, Chen; Li, Jinhui; Zeng, Xianlai

2016-12-01

Lead is not only one of heavy metals imposing environment and health risk, but also critical resource to maintain sustainable development of many industries. Recently, due to the shortage of fossil fuels, clean energy vehicles, including electric bicycle, have emerged and are widely adopted soon in the world. China became the world's largest producer of primary lead and a very significant consumer in the past decade, which has strained the supplies of China's lead deposits from lithosphere and boost the anthropogenic consumption of metallic lead and lead products. Here we summarize that China's lead demand will continually increase due to the rapid growth of electric vehicle, resulting in a short carrying duration of lead even with full lead recycling. With these applications increasing at an annual rate of 2%, the carrying duration of lead resource until 2030 will oblige that recycling rate should be not less than 90%. To sustain lead utilization in China, one approach would be to improve the utilization technology, collection system and recycling technology towards closed-loop supply chain. Other future endeavors should include optimizing lead industrial structure and development of new energy. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

Hu, Jing; Zhang, Xiaolong

2016-11-01

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

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

PubMed Central

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

2012-01-01

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

Overlay accuracy fundamentals

NASA Astrophysics Data System (ADS)

Kandel, Daniel; Levinski, Vladimir; Sapiens, Noam; Cohen, Guy; Amit, Eran; Klein, Dana; Vakshtein, Irina

2012-03-01

Currently, the performance of overlay metrology is evaluated mainly based on random error contributions such as precision and TIS variability. With the expected shrinkage of the overlay metrology budget to < 0.5nm, it becomes crucial to include also systematic error contributions which affect the accuracy of the metrology. Here we discuss fundamental aspects of overlay accuracy and a methodology to improve accuracy significantly. We identify overlay mark imperfections and their interaction with the metrology technology, as the main source of overlay inaccuracy. The most important type of mark imperfection is mark asymmetry. Overlay mark asymmetry leads to a geometrical ambiguity in the definition of overlay, which can be ~1nm or less. It is shown theoretically and in simulations that the metrology may enhance the effect of overlay mark asymmetry significantly and lead to metrology inaccuracy ~10nm, much larger than the geometrical ambiguity. The analysis is carried out for two different overlay metrology technologies: Imaging overlay and DBO (1st order diffraction based overlay). It is demonstrated that the sensitivity of DBO to overlay mark asymmetry is larger than the sensitivity of imaging overlay. Finally, we show that a recently developed measurement quality metric serves as a valuable tool for improving overlay metrology accuracy. Simulation results demonstrate that the accuracy of imaging overlay can be improved significantly by recipe setup optimized using the quality metric. We conclude that imaging overlay metrology, complemented by appropriate use of measurement quality metric, results in optimal overlay accuracy.

A technique for position sensing and improved momentum evaluation of microparticle impacts in space.

NASA Technical Reports Server (NTRS)

Mcdonnell, J. A. M.; Abellanas, C.

1972-01-01

The design of a three element piezoelectric microparticle impact sensing diaphragm is described which is sensitive to the detection of momentum propagated by the bending wave. The design achieves a sensitivity of .03 microdyn/sec and optimizes the detection of the direct-path pulse from impact relative to secondary reflections and interference from discontinuities. Measurement of the relative arrival times and the maximum amplitudes of the outputs from the three piezoelectric sensors leads to the determination of the impact position and the normally resolved impact momentum exchange. Coincidence of the signals and a partial redundancy of data leads to a very high noise discrimination.

SU-D-BRC-02: Application of Six Sigma Approach to Improve the Efficiency of Patient-Specific QA in Proton Therapy

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

LAH, J; Shin, D; Manger, R

Purpose: To show how the Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) can be used for improving and optimizing the efficiency of patient-specific QA process by designing site-specific range tolerances. Methods: The Six Sigma tools (process flow diagram, cause and effect, capability analysis, Pareto chart, and control chart) were utilized to determine the steps that need focus for improving the patient-specific QA process. The patient-specific range QA plans were selected according to 7 treatment site groups, a total of 1437 cases. The process capability index, Cpm was used to guide the tolerance design of patient site-specific range. We also analyzed the financial impactmore » of this project. Results: Our results suggested that the patient range measurements were non-capable at the current tolerance level of ±1 mm in clinical proton plans. The optimized tolerances were calculated for treatment sites. Control charts for the patient QA time were constructed to compare QA time before and after the new tolerances were implemented. It is found that overall processing time was decreased by 24.3% after establishing new site-specific range tolerances. The QA failure for whole process in proton therapy would lead up to a 46% increase in total cost. This result can also predict how costs are affected by changes in adopting the tolerance design. Conclusion: We often believe that the quality and performance of proton therapy can easily be improved by merely tightening some or all of its tolerance requirements. This can become costly, however, and it is not necessarily a guarantee of better performance. The tolerance design is not a task to be undertaken without careful thought. The Six Sigma DMAIC can be used to improve the QA process by setting optimized tolerances. When tolerance design is optimized, the quality is reasonably balanced with time and cost demands.« less

Respiratory motion compensated overlay of surface models from cardiac MR on interventional x-ray fluoroscopy for guidance of cardiac resynchronization therapy procedures

NASA Astrophysics Data System (ADS)

Manzke, R.; Bornstedt, A.; Lutz, A.; Schenderlein, M.; Hombach, V.; Binner, L.; Rasche, V.

2010-02-01

Various multi-center trials have shown that cardiac resynchronization therapy (CRT) is an effective procedure for patients with end-stage drug invariable heart failure (HF). Despite the encouraging results of CRT, at least 30% of patients do not respond to the treatment. Detailed knowledge of the cardiac anatomy (coronary venous tree, left ventricle), functional parameters (i.e. ventricular synchronicity) is supposed to improve CRT patient selection and interventional lead placement for reduction of the number of non-responders. As a pre-interventional imaging modality, cardiac magnetic resonance (CMR) imaging has the potential to provide all relevant information. With functional information from CMR optimal implantation target sites may be better identified. Pre-operative CMR could also help to determine whether useful vein target segments are available for lead placement. Fused with X-ray, the mainstay interventional modality, improved interventional guidance for lead-placement could further help to increase procedure outcome. In this contribution, we present novel and practicable methods for a) pre-operative functional and anatomical imaging of relevant cardiac structures to CRT using CMR, b) 2D-3D registration of CMR anatomy and functional meshes with X-ray vein angiograms and c) real-time capable breathing motion compensation for improved fluoroscopy mesh overlay during the intervention based on right ventricular pacer lead tracking. With these methods, enhanced interventional guidance for left ventricular lead placement is provided.

[Why is brachytherapy still essential in 2017?

PubMed

Haie-Méder, C; Maroun, P; Fumagalli, I; Lazarescu, I; Dumas, I; Martinetti, F; Chargari, C

2018-05-16

These recent years, brachytherapy has benefited from imaging modalities advances. A more systematic use of tomodensitometric, ultrasonographic and MRI images during brachytherapy procedures has allowed an improvement in target and organs at risk assessment as well as their relationship with the applicators. New concepts integrating tumor regression during treatment have been defined and have been clinically validated. New applicators have been developed and are commercially available. Optimization processes have been developed, integrating hypofractionation modalities leading to tumor control improvement. All these opportunities led to further development of brachytherapy, with indisputable ballistic advantages, especially compared to external irradiation. Copyright © 2018. Published by Elsevier SAS.

Prospects for spinel-stabilized, high-capacity lithium-ion battery cathodes

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

Croy, Jason R.; Park, Joong Sun; Shin, Youngho

Herein we report early results on efforts to optimize the electrochemical performance of a cathode composed of a lithium- and manganese-rich “layered-layered-spinel” material for lithium-ion battery applications. Pre-pilot scale synthesis leads to improved particle properties compared with lab-scale efforts, resulting in high capacities (≳200 mAh/g) and good energy densities (>700 Wh/kg) in tests with lithium-ion cells. Subsequent surface modifications give further improvements in rate capabilities and high-voltage stability. These results bode well for advances in the performance of this class of lithium- and manganese-rich cathode materials.

Prospects for spinel-stabilized, high-capacity lithium-ion battery cathodes

DOE PAGES

Croy, Jason R.; Park, Joong Sun; Shin, Youngho; ...

2016-10-13

Herein we report early results on efforts to optimize the electrochemical performance of a cathode composed of a lithium- and manganese-rich “layered-layered-spinel” material for lithium-ion battery applications. Pre-pilot scale synthesis leads to improved particle properties compared with lab-scale efforts, resulting in high capacities (≳200 mAh/g) and good energy densities (>700 Wh/kg) in tests with lithium-ion cells. Subsequent surface modifications give further improvements in rate capabilities and high-voltage stability. These results bode well for advances in the performance of this class of lithium- and manganese-rich cathode materials.

Disease and disaster: Optimal deployment of epidemic control facilities in a spatially heterogeneous population with changing behaviour.

PubMed

Gaythorpe, Katy; Adams, Ben

2016-05-21

Epidemics of water-borne infections often follow natural disasters and extreme weather events that disrupt water management processes. The impact of such epidemics may be reduced by deployment of transmission control facilities such as clinics or decontamination plants. Here we use a relatively simple mathematical model to examine how demographic and environmental heterogeneities, population behaviour, and behavioural change in response to the provision of facilities, combine to determine the optimal configurations of limited numbers of facilities to reduce epidemic size, and endemic prevalence. We show that, if the presence of control facilities does not affect behaviour, a good general rule for responsive deployment to minimise epidemic size is to place them in exactly the locations where they will directly benefit the most people. However, if infected people change their behaviour to seek out treatment then the deployment of facilities offering treatment can lead to complex effects that are difficult to foresee. So careful mathematical analysis is the only way to get a handle on the optimal deployment. Behavioural changes in response to control facilities can also lead to critical facility numbers at which there is a radical change in the optimal configuration. So sequential improvement of a control strategy by adding facilities to an existing optimal configuration does not always produce another optimal configuration. We also show that the pre-emptive deployment of control facilities has conflicting effects. The configurations that minimise endemic prevalence are very different to those that minimise epidemic size. So cost-benefit analysis of strategies to manage endemic prevalence must factor in the frequency of extreme weather events and natural disasters. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Increasing the statistical significance of entanglement detection in experiments.

PubMed

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

2010-05-28

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

Higher Throughput Calorimetry: Opportunities, Approaches and Challenges

PubMed Central

Recht, Michael I.; Coyle, Joseph E.; Bruce, Richard H.

2010-01-01

Higher throughput thermodynamic measurements can provide value in structure-based drug discovery during fragment screening, hit validation, and lead optimization. Enthalpy can be used to detect and characterize ligand binding, and changes that affect the interaction of protein and ligand can sometimes be detected more readily from changes in the enthalpy of binding than from the corresponding free-energy changes or from protein-ligand structures. Newer, higher throughput calorimeters are being incorporated into the drug discovery process. Improvements in titration calorimeters come from extensions of a mature technology and face limitations in scaling. Conversely, array calorimetry, an emerging technology, shows promise for substantial improvements in throughput and material utilization, but improved sensitivity is needed. PMID:20888754

Efficient Online Optimized Quantum Control for Adiabatic Quantum Computation

NASA Astrophysics Data System (ADS)

Quiroz, Gregory

Adiabatic quantum computation (AQC) relies on controlled adiabatic evolution to implement a quantum algorithm. While control evolution can take many forms, properly designed time-optimal control has been shown to be particularly advantageous for AQC. Grover's search algorithm is one such example where analytically-derived time-optimal control leads to improved scaling of the minimum energy gap between the ground state and first excited state and thus, the well-known quadratic quantum speedup. Analytical extensions beyond Grover's search algorithm present a daunting task that requires potentially intractable calculations of energy gaps and a significant degree of model certainty. Here, an in situ quantum control protocol is developed for AQC. The approach is shown to yield controls that approach the analytically-derived time-optimal controls for Grover's search algorithm. In addition, the protocol's convergence rate as a function of iteration number is shown to be essentially independent of system size. Thus, the approach is potentially scalable to many-qubit systems.

Premium cost optimization of operational and maintenance of green building in Indonesia using life cycle assessment method

NASA Astrophysics Data System (ADS)

Latief, Yusuf; Berawi, Mohammed Ali; Basten, Van; Budiman, Rachmat; Riswanto

2017-06-01

Building has a big impact on the environmental developments. There are three general motives in building, namely the economy, society, and environment. Total completed building construction in Indonesia increased by 116% during 2009 to 2011. It made the energy consumption increased by 11% within the last three years. In fact, 70% of energy consumption is used for electricity needs on commercial buildings which leads to an increase of greenhouse gas emissions by 25%. Green Building cycle costs is known as highly building upfront cost in Indonesia. The purpose of optimization in this research improves building performance with some of green concept alternatives. Research methodology is mixed method of qualitative and quantitative approaches through questionnaire surveys and case study. Assessing the successful of optimization functions in the existing green building is based on the operational and maintenance phase with the Life Cycle Assessment Method. Choosing optimization results were based on the largest efficiency of building life cycle and the most effective cost to refund.

Meshes optimized for discrete exterior calculus (DEC).

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

Mousley, Sarah C.; Deakin, Michael; Knupp, Patrick

We study the optimization of an energy function used by the meshing community to measure and improve mesh quality. This energy is non-traditional because it is dependent on both the primal triangulation and its dual Voronoi (power) diagram. The energy is a measure of the mesh's quality for usage in Discrete Exterior Calculus (DEC), a method for numerically solving PDEs. In DEC, the PDE domain is triangulated and this mesh is used to obtain discrete approximations of the continuous operators in the PDE. The energy of a mesh gives an upper bound on the error of the discrete diagonal approximationmore » of the Hodge star operator. In practice, one begins with an initial mesh and then makes adjustments to produce a mesh of lower energy. However, we have discovered several shortcomings in directly optimizing this energy, e.g. its non-convexity, and we show that the search for an optimized mesh may lead to mesh inversion (malformed triangles). We propose a new energy function to address some of these issues.« less

Lattice Boltzmann Simulation Optimization on Leading Multicore Platforms

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

Williams, Samuel; Carter, Jonathan; Oliker, Leonid

2008-02-01

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to a lattice Boltzmann application (LBMHD) that historically has made poor use of scalar microprocessors due to its complex data structures and memory access patterns. We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Clovertown, AMD Opteron X2, Sun Niagara2, STI Cell, as well as the single core Intel Itanium2. Rather than hand-tuning LBMHDmore » for each system, we develop a code generator that allows us identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned LBMHD application achieves up to a 14x improvement compared with the original code. Additionally, we present detailed analysis of each optimization, which reveal surprising hardware bottlenecks and software challenges for future multicore systems and applications.« less

Lattice Boltzmann simulation optimization on leading multicore platforms

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

Williams, S.; Carter, J.; Oliker, L.

2008-01-01

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of searchbased performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to a lattice Boltzmann application (LBMHD) that historically has made poor use of scalar microprocessors due to its complex data structures and memory access patterns. We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Clovertown, AMD Opteron X2, Sun Niagara2, STI Cell, as well as the single core Intel Itanium2. Rather than hand-tuning LBMHDmore » for each system, we develop a code generator that allows us identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our autotuned LBMHD application achieves up to a 14 improvement compared with the original code. Additionally, we present detailed analysis of each optimization, which reveal surprising hardware bottlenecks and software challenges for future multicore systems and applications.« less

Robust optimal design of diffusion-weighted magnetic resonance experiments for skin microcirculation

NASA Astrophysics Data System (ADS)

Choi, J.; Raguin, L. G.

2010-10-01

Skin microcirculation plays an important role in several diseases including chronic venous insufficiency and diabetes. Magnetic resonance (MR) has the potential to provide quantitative information and a better penetration depth compared with other non-invasive methods such as laser Doppler flowmetry or optical coherence tomography. The continuous progress in hardware resulting in higher sensitivity must be coupled with advances in data acquisition schemes. In this article, we first introduce a physical model for quantifying skin microcirculation using diffusion-weighted MR (DWMR) based on an effective dispersion model for skin leading to a q-space model of the DWMR complex signal, and then design the corresponding robust optimal experiments. The resulting robust optimal DWMR protocols improve the worst-case quality of parameter estimates using nonlinear least squares optimization by exploiting available a priori knowledge of model parameters. Hence, our approach optimizes the gradient strengths and directions used in DWMR experiments to robustly minimize the size of the parameter estimation error with respect to model parameter uncertainty. Numerical evaluations are presented to demonstrate the effectiveness of our approach as compared to conventional DWMR protocols.

Optimization of Multiple Related Negotiation through Multi-Negotiation Network

NASA Astrophysics Data System (ADS)

Ren, Fenghui; Zhang, Minjie; Miao, Chunyan; Shen, Zhiqi

In this paper, a Multi-Negotiation Network (MNN) and a Multi- Negotiation Influence Diagram (MNID) are proposed to optimally handle Multiple Related Negotiations (MRN) in a multi-agent system. Most popular, state-of-the-art approaches perform MRN sequentially. However, a sequential procedure may not optimally execute MRN in terms of maximizing the global outcome, and may even lead to unnecessary losses in some situations. The motivation of this research is to use a MNN to handle MRN concurrently so as to maximize the expected utility of MRN. Firstly, both the joint success rate and the joint utility by considering all related negotiations are dynamically calculated based on a MNN. Secondly, by employing a MNID, an agent's possible decision on each related negotiation is reflected by the value of expected utility. Lastly, through comparing expected utilities between all possible policies to conduct MRN, an optimal policy is generated to optimize the global outcome of MRN. The experimental results indicate that the proposed approach can improve the global outcome of MRN in a successful end scenario, and avoid unnecessary losses in an unsuccessful end scenario.

Final Report: Pilot Region-Based Optimization Program for Fund-Lead Sites, EPA Region III

EPA Pesticide Factsheets

This report describes a pilot study for a Region-based optimization program, implemented by a Regional Optimization Evaluation Team (ROET) that was conducted in U.S. EPA Region III at Fund-lead sites with pump-and-treat (P&T) systems.

Rational Design of Novel 1,3-Oxazine Based β-Secretase (BACE1) Inhibitors: Incorporation of a Double Bond To Reduce P-gp Efflux Leading to Robust Aβ Reduction in the Brain.

PubMed

Fuchino, Kouki; Mitsuoka, Yasunori; Masui, Moriyasu; Kurose, Noriyuki; Yoshida, Shuhei; Komano, Kazuo; Yamamoto, Takahiko; Ogawa, Masayoshi; Unemura, Chie; Hosono, Motoko; Ito, Hisanori; Sakaguchi, Gaku; Ando, Shigeru; Ohnishi, Shuichi; Kido, Yasuto; Fukushima, Tamio; Miyajima, Hirofumi; Hiroyama, Shuichi; Koyabu, Kiyotaka; Dhuyvetter, Deborah; Borghys, Herman; Gijsen, Harrie J M; Yamano, Yoshinori; Iso, Yasuyoshi; Kusakabe, Ken-Ichi

2018-05-23

Accumulation of Aβ peptides is a hallmark of Alzheimer's disease (AD) and is considered a causal factor in the pathogenesis of AD. β-Secretase (BACE1) is a key enzyme responsible for producing Aβ peptides, and thus agents that inhibit BACE1 should be beneficial for disease-modifying treatment of AD. Here we describe the discovery and optimization of novel oxazine-based BACE1 inhibitors by lowering amidine basicity with the incorporation of a double bond to improve brain penetration. Starting from a 1,3-dihydrooxazine lead 6 identified by a hit-to-lead SAR following HTS, we adopted a p K a lowering strategy to reduce the P-gp efflux and the high hERG potential leading to the discovery of 15 that produced significant Aβ reduction with long duration in pharmacodynamic models and exhibited wide safety margins in cardiovascular safety models. This compound improved the brain-to-plasma ratio relative to 6 by reducing P-gp recognition, which was demonstrated by a P-gp knockout mouse model.

Design feasibility via ascent optimality for next-generation spacecraft

NASA Astrophysics Data System (ADS)

Miele, A.; Mancuso, S.

This paper deals with the optimization of the ascent trajectories for single-stage-sub-orbit (SSSO), single-stage-to-orbit (SSTO), and two-stage-to-orbit (TSTO) rocket-powered spacecraft. The maximum payload weight problem is studied for different values of the engine specific impulse and spacecraft structural factor. The main conclusions are that: feasibility of SSSO spacecraft is guaranteed for all the parameter combinations considered; feasibility of SSTO spacecraft depends strongly on the parameter combination chosen; not only feasibility of TSTO spacecraft is guaranteed for all the parameter combinations considered, but the TSTO payload is several times the SSTO payload. Improvements in engine specific impulse and spacecraft structural factor are desirable and crucial for SSTO feasibility; indeed, aerodynamic improvements do not yield significant improvements in payload. For SSSO, SSTO, and TSTO spacecraft, simple engineering approximations are developed connecting the maximum payload weight to the engine specific impulse and spacecraft structural factor. With reference to the specific impulse/structural factor domain, these engineering approximations lead to the construction of zero-payload lines separating the feasibility region (positive payload) from the unfeasibility region (negative payload).

Optimizing the performance and structure of the D0 Collie confidence limit evaluator

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

Fishchler, Mark; /Fermilab

2010-07-01

D0 Collie is a program used to perform limit calculations based on ensembles of pseudo-experiments ('PEs'). Since the application of this program to the crucial Higgs mass limit is quite CPU intensive, it has been deemed important to carefully review this program, with an eye toward identifying and implementing potential performance improvements. At the same time, we identify any coding errors or opportunities for potential structural (or algorithm) improvement discovered in the course of gaining sufficient understanding of the workings of Collie to sensibly explore for optimizations. Based on a careful analysis of the program, a series of code changesmore » with potential for improving performance has been identified. The implementation and evaluation of the most important parts of this series has been done, with gratifying speedup results. The bottom line: We have identified and implemented changes leading to a factor of 2.19 speedup in the example program provided, and expected to translate to a factor of roughly 4 speedup in typical realistic usage.« less

Research and development for improved lead-salt diode lasers

NASA Technical Reports Server (NTRS)

Butler, J. F.

1976-01-01

A substantial increase in output power levels for lead-salt diode lasers, through the development of improved fabrication methods, as demonstrated. The goal of 1 mW of CW, single-mode, single-ended power output, was achieved, with exceptional devices exhibiting values greater than 8 mW. It was found that the current tuning rate could be controlled by adjusting the p-n junction depth, allowing the tuning rate to be optimized for particular applications. An unexpected phenomenon was encountered when crystal composition was observed to be significantly altered by annealing at temperatures as low as 600 C; the composition was changed by transport of material through the vapor phase. This effect caused problems in obtaining diode lasers with the desired operating characteristics. It was discovered that the present packaging method introduces gross damaging effects in the laser crystal through pressure applied by the C-bend.

Synthesis and biological evaluation of arctigenin ester and ether derivatives as activators of AMPK.

PubMed

Shen, Sida; Zhuang, Jingjing; Chen, Yijia; Lei, Min; Chen, Jing; Shen, Xu; Hu, Lihong

2013-07-01

A series of new arctigenin and 9-deoxy-arctigenin derivatives bearing different ester and ether side chains at the phenolic hydroxyl positions are designed, synthesized, and evaluated for activating AMPK potency in L6 myoblasts. Initial biological evaluation indicates that some alkyl ester and phenethyl ether arctigenin derivatives display potential activities in AMPK phosphorylation improvement. Further structure-activity relationship analysis shows that arctigenin ester derivatives 3a, 3h and 9-deoxy-arctigenin phenethyl ether derivatives 6a, 6c, 6d activate AMPK more potently than arctigenin. Moreover, the 2-(3,4-dimethoxyphenyl)ethyl ether moiety of 6c has been demonstrated as a potential functional group to improve the effect of AMPK phosphorylation. The structural optimization of arctigenin leads to the identification of 6c as a promising lead compound that exhibits excellent activity in AMPK activation. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Algorithms for the optimization of RBE-weighted dose in particle therapy.

PubMed

Horcicka, M; Meyer, C; Buschbacher, A; Durante, M; Krämer, M

2013-01-21

We report on various algorithms used for the nonlinear optimization of RBE-weighted dose in particle therapy. Concerning the dose calculation carbon ions are considered and biological effects are calculated by the Local Effect Model. Taking biological effects fully into account requires iterative methods to solve the optimization problem. We implemented several additional algorithms into GSI's treatment planning system TRiP98, like the BFGS-algorithm and the method of conjugated gradients, in order to investigate their computational performance. We modified textbook iteration procedures to improve the convergence speed. The performance of the algorithms is presented by convergence in terms of iterations and computation time. We found that the Fletcher-Reeves variant of the method of conjugated gradients is the algorithm with the best computational performance. With this algorithm we could speed up computation times by a factor of 4 compared to the method of steepest descent, which was used before. With our new methods it is possible to optimize complex treatment plans in a few minutes leading to good dose distributions. At the end we discuss future goals concerning dose optimization issues in particle therapy which might benefit from fast optimization solvers.

Axiomatic Design of a Framework for the Comprehensive Optimization of Patient Flows in Hospitals

PubMed Central

Matt, Dominik T.

2017-01-01

Lean Management and Six Sigma are nowadays applied not only to the manufacturing industry but also to service industry and public administration. The manifold variables affecting the Health Care system minimize the effect of a narrow Lean intervention. Therefore, this paper aims to discuss a comprehensive, system-based approach to achieve a factual holistic optimization of patient flows. This paper debates the efficacy of Lean principles applied to the optimization of patient flows and related activities, structures, and resources, developing a theoretical framework based on the principles of the Axiomatic Design. The demand for patient-oriented and efficient health services leads to use these methodologies to improve hospital processes. In the framework, patients with similar characteristics are clustered in families to achieve homogeneous flows through the value stream. An optimization checklist is outlined as the result of the mapping between Functional Requirements and Design Parameters, with the right sequence of the steps to optimize the patient flow according to the principles of Axiomatic Design. The Axiomatic Design-based top-down implementation of Health Care evidence, according to Lean principles, results in a holistic optimization of hospital patient flows, by reducing the complexity of the system. PMID:29065578

Algorithms for the optimization of RBE-weighted dose in particle therapy

NASA Astrophysics Data System (ADS)

Horcicka, M.; Meyer, C.; Buschbacher, A.; Durante, M.; Krämer, M.

2013-01-01

We report on various algorithms used for the nonlinear optimization of RBE-weighted dose in particle therapy. Concerning the dose calculation carbon ions are considered and biological effects are calculated by the Local Effect Model. Taking biological effects fully into account requires iterative methods to solve the optimization problem. We implemented several additional algorithms into GSI's treatment planning system TRiP98, like the BFGS-algorithm and the method of conjugated gradients, in order to investigate their computational performance. We modified textbook iteration procedures to improve the convergence speed. The performance of the algorithms is presented by convergence in terms of iterations and computation time. We found that the Fletcher-Reeves variant of the method of conjugated gradients is the algorithm with the best computational performance. With this algorithm we could speed up computation times by a factor of 4 compared to the method of steepest descent, which was used before. With our new methods it is possible to optimize complex treatment plans in a few minutes leading to good dose distributions. At the end we discuss future goals concerning dose optimization issues in particle therapy which might benefit from fast optimization solvers.

Low NOx combustion and SCR flow field optimization in a low volatile coal fired boiler.

PubMed

Liu, Xing; Tan, Houzhang; Wang, Yibin; Yang, Fuxin; Mikulčić, Hrvoje; Vujanović, Milan; Duić, Neven

2018-08-15

Low NO x burner redesign and deep air staging have been carried out to optimize the poor ignition and reduce the NO x emissions in a low volatile coal fired 330 MW e boiler. Residual swirling flow in the tangentially-fired furnace caused flue gas velocity deviations at furnace exit, leading to flow field unevenness in the SCR (selective catalytic reduction) system and poor denitrification efficiency. Numerical simulations on the velocity field in the SCR system were carried out to determine the optimal flow deflector arrangement to improve flow field uniformity of SCR system. Full-scale experiment was performed to investigate the effect of low NO x combustion and SCR flow field optimization. Compared with the results before the optimization, the NO x emissions at furnace exit decreased from 550 to 650 mg/Nm³ to 330-430 mg/Nm³. The sample standard deviation of the NO x emissions at the outlet section of SCR decreased from 34.8 mg/Nm³ to 7.8 mg/Nm³. The consumption of liquid ammonia reduced from 150 to 200 kg/h to 100-150 kg/h after optimization. Copyright © 2018. Published by Elsevier Ltd.

Multiobjective Multifactorial Optimization in Evolutionary Multitasking.

PubMed

Gupta, Abhishek; Ong, Yew-Soon; Feng, Liang; Tan, Kay Chen

2016-05-03

In recent decades, the field of multiobjective optimization has attracted considerable interest among evolutionary computation researchers. One of the main features that makes evolutionary methods particularly appealing for multiobjective problems is the implicit parallelism offered by a population, which enables simultaneous convergence toward the entire Pareto front. While a plethora of related algorithms have been proposed till date, a common attribute among them is that they focus on efficiently solving only a single optimization problem at a time. Despite the known power of implicit parallelism, seldom has an attempt been made to multitask, i.e., to solve multiple optimization problems simultaneously. It is contended that the notion of evolutionary multitasking leads to the possibility of automated transfer of information across different optimization exercises that may share underlying similarities, thereby facilitating improved convergence characteristics. In particular, the potential for automated transfer is deemed invaluable from the standpoint of engineering design exercises where manual knowledge adaptation and reuse are routine. Accordingly, in this paper, we present a realization of the evolutionary multitasking paradigm within the domain of multiobjective optimization. The efficacy of the associated evolutionary algorithm is demonstrated on some benchmark test functions as well as on a real-world manufacturing process design problem from the composites industry.

Optimization of Error-Bounded Lossy Compression for Hard-to-Compress HPC Data

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

Di, Sheng; Cappello, Franck

Since today’s scientific applications are producing vast amounts of data, compressing them before storage/transmission is critical. Results of existing compressors show two types of HPC data sets: highly compressible and hard to compress. In this work, we carefully design and optimize the error-bounded lossy compression for hard-tocompress scientific data. We propose an optimized algorithm that can adaptively partition the HPC data into best-fit consecutive segments each having mutually close data values, such that the compression condition can be optimized. Another significant contribution is the optimization of shifting offset such that the XOR-leading-zero length between two consecutive unpredictable data points canmore » be maximized. We finally devise an adaptive method to select the best-fit compressor at runtime for maximizing the compression factor. We evaluate our solution using 13 benchmarks based on real-world scientific problems, and we compare it with 9 other state-of-the-art compressors. Experiments show that our compressor can always guarantee the compression errors within the user-specified error bounds. Most importantly, our optimization can improve the compression factor effectively, by up to 49% for hard-tocompress data sets with similar compression/decompression time cost.« less

Axiomatic Design of a Framework for the Comprehensive Optimization of Patient Flows in Hospitals.

PubMed

Arcidiacono, Gabriele; Matt, Dominik T; Rauch, Erwin

2017-01-01

Lean Management and Six Sigma are nowadays applied not only to the manufacturing industry but also to service industry and public administration. The manifold variables affecting the Health Care system minimize the effect of a narrow Lean intervention. Therefore, this paper aims to discuss a comprehensive, system-based approach to achieve a factual holistic optimization of patient flows. This paper debates the efficacy of Lean principles applied to the optimization of patient flows and related activities, structures, and resources, developing a theoretical framework based on the principles of the Axiomatic Design. The demand for patient-oriented and efficient health services leads to use these methodologies to improve hospital processes. In the framework, patients with similar characteristics are clustered in families to achieve homogeneous flows through the value stream. An optimization checklist is outlined as the result of the mapping between Functional Requirements and Design Parameters, with the right sequence of the steps to optimize the patient flow according to the principles of Axiomatic Design. The Axiomatic Design-based top-down implementation of Health Care evidence, according to Lean principles, results in a holistic optimization of hospital patient flows, by reducing the complexity of the system.

Axiomatic Design of a Framework for the Comprehensive Optimization of Patient Flows in Hospitals

PubMed

Arcidiacono, Gabriele; Matt, Dominik T.; Rauch, Erwin

2017-01-01

Lean Management and Six Sigma are nowadays applied not only to the manufacturing industry but also to service industry and public administration. The manifold variables affecting the Health Care system minimize the effect of a narrow Lean intervention. Therefore, this paper aims to discuss a comprehensive, system-based approach to achieve a factual holistic optimization of patient flows. This paper debates the efficacy of Lean principles applied to the optimization of patient flows and related activities, structures, and resources, developing a theoretical framework based on the principles of the Axiomatic Design. The demand for patient-oriented and efficient health services leads to use these methodologies to improve hospital processes. In the framework, patients with similar characteristics are clustered in families to achieve homogeneous flows through the value stream. An optimization checklist is outlined as the result of the mapping between Functional Requirements and Design Parameters, with the right sequence of the steps to optimize the patient flow according to the principles of Axiomatic Design. The Axiomatic Design-based top-down implementation of Health Care evidence, according to Lean principles, results in a holistic optimization of hospital patient flows, by reducing the complexity of the system. © 2017 Gabriele Arcidiacono et al.

A new method for determining the optimal lagged ensemble

PubMed Central

DelSole, T.; Tippett, M. K.; Pegion, K.

2017-01-01

Abstract We propose a general methodology for determining the lagged ensemble that minimizes the mean square forecast error. The MSE of a lagged ensemble is shown to depend only on a quantity called the cross‐lead error covariance matrix, which can be estimated from a short hindcast data set and parameterized in terms of analytic functions of time. The resulting parameterization allows the skill of forecasts to be evaluated for an arbitrary ensemble size and initialization frequency. Remarkably, the parameterization also can estimate the MSE of a burst ensemble simply by taking the limit of an infinitely small interval between initialization times. This methodology is applied to forecasts of the Madden Julian Oscillation (MJO) from version 2 of the Climate Forecast System version 2 (CFSv2). For leads greater than a week, little improvement is found in the MJO forecast skill when ensembles larger than 5 days are used or initializations greater than 4 times per day. We find that if the initialization frequency is too infrequent, important structures of the lagged error covariance matrix are lost. Lastly, we demonstrate that the forecast error at leads ≥10 days can be reduced by optimally weighting the lagged ensemble members. The weights are shown to depend only on the cross‐lead error covariance matrix. While the methodology developed here is applied to CFSv2, the technique can be easily adapted to other forecast systems. PMID:28580050

Tin and germanium based two-dimensional Ruddlesden-Popper hybrid perovskites for potential lead-free photovoltaic and photoelectronic applications.

PubMed

Ma, Liang; Ju, Ming-Gang; Dai, Jun; Zeng, Xiao Cheng

2018-06-21

Despite their high power conversion efficiency, the commercial applications of hybrid organic-inorganic lead (Pb) halide perovskite based solar cells are still hampered by concerns about the toxicity of Pb and the structural stability in open air. Herein, based on density-functional theory computation, we show that lead-free tin (Sn) and germanium (Ge) based two-dimensional (2D) Ruddlesden-Popper hybrid organic-inorganic perovskites with a thickness of a few unit-cells, BA2MAn-1MnI3n+1 (M = Sn or Ge, n = 2-4), possess desirable electronic, excitonic and light absorption properties, thereby showing promise for photovoltaic and/or photoelectronic applications. In particular, we show that by increasing the layer thickness of the Sn-based 2D perovskites, the bandgap can be lowered towards the optimal range (0.9-1.6 eV) for solar cells. Meanwhile, the exciton binding energy is reduced to a more optimal value. In addition, theoretical assessment indicates that the thermodynamic stability of Sn-/Ge-based 2D perovskites is notably enhanced compared to that of their 3D analogues. These features render the Sn-/Ge-based 2D hybrid perovskites with a thickness of a few tens of unit cells promising lead-free perovskites with much improved structural stabilities for photovoltaic and/or photoelectronic applications.

Modeling and optimization of a concentrated solar supercritical CO2 power plant

NASA Astrophysics Data System (ADS)

Osorio, Julian D.

Renewable energy sources are fundamental alternatives to supply the rising energy demand in the world and to reduce or replace fossil fuel technologies. In order to make renewable-based technologies suitable for commercial and industrial applications, two main challenges need to be solved: the design and manufacture of highly efficient devices and reliable systems to operate under intermittent energy supply conditions. In particular, power generation technologies based on solar energy are one of the most promising alternatives to supply the world energy demand and reduce the dependence on fossil fuel technologies. In this dissertation, the dynamic behavior of a Concentrated Solar Power (CSP) supercritical CO2 cycle is studied under different seasonal conditions. The system analyzed is composed of a central receiver, hot and cold thermal energy storage units, a heat exchanger, a recuperator, and multi-stage compression-expansion subsystems with intercoolers and reheaters between compressors and turbines respectively. The effects of operating and design parameters on the system performance are analyzed. Some of these parameters are the mass flow rate, intermediate pressures, number of compression-expansion stages, heat exchangers' effectiveness, multi-tank thermal energy storage, overall heat transfer coefficient between the solar receiver and the environment and the effective area of the recuperator. Energy and exergy models for each component of the system are developed to optimize operating parameters in order to lead to maximum efficiency. From the exergy analysis, the components with high contribution to exergy destruction were identified. These components, which represent an important potential of improvement, are the recuperator, the hot thermal energy storage tank and the solar receiver. Two complementary alternatives to improve the efficiency of concentrated solar thermal systems are proposed in this dissertation: the optimization of the system's operating parameters and optimization of less efficient components. The parametric optimization is developed for a 1MW reference CSP system with CO2 as the working fluid. The component optimization, focused on the less efficient components, comprises some design modifications to the traditional component configuration for the recuperator, the hot thermal energy storage tank and the solar receiver. The proposed optimization alternatives include the heat exchanger's effectiveness enhancement by optimizing fins shapes, multi-tank thermal energy storage configurations for the hot thermal energy storage tank and the incorporation of a transparent insulation material into the solar receiver. Some of the optimizations are conducted in a generalized way, using dimensionless models to be applicable no only to the CSP but also to other thermal systems. This project is therefore an effort to improve the efficiency of power generation systems based on solar energy in order to make them competitive with conventional fossil fuel power generation devices. The results show that the parametric optimization leads the system to an efficiency of about 21% and a maximum power output close to 1.5 MW. The process efficiencies obtained in this work, of more than 21%, are relatively good for a solar-thermal conversion system and are also comparable with efficiencies of conversion of high performance PV panels. The thermal energy storage allows the system to operate for several hours after sunset. This operating time is approximately increased from 220 to 480 minutes after optimization. The hot and cold thermal energy storage also lessens the temperature fluctuations by providing smooth changes of temperatures at the turbines' and compressors' inlets. Additional improvements in the overall system efficiency are possible by optimizing the less efficient components. In particular, the fin's effectiveness can be improved in more than 5% after its shape is optimized, increments in the efficiency of the thermal energy storage of about 5.7% are possible when the mass is divided into four tanks, and solar receiver efficiencies up to 70% can be maintained for high operating temperatures (~ 1200°C) when a transparent insulation material is incorporated to the receiver. The results obtained in this dissertation indicate that concentrated solar systems using supercritical CO2 could be a viable alternative to satisfying energy needs in desert areas with scarce water and fossil fuel resources.

Optimization of Pockels electric field in transverse modulated optical voltage sensor

NASA Astrophysics Data System (ADS)

Huang, Yifan; Xu, Qifeng; Chen, Kun-Long; Zhou, Jie

2018-05-01

This paper investigates the possibilities of optimizing the Pockels electric field in a transverse modulated optical voltage sensor with a spherical electrode structure. The simulations show that due to the edge effect and the electric field concentrations and distortions, the electric field distributions in the crystal are non-uniform. In this case, a tiny variation in the light path leads to an integral error of more than 0.5%. Moreover, a 2D model cannot effectively represent the edge effect, so a 3D model is employed to optimize the electric field distributions. Furthermore, a new method to attach a quartz crystal to the electro-optic crystal along the electric field direction is proposed to improve the non-uniformity of the electric field. The integral error is reduced therefore from 0.5% to 0.015% and less. The proposed method is simple, practical and effective, and it has been validated by numerical simulations and experimental tests.

Turbopump Performance Improved by Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Oyama, Akira; Liou, Meng-Sing

2002-01-01

The development of design optimization technology for turbomachinery has been initiated using the multiobjective evolutionary algorithm under NASA's Intelligent Synthesis Environment and Revolutionary Aeropropulsion Concepts programs. As an alternative to the traditional gradient-based methods, evolutionary algorithms (EA's) are emergent design-optimization algorithms modeled after the mechanisms found in natural evolution. EA's search from multiple points, instead of moving from a single point. In addition, they require no derivatives or gradients of the objective function, leading to robustness and simplicity in coupling any evaluation codes. Parallel efficiency also becomes very high by using a simple master-slave concept for function evaluations, since such evaluations often consume the most CPU time, such as computational fluid dynamics. Application of EA's to multiobjective design problems is also straightforward because EA's maintain a population of design candidates in parallel. Because of these advantages, EA's are a unique and attractive approach to real-world design optimization problems.

An Optimal Design for Placements of Tsunami Observing Systems Around the Nankai Trough, Japan

NASA Astrophysics Data System (ADS)

Mulia, I. E.; Gusman, A. R.; Satake, K.

2017-12-01

Presently, there are numerous tsunami observing systems deployed in several major tsunamigenic regions throughout the world. However, documentations on how and where to optimally place such measurement devices are limited. This study presents a methodological approach to select the best and fewest observation points for the purpose of tsunami source characterizations, particularly in the form of fault slip distributions. We apply the method to design a new tsunami observation network around the Nankai Trough, Japan. In brief, our method can be divided into two stages: initialization and optimization. The initialization stage aims to identify favorable locations of observation points, as well as to determine the initial number of observations. These points are generated based on extrema of an empirical orthogonal function (EOF) spatial modes derived from 11 hypothetical tsunami events in the region. In order to further improve the accuracy, we apply an optimization algorithm called a mesh adaptive direct search (MADS) to remove redundant measurements from the initially generated points by the first stage. A combinatorial search by the MADS will improve the accuracy and reduce the number of observations simultaneously. The EOF analysis of the hypothetical tsunamis using first 2 leading modes with 4 extrema on each mode results in 30 observation points spread along the trench. This is obtained after replacing some clustered points within the radius of 30 km with only one representative. Furthermore, the MADS optimization can improve the accuracy of the EOF-generated points by approximately 10-20% with fewer observations (23 points). Finally, we compare our result with the existing observation points (68 stations) in the region. The result shows that the optimized design with fewer number of observations can produce better source characterizations with approximately 20-60% improvement of accuracies at all the 11 hypothetical cases. It should be note, however, that our design is a tsunami-based approach, some of the existing observing systems are equipped with additional devices to measure other parameter of interests, i.e., for monitoring seismic activities.

Crystal Growth and Dissolution of Methylammonium Lead Iodide Perovskite in Sequential Deposition: Correlation between Morphology Evolution and Photovoltaic Performance.

PubMed

Hsieh, Tsung-Yu; Huang, Chi-Kai; Su, Tzu-Sen; Hong, Cheng-You; Wei, Tzu-Chien

2017-03-15

Crystal morphology and structure are important for improving the organic-inorganic lead halide perovskite semiconductor property in optoelectronic, electronic, and photovoltaic devices. In particular, crystal growth and dissolution are two major phenomena in determining the morphology of methylammonium lead iodide perovskite in the sequential deposition method for fabricating a perovskite solar cell. In this report, the effect of immersion time in the second step, i.e., methlyammonium iodide immersion in the morphological, structural, optical, and photovoltaic evolution, is extensively investigated. Supported by experimental evidence, a five-staged, time-dependent evolution of the morphology of methylammonium lead iodide perovskite crystals is established and is well connected to the photovoltaic performance. This result is beneficial for engineering optimal time for methylammonium iodide immersion and converging the solar cell performance in the sequential deposition route. Meanwhile, our result suggests that large, well-faceted methylammonium lead iodide perovskite single crystal may be incubated by solution process. This offers a low cost route for synthesizing perovskite single crystal.

Determination of lead at trace levels in mussel and sea water samples using vortex assisted dispersive liquid-liquid microextraction-slotted quartz tube-flame atomic absorption spectrometry.

PubMed

Erarpat, Sezin; Özzeybek, Gözde; Chormey, Dotse Selali; Bakırdere, Sezgin

2017-12-01

In this study, dispersive liquid-liquid microextraction (DLLME) and slotted quartz tube (SQT) were coupled to flame atomic absorption spectrometry (FAAS) to increase the sensitivity of lead. Conditions such as the formation of the lead-dithizone complex, efficiency of the DLLME method and the output of the SQT were systematically optimized to improve the detection limit for the analyte. The conventional FAAS system was improved upon by about 3.0 times with SQT-FAAS, 32 times with DLLME-FAAS and 142 times with DLLME-SQT-FAAS. The method was applicable over a wide linear range (10-500 μg L -1 ). The limit of detection (LOD) determined by DLLME-SQT-FAAS for seawater and mussel were 2.7 μg L -1 and 270 μg kg -1 , respectively. The percent recoveries obtained for mussel and seawater samples (spiked at 20 and 50 μg L -1 ) were 95-96% and 98-110%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization model for the allocation of water resources based on the maximization of employment in the agriculture and industry sectors

NASA Astrophysics Data System (ADS)

Habibi Davijani, M.; Banihabib, M. E.; Nadjafzadeh Anvar, A.; Hashemi, S. R.

2016-02-01

In many discussions, work force is mentioned as the most important factor of production. Principally, work force is a factor which can compensate for the physical and material limitations and shortcomings of other factors to a large extent which can help increase the production level. On the other hand, employment is considered as an effective factor in social issues. The goal of the present research is the allocation of water resources so as to maximize the number of jobs created in the industry and agriculture sectors. An objective that has attracted the attention of policy makers involved in water supply and distribution is the maximization of the interests of beneficiaries and consumers in case of certain policies adopted. The present model applies the particle swarm optimization (PSO) algorithm in order to determine the optimum amount of water allocated to each water-demanding sector, area under cultivation, agricultural production, employment in the agriculture sector, industrial production and employment in the industry sector. Based on the results obtained from this research, by optimally allocating water resources in the central desert region of Iran, 1096 jobs can be created in the industry and agriculture sectors, which constitutes an improvement of about 13% relative to the previous situation (non-optimal water utilization). It is also worth mentioning that by optimizing the employment factor as a social parameter, the other areas such as the economic sector are influenced as well. For example, in this investigation, the resulting economic benefits (incomes) have improved from 73 billion Rials at baseline employment figures to 112 billion Rials in the case of optimized employment condition. Therefore, it is necessary to change the inter-sector and intra-sector water allocation models in this region, because this change not only leads to more jobs in this area, but also causes an improvement in the region's economic conditions.

Design and control of a novel two-speed Uninterrupted Mechanical Transmission for electric vehicles

NASA Astrophysics Data System (ADS)

Fang, Shengnan; Song, Jian; Song, Haijun; Tai, Yuzhuo; Li, Fei; Sinh Nguyen, Truong

2016-06-01

Conventional all-electric vehicles (EV) adopt single-speed transmission due to its low cost and simple construction. However, with the adoption of this type of driveline system, development of EV technology leads to the growing performance requirements of drive motor. Introducing a multi-speed or two-speed transmission to EV offers the possibility of efficiency improvement of the whole powertrain. This paper presents an innovative two-speed Uninterrupted Mechanical Transmission (UMT), which consists of an epicyclic gearing system, a centrifugal clutch and a brake band, allowing the seamless shifting between two gears. Besides, driver's intention is recognized by the control system which is based on fuzzy logic controller (FLC), utilizing the signals of vehicle velocity and accelerator pedal position. The novel UMT shows better dynamic and comfort performance in compare with the optimized AMT with the same gear ratios. Comparison between the control strategy with recognition of driver intention and the conventional two-parameter gear shifting strategy is presented. And the simulation and analysis of the middle layer of optimal gearshift control algorithm is detailed. The results indicate that the UMT adopting FLC and optimal control method provides a significant improvement of energy efficiency, dynamic performance and shifting comfort for EV.

Optimized, unequal pulse spacing in multiple echo sequences improves refocusing in magnetic resonance.

PubMed

Jenista, Elizabeth R; Stokes, Ashley M; Branca, Rosa Tamara; Warren, Warren S

2009-11-28

A recent quantum computing paper (G. S. Uhrig, Phys. Rev. Lett. 98, 100504 (2007)) analytically derived optimal pulse spacings for a multiple spin echo sequence designed to remove decoherence in a two-level system coupled to a bath. The spacings in what has been called a "Uhrig dynamic decoupling (UDD) sequence" differ dramatically from the conventional, equal pulse spacing of a Carr-Purcell-Meiboom-Gill (CPMG) multiple spin echo sequence. The UDD sequence was derived for a model that is unrelated to magnetic resonance, but was recently shown theoretically to be more general. Here we show that the UDD sequence has theoretical advantages for magnetic resonance imaging of structured materials such as tissue, where diffusion in compartmentalized and microstructured environments leads to fluctuating fields on a range of different time scales. We also show experimentally, both in excised tissue and in a live mouse tumor model, that optimal UDD sequences produce different T(2)-weighted contrast than do CPMG sequences with the same number of pulses and total delay, with substantial enhancements in most regions. This permits improved characterization of low-frequency spectral density functions in a wide range of applications.

The PDB_REDO server for macromolecular structure model optimization.

PubMed

Joosten, Robbie P; Long, Fei; Murshudov, Garib N; Perrakis, Anastassis

2014-07-01

The refinement and validation of a crystallographic structure model is the last step before the coordinates and the associated data are submitted to the Protein Data Bank (PDB). The success of the refinement procedure is typically assessed by validating the models against geometrical criteria and the diffraction data, and is an important step in ensuring the quality of the PDB public archive [Read et al. (2011 ▶), Structure, 19, 1395-1412]. The PDB_REDO procedure aims for 'constructive validation', aspiring to consistent and optimal refinement parameterization and pro-active model rebuilding, not only correcting errors but striving for optimal interpretation of the electron density. A web server for PDB_REDO has been implemented, allowing thorough, consistent and fully automated optimization of the refinement procedure in REFMAC and partial model rebuilding. The goal of the web server is to help practicing crystallo-graphers to improve their model prior to submission to the PDB. For this, additional steps were implemented in the PDB_REDO pipeline, both in the refinement procedure, e.g. testing of resolution limits and k-fold cross-validation for small test sets, and as new validation criteria, e.g. the density-fit metrics implemented in EDSTATS and ligand validation as implemented in YASARA. Innovative ways to present the refinement and validation results to the user are also described, which together with auto-generated Coot scripts can guide users to subsequent model inspection and improvement. It is demonstrated that using the server can lead to substantial improvement of structure models before they are submitted to the PDB.

The PDB_REDO server for macromolecular structure model optimization

PubMed Central

Joosten, Robbie P.; Long, Fei; Murshudov, Garib N.; Perrakis, Anastassis

2014-01-01

The refinement and validation of a crystallographic structure model is the last step before the coordinates and the associated data are submitted to the Protein Data Bank (PDB). The success of the refinement procedure is typically assessed by validating the models against geometrical criteria and the diffraction data, and is an important step in ensuring the quality of the PDB public archive [Read et al. (2011 ▶), Structure, 19, 1395–1412]. The PDB_REDO procedure aims for ‘constructive validation’, aspiring to consistent and optimal refinement parameterization and pro-active model rebuilding, not only correcting errors but striving for optimal interpretation of the electron density. A web server for PDB_REDO has been implemented, allowing thorough, consistent and fully automated optimization of the refinement procedure in REFMAC and partial model rebuilding. The goal of the web server is to help practicing crystallo­graphers to improve their model prior to submission to the PDB. For this, additional steps were implemented in the PDB_REDO pipeline, both in the refinement procedure, e.g. testing of resolution limits and k-fold cross-validation for small test sets, and as new validation criteria, e.g. the density-fit metrics implemented in EDSTATS and ligand validation as implemented in YASARA. Innovative ways to present the refinement and validation results to the user are also described, which together with auto-generated Coot scripts can guide users to subsequent model inspection and improvement. It is demonstrated that using the server can lead to substantial improvement of structure models before they are submitted to the PDB. PMID:25075342

Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements

PubMed Central

Whitaker, May

2016-01-01

Purpose Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. Material and methods This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. Results The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. Conclusions The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected. PMID:27504129

Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements.

PubMed

Poder, Joel; Whitaker, May

2016-06-01

Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected.

Spatial enhancement of ECG using diagnostic similarity score based lead selective multi-scale linear model.

PubMed

Nallikuzhy, Jiss J; Dandapat, S

2017-06-01

In this work, a new patient-specific approach to enhance the spatial resolution of ECG is proposed and evaluated. The proposed model transforms a three-lead ECG into a standard twelve-lead ECG thereby enhancing its spatial resolution. The three leads used for prediction are obtained from the standard twelve-lead ECG. The proposed model takes advantage of the improved inter-lead correlation in wavelet domain. Since the model is patient-specific, it also selects the optimal predictor leads for a given patient using a lead selection algorithm. The lead selection algorithm is based on a new diagnostic similarity score which computes the diagnostic closeness between the original and the spatially enhanced leads. Standard closeness measures are used to assess the performance of the model. The similarity in diagnostic information between the original and the spatially enhanced leads are evaluated using various diagnostic measures. Repeatability and diagnosability are performed to quantify the applicability of the model. A comparison of the proposed model is performed with existing models that transform a subset of standard twelve-lead ECG into the standard twelve-lead ECG. From the analysis of the results, it is evident that the proposed model preserves diagnostic information better compared to other models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Epidural anaesthesia and analgesia - effects on surgical stress responses and implications for postoperative nutrition.

PubMed

Holte, K; Kehlet, H

2002-06-01

Surgical injury leads to an endocrine-metabolic and inflammatory response with protein catabolism, increased cardiovascular demands, impaired pulmonary function and paralytic ileus, the most important release mechanisms being afferent neural stimuli and inflammatory mediators. Epidural local anaesthetic blockade of afferent stimuli reduces endocrine metabolic responses, and improve postoperative catabolism. Furthermore, dynamic pain relief is achieved with improved pulmonary function and a pronounced reduction of postoperative ileus, thereby providing optimal conditions for improved mobilization and oral nutrition, and preservation of body composition and muscle function. Studies integrating continuous epidural local anaesthetics with enforced early nutrition and mobilization uniformly suggest an improved recovery, decreased hospital stay and convalescence. Epidural local anaesthetics should be included in a multi-modal rehabilitation programme after major surgical procedures in order to facilitate oral nutrition, improve recovery and reduce morbidity.

Study on optimization of the short-term operation of cascade hydropower stations by considering output error

NASA Astrophysics Data System (ADS)

Wang, Liping; Wang, Boquan; Zhang, Pu; Liu, Minghao; Li, Chuangang

2017-06-01

The study of reservoir deterministic optimal operation can improve the utilization rate of water resource and help the hydropower stations develop more reasonable power generation schedules. However, imprecise forecasting inflow may lead to output error and hinder implementation of power generation schedules. In this paper, output error generated by the uncertainty of the forecasting inflow was regarded as a variable to develop a short-term reservoir optimal operation model for reducing operation risk. To accomplish this, the concept of Value at Risk (VaR) was first applied to present the maximum possible loss of power generation schedules, and then an extreme value theory-genetic algorithm (EVT-GA) was proposed to solve the model. The cascade reservoirs of Yalong River Basin in China were selected as a case study to verify the model, according to the results, different assurance rates of schedules can be derived by the model which can present more flexible options for decision makers, and the highest assurance rate can reach 99%, which is much higher than that without considering output error, 48%. In addition, the model can greatly improve the power generation compared with the original reservoir operation scheme under the same confidence level and risk attitude. Therefore, the model proposed in this paper can significantly improve the effectiveness of power generation schedules and provide a more scientific reference for decision makers.

Optimization on Fc for Improvement of Stability and Aggregation Resistance.

PubMed

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

2016-01-01

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

Molecular basis of the potential of vitamin D to prevent cancer.

PubMed

Ingraham, Betty A; Bragdon, Beth; Nohe, Anja

2008-01-01

To review current research findings in cell biology, epidemiology, preclinical, and clinical trials on the protective effects of vitamin D against the development of cancers of the breast, colon, prostate, lung, and ovary. Current recommendations for optimal vitamin D status, the movement towards revision of standards, and reflections on healthy exposure to sunlight are also reviewed. Search methodology: A literature search was conducted in April and updated in September 2007. The Medline and Web of Knowledge databases were searched for primary and review articles published between 1970 and 2007, using the search terms 'vitamin D', 'calcitriol', 'cancer', 'chemoprevention', 'nuclear receptor', 'vitamin D receptor', 'apoptosis', 'cell cycle', 'epidemiology', and 'cell adhesion molecule'. Articles that focused on epidemiological, preclinical, and clinical evidence for vitamin D's effects were selected and additional articles were obtained from reference lists of the retrieved articles. An increasing body of research supports the hypothesis that the active form of vitamin D has significant, protective effects against the development of cancer. Epidemiological studies show an inverse association between sun exposure, serum levels of 25(OH)D, and intakes of vitamin D and risk of developing and/or surviving cancer. The protective effects of vitamin D result from its role as a nuclear transcription factor that regulates cell growth, differentiation, apoptosis and a wide range of cellular mechanisms central to the development of cancer. A significant number of individuals have serum vitamin D levels lower than what appears to protect against cancer, and the research community is currently revising the guidelines for optimal health. This will lead to improved public health policies and to reduced risk of cancer. Research strongly supports the view that efforts to improve vitamin D status would have significant protective effects against the development of cancer. The clinical research community is currently revising recommendations for optimal serum levels and for sensible levels of sun exposure, to levels greater than previously thought. Currently, most experts in the field believe that intakes of between 1000 and 4000 IU will lead to a more healthy level of serum 25(OH)D, at approximately 75 nmol/L that will offer significant protection effects against cancers of the breast, colon, prostate, ovary, lungs, and pancreas. The first randomized trial has shown significant protection against breast cancer, and other clinical trials will follow and ultimately lead to improved public health policies and significantly fewer cancers.

Adjoint optimization of natural convection problems: differentially heated cavity

NASA Astrophysics Data System (ADS)

Saglietti, Clio; Schlatter, Philipp; Monokrousos, Antonios; Henningson, Dan S.

2017-12-01

Optimization of natural convection-driven flows may provide significant improvements to the performance of cooling devices, but a theoretical investigation of such flows has been rarely done. The present paper illustrates an efficient gradient-based optimization method for analyzing such systems. We consider numerically the natural convection-driven flow in a differentially heated cavity with three Prandtl numbers (Pr=0.15{-}7) at super-critical conditions. All results and implementations were done with the spectral element code Nek5000. The flow is analyzed using linear direct and adjoint computations about a nonlinear base flow, extracting in particular optimal initial conditions using power iteration and the solution of the full adjoint direct eigenproblem. The cost function for both temperature and velocity is based on the kinetic energy and the concept of entransy, which yields a quadratic functional. Results are presented as a function of Prandtl number, time horizons and weights between kinetic energy and entransy. In particular, it is shown that the maximum transient growth is achieved at time horizons on the order of 5 time units for all cases, whereas for larger time horizons the adjoint mode is recovered as optimal initial condition. For smaller time horizons, the influence of the weights leads either to a concentric temperature distribution or to an initial condition pattern that opposes the mean shear and grows according to the Orr mechanism. For specific cases, it could also been shown that the computation of optimal initial conditions leads to a degenerate problem, with a potential loss of symmetry. In these situations, it turns out that any initial condition lying in a specific span of the eigenfunctions will yield exactly the same transient amplification. As a consequence, the power iteration converges very slowly and fails to extract all possible optimal initial conditions. According to the authors' knowledge, this behavior is illustrated here for the first time.

Numerical verification of two-component dental implant in the context of fatigue life for various load cases.

PubMed

Szajek, Krzysztof; Wierszycki, Marcin

2016-01-01

Dental implant designing is a complex process which considers many limitations both biological and mechanical in nature. In earlier studies, a complete procedure for improvement of two-component dental implant was proposed. However, the optimization tasks carried out required assumption on representative load case, which raised doubts on optimality for the other load cases. This paper deals with verification of the optimal design in context of fatigue life and its main goal is to answer the question if the assumed load scenario (solely horizontal occlusal load) leads to the design which is also "safe" for oblique occlussal loads regardless the angle from an implant axis. The verification is carried out with series of finite element analyses for wide spectrum of physiologically justified loads. The design of experiment methodology with full factorial technique is utilized. All computations are done in Abaqus suite. The maximal Mises stress and normalized effective stress amplitude for various load cases are discussed and compared with the assumed "safe" limit (equivalent of fatigue life for 5e6 cycles). The obtained results proof that coronial-appical load component should be taken into consideration in the two component dental implant when fatigue life is optimized. However, its influence in the analyzed case is small and does not change the fact that the fatigue life improvement is observed for all components within whole range of analyzed loads.

Lead optimization attrition analysis (LOAA): a novel and general methodology for medicinal chemistry.

PubMed

Munson, Mark; Lieberman, Harvey; Tserlin, Elina; Rocnik, Jennifer; Ge, Jie; Fitzgerald, Maria; Patel, Vinod; Garcia-Echeverria, Carlos

2015-08-01

Herein, we report a novel and general method, lead optimization attrition analysis (LOAA), to benchmark two distinct small-molecule lead series using a relatively unbiased, simple technique and commercially available software. We illustrate this approach with data collected during lead optimization of two independent oncology programs as a case study. Easily generated graphics and attrition curves enabled us to calibrate progress and support go/no go decisions on each program. We believe that this data-driven technique could be used broadly by medicinal chemists and management to guide strategic decisions during drug discovery. Copyright © 2015 Elsevier Ltd. All rights reserved.

Influence of optimized leading-edge deflection and geometric anhedral on the low-speed aerodynamic characteristics of a low-aspect-ratio highly swept arrow-wing configuration. [langley 7 by 10 foot tunnel

NASA Technical Reports Server (NTRS)

Coe, P. L., Jr.; Huffman, J. K.

1979-01-01

An investigation conducted in the Langley 7 by 10 foot tunnel to determine the influence of an optimized leading-edge deflection on the low speed aerodynamic performance of a configuration with a low aspect ratio, highly swept wing. The sensitivity of the lateral stability derivative to geometric anhedral was also studied. The optimized leading edge deflection was developed by aligning the leading edge with the incoming flow along the entire span. Owing to spanwise variation of unwash, the resulting optimized leading edge was a smooth, continuously warped surface for which the deflection varied from 16 deg at the side of body to 50 deg at the wing tip. For the particular configuration studied, levels of leading-edge suction on the order of 90 percent were achieved. The results of tests conducted to determine the sensitivity of the lateral stability derivative to geometric anhedral indicate values which are in reasonable agreement with estimates provided by simple vortex-lattice theories.

Enhanced photon management in silicon thin film solar cells with different front and back interface texture

PubMed Central

Tamang, Asman; Hongsingthong, Aswin; Jovanov, Vladislav; Sichanugrist, Porponth; Khan, Bakhtiar A.; Dewan, Rahul; Konagai, Makoto; Knipp, Dietmar

2016-01-01

Light trapping and photon management of silicon thin film solar cells can be improved by a separate optimization of the front and back contact textures. A separate optimization of the front and back contact textures is investigated by optical simulations taking realistic device geometries into consideration. The optical simulations are confirmed by experimentally realized 1 μm thick microcrystalline silicon solar cells. The different front and back contact textures lead to an enhancement of the short circuit current by 1.2 mA/cm2 resulting in a total short circuit current of 23.65 mA/cm2 and an energy conversion efficiency of 8.35%. PMID:27481226

Determination of Organophosphate Pesticides at a Carbon Nanotube/Organophosphorus Hydrolase Electrochemical Biosensor

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

Deo, R P.; Wang, Joseph; Block, I

2005-02-08

An amperometric biosensor for organophosphorus (OP) pesticides based on a carbon-nanotube (CNT) modified transducer and an organophosphorus hydrolase (OPH) biocatalyst is described. A bilayer approach with the OPH layer atop of the CNT film was used for preparing the CNT/OPH biosensor. The CNT layer leads to a greatly improved anodic detection of the enzymatically-generated p-nitrophenol product, including higher sensitivity and stability. The sensor performance was optimized with respect to the surface modification and operating conditions. Under the optimal conditions the biosensor was used to measure as low as 0.15 {micro}M paraoxon and 0.8 {micro}M methyl parathion with sensitivities of 25more » and 6 nA/{micro}M, respectively.« less

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.

Optimal design of active EMC filters

NASA Astrophysics Data System (ADS)

Chand, B.; Kut, T.; Dickmann, S.

2013-07-01

A recent trend in automotive industry is adding electrical drive systems to conventional drives. The electrification allows an expansion of energy sources and provides great opportunities for environmental friendly mobility. The electrical powertrain and its components can also cause disturbances which couple into nearby electronic control units and communication cables. Therefore the communication can be degraded or even permanently disrupted. To minimize these interferences, different approaches are possible. One possibility is to use EMC filters. However, the diversity of filters is very large and the determination of an appropriate filter for each application is time-consuming. Therefore, the filter design is determined by using a simulation tool including an effective optimization algorithm. This method leads to improvements in terms of weight, volume and cost.

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description.

PubMed

Spyrakis, Francesca; Cavasotto, Claudio N

2015-10-01

Structure-based virtual screening is currently an established tool in drug lead discovery projects. Although in the last years the field saw an impressive progress in terms of algorithm development, computational performance, and retrospective and prospective applications in ligand identification, there are still long-standing challenges where further improvement is needed. In this review, we consider the conceptual frame, state-of-the-art and recent developments of three critical "structural" issues in structure-based drug lead discovery: the use of homology modeling to accurately model the binding site when no experimental structures are available, the necessity of accounting for the dynamics of intrinsically flexible systems as proteins, and the importance of considering active site water molecules in lead identification and optimization campaigns. Copyright © 2015 Elsevier Inc. All rights reserved.

Application of Semipermeable Membranes in Glucose Biosensing

PubMed Central

Kulkarni, Tanmay; Slaughter, Gymama

2016-01-01

Glucose biosensors have received significant attention in recent years due to the escalating mortality rate of diabetes mellitus. Although there is currently no cure for diabetes mellitus, individuals living with diabetes can lead a normal life by maintaining tight control of their blood glucose levels using glucose biosensors (e.g., glucometers). Current research in the field is focused on the optimization and improvement in the performance of glucose biosensors by employing a variety of glucose selective enzymes, mediators and semipermeable membranes to improve the electron transfer between the active center of the enzyme and the electrode substrate. Herein, we summarize the different semipermeable membranes used in the fabrication of the glucose biosensor, that result in improved biosensor sensitivity, selectivity, dynamic range, response time and stability. PMID:27983630

Improved high operating temperature MCT MWIR modules

NASA Astrophysics Data System (ADS)

Lutz, H.; Breiter, R.; Figgemeier, H.; Schallenberg, T.; Schirmacher, W.; Wollrab, R.

2014-06-01

High operating temperature (HOT) IR-detectors are a key factor to size, weight and power (SWaP) reduced IR-systems. Such systems are essential to provide infantrymen with low-weight handheld systems with increased battery lifetimes or most compact clip-on weapon sights in combination with high electro-optical performance offered by cooled IR-technology. AIM's MCT standard n-on-p technology with vacancy doping has been optimized over many years resulting in MWIR-detectors with excellent electro-optical performance up to operating temperatures of ~120K. In the last years the effort has been intensified to improve this standard technology by introducing extrinsic doping with Gold as an acceptor. As a consequence the dark current could considerably be suppressed and allows for operation at ~140K with good e/o performance. More detailed investigations showed that limitation for HOT > 140K is explained by consequences from rising dark current rather than from defective pixel level. Recently, several crucial parameters were identified showing great promise for further optimization of HOT-performance. Among those, p-type concentration could successfully be reduced from the mid 1016 / cm3 to the lower 1015/ cm3 range. Since AIM is one of the leading manufacturers of split linear cryocoolers, an increase in operating temperature will directly lead to IR-modules with improved SWaP characteristics by making use of the miniature members of its SX cooler family with single piston and balancer technology. The paper will present recent progress in the development of HOT MWIR-detector arrays at AIM and show electro-optical performance data in comparison to focal plane arrays produced in the standard technology.

Geometrizing adiabatic quantum computation

NASA Astrophysics Data System (ADS)

Rezakhani, Ali; Kuo, Wan-Jung; Hamma, Alioscia; Lidar, Daniel; Zanardi, Paolo

2010-03-01

A time-optimal approach to adiabatic quantum computation (AQC) is formulated. The corresponding natural Riemannian metric is also derived, through which AQC can be understood as the problem of finding a geodesic on the manifold of control parameters. We demonstrate this geometrization through some examples, where we show that it leads to improved performance of AQC, and sheds light on the roles of entanglement and curvature of the control manifold in algorithmic performance. The underlying connection with quantum phase transitions is also explored.

[Improvement of higher medical education via the system of quality specialist training].

PubMed

Artiukhov, I P; Samotesov, P A; Nikulina, S Iu; Salmina, A B; Petrova, M M; Gritsan, A I; Rossiev, D A

2009-01-01

Development of the system of management of quality specialist training in the Kraysnoysrsk State Medical Academy allowed to optimize administration and academic process, create conditions for introduction of innovative technologies in educational, research, and clinico-diagnostic activities for the purpose of their standardization and realization of managerial decisions. The new system promotes organization of administrative and educational work of the Academy in line with leading trends of regional development, stimulates creativity and strategic planning.

The aerodynamic design of an advanced rotor airfoil

NASA Technical Reports Server (NTRS)

Blackwell, J. A., Jr.; Hinson, B. L.

1978-01-01

An advanced rotor airfoil, designed utilizing supercritical airfoil technology and advanced design and analysis methodology is described. The airfoil was designed subject to stringent aerodynamic design criteria for improving the performance over the entire rotor operating regime. The design criteria are discussed. The design was accomplished using a physical plane, viscous, transonic inverse design procedure, and a constrained function minimization technique for optimizing the airfoil leading edge shape. The aerodynamic performance objectives of the airfoil are discussed.

Halogenase engineering and its utility in medicinal chemistry.

PubMed

Fraley, Amy E; Sherman, David H

2018-06-15

Halogenation is commonly used in medicinal chemistry to improve the potency of pharmaceutical leads. While synthetic methods for halogenation present selectivity and reactivity challenges, halogenases have evolved over time to perform selective reactions under benign conditions. The optimization of halogenation biocatalysts has utilized enzyme evolution and structure-based engineering alongside biotransformation in a variety of systems to generate stable site-selective variants. The recent improvements in halogenase-catalyzed reactions has demonstrated the utility of these biocatalysts for industrial purposes, and their ability to achieve a broad substrate scope implies a synthetic tractability with increasing relevance in medicinal chemistry. Copyright © 2018 Elsevier Ltd. All rights reserved.

Impact of chronobiology on neuropathic pain treatment.

PubMed

Gilron, Ian

2016-01-01

Inflammatory pain exhibits circadian rhythmicity. Recently, a distinct diurnal pattern has been described for peripheral neuropathic conditions. This diurnal variation has several implications: advancing understanding of chronobiology may facilitate identification of new and improved treatments; developing pain-contingent strategies that maximize treatment at times of the day associated with highest pain intensity may provide optimal pain relief as well as minimize treatment-related adverse effects (e.g., daytime cognitive dysfunction); and consideration of the impact of chronobiology on pain measurement may lead to improvements in analgesic study design that will maximize assay sensitivity of clinical trials. Recent and ongoing chronobiology studies are thus expected to advance knowledge and treatment of neuropathic pain.

Interpolation of longitudinal shape and image data via optimal mass transport

NASA Astrophysics Data System (ADS)

Gao, Yi; Zhu, Liang-Jia; Bouix, Sylvain; Tannenbaum, Allen

2014-03-01

Longitudinal analysis of medical imaging data has become central to the study of many disorders. Unfortunately, various constraints (study design, patient availability, technological limitations) restrict the acquisition of data to only a few time points, limiting the study of continuous disease/treatment progression. Having the ability to produce a sensible time interpolation of the data can lead to improved analysis, such as intuitive visualizations of anatomical changes, or the creation of more samples to improve statistical analysis. In this work, we model interpolation of medical image data, in particular shape data, using the theory of optimal mass transport (OMT), which can construct a continuous transition from two time points while preserving "mass" (e.g., image intensity, shape volume) during the transition. The theory even allows a short extrapolation in time and may help predict short-term treatment impact or disease progression on anatomical structure. We apply the proposed method to the hippocampus-amygdala complex in schizophrenia, the heart in atrial fibrillation, and full head MR images in traumatic brain injury.

Quenching Mo optical losses in CIGS solar cells by a point contacted dual-layer dielectric spacer: a 3-D optical study.

PubMed

Rezaei, Nasim; Isabella, Olindo; Vroon, Zeger; Zeman, Miro

2018-01-22

A 3-D optical modelling was calibrated to calculate the light absorption and the total reflection of fabricated CIGS solar cells. Absorption losses at molybdenum (Mo) / CIGS interface were explained in terms of plasmonic waves. To quench these losses, we assumed the insertion of a lossless dielectric spacer between Mo and CIGS, whose optical properties were varied. We show that such a spacer with low refractive index and proper thickness can significantly reduce absorption in Mo in the long wavelength regime and improve the device's rear reflectance, thus leading to enhanced light absorption in the CIGS layer. Therefore, we optimized a realistic two-layer MgF 2 / Al 2 O 3 dielectric spacer to exploit (i) the passivation properties of ultra-thin Al 2 O 3 on the CIGS side for potential high open-circuit voltage and (ii) the low refractive index of MgF 2 on the Mo side to reduce its optical losses. Combining our realistic spacer with optically-optimized point contacts increases the implied photocurrent density of a 750 nm-thick CIGS layer by 10% for the wavelengths between 700 and 1150 nm with respect to the reference cell. The elimination of plasmonic resonances in the new structure leads to a higher electric field magnitude at the bottom of CIGS layer and justifies the improved optical performance.

Multiplexing a high-throughput liability assay to leverage efficiencies.

PubMed

Herbst, John; Anthony, Monique; Stewart, Jeremy; Connors, David; Chen, Taosheng; Banks, Martyn; Petrillo, Edward W; Agler, Michele

2009-06-01

In order to identify potential cytochrome P-450 3A4 (drug-metabolizing enzyme) inducers at an early stage of the drug discovery process, a cell-based transactivation high-throughput luciferase reporter assay for the human pregnane X receptor (PXR) in HepG2 cells has been implemented and multiplexed with a viability end point for data interpretation, as part of a Lead Profiling portfolio of assays. As a routine part of Lead Profiling operations, assays are periodically evaluated for utility as well as for potential improvements in technology or process. We used a recent evaluation of our PXR-transactivation assay as a model for the application of Lean Thinking-based process analysis to lab-bench assay optimization and automation. This resulted in the development of a 384-well multiplexed homogeneous assay simultaneously detecting PXR transactivation and HepG2 cell cytotoxicity. In order to multiplex fluorescent and luminescent read-outs, modifications to each assay were necessary, which included optimization of multiple assay parameters such as cell density, plate type, and reagent concentrations. Subsequently, a set of compounds including known cytotoxic compounds and PXR inducers were used to validate the multiplexed assay. Results from the multiplexed assay correlate well with those from the singleplexed assay formats measuring PXR transactivation and viability separately. Implementation of the multiplexed assay for routine compound profiling provides improved data quality, sample conservation, cost savings, and resource efficiencies.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

WINGDES2 - WING DESIGN AND ANALYSIS CODE

NASA Technical Reports Server (NTRS)

Carlson, H. W.

1994-01-01

This program provides a wing design algorithm based on modified linear theory which takes into account the effects of attainable leading-edge thrust. A primary objective of the WINGDES2 approach is the generation of a camber surface as mild as possible to produce drag levels comparable to those attainable with full theoretical leading-edge thrust. WINGDES2 provides both an analysis and a design capability and is applicable to both subsonic and supersonic flow. The optimization can be carried out for designated wing portions such as leading and trailing edge areas for the design of mission-adaptive surfaces, or for an entire planform such as a supersonic transport wing. This program replaces an earlier wing design code, LAR-13315, designated WINGDES. WINGDES2 incorporates modifications to improve numerical accuracy and provides additional capabilities. A means of accounting for the presence of interference pressure fields from airplane components other than the wing and a direct process for selection of flap surfaces to approach the performance levels of the optimized wing surfaces are included. An increased storage capacity allows better numerical representation of those configurations that have small chord leading-edge or trailing-edge design areas. WINGDES2 determines an optimum combination of a series of candidate surfaces rather than the more commonly used candidate loadings. The objective of the design is the recovery of unrealized theoretical leading-edge thrust of the input flat surface by shaping of the design surface to create a distributed thrust and thus minimize drag. The input consists of airfoil section thickness data, leading and trailing edge planform geometry, and operational parameters such as Mach number, Reynolds number, and design lift coefficient. Output includes optimized camber surface ordinates, pressure coefficient distributions, and theoretical aerodynamic characteristics. WINGDES2 is written in FORTRAN V for batch execution and has been implemented on a CDC CYBER computer operating under NOS 2.7.1 with a central memory requirement of approximately 344K (octal) of 60 bit words. This program was developed in 1984, and last updated in 1990. CDC and CYBER are trademarks of Control Data Corporation.

New tools for optimizing fluid resuscitation in acute pancreatitis

PubMed Central

Bortolotti, Perrine; Saulnier, Fabienne; Colling, Delphine; Redheuil, Alban; Preau, Sebastien

2014-01-01

Acute pancreatitis (AP) is a frequent disease with degrees of increasing severity responsible for high morbidity. Despite continuous improvement in care, mortality remains significant. Because hypovolemia, together with microcirculatory dysfunction lead to poor outcome, fluid therapy remains a cornerstone of the supportive treatment. However, poor clinical evidence actually support the aggressive fluid therapy recommended in recent guidelines since available data are controversial. Fluid management remains unclear and leads to current heterogeneous practice. Different strategies may help to improve fluid resuscitation in AP. On one hand, integration of fluid therapy in a global hemodynamic resuscitation has been demonstrated to improve outcome in surgical or septic patients. Tailored fluid administration after early identification of patients with high-risk of poor outcome presenting inadequate tissue oxygenation is a major part of this strategy. On the other hand, new decision parameters have been developed recently to improve safety and efficiency of fluid therapy in critically ill patients. In this review, we propose a personalized strategy integrating these new concepts in the early fluid management of AP. This new approach paves the way to a wide range of clinical studies in the field of AP. PMID:25473163

Improved Composites Using Crosslinked, Surface-Modified Carbon Nanotube Materials

NASA Technical Reports Server (NTRS)

Baker, James Stewart

2014-01-01

Individual carbon nanotubes (CNTs) exhibit exceptional tensile strength and stiffness; however, these properties have not translated well to the macroscopic scale. Premature failure of bulk CNT materials under tensile loading occurs due to the relatively weak frictional forces between adjacent CNTs, leading to poor load transfer through the material. When used in polymer matrix composites (PMCs), the weak nanotube-matrix interaction leads to the CNTs providing less than optimal reinforcement.Our group is examining the use of covalent crosslinking and surface modification as a means to improve the tensile properties of PMCs containing carbon nanotubes. Sheet material comprised of unaligned multi-walled carbon nanotubes (MWCNT) was used as a drop-in replacement for carbon fiber in the composites. A variety of post-processing methods have been examined for covalently crosslinking the CNTs to overcome the weak inter-nanotube shear interactions, resulting in improved tensile strength and modulus for the bulk sheet material. Residual functional groups from the crosslinking chemistry may have the added benefit of improving the nanotube-matrix interaction. Composites prepared using these crosslinked, surface-modified nanotube sheet materials exhibit superior tensile properties to composites using the as received CNT sheet material.

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

PubMed

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

2015-03-01

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

Monte Carlo simulation of moderator and reflector in coal analyzer based on a D-T neutron generator.

PubMed

Shan, Qing; Chu, Shengnan; Jia, Wenbao

2015-11-01

Coal is one of the most popular fuels in the world. The use of coal not only produces carbon dioxide, but also contributes to the environmental pollution by heavy metals. In prompt gamma-ray neutron activation analysis (PGNAA)-based coal analyzer, the characteristic gamma rays of C and O are mainly induced by fast neutrons, whereas thermal neutrons can be used to induce the characteristic gamma rays of H, Si, and heavy metals. Therefore, appropriate thermal and fast neutrons are beneficial in improving the measurement accuracy of heavy metals, and ensure that the measurement accuracy of main elements meets the requirements of the industry. Once the required yield of the deuterium-tritium (d-T) neutron generator is determined, appropriate thermal and fast neutrons can be obtained by optimizing the neutron source term. In this article, the Monte Carlo N-Particle (MCNP) Transport Code and Evaluated Nuclear Data File (ENDF) database are used to optimize the neutron source term in PGNAA-based coal analyzer, including the material and shape of the moderator and neutron reflector. The optimized targets include two points: (1) the ratio of the thermal to fast neutron is 1:1 and (2) the total neutron flux from the optimized neutron source in the sample increases at least 100% when compared with the initial one. The simulation results show that, the total neutron flux in the sample increases 102%, 102%, 85%, 72%, and 62% with Pb, Bi, Nb, W, and Be reflectors, respectively. Maximum optimization of the targets is achieved when the moderator is a 3-cm-thick lead layer coupled with a 3-cm-thick high-density polyethylene (HDPE) layer, and the neutron reflector is a 27-cm-thick hemispherical lead layer. Copyright © 2015 Elsevier Ltd. All rights reserved.

The selection of the optimal baseline in the front-view monocular vision system

NASA Astrophysics Data System (ADS)

Xiong, Bincheng; Zhang, Jun; Zhang, Daimeng; Liu, Xiaomao; Tian, Jinwen

2018-03-01

In the front-view monocular vision system, the accuracy of solving the depth field is related to the length of the inter-frame baseline and the accuracy of image matching result. In general, a longer length of the baseline can lead to a higher precision of solving the depth field. However, at the same time, the difference between the inter-frame images increases, which increases the difficulty in image matching and the decreases matching accuracy and at last may leads to the failure of solving the depth field. One of the usual practices is to use the tracking and matching method to improve the matching accuracy between images, but this algorithm is easy to cause matching drift between images with large interval, resulting in cumulative error in image matching, and finally the accuracy of solving the depth field is still very low. In this paper, we propose a depth field fusion algorithm based on the optimal length of the baseline. Firstly, we analyze the quantitative relationship between the accuracy of the depth field calculation and the length of the baseline between frames, and find the optimal length of the baseline by doing lots of experiments; secondly, we introduce the inverse depth filtering technique for sparse SLAM, and solve the depth field under the constraint of the optimal length of the baseline. By doing a large number of experiments, the results show that our algorithm can effectively eliminate the mismatch caused by image changes, and can still solve the depth field correctly in the large baseline scene. Our algorithm is superior to the traditional SFM algorithm in time and space complexity. The optimal baseline obtained by a large number of experiments plays a guiding role in the calculation of the depth field in front-view monocular.

Distributed Optimization of Multi-Agent Systems: Framework, Local Optimizer, and Applications

NASA Astrophysics Data System (ADS)

Zu, Yue

Convex optimization problem can be solved in a centralized or distributed manner. Compared with centralized methods based on single-agent system, distributed algorithms rely on multi-agent systems with information exchanging among connected neighbors, which leads to great improvement on the system fault tolerance. Thus, a task within multi-agent system can be completed with presence of partial agent failures. By problem decomposition, a large-scale problem can be divided into a set of small-scale sub-problems that can be solved in sequence/parallel. Hence, the computational complexity is greatly reduced by distributed algorithm in multi-agent system. Moreover, distributed algorithm allows data collected and stored in a distributed fashion, which successfully overcomes the drawbacks of using multicast due to the bandwidth limitation. Distributed algorithm has been applied in solving a variety of real-world problems. Our research focuses on the framework and local optimizer design in practical engineering applications. In the first one, we propose a multi-sensor and multi-agent scheme for spatial motion estimation of a rigid body. Estimation performance is improved in terms of accuracy and convergence speed. Second, we develop a cyber-physical system and implement distributed computation devices to optimize the in-building evacuation path when hazard occurs. The proposed Bellman-Ford Dual-Subgradient path planning method relieves the congestion in corridor and the exit areas. At last, highway traffic flow is managed by adjusting speed limits to minimize the fuel consumption and travel time in the third project. Optimal control strategy is designed through both centralized and distributed algorithm based on convex problem formulation. Moreover, a hybrid control scheme is presented for highway network travel time minimization. Compared with no controlled case or conventional highway traffic control strategy, the proposed hybrid control strategy greatly reduces total travel time on test highway network.

American Society for Enhanced Recovery (ASER) and Perioperative Quality Initiative (POQI) Joint Consensus Statement on Optimal Analgesia within an Enhanced Recovery Pathway for Colorectal Surgery: Part 2-From PACU to the Transition Home.

PubMed

Scott, Michael J; McEvoy, Matthew D; Gordon, Debra B; Grant, Stuart A; Thacker, Julie K M; Wu, Christopher L; Gan, Tong J; Mythen, Monty G; Shaw, Andrew D; Miller, Timothy E

2017-01-01

Within an enhanced recovery pathway (ERP), the approach to treating pain should be multifaceted and the goal should be to deliver "optimal analgesia", which we define in this paper as a technique that optimizes patient comfort and facilitates functional recovery with the fewest medication side effects. With input from a multidisciplinary, international group of experts and through a structured review of the literature and use of a modified Delphi method, we achieved consensus surrounding the topic of optimal analgesia in the perioperative period for colorectal surgery patients. As a part of the first Perioperative Quality Improvement (POQI) workgroup meeting, we sought to develop a consensus document describing a comprehensive, yet rational and practical, approach for developing an evidence-based plan for achieving optimal analgesia, specifically for a colorectal surgery within an ERP. The goal was twofold: (a) that application of this process would lead to improved patient outcomes and (b) that investigation of the questions raised would identify knowledge gaps to aid the direction for research into analgesia within ERPs in the years to come. This document details the evidence for a wide range of analgesic components, with particular focus on care in the post-anesthesia care unit, general care ward, and transition to home after discharge. The preoperative and operative consensus statement for analgesia was covered in Part 1 of this paper. The overall conclusion is that the combination of analgesic techniques employed in the perioperative period is not important as long as it is effective in delivering the goal of "optimal analgesia" as set forth in this document.

Optimization of rotational arc station parameter optimized radiation therapy.

PubMed

Dong, P; Ungun, B; Boyd, S; Xing, L

2016-09-01

To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was reduced by 8% and 6%, respectively. For the brain case, the doses to the eyes, chiasm, and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the head and neck case. The dosimetric quality and delivery efficiency presented here indicate that SPORT is an intriguing alternative treatment modality. With the widespread adoption of digital linac, SPORT should lead to improved patient care in the future.

Optimization of rotational arc station parameter optimized radiation therapy

PubMed Central

Dong, P.; Ungun, B.; Boyd, S.; Xing, L.

2016-01-01

Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was reduced by 8% and 6%, respectively. For the brain case, the doses to the eyes, chiasm, and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the head and neck case. Conclusions: The dosimetric quality and delivery efficiency presented here indicate that SPORT is an intriguing alternative treatment modality. With the widespread adoption of digital linac, SPORT should lead to improved patient care in the future. PMID:27587028

Optimization of rotational arc station parameter optimized radiation therapy

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

Dong, P.; Ungun, B.

Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trappedmore » in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was reduced by 8% and 6%, respectively. For the brain case, the doses to the eyes, chiasm, and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the head and neck case. Conclusions: The dosimetric quality and delivery efficiency presented here indicate that SPORT is an intriguing alternative treatment modality. With the widespread adoption of digital linac, SPORT should lead to improved patient care in the future.« less

The effect of different control point sampling sequences on convergence of VMAT inverse planning

NASA Astrophysics Data System (ADS)

Pardo Montero, Juan; Fenwick, John D.

2011-04-01

A key component of some volumetric-modulated arc therapy (VMAT) optimization algorithms is the progressive addition of control points to the optimization. This idea was introduced in Otto's seminal VMAT paper, in which a coarse sampling of control points was used at the beginning of the optimization and new control points were progressively added one at a time. A different form of the methodology is also present in the RapidArc optimizer, which adds new control points in groups called 'multiresolution levels', each doubling the number of control points in the optimization. This progressive sampling accelerates convergence, improving the results obtained, and has similarities with the ordered subset algorithm used to accelerate iterative image reconstruction. In this work we have used a VMAT optimizer developed in-house to study the performance of optimization algorithms which use different control point sampling sequences, most of which fall into three different classes: doubling sequences, which add new control points in groups such that the number of control points in the optimization is (roughly) doubled; Otto-like progressive sampling which adds one control point at a time, and equi-length sequences which contain several multiresolution levels each with the same number of control points. Results are presented in this study for two clinical geometries, prostate and head-and-neck treatments. A dependence of the quality of the final solution on the number of starting control points has been observed, in agreement with previous works. We have found that some sequences, especially E20 and E30 (equi-length sequences with 20 and 30 multiresolution levels, respectively), generate better results than a 5 multiresolution level RapidArc-like sequence. The final value of the cost function is reduced up to 20%, such reductions leading to small improvements in dosimetric parameters characterizing the treatments—slightly more homogeneous target doses and better sparing of the organs at risk.

On the role of the optimization algorithm of RapidArc(®) volumetric modulated arc therapy on plan quality and efficiency.

PubMed

Vanetti, Eugenio; Nicolini, Giorgia; Nord, Janne; Peltola, Jarkko; Clivio, Alessandro; Fogliata, Antonella; Cozzi, Luca

2011-11-01

The RapidArc volumetric modulated arc therapy (VMAT) planning process is based on a core engine, the so-called progressive resolution optimizer (PRO). This is the optimization algorithm used to determine the combination of field shapes, segment weights (with dose rate and gantry speed variations), which best approximate the desired dose distribution in the inverse planning problem. A study was performed to assess the behavior of two versions of PRO. These two versions mostly differ in the way continuous variables describing the modulated arc are sampled into discrete control points, in the planning efficiency and in the presence of some new features. The analysis aimed to assess (i) plan quality, (ii) technical delivery aspects, (iii) agreement between delivery and calculations, and (iv) planning efficiency of the two versions. RapidArc plans were generated for four groups of patients (five patients each): anal canal, advanced lung, head and neck, and multiple brain metastases and were designed to test different levels of planning complexity and anatomical features. Plans from optimization with PRO2 (first generation of RapidArc optimizer) were compared against PRO3 (second generation of the algorithm). Additional plans were optimized with PRO3 using new features: the jaw tracking, the intermediate dose and the air cavity correction options. Results showed that (i) plan quality was generally improved with PRO3 and, although not for all parameters, some of the scored indices showed a macroscopic improvement with PRO3. (ii) PRO3 optimization leads to simpler patterns of the dynamic parameters particularly for dose rate. (iii) No differences were observed between the two algorithms in terms of pretreatment quality assurance measurements and (iv) PRO3 optimization was generally faster, with a time reduction of a factor approximately 3.5 with respect to PRO2. These results indicate that PRO3 is either clinically beneficial or neutral in terms of dosimetric quality while it showed significant advantages in speed and technical aspects.

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Kalman filter based control for Adaptive Optics

NASA Astrophysics Data System (ADS)

Petit, Cyril; Quiros-Pacheco, Fernando; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Fusco, Thierry

2004-12-01

Classical Adaptive Optics suffer from a limitation of the corrected Field Of View. This drawback has lead to the development of MultiConjugated Adaptive Optics. While the first MCAO experimental set-ups are presently under construction, little attention has been paid to the control loop. This is however a key element in the optimization process especially for MCAO systems. Different approaches have been proposed in recent articles for astronomical applications : simple integrator, Optimized Modal Gain Integrator and Kalman filtering. We study here Kalman filtering which seems a very promising solution. Following the work of Brice Leroux, we focus on a frequential characterization of kalman filters, computing a transfer matrix. The result brings much information about their behaviour and allows comparisons with classical controllers. It also appears that straightforward improvements of the system models can lead to static aberrations and vibrations filtering. Simulation results are proposed and analysed thanks to our frequential characterization. Related problems such as model errors, aliasing effect reduction or experimental implementation and testing of Kalman filter control loop on a simplified MCAO experimental set-up could be then discussed.

Optimization of gas condensate Field A development on the basis of "reservoir - gathering facilities system" integrated model

NASA Astrophysics Data System (ADS)

Demidova, E. A.; Maksyutina, O. V.

2015-02-01

It is known that many gas condensate fields are challenged with liquid loading and condensate banking problems. Therefore, gas production is declining with time. In this paper hydraulic fracturing treatment was considered as a method to improve the productivity of wells and consequently to exclude the factors that lead to production decline. This paper presents the analysis of gas condensate Field A development optimization with the purpose of maintaining constant gas production at the 2013 level for 8 years taking into account mentioned factors . To optimize the development of the filed, an integrated model was created. The integrated model of the field implies constructing the uniform model of the field consisting of the coupling models of the reservoir, wells and surface facilities. This model allowed optimizing each of the elements of the model separately and also taking into account the mutual influence of these elements. Using the integrated model, five development scenarios were analyzed and an optimal scenario was chosen. The NPV of this scenario equals 7,277 mln RUR, cumulative gas production - 12,160.6 mln m3, cumulative condensate production - 1.8 mln tons.

Extending flood forecasting lead time in large basin by coupling bias-corrected WRF QPF with distributed hydrological model

NASA Astrophysics Data System (ADS)

LI, J.; Chen, Y.; Wang, H. Y.

2016-12-01

In large basin flood forecasting, the forecasting lead time is very important. Advances in numerical weather forecasting in the past decades provides new input to extend flood forecasting lead time in large rivers. Challenges for fulfilling this goal currently is that the uncertainty of QPF with these kinds of NWP models are still high, so controlling the uncertainty of QPF is an emerging technique requirement.The Weather Research and Forecasting (WRF) model is one of these NWPs, and how to control the QPF uncertainty of WRF is the research topic of many researchers among the meteorological community. In this study, the QPF products in the Liujiang river basin, a big river with a drainage area of 56,000 km2, was compared with the ground observation precipitation from a rain gauge networks firstly, and the results show that the uncertainty of the WRF QPF is relatively high. So a post-processed algorithm by correlating the QPF with the observed precipitation is proposed to remove the systematical bias in QPF. With this algorithm, the post-processed WRF QPF is close to the ground observed precipitation in area-averaged precipitation. Then the precipitation is coupled with the Liuxihe model, a physically based distributed hydrological model that is widely used in small watershed flash flood forecasting. The Liuxihe Model has the advantage with gridded precipitation from NWP and could optimize model parameters when there are some observed hydrological data even there is only a few, it also has very high model resolution to improve model performance, and runs on high performance supercomputer with parallel algorithm if executed in large rivers. Two flood events in the Liujiang River were collected, one was used to optimize the model parameters and another is used to validate the model. The results show that the river flow simulation has been improved largely, and could be used for real-time flood forecasting trail in extending flood forecasting leading time.

Intraoperative acceleration measurements to quantify improvement in tremor during deep brain stimulation surgery.

PubMed

Shah, Ashesh; Coste, Jérôme; Lemaire, Jean-Jacques; Taub, Ethan; Schüpbach, W M Michael; Pollo, Claudio; Schkommodau, Erik; Guzman, Raphael; Hemm-Ode, Simone

2017-05-01

Deep brain stimulation (DBS) surgery is extensively used in the treatment of movement disorders. Nevertheless, methods to evaluate the clinical response during intraoperative stimulation tests to identify the optimal position for the implantation of the chronic DBS lead remain subjective. In this paper, we describe a new, versatile method for quantitative intraoperative evaluation of improvement in tremor with an acceleration sensor that is mounted on the patient's wrist during surgery. At each anatomical test position, the improvement in tremor compared to the initial tremor is estimated on the basis of extracted outcome measures. This method was tested on 15 tremor patients undergoing DBS surgery in two centers. Data from 359 stimulation tests were acquired. Our results suggest that accelerometric evaluation detects tremor changes more sensitively than subjective visual ratings. The effective stimulation current amplitudes identified from the quantitative data (1.1 ± 0.8 mA) are lower than those identified by visual evaluation (1.7 ± 0.8 mA) for similar improvement in tremor. Additionally, if these data had been used to choose the chronic implant position of the DBS lead, 15 of the 26 choices would have been different. These results show that our method of accelerometric evaluation can potentially improve DBS targeting.

A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning

NASA Astrophysics Data System (ADS)

Liu, Hongcheng; Dong, Peng; Xing, Lei

2017-08-01

{{\\ell }2,1} -minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the {{\\ell }2,1} -based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the {{\\ell }2,1} -minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the {{\\ell }2,1} -minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the {{\\ell }2,1} -minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

Exploring codon context bias for synthetic gene design of a thermostable invertase in Escherichia coli.

PubMed

Pek, Han Bin; Klement, Maximilian; Ang, Kok Siong; Chung, Bevan Kai-Sheng; Ow, Dave Siak-Wei; Lee, Dong-Yup

2015-01-01

Various isoforms of invertases from prokaryotes, fungi, and higher plants has been expressed in Escherichia coli, and codon optimisation is a widely-adopted strategy for improvement of heterologous enzyme expression. Successful synthetic gene design for recombinant protein expression can be done by matching its translational elongation rate against heterologous host organisms via codon optimization. Amongst the various design parameters considered for the gene synthesis, codon context bias has been relatively overlooked compared to individual codon usage which is commonly adopted in most of codon optimization tools. In addition, matching the rates of transcription and translation based on secondary structure may lead to enhanced protein folding. In this study, we evaluated codon context fitness as design criterion for improving the expression of thermostable invertase from Thermotoga maritima in Escherichia coli and explored the relevance of secondary structure regions for folding and expression. We designed three coding sequences by using (1) a commercial vendor optimized gene algorithm, (2) codon context for the whole gene, and (3) codon context based on the secondary structure regions. Then, the codon optimized sequences were transformed and expressed in E. coli. From the resultant enzyme activities and protein yield data, codon context fitness proved to have the highest activity as compared to the wild-type control and other criteria while secondary structure-based strategy is comparable to the control. Codon context bias was shown to be a relevant parameter for enhancing enzyme production in Escherichia coli by codon optimization. Thus, we can effectively design synthetic genes within heterologous host organisms using this criterion. Copyright © 2015 Elsevier Inc. All rights reserved.

A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning.

PubMed

Liu, Hongcheng; Dong, Peng; Xing, Lei

2017-07-20

[Formula: see text]-minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the [Formula: see text]-based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the [Formula: see text]-minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the [Formula: see text]-minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the [Formula: see text]-minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

NASA Technical Reports Server (NTRS)

Venter, Gerhard; Sobieszczanski-Sobieski, Jaroslaw

2005-01-01

A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.

A globally optimal k-anonymity method for the de-identification of health data.

PubMed

El Emam, Khaled; Dankar, Fida Kamal; Issa, Romeo; Jonker, Elizabeth; Amyot, Daniel; Cogo, Elise; Corriveau, Jean-Pierre; Walker, Mark; Chowdhury, Sadrul; Vaillancourt, Regis; Roffey, Tyson; Bottomley, Jim

2009-01-01

Explicit patient consent requirements in privacy laws can have a negative impact on health research, leading to selection bias and reduced recruitment. Often legislative requirements to obtain consent are waived if the information collected or disclosed is de-identified. The authors developed and empirically evaluated a new globally optimal de-identification algorithm that satisfies the k-anonymity criterion and that is suitable for health datasets. Authors compared OLA (Optimal Lattice Anonymization) empirically to three existing k-anonymity algorithms, Datafly, Samarati, and Incognito, on six public, hospital, and registry datasets for different values of k and suppression limits. Measurement Three information loss metrics were used for the comparison: precision, discernability metric, and non-uniform entropy. Each algorithm's performance speed was also evaluated. The Datafly and Samarati algorithms had higher information loss than OLA and Incognito; OLA was consistently faster than Incognito in finding the globally optimal de-identification solution. For the de-identification of health datasets, OLA is an improvement on existing k-anonymity algorithms in terms of information loss and performance.

Minimizing finite-volume discretization errors on polyhedral meshes

NASA Astrophysics Data System (ADS)

Mouly, Quentin; Evrard, Fabien; van Wachem, Berend; Denner, Fabian

2017-11-01

Tetrahedral meshes are widely used in CFD to simulate flows in and around complex geometries, as automatic generation tools now allow tetrahedral meshes to represent arbitrary domains in a relatively accessible manner. Polyhedral meshes, however, are an increasingly popular alternative. While tetrahedron have at most four neighbours, the higher number of neighbours per polyhedral cell leads to a more accurate evaluation of gradients, essential for the numerical resolution of PDEs. The use of polyhedral meshes, nonetheless, introduces discretization errors for finite-volume methods: skewness and non-orthogonality, which occur with all sorts of unstructured meshes, as well as errors due to non-planar faces, specific to polygonal faces with more than three vertices. Indeed, polyhedral mesh generation algorithms cannot, in general, guarantee to produce meshes free of non-planar faces. The presented work focuses on the quantification and optimization of discretization errors on polyhedral meshes in the context of finite-volume methods. A quasi-Newton method is employed to optimize the relevant mesh quality measures. Various meshes are optimized and CFD results of cases with known solutions are presented to assess the improvements the optimization approach can provide.

A methodology to guide the selection of composite materials in a wind turbine rotor blade design process

NASA Astrophysics Data System (ADS)

Bortolotti, P.; Adolphs, G.; Bottasso, C. L.

2016-09-01

This work is concerned with the development of an optimization methodology for the composite materials used in wind turbine blades. Goal of the approach is to guide designers in the selection of the different materials of the blade, while providing indications to composite manufacturers on optimal trade-offs between mechanical properties and material costs. The method works by using a parametric material model, and including its free parameters amongst the design variables of a multi-disciplinary wind turbine optimization procedure. The proposed method is tested on the structural redesign of a conceptual 10 MW wind turbine blade, its spar caps and shell skin laminates being subjected to optimization. The procedure identifies a blade optimum for a new spar cap laminate characterized by a higher longitudinal Young's modulus and higher cost than the initial one, which however in turn induce both cost and mass savings in the blade. In terms of shell skin, the adoption of a laminate with intermediate properties between a bi-axial one and a tri-axial one also leads to slight structural improvements.

Improved Detection of Botulinum Neurotoxin Serotype A by Endopep-MS through Peptide Substrate Modification

PubMed Central

Wang, Dongxia; Baudys, Jakub; Ye, Yiming; Rees, Jon C.; Barr, John R.; Pirkle, James L.; Kalb, Suzanne R.

2015-01-01

Botulinum neurotoxins (BoNTs) are a family of seven toxin serotypes that are the most toxic substances known to man. Intoxication with BoNT causes flaccid paralysis and can lead to death if untreated with serotype specific antibodies. Supportive care, including ventilation, may be necessary. Rapid and sensitive detection of BoNT is necessary for timely clinical confirmation of clinical botulism. Previously, our laboratory developed a fast and sensitive mass spectrometry (MS) method termed the Endopep-MS assay. The BoNT serotypes are rapidly detected and differentiated by extracting the toxin with serotype specific antibodies and detecting the unique and serotype specific cleavage products of peptide substrates that mimic the sequence of the BoNT native targets. To further improve the sensitivity of the Endopep-MS assay, we report here the optimization of the substrate peptide for the detection of BoNT/A. Modifications on the terminal groups of the original peptide substrate with acetylation and amidation significantly improved the detection of BoNT/A cleavage products. The replacement of some internal amino acid residues with single or multiple substitutions led to further improvement. An optimized peptide increased assay sensitivity five fold with toxin spiked into buffer solution or different biological matrices. PMID:23017875

Parallel-Vector Algorithm For Rapid Structural Anlysis

NASA Technical Reports Server (NTRS)

Agarwal, Tarun R.; Nguyen, Duc T.; Storaasli, Olaf O.

1993-01-01

New algorithm developed to overcome deficiency of skyline storage scheme by use of variable-band storage scheme. Exploits both parallel and vector capabilities of modern high-performance computers. Gives engineers and designers opportunity to include more design variables and constraints during optimization of structures. Enables use of more refined finite-element meshes to obtain improved understanding of complex behaviors of aerospace structures leading to better, safer designs. Not only attractive for current supercomputers but also for next generation of shared-memory supercomputers.

Measurements of Raman crystallinity profiles in thin-film microcrystalline silicon solar cells

NASA Astrophysics Data System (ADS)

Choong, G.; Vallat-Sauvain, E.; Multone, X.; Fesquet, L.; Kroll, U.; Meier, J.

2013-06-01

Wedge-polished thin film microcrystalline silicon solar cells are prepared and used for micro-Raman measurements. Thereby, the variations of the Raman crystallinity with depth are accessed easily. Depth resolution limits of the measurement set-up are established and calculations evidencing the role of optical limits are presented. Due to this new technique, Raman crystallinity profiles of two microcrystalline silicon cells give first hints for the optimization of the profile leading to improved electrical performance of such devices.

Antimalarial Pyrido[1,2-a]benzimidazoles: Lead Optimization, Parasite Life Cycle Stage Profile, Mechanistic Evaluation, Killing Kinetics, and in Vivo Oral Efficacy in a Mouse Model.

PubMed

Singh, Kawaljit; Okombo, John; Brunschwig, Christel; Ndubi, Ferdinand; Barnard, Linley; Wilkinson, Chad; Njogu, Peter M; Njoroge, Mathew; Laing, Lizahn; Machado, Marta; Prudêncio, Miguel; Reader, Janette; Botha, Mariette; Nondaba, Sindisiwe; Birkholtz, Lyn-Marie; Lauterbach, Sonja; Churchyard, Alisje; Coetzer, Theresa L; Burrows, Jeremy N; Yeates, Clive; Denti, Paolo; Wiesner, Lubbe; Egan, Timothy J; Wittlin, Sergio; Chibale, Kelly

2017-02-23

Further structure-activity relationship (SAR) studies on the recently identified pyrido[1,2-a]benzimidazole (PBI) antimalarials have led to the identification of potent, metabolically stable compounds with improved in vivo oral efficacy in the P. berghei mouse model and additional activity against parasite liver and gametocyte stages, making them potential candidates for preclinical development. Inhibition of hemozoin formation possibly contributes to the mechanism of action.

ERP System Implementation: An Oil and Gas Exploration Sector Perspective

NASA Astrophysics Data System (ADS)

Mishra, Alok; Mishra, Deepti

Enterprise Resource Planning (ERP) systems provide integration and optimization of various business processes which leads to improved planning and decision quality, smoother coordination between business units resulting in higher efficiency, and quicker response time to customer demands and inquiries. This paper reports challenges, opportunities and outcome of ERP implementation in Oil & Gas exploration sector. This study will facilitate in understanding transition, constraints and implementation of ERP in this sector and also provide guidelines from lessons learned in this regard.

Quantum key distribution with finite resources: Secret key rates via Renyi entropies

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

Abruzzo, Silvestre; Kampermann, Hermann; Mertz, Markus

A realistic quantum key distribution (QKD) protocol necessarily deals with finite resources, such as the number of signals exchanged by the two parties. We derive a bound on the secret key rate which is expressed as an optimization problem over Renyi entropies. Under the assumption of collective attacks by an eavesdropper, a computable estimate of our bound for the six-state protocol is provided. This bound leads to improved key rates in comparison to previous results.

[When hair starts to fall out].

PubMed

de Lorenzi, Caroline; Quenan, Sandrine

2018-03-28

Hair loss causes physical and psychological distress and represents a common motive of consultation both in general practice and dermatology. Causes of hair loss are highly diverse and can lead to a challenging diagnosis, which can delay its management. Knowledge of the main causes and their different mechanisms are thus necessary in order to optimize both the diagnosis and treatment. The purpose of this paper is to describe the main causes of hair loss in order to improve its diagnosis and management.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Development of a Control Optimization System for Real Time Monitoring of Managed Aquifer Recharge and Recovery Systems Using Intelligent Sensors

NASA Astrophysics Data System (ADS)

Smits, K. M.; Drumheller, Z. W.; Lee, J. H.; Illangasekare, T. H.; Regnery, J.; Kitanidis, P. K.

2015-12-01

Aquifers around the world show troubling signs of irreversible depletion and seawater intrusion as climate change, population growth, and urbanization lead to reduced natural recharge rates and overuse. Scientists and engineers have begun to revisit the technology of managed aquifer recharge and recovery (MAR) as a means to increase the reliability of the diminishing and increasingly variable groundwater supply. Unfortunately, MAR systems remain wrought with operational challenges related to the quality and quantity of recharged and recovered water stemming from a lack of data-driven, real-time control. This research seeks to develop and validate a general simulation-based control optimization algorithm that relies on real-time data collected though embedded sensors that can be used to ease the operational challenges of MAR facilities. Experiments to validate the control algorithm were conducted at the laboratory scale in a two-dimensional synthetic aquifer under both homogeneous and heterogeneous packing configurations. The synthetic aquifer used well characterized technical sands and the electrical conductivity signal of an inorganic conservative tracer as a surrogate measure for water quality. The synthetic aquifer was outfitted with an array of sensors and an autonomous pumping system. Experimental results verified the feasibility of the approach and suggested that the system can improve the operation of MAR facilities. The dynamic parameter inversion reduced the average error between the simulated and observed pressures between 12.5 and 71.4%. The control optimization algorithm ran smoothly and generated optimal control decisions. Overall, results suggest that with some improvements to the inversion and interpolation algorithms, which can be further advanced through testing with laboratory experiments using sensors, the concept can successfully improve the operation of MAR facilities.

Performance enhancement of linear stirling cryocoolers

NASA Astrophysics Data System (ADS)

Korf, Herbert; Ruehlich, Ingo; Wiedmann, Th.

2000-12-01

Performance and reliability parameters of the AIM Stirling coolers have been presented in several previous publications. This paper focuses on recent developments at AIM for the COP improvement of cryocoolers in IR-detectors and systems applications. Improved COP of cryocoolers is a key for optimized form factors, weight and reliability. In addition, some systems are critical for minimum input power and consequently minimum electromagnetic interference or magnetic stray fields, heat sinking or minimum stress under high g-level, etc. Although performance parameters and loss mechanism are well understood and can be calculated precisely, several losses still had been excessive and needed to be minimized. The AIM program is based on the SADA I cryocooler, which now is optimized to carry 4.3 W net heat load at 77K. As this program will lead into applications on a space platform, in a next step AIM is introducing flexure bearings and in a final step, an advanced pulse tube cold head will be implemented. The performance of the SADA II cooler is also improved by using the same tools and methods than used for the performance increase of the SADA I cooler by a factor of two. The main features are summarized together with measured or calculated performance data.

Unexpected and rapid recovery of left ventricular function in patients with peripartum cardiomyopathy: impact of cardiac resynchronization therapy.

PubMed

Mouquet, Frederic; Mostefa Kara, Meriem; Lamblin, Nicolas; Coulon, Capucine; Langlois, Stephane; Marquie, Christelle; de Groote, Pascal

2012-05-01

Aim Peripartum cardiomyopathy (PPCM) is a rare cause of dilated cardiomyopathy responsible for heart failure toward the end of pregnancy, which can lead to chronic heart failure in 50% of cases. In this short report, we assessed the benefit of cardiac resynchronization in patients with PPCM and chronic systolic dysfunction despite optimal medical treatment. For the last 10 years, we managed eight patients diagnosed with PPCM. Two of them presented severe systolic dysfunction, and medical treatment resulted in limited improvement from 10% to 25% and from 25% to 28% despite optimal treatment for 9 and 6 years, respectively. These two patients were porposed to receive an implantatable cardioverter defibrillator (ICD) and cardiac resynchronization therapy (CRT). Six months after ICD-CRT treatment, we observed a significant improvement in systolic function from 25% to 45% and 28% to 50%, respectively, and positive remodelling with reduction of left ventricular end-diastolic volume from 216 to 144 mL and from 354 to 105 mL, which represent a 34% and a 70% reduction, respectively. Physicians in charge of patients with PPCM should offer the opportunity of CRT for patients whose cardiac function has not significantly improved under standard medical treatment.

Hydrophobic Polystyrene Passivation Layer for Simultaneously Improved Efficiency and Stability in Perovskite Solar Cells.

PubMed

Li, Minghua; Yan, Xiaoqin; Kang, Zhuo; Huan, Yahuan; Li, Yong; Zhang, Ruxiao; Zhang, Yue

2018-06-06

The major restraint for the commercialization of the high-performance hybrid metal halide perovskite solar cells is the long-term stability, especially at the infirm interface between the perovskite film and organic charge-transfer layer. Recently, engineering the interface between the perovskite and spiro-OMeTAD becomes an effective strategy to simultaneously improve the efficiency and stability in the perovskite solar cells. In this work, we demonstrated that introducing an interfacial polystyrene layer between the perovskite film and spiro-OMeTAD layer can effectively improve the perovskite solar cells photovoltaic performance. The inserted polystyrene layer can passivate the interface traps and defects effectively and decrease the nonradiative recombination, leading to enhanced photoluminescence intensity and carrier lifetime, without compromising the carrier extraction and transfer. Under the optimized condition, the perovskite solar cells with the polystyrene layer achieve an enhanced average power efficiency of about 19.61% (20.46% of the best efficiency) from about 17.63% with negligible current density-voltage hysteresis. Moreover, the optimized perovskite solar cells with the hydrophobic polystyrene layer can maintain about 85% initial efficiency after 2 months storage in open air conditions without encapsulation.

Systems oncology: towards patient-specific treatment regimes informed by multiscale mathematical modelling.

PubMed

Powathil, Gibin G; Swat, Maciej; Chaplain, Mark A J

2015-02-01

The multiscale complexity of cancer as a disease necessitates a corresponding multiscale modelling approach to produce truly predictive mathematical models capable of improving existing treatment protocols. To capture all the dynamics of solid tumour growth and its progression, mathematical modellers need to couple biological processes occurring at various spatial and temporal scales (from genes to tissues). Because effectiveness of cancer therapy is considerably affected by intracellular and extracellular heterogeneities as well as by the dynamical changes in the tissue microenvironment, any model attempt to optimise existing protocols must consider these factors ultimately leading to improved multimodal treatment regimes. By improving existing and building new mathematical models of cancer, modellers can play important role in preventing the use of potentially sub-optimal treatment combinations. In this paper, we analyse a multiscale computational mathematical model for cancer growth and spread, incorporating the multiple effects of radiation therapy and chemotherapy in the patient survival probability and implement the model using two different cell based modelling techniques. We show that the insights provided by such multiscale modelling approaches can ultimately help in designing optimal patient-specific multi-modality treatment protocols that may increase patients quality of life. Copyright © 2014 Elsevier Ltd. All rights reserved.

Improvement of the Laser-Induced Breakdown Spectroscopy method sensitivity by the usage of combination of Ag-nanoparticles and vacuum conditions

NASA Astrophysics Data System (ADS)

Sládková, Lucia; Prochazka, David; Pořízka, Pavel; Škarková, Pavlína; Remešová, Michaela; Hrdlička, Aleš; Novotný, Karel; Čelko, Ladislav; Kaiser, Jozef

2017-01-01

In this work we studied the effect of vacuum (low pressure) conditions on the behavior of laser-induced plasma (LIP) created on a sample surface covered with silver nanoparticles (Ag-NPs), i.e. Nanoparticles-Enhanced Laser-Induced Breakdown Spectroscopy (NELIBS) experiment in a vacuum. The focus was put on the step by step optimization of the measurement parameters, such as energy of the laser pulse, temporally resolved detection, ambient pressure, and different content of Ag-NPs applied on the sample surface. The measurement parameters were optimized in order to achieve the greatest enhancement represented as the signal-to-noise ratio (SNR) of NELIBS signal to the SNR of LIBS signal. The presence of NPs involved in the ablation process enhances LIP intensity; hence the improvement in the analytical sensitivity was yielded. A leaded brass standard was analyzed with the emphasis on the signal enhancement of Pb traces. We gained enhancement by a factor of four. Although the low pressure had no significant influence on the LIP signal enhancement compared to that under ambient conditions, the SNR values were noticeably improved with the implementation of the NPs.

Derivation of orthogonal leads from the 12-lead electrocardiogram. Performance of an atrial-based transform for the derivation of P loops.

PubMed

Guillem, M Salud; Sahakian, Alan V; Swiryn, Steven

2008-01-01

The objective of this study was the evaluation of the accuracy of Dower inverse transform for the derivation of the P wave in orthogonal leads. We tested the accuracy of Dower transform on the P wave and compared it with a P-wave-optimized transform in a database of 123 simultaneous recordings of electrocardiograms and vectorcardiograms. This new transform achieved a lower error when we compared derived vs true measured P waves (mean +/- SD, 12.2 +/- 8.0 VRMS) than Dower transform (14.4 +/- 9.5 Root mean squared voltage) and higher correlation values (Rx, 0.93 +/- 0.12; Ry, 0.90 +/- 0.27; Rz, 0.91 +/- 0.18; vs Dower: Rx, 0.88 +/- 0.15; Ry, 0.91 +/- 0.26; Rz, 0.85 +/- 0.23). We conclude that derivation of orthogonal leads for the P wave can be improved by using an atrial-based transform matrix.

Development of new positive-grid alloy and its application to long-life batteries for automotive industry

NASA Astrophysics Data System (ADS)

Furukawa, Jun; Nehyo, Y.; Shiga, S.

Positive-grid corrosion and its resulting creep or growth is one of the major causes of the failure of automotive lead-acid batteries. The importance of grid corrosion and growth is increasing given the tendency for rising temperatures in the engine compartments of modern vehicles. In order to cope with this situation, a new lead alloy has been developed for positive-grids by utilizing an optimized combination of lead-calcium-tin and barium. In addition to enhanced mechanical strength at high temperature, the corrosion-resistance of the grid is improved by as much as two-fold so that the high temperature durability of batteries using such grids has been demonstrated in both hot SAE J240 tests and in field trials in Japan and Thailand. A further advantage of the alloy is its recycleability compared with alloys containing silver. The new alloy gives superior performance in both 12-V flooded and 36-V valve-regulated lead-acid (VRLA) batteries.

Enhanced Solubility and Dissolution Rate of Lacidipine Nanosuspension: Formulation Via Antisolvent Sonoprecipitation Technique and Optimization Using Box-Behnken Design.

PubMed

Kassem, Mohamed A A; ElMeshad, Aliaa N; Fares, Ahmed R

2017-05-01

Lacidipine (LCDP) is a highly lipophilic calcium channel blocker of poor aqueous solubility leading to poor oral absorption. This study aims to prepare and optimize LCDP nanosuspensions using antisolvent sonoprecipitation technique to enhance the solubility and dissolution of LCDP. A three-factor, three-level Box-Behnken design was employed to optimize the formulation variables to obtain LCDP nanosuspension of small and uniform particle size. Formulation variables were as follows: stabilizer to drug ratio (A), sodium deoxycholate percentage (B), and sonication time (C). LCDP nanosuspensions were assessed for particle size, zeta potential, and polydispersity index. The formula with the highest desirability (0.969) was chosen as the optimized formula. The values of the formulation variables (A, B, and C) in the optimized nanosuspension were 1.5, 100%, and 8 min, respectively. Optimal LCDP nanosuspension had particle size (PS) of 273.21 nm, zeta potential (ZP) of -32.68 mV and polydispersity index (PDI) of 0.098. LCDP nanosuspension was characterized using x-ray powder diffraction, differential scanning calorimetry, and transmission electron microscopy. LCDP nanosuspension showed saturation solubility 70 times that of raw LCDP in addition to significantly enhanced dissolution rate due to particle size reduction and decreased crystallinity. These results suggest that the optimized LCDP nanosuspension could be promising to improve oral absorption of LCDP.

Optimization of ramp area aircraft push back time windows in the presence of uncertainty

NASA Astrophysics Data System (ADS)

Coupe, William Jeremy

It is well known that airport surface traffic congestion at major airports is responsible for increased taxi-out times, fuel burn and excess emissions and there is potential to mitigate these negative consequences through optimizing airport surface traffic operations. Due to a highly congested voice communication channel between pilots and air traffic controllers and a data communication channel that is used only for limited functions, one of the most viable near-term strategies for improvement of the surface traffic is issuing a push back advisory to each departing aircraft. This dissertation focuses on the optimization of a push back time window for each departing aircraft. The optimization takes into account both spatial and temporal uncertainties of ramp area aircraft trajectories. The uncertainties are described by a stochastic kinematic model of aircraft trajectories, which is used to infer distributions of combinations of push back times that lead to conflict among trajectories from different gates. The model is validated and the distributions are included in the push back time window optimization. Under the assumption of a fixed taxiway spot schedule, the computed push back time windows can be integrated with a higher level taxiway scheduler to optimize the flow of traffic from the gate to the departure runway queue. To enable real-time decision making the computational time of the push back time window optimization is critical and is analyzed throughout.

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

PubMed

Byron, Kelly; Bluvshtein, Vlad; Lucke, Lori

2013-01-01

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

Spinal cord stimulation for treatment of the pain associated with hereditary multiple osteochondromas

PubMed Central

Mirpuri, Ravi G; Brammeier, Jereme; Chen, Hamilton; Hsu, Frank PK; Chiu, Vi K; Chang, Eric Y

2015-01-01

Objective Hereditary multiple osteochondromas (HMO) usually presents with neoplastic lesions throughout the skeletal system. These lesions frequently cause chronic pain and are conventionally treated with surgical resection and medication. In cases where conventional treatments have failed, spinal cord stimulation (SCS) could be considered as a potential option for pain relief. The objective of this case was to determine if SCS may have a role in treating pain secondary to neoplastic lesions from HMO. Case presentation We report a 65-year-old female who previously received both surgical and pharmacological interventions for treating HMO neoplastic pain in the lumbar, pelvis, femur, and tibial regions. These interventions either failed to offer significant pain relief or caused excessive lethargy. A SCS trial was then offered with a dual 16-contact lead trial leading to 70%–80% improvement in pain from baseline and 85% reduction in oxycodone IR intake. This was followed by permanent implantation of two 2×8 contact paddle leads (T7–T8 and T9–T10 interspaces). After 8-week follow-up, settings were further optimized resulting in an additional 30% improvement in pain compared to last visit. At 6-month follow-up, the patient reported continued pain relief. Conclusion This case demonstrates the first successful use of SCS to treat both HMO and nonmalignant neoplastic-related pain. The patient reported pain improvement from baseline, reduced pain medication requirements, and subjective improvement in quality of life. Additionally, this case demonstrates the potential advantage of trialing multiple painful areas with a 16-contact lead in order to avoid multiple trials and placement. PMID:26316806

High Throughput Screening Identifies Novel Lead Compounds with Activity against Larval, Juvenile and Adult Schistosoma mansoni

PubMed Central

Gardner, J. Mark F.; Bell, Andrew S.; Parkinson, Tanya; Bickle, Quentin

2016-01-01

An estimated 600 million people are affected by the helminth disease schistosomiasis caused by parasites of the genus Schistosoma. There is currently only one drug recommended for treating schistosomiasis, praziquantel (PZQ), which is effective against adult worms but not against the juvenile stage. In an attempt to identify improved drugs for treating the disease, we have carried out high throughput screening of a number of small molecule libraries with the aim of identifying lead compounds with balanced activity against all life stages of Schistosoma. A total of almost 300,000 compounds were screened using a high throughput assay based on motility of worm larvae and image analysis of assay plates. Hits were screened against juvenile and adult worms to identify broadly active compounds and against a mammalian cell line to assess cytotoxicity. A number of compounds were identified as promising leads for further chemical optimization. PMID:27128493

TH-EF-BRB-02: Feasibility of Optimization for Dynamic Trajectory Radiotherapy

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

Fix, MK; Frei, D; Volken, W

2016-06-15

Purpose: Over the last years, volumetric modulated arc therapy (VMAT) has been widely introduced into clinical routine using a coplanar delivery technique. However, VMAT might be improved by including dynamic couch and collimator rotations, leading to dynamic trajectory radiotherapy (DTRT). In this work the feasibility and the potential benefit of DTRT was investigated. Methods: A general framework for the optimization was developed using the Eclipse Scripting Research Application Programming Interface (ESRAPI). Based on contoured target and organs at risk (OARs), the structures are extracted using the ESRAPI. Sampling potential beam directions, regularly distributed on a sphere using a Fibanocci-lattice, themore » fractional volume-overlap of each OAR and the target is determined and used to establish dynamic gantry-couch movements. Then, for each gantry-couch track the most suitable collimator angle is determined for each control point by optimizing the area between the MLC leaves and the target contour. The resulting dynamic trajectories are used as input to perform the optimization using a research version of the VMAT optimization algorithm and the ESRAPI. The feasibility of this procedure was tested for a clinically motivated head and neck case. Resulting dose distributions for the VMAT plan and for the dynamic trajectory treatment plan were compared based on DVH-parameters. Results: While the DVH for the target is virtually preserved, improvements in maximum dose for the DTRT plan were achieved for all OARs except for the inner-ear, where maximum dose remains the same. The major improvements in maximum dose were 6.5% of the prescribed dose (66 Gy) for the parotid and 5.5% for the myelon and the eye. Conclusion: The result of this work suggests that DTRT has a great potential to reduce dose to OARs with similar target coverage when compared to conventional VMAT treatment plans. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.« less

A Search for WIMP Dark Matter Using an Optimized Chi-square Technique on the Final Data from the Cryogenic Dark Matter Search Experiment (CDMS II)

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

Manungu Kiveni, Joseph

2012-12-01

This dissertation describes the results of a WIMP search using CDMS II data sets accumulated at the Soudan Underground Laboratory in Minnesota. Results from the original analysis of these data were published in 2009; two events were observed in the signal region with an expected leakage of 0.9 events. Further investigation revealed an issue with the ionization-pulse reconstruction algorithm leading to a software upgrade and a subsequent reanalysis of the data. As part of the reanalysis, I performed an advanced discrimination technique to better distinguish (potential) signal events from backgrounds using a 5-dimensional chi-square method. This dataanalysis technique combines themore » event information recorded for each WIMP-search event to derive a backgrounddiscrimination parameter capable of reducing the expected background to less than one event, while maintaining high efficiency for signal events. Furthermore, optimizing the cut positions of this 5-dimensional chi-square parameter for the 14 viable germanium detectors yields an improved expected sensitivity to WIMP interactions relative to previous CDMS results. This dissertation describes my improved (and optimized) discrimination technique and the results obtained from a blind application to the reanalyzed CDMS II WIMP-search data.« less

Reconstruction after complex facial trauma: achieving optimal outcome through multiple contemporary surgeries.

PubMed

Jaiswal, Rohit; Pu, Lee L Q

2013-04-01

Major facial trauma injuries often require complex repair. Traditionally, the reconstruction of such injuries has primarily utilized only free tissue transfer. However, the advent of newer, contemporary procedures may lead to potential reconstructive improvement through the use of complementary procedures after free flap reconstruction. An 18-year-old male patient suffered a major left facial degloving injury resulting in soft-tissue defect with exposed zygoma, and parietal bone. Multiple operations were undertaken in a staged manner for reconstruction. A state-of-the-art free anterolateral thigh (ALT) perforator flap and Medpor implant reconstruction of the midface were initially performed, followed by flap debulking, lateral canthopexy, midface lift with redo canthopexy, scalp tissue expansion for hairline reconstruction, and epidermal skin grafting for optimal skin color matching. Over a follow-up period of 2 years, a good and impressive reconstructive result was achieved through the use of multiple contemporary reconstructive procedures following an excellent free ALT flap reconstruction. Multiple staged reconstructions are essential in producing an optimal outcome in this complex facial injury that would likely not have been produced through a 1-stage traditional free flap reconstruction. Utilizing multiple, sequential contemporary surgeries may substantially improve outcome through the enhancement and refinement of results based on possibly the best initial soft-tissue reconstruction.

Update 2014: advances to optimize 6-mercaptopurine and azathioprine to reduce toxicity and improve efficacy in the management of IBD.

PubMed

Amin, Jaimin; Huang, Brian; Yoon, Jessica; Shih, David Q

2015-02-01

The thiopurine drugs, 6-mercaptopurine (6-MP) and azathioprine (AZA), remain as a mainstay therapy in inflammatory bowel disease (IBD). Differences in metabolism of these drugs lead to individual variation in thiopurine metabolite levels that can determine its therapeutic efficacy and development of adverse reactions. In this update, we will review thiopurine metabolic pathway along with the up-to-date approaches in administering thiopurine medications based on the current literature. A search of the PubMed database by 2 independent reviewers identifying 98 articles evaluating thiopurine metabolism and IBD management. Monitoring thiopurine metabolites can assist physicians in optimizing 6-MP and AZA therapy in treating patients with IBD. Of the dosing strategies reviewed, we found evidence for monitoring thiopurine metabolite level, use of allopurinol with thiopurine, use of mesalamine with thiopurine, combination therapy with thiopurine and anti-tumor necrosis factor agents, and split dosing of AZA or 6-MP to optimize thiopurine therapy and minimize adverse effects in IBD. Based on the currently available literature, various dosing strategies to improve therapeutic response and reduce adverse reactions can be considered, including use of allopurinol with thiopurine, use of mesalamine with thiopurine, combination therapy with thiopurine and anti-tumor necrosis factor agents, and split dosing of thiopurine.

Nano-SiC region formation in (100) Si-on-insulator substrate: Optimization of hot-C+-ion implantation process to improve photoluminescence intensity

NASA Astrophysics Data System (ADS)

Mizuno, Tomohisa; Omata, Yuhsuke; Kanazawa, Rikito; Iguchi, Yusuke; Nakada, Shinji; Aoki, Takashi; Sasaki, Tomokazu

2018-04-01

We experimentally studied the optimization of the hot-C+-ion implantation process for forming nano-SiC (silicon carbide) regions in a (100) Si-on-insulator substrate at various hot-C+-ion implantation temperatures and C+ ion doses to improve photoluminescence (PL) intensity for future Si-based photonic devices. We successfully optimized the process by hot-C+-ion implantation at a temperature of about 700 °C and a C+ ion dose of approximately 4 × 1016 cm-2 to realize a high intensity of PL emitted from an approximately 1.5-nm-thick C atom segregation layer near the surface-oxide/Si interface. Moreover, atom probe tomography showed that implanted C atoms cluster in the Si layer and near the oxide/Si interface; thus, the C content locally condenses even in the C atom segregation layer, which leads to SiC formation. Corrector-spherical aberration transmission electron microscopy also showed that both 4H-SiC and 3C-SiC nanoareas near both the surface-oxide/Si and buried-oxide/Si interfaces partially grow into the oxide layer, and the observed PL photons are mainly emitted from the surface SiC nano areas.

Agroecology and healthy food systems in semi-humid tropical Africa: Participatory research with vulnerable farming households in Malawi.

PubMed

Nyantakyi-Frimpong, Hanson; Kangmennaang, Joseph; Bezner Kerr, Rachel; Luginaah, Isaac; Dakishoni, Laifolo; Lupafya, Esther; Shumba, Lizzie; Katundu, Mangani

2017-11-01

This paper assesses the relationship between agroecology, food security, and human health. Specifically, we ask if agroecology can lead to improved food security and human health among vulnerable smallholder farmers in semi-humid tropical Africa. The empirical evidence comes from a cross-sectional household survey (n=1000) in two districts in Malawi, a small country in semi-humid, tropical Africa. The survey consisted of 571 agroecology-adoption and 429 non-agroecology-adoption households. Ordered logistics regression and average treatment effects models were used to determine the effect of agroecology adoption on self-reported health. Our results show that agroecology-adoption households (OR=1.37, p=0.05) were more likely to report optimal health status, and the average treatment effect shows that adopters were 12% more likely to be in optimal health. Furthermore, being moderately food insecure (OR=0.59, p=0.05) and severely food insecure (OR=0.89, p=0.10) were associated with less likelihood of reporting optimal health status. The paper concludes that with the adoption of agroecology in the semi-humid tropics, it is possible for households to diversify their crops and diets, a condition that has strong implications for improved food security, good nutrition and human health. Copyright © 2016 Elsevier B.V. All rights reserved.

Towards high efficiency heliostat fields

NASA Astrophysics Data System (ADS)

Arbes, Florian; Wöhrbach, Markus; Gebreiter, Daniel; Weinrebe, Gerhard

2017-06-01

CSP power plants have great potential to substantially contribute to world energy supply. To set this free, cost reductions are required for future projects. Heliostat field layout optimization offers a great opportunity to improve field efficiency. Field efficiency primarily depends on the positions of the heliostats around the tower, commonly known as the heliostat field layout. Heliostat shape also influences efficiency. Improvements to optical efficiency results in electricity cost reduction without adding any extra technical complexity. Due to computational challenges heliostat fields are often arranged in patterns. The mathematical models of the radial staggered or spiral patterns are based on two parameters and thus lead to uniform patterns. Optical efficiencies of a heliostat field do not change uniformly with the distance to the tower, they even differ in the northern and southern field. A fixed pattern is not optimal in many parts of the heliostat field, especially when used as large scaled heliostat field. In this paper, two methods are described which allow to modify field density suitable to inconsistent field efficiencies. A new software for large scale heliostat field evaluation is presented, it allows for fast optimizations of several parameters for pattern modification routines. It was used to design a heliostat field with 23,000 heliostats, which is currently planned for a site in South Africa.

Poster - 52: Smoothing constraints in Modulated Photon Radiotherapy (XMRT) fluence map optimization

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

McGeachy, Philip; Villarreal-Barajas, Jose Eduardo

Purpose: Modulated Photon Radiotherapy (XMRT), which simultaneously optimizes photon beamlet energy (6 and 18 MV) and fluence, has recently shown dosimetric improvement in comparison to conventional IMRT. That said, the degree of smoothness of resulting fluence maps (FMs) has yet to be investigated and could impact the deliverability of XMRT. This study looks at investigating FM smoothness and imposing smoothing constraint in the fluence map optimization. Methods: Smoothing constraints were modeled in the XMRT algorithm with the sum of positive gradient (SPG) technique. XMRT solutions, with and without SPG constraints, were generated for a clinical prostate scan using standard dosimetricmore » prescriptions, constraints, and a seven coplanar beam arrangement. The smoothness, with and without SPG constraints, was assessed by looking at the absolute and relative maximum SPG scores for each fluence map. Dose volume histograms were utilized when evaluating impact on the dose distribution. Results: Imposing SPG constraints reduced the absolute and relative maximum SPG values by factors of up to 5 and 2, respectively, when compared with their non-SPG constrained counterparts. This leads to a more seamless conversion of FMS to their respective MLC sequences. This improved smoothness resulted in an increase to organ at risk (OAR) dose, however the increase is not clinically significant. Conclusions: For a clinical prostate case, there was a noticeable improvement in the smoothness of the XMRT FMs when SPG constraints were applied with a minor increase in dose to OARs. This increase in OAR dose is not clinically meaningful.« less

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

DOE PAGES

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

2015-04-08

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

Multi response optimization of internal grinding process parameters for outer ring using Taguchi method and PCR-TOPSIS

NASA Astrophysics Data System (ADS)

Wisnuadi, Alief Regyan; Damayanti, Retno Wulan; Pujiyanto, Eko

2018-02-01

Bearing is one of the most widely used parts in automotive industry. One of the leading bearing manufacturing companies in the world is SKF Indonesia. This company must produce bearing with international standard. SKF Indonesia must do continuous improvement in order to face competition. During this time, SKF Indonesia is only performing quality control at its Quality Assurance department. In other words, quality improvement at SKF Indonesia has not been done thoroughly. The purpose of this research is to improve quality of outer ring product at SKF Indonesia by conducting an internal grinding process experiment about setting speed ratio, fine position, and spark out grinding time. The specific purpose of this experiment is to optimize some quality responses such as roughness, roundness, and cycle time. All of the response in this experiment were smaller the better. Taguchi method and PCR-TOPSIS are used for the optimization process. The result of this research shows that by using Taguchi method and PCR-TOPSIS, the optimum condition occurs on speed ratio 36, fine position 18 µm/s and spark out 0.5 s. The optimum conditions result were roughness 0.398 µm, roundness 1.78 µm and cycle time 8.1 s. This results have been better than the previous results and meet the standards. The roughness of 0.523 µm decrease to 0.398 µm and the average cycle time of 8.5 s decrease to 8.1 s.

Engineering microorganisms for improving polyhydroxyalkanoate biosynthesis.

PubMed

Chen, Guo-Qiang; Jiang, Xiao-Ran

2017-11-20

Biosynthesis of polyhydroxyalkanoates (PHA) has been studied since the 1920s. The biosynthesis pathways have been well understood and various attempts have been made to improve the PHA biosynthesis efficiency. Recent progresses have been focused on systematic improvements on PHA biosynthesis including changing growth pattern for rapid proliferation, engineering to enlarge cell sizes for more PHA accumulation space, reprogramming the PHA synthesis pathways using optimized RBS and promoter, redirecting metabolic flux to PHA synthesis using CRISPR/Cas9 tools, and very importantly, the employment of non-traditional host such as halophiles for reduced complexity on PHA production. All of the efforts should lead to ultrahigh PHA accumulation, controllable PHA compositions and molecular weights, open and continuous PHA production with gravity separation processes, resulting in competitive PHA production cost. Copyright © 2017 Elsevier Ltd. All rights reserved.

Q-factor improvement of degenerate four-wave-mixing regenerators for ASE degraded signals

NASA Astrophysics Data System (ADS)

Lu, Hang; Wu, Bao-jian; Geng, Yong; Zhou, Xing-yu; Sun, Fan

2017-11-01

All-optical regenerators can be used to suppress amplified spontaneous emission (ASE) noise introduced by cascaded erbium doped fiber amplifiers (EDFAs) in optical fiber communication systems and lead to the improvement of optical receiver sensitivity. By introducing the Q-factor transfer function (QTF), we evaluate the Q-factor performance of degenerate four-wave mixing (DFWM) regenerators with clock pump and reveal the differences between the optimal input powers determined from the static and dynamic power tranfer function (PTF) and the QTF curves. Our simulation shows that the clock-pump regnerator is capable of improving the Q-facor and receiver sensitivity for 40 Gbit/s ASE-degraded return-to-zero on-off keying (RZ-OOK) signal by 2.58 dB and 4.2 dB, respectively.

Improved efficiency of NiOx-based p-i-n perovskite solar cells by using PTEG-1 as electron transport layer

NASA Astrophysics Data System (ADS)

Groeneveld, Bart G. H. M.; Najafi, Mehrdad; Steensma, Bauke; Adjokatse, Sampson; Fang, Hong-Hua; Jahani, Fatemeh; Qiu, Li; ten Brink, Gert H.; Hummelen, Jan C.; Loi, Maria Antonietta

2017-07-01

We present efficient p-i-n type perovskite solar cells using NiOx as the hole transport layer and a fulleropyrrolidine with a triethylene glycol monoethyl ether side chain (PTEG-1) as electron transport layer. This electron transport layer leads to higher power conversion efficiencies compared to perovskite solar cells with PCBM (phenyl-C61-butyric acid methyl ester). The improved performance of PTEG-1 devices is attributed to the reduced trap-assisted recombination and improved charge extraction in these solar cells, as determined by light intensity dependence and photoluminescence measurements. Through optimization of the hole and electron transport layers, the power conversion efficiency of the NiOx/perovskite/PTEG-1 solar cells was increased up to 16.1%.

Individualized treatment with transcranial direct current stimulation in patients with chronic non-fluent aphasia due to stroke

PubMed Central

Shah-Basak, Priyanka P.; Norise, Catherine; Garcia, Gabriella; Torres, Jose; Faseyitan, Olufunsho; Hamilton, Roy H.

2015-01-01

While evidence suggests that transcranial direct current stimulation (tDCS) may facilitate language recovery in chronic post-stroke aphasia, individual variability in patient response to different patterns of stimulation remains largely unexplored. We sought to characterize this variability among chronic aphasic individuals, and to explore whether repeated stimulation with an individualized optimal montage could lead to persistent reduction of aphasia severity. In a two-phase study, we first stimulated patients with four active montages (left hemispheric anode or cathode; right hemispheric anode or cathode) and one sham montage (Phase 1). We examined changes in picture naming ability to address (1) variability in response to different montages among our patients, and (2) whether individual patients responded optimally to at least one montage. During Phase 2, subjects who responded in Phase 1 were randomized to receive either real-tDCS or to receive sham stimulation (10 days); patients who were randomized to receive sham stimulation first were then crossed over to receive real-tDCS (10 days). In both phases, 2 mA tDCS was administered for 20 min per real-tDCS sessions and patients performed a picture naming task during stimulation. Patients' language ability was re-tested after 2-weeks and 2-months following real and sham tDCS in Phase 2. In Phase 1, despite considerable individual variability, the greatest average improvement was observed after left-cathodal stimulation. Seven out of 12 subjects responded optimally to at least one montage as demonstrated by transient improvement in picture-naming. In Phase 2, aphasia severity improved at 2-weeks and 2-months following real-tDCS but not sham. Despite individual variability with respect to optimal tDCS approach, certain montages result in consistent transient improvement in persons with chronic post-stroke aphasia. This preliminary study supports the notion that individualized tDCS treatment may enhance aphasia recovery in a persistent manner. PMID:25954178

Planning intensive care unit design using computer simulation modeling: optimizing integration of clinical, operational, and architectural requirements.

PubMed

OʼHara, Susan

2014-01-01

Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses' role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.

Automated sample plan selection for OPC modeling

NASA Astrophysics Data System (ADS)

Casati, Nathalie; Gabrani, Maria; Viswanathan, Ramya; Bayraktar, Zikri; Jaiswal, Om; DeMaris, David; Abdo, Amr Y.; Oberschmidt, James; Krause, Andreas

2014-03-01

It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

An efficient interior-point algorithm with new non-monotone line search filter method for nonlinear constrained programming

NASA Astrophysics Data System (ADS)

Wang, Liwei; Liu, Xinggao; Zhang, Zeyin

2017-02-01

An efficient primal-dual interior-point algorithm using a new non-monotone line search filter method is presented for nonlinear constrained programming, which is widely applied in engineering optimization. The new non-monotone line search technique is introduced to lead to relaxed step acceptance conditions and improved convergence performance. It can also avoid the choice of the upper bound on the memory, which brings obvious disadvantages to traditional techniques. Under mild assumptions, the global convergence of the new non-monotone line search filter method is analysed, and fast local convergence is ensured by second order corrections. The proposed algorithm is applied to the classical alkylation process optimization problem and the results illustrate its effectiveness. Some comprehensive comparisons to existing methods are also presented.

An update on the use of massive transfusion protocols in obstetrics.

PubMed

Pacheco, Luis D; Saade, George R; Costantine, Maged M; Clark, Steven L; Hankins, Gary D V

2016-03-01

Obstetrical hemorrhage remains a leading cause of maternal mortality worldwide. New concepts involving the pathophysiology of hemorrhage have been described and include early activation of both the protein C and fibrinolytic pathways. New strategies in hemorrhage treatment include the use of hemostatic resuscitation, although the optimal ratio to administer the various blood products is still unknown. Massive transfusion protocols involve the early utilization of blood products and limit the traditional approach of early massive crystalloid-based resuscitation. The evidence behind hemostatic resuscitation has changed in the last few years, and debate is ongoing regarding optimal transfusion strategies. The use of tranexamic acid, fibrinogen concentrates, and prothrombin complex concentrates has emerged as new potential alternative treatment strategies with improved safety profiles. Copyright © 2016 Elsevier Inc. All rights reserved.

Novel 1,2-dihydroquinazolin-2-ones: Design, synthesis, and biological evaluation against Trypanosoma brucei.

PubMed

Pham, ThanhTruc; Walden, Madeline; Butler, Christopher; Diaz-Gonzalez, Rosario; Pérez-Moreno, Guiomar; Ceballos-Pérez, Gloria; Gomez-Pérez, Veronica; García-Hernández, Raquel; Zecca, Henry; Krakoff, Emma; Kopec, Brian; Ichire, Ogar; Mackenzie, Caden; Pitot, Marika; Ruiz, Luis Miguel; Gamarro, Francisco; González-Pacanowska, Dolores; Navarro, Miguel; Dounay, Amy B

2017-08-15

In 2014, a published report of the high-throughput screen of>42,000 kinase inhibitors from GlaxoSmithKline against T. brucei identified 797 potent and selective hits. From this rich data set, we selected NEU-0001101 (1) for hit-to-lead optimization. Through our preliminary compound synthesis and SAR studies, we have confirmed the previously reported activity of 1 in a T. brucei cell proliferation assay and have identified alternative groups to replace the pyridyl ring in 1. Pyrazole 24 achieves improvements in both potency and lipophilicity relative to 1, while also showing good in vitro metabolic stability. The SAR developed on 24 provides new directions for further optimization of this novel scaffold for anti-trypanosomal drug discovery. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discovery of Potent Non-Nucleoside Inhibitors of Dengue Viral RNA-Dependent RNA Polymerase from a Fragment Hit Using Structure-Based Drug Design.

PubMed

Yokokawa, Fumiaki; Nilar, Shahul; Noble, Christian G; Lim, Siew Pheng; Rao, Ranga; Tania, Stefani; Wang, Gang; Lee, Gladys; Hunziker, Jürg; Karuna, Ratna; Manjunatha, Ujjini; Shi, Pei-Yong; Smith, Paul W

2016-04-28

The discovery and optimization of non-nucleoside dengue viral RNA-dependent-RNA polymerase (RdRp) inhibitors are described. An X-ray-based fragment screen of Novartis' fragment collection resulted in the identification of a biphenyl acetic acid fragment 3, which bound in the palm subdomain of RdRp. Subsequent optimization of the fragment hit 3, relying on structure-based design, resulted in a >1000-fold improvement in potency in vitro and acquired antidengue activity against all four serotypes with low micromolar EC50 in cell-based assays. The lead candidate 27 interacts with a novel binding pocket in the palm subdomain of the RdRp and exerts a promising activity against all clinically relevant dengue serotypes.

Structural and biological evaluation of a novel series of benzimidazole inhibitors of Francisella tularensis enoyl-ACP reductase (FabI)

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

Mehboob, Shahila; Song, Jinhua; Hevener, Kirk E.

Francisella tularensis, the causative agent of tularemia, presents a significant biological threat and is a Category A priority pathogen due to its potential for weaponization. In the bacterial FASII pathway we found it a viable target for the development of novel antibacterial agents treating Gram-negative infections. Here, we report the advancement of a promising series of benzimidazole FabI (enoyl-ACP reductase) inhibitors to a second-generation using a systematic, structure-guided lead optimization strategy, and the determination of several co-crystal structures that confirm the binding mode of designed inhibitors. Furthermore, these compounds display an improved low nanomolar enzymatic activity as well as promisingmore » low microgram/mL antibacterial activity against both F. tularensis and Staphylococcus aureus and its methicillin-resistant strain (MRSA). Finally, the improvements in activity accompanying structural modifications lead to a better understanding of the relationship between the chemical structure and biological activity that encompasses both enzymatic and whole-cell activity.« less

Structural and biological evaluation of a novel series of benzimidazole inhibitors of Francisella tularensis enoyl-ACP reductase (FabI)

DOE PAGES

Mehboob, Shahila; Song, Jinhua; Hevener, Kirk E.; ...

2015-01-29

Francisella tularensis, the causative agent of tularemia, presents a significant biological threat and is a Category A priority pathogen due to its potential for weaponization. In the bacterial FASII pathway we found it a viable target for the development of novel antibacterial agents treating Gram-negative infections. Here, we report the advancement of a promising series of benzimidazole FabI (enoyl-ACP reductase) inhibitors to a second-generation using a systematic, structure-guided lead optimization strategy, and the determination of several co-crystal structures that confirm the binding mode of designed inhibitors. Furthermore, these compounds display an improved low nanomolar enzymatic activity as well as promisingmore » low microgram/mL antibacterial activity against both F. tularensis and Staphylococcus aureus and its methicillin-resistant strain (MRSA). Finally, the improvements in activity accompanying structural modifications lead to a better understanding of the relationship between the chemical structure and biological activity that encompasses both enzymatic and whole-cell activity.« less

An ion-gated bipolar amplifier for ion sensing with enhanced signal and improved noise performance

NASA Astrophysics Data System (ADS)

Zhang, Da; Gao, Xindong; Chen, Si; Norström, Hans; Smith, Ulf; Solomon, Paul; Zhang, Shi-Li; Zhang, Zhen

2014-08-01

This work presents a proof-of-concept ion-sensitive device operating in electrolytes. The device, i.e., an ion-gated bipolar amplifier (IGBA), consists of a modified ion-sensitive field-effect transistor (ISFET) intimately integrated with a vertical bipolar junction transistor for immediate current amplification without introducing additional noise. With the current non-optimized design, the IGBA is already characterized by a 70-fold internal amplification of the ISFET output signal. This signal amplification is retained when the IGBA is used for monitoring pH variations. The tight integration significantly suppresses the interference of the IGBA signal by external noise, which leads to an improvement in signal-to-noise performance compared to its ISFET reference. The IGBA concept is especially suitable for biochips with millions of electric sensors that are connected to peripheral readout circuitry via extensive metallization which may in turn invite external interferences leading to contamination of the signal before it reaches the first external amplification stage.

Large enhancement of thermoelectric effects in a tunneling-coupled parallel DQD-AB ring attached to one normal and one superconducting lead

NASA Astrophysics Data System (ADS)

Yao, Hui; Zhang, Chao; Li, Zhi-Jian; Nie, Yi-Hang; Niu, Peng-bin

2018-05-01

We theoretically investigate the thermoelectric properties in a tunneling-coupled parallel DQD-AB ring attached to one normal and one superconducting lead. The role of the intrinsic and extrinsic parameters in improving thermoelectric properties is discussed. The peak value of figure of merit near gap edges increases with the asymmetry parameter decreasing, particularly, when asymmetry parameter is less than 0.5, the figure of merit near gap edges rapidly rises. When the interdot coupling strengh is less than the superconducting gap the thermopower spectrum presents a single-platform structure. While when the interdot coupling strengh is larger than the gap, a double-platform structure appears in thermopower spectrum. Outside the gap the peak values of figure of merit might reach the order of 102. On the basis of optimizing internal parameters the thermoelectric conversion efficiency of the device can be further improved by appropriately matching the total magnetic flux and the flux difference between two subrings.

It takes a team: reflections on insecticide discoveries, toxicological problems and enjoying the unexpected.

PubMed

Wing, Keith D

2017-04-01

Absorption/distribution/metabolism/excretion (ADME)-related studies are mandatory in agrochemical development/registration, but can also play a valuable role in the discovery process. In combination with target-site potency, bioavailability/ADME characteristics determine agrochemical bioactivity and selectivity, and these concerns can dictate the fate of a discovery lead area. Bioavailability/ADME research was critical to the eventual commercialization of three different insecticide chemistries examined in this paper. In one situation, improved systemicity in anthranilic diamides was required to expand pest spectrum. In another, ADME tools were needed to improve the selective toxicity and non-target safety of sodium channel blocker insecticides. Finally, differential ADME characteristics of two classes of hormone agonists dictated differential insecticidal activity, and were useful in optimizing the dibenzoylhydrazine ecdysone agonists. ADME discovery research will help companies to advance novel, efficacious and selective agrochemicals, but organizational patience and a desire to understand lead areas in depth are required. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

An analytical design procedure for the determination of effective leading edge extensions on thick delta wings

NASA Technical Reports Server (NTRS)

Ghaffari, F.; Chaturvedi, S. K.

1984-01-01

An analytical design procedure for leading edge extensions (LEE) was developed for thick delta wings. This LEE device is designed to be mounted to a wing along the pseudo-stagnation stream surface associated with the attached flow design lift coefficient of greater than zero. The intended purpose of this device is to improve the aerodynamic performance of high subsonic and low supersonic aircraft at incidences above that of attached flow design lift coefficient, by using a vortex system emanating along the leading edges of the device. The low pressure associated with these vortices would act on the LEE upper surface and the forward facing area at the wing leading edges, providing an additional lift and effective leading edge thrust recovery. The first application of this technique was to a thick, round edged, twisted and cambered wing of approximately triangular planform having a sweep of 58 deg and aspect ratio of 2.30. The panel aerodynamics and vortex lattice method with suction analogy computer codes were employed to determine the pseudo-stagnation stream surface and an optimized LEE planform shape.

Mitochondria and heart failure.

PubMed

Murray, Andrew J; Edwards, Lindsay M; Clarke, Kieran

2007-11-01

Energetic abnormalities in cardiac and skeletal muscle occur in heart failure and correlate with clinical symptoms and mortality. It is likely that the cellular mechanism leading to energetic failure involves mitochondrial dysfunction. Therefore, it is crucial to elucidate the causes of mitochondrial myopathy, in order to improve cardiac and skeletal muscle function, and hence quality of life, in heart failure patients. Recent studies identified several potential stresses that lead to mitochondrial dysfunction in heart failure. Chronically elevated plasma free fatty acid levels in heart failure are associated with decreased metabolic efficiency and cellular insulin resistance. Tissue hypoxia, resulting from low cardiac output and endothelial impairment, can lead to oxidative stress and mitochondrial DNA damage, which in turn causes dysfunction and loss of mitochondrial mass. Therapies aimed at protecting mitochondrial function have shown promise in patients and animal models with heart failure. Despite current therapies, which provide substantial benefit to patients, heart failure remains a relentlessly progressive disease, and new approaches to treatment are necessary. Novel pharmacological agents are needed that optimize substrate metabolism and maintain mitochondrial integrity, improve oxidative capacity in heart and skeletal muscle, and alleviate many of the clinical symptoms associated with heart failure.

Velocity field measurements in the wake of a propeller model

NASA Astrophysics Data System (ADS)

Mukund, R.; Kumar, A. Chandan

2016-10-01

Turboprop configurations are being revisited for the modern-day regional transport aircrafts for their fuel efficiency. The use of laminar flow wings is an effort in this direction. One way to further improve their efficiency is by optimizing the flow over the wing in the propeller wake. Previous studies have focused on improving the gross aerodynamic characteristics of the wing. It is known that the propeller slipstream causes early transition of the boundary layer on the wing. However, an optimized design of the propeller and wing combination could delay this transition and decrease the skin friction drag. Such a wing design would require the detailed knowledge of the development of the slipstream in isolated conditions. There are very few studies in the literature addressing the requirements of transport aircraft having six-bladed propeller and cruising at a high propeller advance ratio. Low-speed wind tunnel experiments have been conducted on a powered propeller model in isolated conditions, measuring the velocity field in the vertical plane behind the propeller using two-component hot-wire anemometry. The data obtained clearly resolved the mean velocity, the turbulence, the ensemble phase averages and the structure and development of the tip vortex. The turbulence in the slipstream showed that transition could be close to the leading edge of the wing, making it a fine case for optimization. The development of the wake with distance shows some interesting flow features, and the data are valuable for flow computation and optimization.

Improved specimen reconstruction by Hilbert phase contrast tomography.

PubMed

Barton, Bastian; Joos, Friederike; Schröder, Rasmus R

2008-11-01

The low signal-to-noise ratio (SNR) in images of unstained specimens recorded with conventional defocus phase contrast makes it difficult to interpret 3D volumes obtained by electron tomography (ET). The high defocus applied for conventional tilt series generates some phase contrast but leads to an incomplete transfer of object information. For tomography of biological weak-phase objects, optimal image contrast and subsequently an optimized SNR are essential for the reconstruction of details such as macromolecular assemblies at molecular resolution. The problem of low contrast can be partially solved by applying a Hilbert phase plate positioned in the back focal plane (BFP) of the objective lens while recording images in Gaussian focus. Images recorded with the Hilbert phase plate provide optimized positive phase contrast at low spatial frequencies, and the contrast transfer in principle extends to the information limit of the microscope. The antisymmetric Hilbert phase contrast (HPC) can be numerically converted into isotropic contrast, which is equivalent to the contrast obtained by a Zernike phase plate. Thus, in-focus HPC provides optimal structure factor information without limiting effects of the transfer function. In this article, we present the first electron tomograms of biological specimens reconstructed from Hilbert phase plate image series. We outline the technical implementation of the phase plate and demonstrate that the technique is routinely applicable for tomography. A comparison between conventional defocus tomograms and in-focus HPC volumes shows an enhanced SNR and an improved specimen visibility for in-focus Hilbert tomography.

Laser-drilled micro-hole arrays on polyurethane synthetic leather for improvement of water vapor permeability

NASA Astrophysics Data System (ADS)

Wu, Y.; Wang, A. H.; Zheng, R. R.; Tang, H. Q.; Qi, X. Y.; Ye, B.

2014-06-01

Three kinds of lasers at 1064, 532 and 355 nm wavelengths respectively were adopted to construct micro-hole arrays on polyurethane (PU) synthetic leather with an aim to improve water vapor permeability (WVP) of PU synthetic leather. The morphology of the laser-drilled micro-holes was observed to optimize laser parameters. The WVP and slit tear resistance of the laser-drilled leather were measured. Results show that the optimized pulse energy for the 1064, 532 and 355 nm lasers are 0.8, 1.1 and 0.26 mJ, respectively. The diameters of the micro-holes drilled with the optimized laser pulse energy were about 20, 15 and 10 μm, respectively. The depths of the micro-holes drilled with the optimized pulse energy were about 21, 60 and 69 μm, respectively. Compared with the untreated samples, the highest WVP growth ratio was 38.4%, 46.8% and 53.5% achieved by the 1064, 532 and 355 nm lasers, respectively. And the highest decreasing ratio of slit tear resistance was 11.1%, 14.8%, and 22.5% treated by the 1064, 532 and 355 nm lasers, respectively. Analysis of the interaction mechanism between laser beams at three kinds of laser wavelengths and the PU synthetic leather revealed that laser micro-drilling at 355 nm wavelength displayed both photochemical ablation and photothermal ablation, while laser micro-drilling at 1064 and 532 nm wavelengths leaded to photothermal ablation only.

Topology optimization of two-dimensional elastic wave barriers

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Discovery and optimization of potent and selective imidazopyridine and imidazopyridazine mTOR inhibitors.

PubMed

Peterson, Emily A; Boezio, Alessandro A; Andrews, Paul S; Boezio, Christiane M; Bush, Tammy L; Cheng, Alan C; Choquette, Deborah; Coats, James R; Colletti, Adria E; Copeland, Katrina W; DuPont, Michelle; Graceffa, Russell; Grubinska, Barbara; Kim, Joseph L; Lewis, Richard T; Liu, Jingzhou; Mullady, Erin L; Potashman, Michele H; Romero, Karina; Shaffer, Paul L; Stanton, Mary K; Stellwagen, John C; Teffera, Yohannes; Yi, Shuyan; Cai, Ti; La, Daniel S

2012-08-01

mTOR is a critical regulator of cellular signaling downstream of multiple growth factors. The mTOR/PI3K/AKT pathway is frequently mutated in human cancers and is thus an important oncology target. Herein we report the evolution of our program to discover ATP-competitive mTOR inhibitors that demonstrate improved pharmacokinetic properties and selectivity compared to our previous leads. Through targeted SAR and structure-guided design, new imidazopyridine and imidazopyridazine scaffolds were identified that demonstrated superior inhibition of mTOR in cellular assays, selectivity over the closely related PIKK family and improved in vivo clearance over our previously reported benzimidazole series. Copyright © 2012. Published by Elsevier Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

Optimization of sparse matrix-vector multiplication on emerging multicore platforms

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

Williams, Samuel; Oliker, Leonid; Vuduc, Richard

2007-01-01

We are witnessing a dramatic change in computer architecture due to the multicore paradigm shift, as every electronic device from cell phones to supercomputers confronts parallelism of unprecedented scale. To fully unleash the potential of these systems, the HPC community must develop multicore specific optimization methodologies for important scientific computations. In this work, we examine sparse matrix-vector multiply (SpMV) - one of the most heavily used kernels in scientific computing - across a broad spectrum of multicore designs. Our experimental platform includes the homogeneous AMD dual-core and Intel quad-core designs, the heterogeneous STI Cell, as well as the first scientificmore » study of the highly multithreaded Sun Niagara2. We present several optimization strategies especially effective for the multicore environment, and demonstrate significant performance improvements compared to existing state-of-the-art serial and parallel SpMV implementations. Additionally, we present key insights into the architectural tradeoffs of leading multicore design strategies, in the context of demanding memory-bound numerical algorithms.« less

Uncovering a New Moral Dilemma of Economic Optimization in Biotechnological Processing.

PubMed

Vochozka, Marek; Stehel, Vojtěch; Maroušková, Anna

2017-06-08

The trend of emerging biorefineries is to process the harvest as efficiently as possible and without any waste. From the most valuable phytomass, refined medicines, enzymes, dyes and other special reactants are created. Functional foods, food ingredients, oils, alcohol, solvents, plastics, fillers and a wide variety of other chemical products follow. After being treated with nutrient recovery techniques (for fertilizer production), biofuels or soil improvers are produced from the leftovers. Economic optimization algorithms have confirmed that such complex biorefineries can be financially viable only when a high degree of feedstock concentration is included. Because the plant material is extremely voluminous before processing, the farming intensity of special plants increases in the nearest vicinity of agglomerations where the biorefineries are built for logistical reasons. Interdisciplinary analyses revealed that these optimization measures lead to significantly increased pollen levels in neighbouring urban areas and subsequently an increased risk of allergies, respectively costs to the national health system. A new moral dilemma between the shareholder's profit and public interest was uncovered and subjected to disputation.

Narcissistic personality and risk perception among Chinese aviators: The mediating role of promotion focus.

PubMed

Ju, Chengting; Ji, Ming; Lan, Jijun; You, Xuqun

2017-12-01

Optimism bias is a crucial feature of risk perception that leads to increased risk-taking behaviour, which is a particularly salient issue among pilots in aviation settings due to the high-stakes nature of flight. The current study sought to address the roles of narcissism and promotion focus on optimism bias in risk perception in aviation context. Participants were 239 male flight cadets from the Civil Aviation Flight University of China who completed the Narcissistic Personality Inventory-13, the Work Regulatory Focus Scale, and an indirect measure of unrealistic optimism in risk perception, which measured risk perception for the individual and the risk assumed by other individuals performing the same task. Higher narcissism increased the likelihood of underestimating personal risks, an effect that was mediated by high promotion focus motivation, such that high narcissism led to high promotion focus motivation. The findings have important implications for improving the accuracy of risk perception in aviation risks among aviators. © 2016 International Union of Psychological Science.

The design and implementation of a parallel unstructured Euler solver using software primitives

NASA Technical Reports Server (NTRS)

Das, R.; Mavriplis, D. J.; Saltz, J.; Gupta, S.; Ponnusamy, R.

1992-01-01

This paper is concerned with the implementation of a three-dimensional unstructured grid Euler-solver on massively parallel distributed-memory computer architectures. The goal is to minimize solution time by achieving high computational rates with a numerically efficient algorithm. An unstructured multigrid algorithm with an edge-based data structure has been adopted, and a number of optimizations have been devised and implemented in order to accelerate the parallel communication rates. The implementation is carried out by creating a set of software tools, which provide an interface between the parallelization issues and the sequential code, while providing a basis for future automatic run-time compilation support. Large practical unstructured grid problems are solved on the Intel iPSC/860 hypercube and Intel Touchstone Delta machine. The quantitative effect of the various optimizations are demonstrated, and we show that the combined effect of these optimizations leads to roughly a factor of three performance improvement. The overall solution efficiency is compared with that obtained on the CRAY-YMP vector supercomputer.

Optimal geometrical design of inertial vibration DC piezoelectric nanogenerators based on obliquely aligned InN nanowire arrays.

PubMed

Ku, Nai-Jen; Liu, Guocheng; Wang, Chao-Hung; Gupta, Kapil; Liao, Wei-Shun; Ban, Dayan; Liu, Chuan-Pu

2017-09-28

Piezoelectric nanogenerators have been investigated to generate electricity from environmental vibrations due to their energy conversion capabilities. In this study, we demonstrate an optimal geometrical design of inertial vibration direct-current piezoelectric nanogenerators based on obliquely aligned InN nanowire (NW) arrays with an optimized oblique angle of ∼58°, and driven by the inertial force of their own weight, using a mechanical shaker without any AC/DC converters. The nanogenerator device manifests potential applications not only as a unique energy harvesting device capable of scavenging energy from weak mechanical vibrations, but also as a sensitive strain sensor. The maximum output power density of the nanogenerator is estimated to be 2.9 nW cm -2 , leading to an improvement of about 3-12 times that of vertically aligned ZnO NW DC nanogenerators. Integration of two nanogenerators also exhibits a linear increase in the output power, offering an enormous potential for the creation of self-powered sustainable nanosystems utilizing incessantly natural ambient energy sources.

Short-term Operation of Multi-purpose Reservoir using Model Predictive Control

NASA Astrophysics Data System (ADS)

Uysal, Gokcen; Schwanenberg, Dirk; Alvarado Montero, Rodolfo; Sensoy, Aynur; Arda Sorman, Ali

2017-04-01

Operation of water structures especially with conflicting water supply and flood mitigation objectives is under more stress attributed to growing water demand and changing hydro-climatic conditions. Model Predictive Control (MPC) based optimal control solutions has been successfully applied to different water resources applications. In this study, Feedback Control (FBC) and MPC get combined and an improved joint optimization-simulation operating scheme is proposed. Water supply and flood control objectives are fulfilled by incorporating the long term water supply objectives into a time-dependent variable guide curve policy whereas the extreme floods are attenuated by means of short-term optimization based on MPC. A final experiment is carried out to assess the lead time performance and reliability of forecasts in a hindcasting experiment with imperfect, perturbed forecasts. The framework is tested in Yuvacık Dam reservoir where the main water supply reservoir of Kocaeli City in the northwestern part of Turkey (the Marmara region) and it requires a challenging gate operation due to restricted downstream flow conditions.

[Financial rating optimization in pressure ulcers management: yes, but at what price?].

PubMed

Crouzet, C; Chaput, B; Grolleau, J-L

2013-06-01

The surgical management of pressure ulcers remains very expensive even if preventive measures and improved care pathways allowed to reduce spending in this domain in recent years. Since 2004, the funding of French hospitals by "fee-for-service" and the needs of saving health spending necessarily compels us to interest ourselves in these purely economic considerations and sometimes modify our requirements for hospital stay to optimize a "patient' valorisation group". In the future, this may lead the surgeon to bias the real needs of the patient for the benefit of hospital establishment. Through a medico-economic analysis of our practices conducted in the plastic surgery department of the University hospital of Toulouse, we tried to identify how to optimize the surgical management of pressure ulcers in terms of valorisation of hospital stay. The aim is still to remain critical about the aberrations that this could introduce in the future for our clinical activity. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Experimental Research on Optimizing Inlet Airflow of Wet Cooling Towers under Crosswind Conditions

NASA Astrophysics Data System (ADS)

Chen, You Liang; Shi, Yong Feng; Hao, Jian Gang; Chang, Hao; Sun, Feng Zhong

2018-01-01

A new approach of installing air deflectors around tower inlet circumferentially was proposed to optimize the inlet airflow and reduce the adverse effect of crosswinds on the thermal performance of natural draft wet cooling towers (NDWCT). And inlet airflow uniformity coefficient was defined to analyze the uniformity of circumferential inlet airflow quantitatively. Then the effect of air deflectors on the NDWCT performance was investigated experimentally. By contrast between inlet air flow rate and cooling efficiency, it has been found that crosswinds not only decrease the inlet air flow rate, but also reduce the uniformity of inlet airflow, which reduce NDWCT performance jointly. After installing air deflectors, the inlet air flow rate and uniformity coefficient increase, the uniformity of heat and mass transfer increases correspondingly, which improve the cooling performance. In addition, analysis on Lewis factor demonstrates that the inlet airflow optimization has more enhancement of heat transfer than mass transfer, but leads to more water evaporation loss.

Comparative study of popular objective functions for damping power system oscillations in multimachine system.

PubMed

Islam, Naz Niamul; Hannan, M A; Shareef, Hussain; Mohamed, Azah; Salam, M A

2014-01-01

Power oscillation damping controller is designed in linearized model with heuristic optimization techniques. Selection of the objective function is very crucial for damping controller design by optimization algorithms. In this research, comparative analysis has been carried out to evaluate the effectiveness of popular objective functions used in power system oscillation damping. Two-stage lead-lag damping controller by means of power system stabilizers is optimized using differential search algorithm for different objective functions. Linearized model simulations are performed to compare the dominant mode's performance and then the nonlinear model is continued to evaluate the damping performance over power system oscillations. All the simulations are conducted in two-area four-machine power system to bring a detailed analysis. Investigated results proved that multiobjective D-shaped function is an effective objective function in terms of moving unstable and lightly damped electromechanical modes into stable region. Thus, D-shape function ultimately improves overall system damping and concurrently enhances power system reliability.

In silico optimization of pharmacokinetic properties and receptor binding affinity simultaneously: a 'parallel progression approach to drug design' applied to β-blockers.

PubMed

Advani, Poonam; Joseph, Blessy; Ambre, Premlata; Pissurlenkar, Raghuvir; Khedkar, Vijay; Iyer, Krishna; Gabhe, Satish; Iyer, Radhakrishnan P; Coutinho, Evans

2016-01-01

The present work exploits the potential of in silico approaches for minimizing attrition of leads in the later stages of drug development. We propose a theoretical approach, wherein 'parallel' information is generated to simultaneously optimize the pharmacokinetics (PK) and pharmacodynamics (PD) of lead candidates. β-blockers, though in use for many years, have suboptimal PKs; hence are an ideal test series for the 'parallel progression approach'. This approach utilizes molecular modeling tools viz. hologram quantitative structure activity relationships, homology modeling, docking, predictive metabolism, and toxicity models. Validated models have been developed for PK parameters such as volume of distribution (log Vd) and clearance (log Cl), which together influence the half-life (t1/2) of a drug. Simultaneously, models for PD in terms of inhibition constant pKi have been developed. Thus, PK and PD properties of β-blockers were concurrently analyzed and after iterative cycling, modifications were proposed that lead to compounds with optimized PK and PD. We report some of the resultant re-engineered β-blockers with improved half-lives and pKi values comparable with marketed β-blockers. These were further analyzed by the docking studies to evaluate their binding poses. Finally, metabolic and toxicological assessment of these molecules was done through in silico methods. The strategy proposed herein has potential universal applicability, and can be used in any drug discovery scenario; provided that the data used is consistent in terms of experimental conditions, endpoints, and methods employed. Thus the 'parallel progression approach' helps to simultaneously fine-tune various properties of the drug and would be an invaluable tool during the drug development process.

Development of tellurium oxide and lead-bismuth oxide glasses for mid-wave infra-red transmission optics

NASA Astrophysics Data System (ADS)

Zhou, Beiming; Rapp, Charles F.; Driver, John K.; Myers, Michael J.; Myers, John D.; Goldstein, Jonathan; Utano, Rich; Gupta, Shantanu

2013-03-01

Heavy metal oxide glasses exhibiting high transmission in the Mid-Wave Infra-Red (MWIR) spectrum are often difficult to manufacture in large sizes with optimized physical and optical properties. In this work, we researched and developed improved tellurium-zinc-barium and lead-bismuth-gallium heavy metal oxide glasses for use in the manufacture of fiber optics, optical components and laser gain materials. Two glass families were investigated, one based upon tellurium and another based on lead-bismuth. Glass compositions were optimized for stability and high transmission in the MWIR. Targeted glass specifications included low hydroxyl concentration, extended MWIR transmission window, and high resistance against devitrification upon heating. Work included the processing of high purity raw materials, melting under controlled dry Redox balanced atmosphere, finning, casting and annealing. Batch melts as large as 4 kilograms were sprue cast into aluminum and stainless steel molds or temperature controlled bronze tube with mechanical bait. Small (100g) test melts were typically processed in-situ in a 5%Au°/95%Pt° crucible. Our group manufactured and evaluated over 100 different experimental heavy metal glass compositions during a two year period. A wide range of glass melting, fining, casting techniques and experimental protocols were employed. MWIR glass applications include remote sensing, directional infrared counter measures, detection of explosives and chemical warfare agents, laser detection tracking and ranging, range gated imaging and spectroscopy. Enhanced long range mid-infrared sensor performance is optimized when operating in the atmospheric windows from ~ 2.0 to 2.4μm, ~ 3.5 to 4.3μm and ~ 4.5 to 5.0μm.

Surface Plasmon Resonance kinetic analysis of the interaction between G-quadruplex nucleic acids and an anti-G-quadruplex monoclonal antibody.

PubMed

Lago, Sara; Nadai, Matteo; Rossetto, Monica; Richter, Sara N

2018-06-01

G-quadruplexes (G4s) are nucleic acids secondary structures formed in guanine-rich sequences. Anti-G4 antibodies represent a tool for the direct investigation of G4s in cells. Surface Plasmon Resonance (SPR) is a highly sensitive technology, suitable for assessing the affinity between biomolecules. We here aimed at improving the orientation of an anti-G4 antibody on the SPR sensor chip to optimize detection of binding antigens. SPR was employed to characterize the anti-G4 antibody interaction with G4 and non-G4 oligonucleotides. Dextran-functionalized sensor chips were used both in covalent coupling and capturing procedures. The use of two leading molecule for orienting the antibody of interest allowed to improve its activity from completely non-functional to 65% active. The specificity of the anti-G4 antobody for G4 structures could thus be assessed with high sensitivity and reliability. Optimization of the immobilization protocol for SPR biosensing, allowed us to determine the anti-G4 antibody affinity and specificity for G4 antigens with higher sensitivity with respect to other in vitro assays such as ELISA. Anti-G4 antibody specificity is a fundamental assumption for the future utilization of this kind of antibodies for monitoring G4s directly in cells. The heterogeneous orientation of amine-coupling immobilized ligands is a general problem that often leads to partial or complete inactivation of the molecules. Here we describe a new strategy for improving ligand orientation: driving it from two sides. This principle can be virtually applied to every molecule that loses its activity or is poorly immobilized after standard coupling to the SPR chip surface. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

[Analysis of washing efficiency and change in lead speciation in lead-contaminated soil of a battery factory].

PubMed

Ren, Bei; Huang, Jin-lou; Miao, Ming-sheng

2013-09-01

Lead-contaminated soil with different pollution load in a lead battery factory in the southwest of China was chosen as the research object, the lead content and speciation were analyzed, and different washing agents were screened. The lead washing efficiency and lead speciation were analyzed under different pH conditions, and the soil of different particle size was washed using different duration to determine the best washing time. The results showed that the soil of sites A and B in the factory was severely contaminated, the lead concentration reaching 15,703.22 mg x kg(-1) and 1747.78 mg x kg(-1), respectively, and the proportion of the active-state lead was relatively high, while the residue state accounted for only 17.32%, 11.64%, 14.6% and 10.2%. EDTA and hydrochloric acid showed the best extraction effect in the 5 washing agents tested, which included EDTA, hydrochloric acid, citric acid, rhamnolipid and SDS. Cleaning under acidic conditions could not only effectively extract the total amount of lead but also effectively reduce the environmental risk of active-state lead. pH 4-7 was suggested as the most appropriate condition. The cleaning effect of coarse sand and fine sand was good, while for washing powder clay, it is better to improve the process, with the optimal washing time determined as 240 min.

High-Fidelity Aerostructural Optimization of Nonplanar Wings for Commercial Transport Aircraft

NASA Astrophysics Data System (ADS)

Khosravi, Shahriar

Although the aerospace sector is currently responsible for a relatively small portion of global anthropogenic greenhouse gas emissions, the growth of the airline industry raises serious concerns about the future of commercial aviation. As a result, the development of new aircraft design concepts with the potential to improve fuel efficiency remains an important priority. Numerical optimization based on high-fidelity physics has become an increasingly attractive tool over the past fifteen years in the search for environmentally friendly aircraft designs that reduce fuel consumption. This approach is able to discover novel design concepts and features that may never be considered without optimization. This can help reduce the economic costs and risks associated with developing new aircraft concepts by providing a more realistic assessment early in the design process. This thesis provides an assessment of the potential efficiency improvements obtained from nonplanar wings through the application of fully coupled high-fidelity aerostructural optimization. In this work, we conduct aerostructural optimization using the Euler equations to model the flow along with a viscous drag estimate based on the surface area. A major focus of the thesis is on finding the optimal shape and performance benefits of nonplanar wingtip devices. Two winglet configurations are considered: winglet-up and winglet-down. These are compared to optimized planar wings of the same projected span in order to quantify the possible drag reductions offered by winglets. In addition, the drooped wing is studied in the context of exploratory optimization. The main results show that the winglet-down configuration is the most efficient winglet shape, reducing the drag by approximately 2% at the same weight in comparison to a planar wing. There are two reasons for the superior performance of this design. First, this configuration moves the tip vortex further away from the wing. Second, the winglet-down concept has a higher projected span at the deflected state due to the structural deflections. Finally, the exploratory optimization studies lead to a drooped wing with the potential to increase range by 4.9% relative to a planar wing.

Image-based optimization of coronal magnetic field models for improved space weather forecasting

NASA Astrophysics Data System (ADS)

Uritsky, V. M.; Davila, J. M.; Jones, S. I.; MacNeice, P. J.

2017-12-01

The existing space weather forecasting frameworks show a significant dependence on the accuracy of the photospheric magnetograms and the extrapolation models used to reconstruct the magnetic filed in the solar corona. Minor uncertainties in the magnetic field magnitude and direction near the Sun, when propagated through the heliosphere, can lead to unacceptible prediction errors at 1 AU. We argue that ground based and satellite coronagraph images can provide valid geometric constraints that could be used for improving coronal magnetic field extrapolation results, enabling more reliable forecasts of extreme space weather events such as major CMEs. In contrast to the previously developed loop segmentation codes designed for detecting compact closed-field structures above solar active regions, we focus on the large-scale geometry of the open-field coronal regions up to 1-2 solar radii above the photosphere. By applying the developed image processing techniques to high-resolution Mauna Loa Solar Observatory images, we perform an optimized 3D B-line tracing for a full Carrington rotation using the magnetic field extrapolation code developed S. Jones at al. (ApJ 2016, 2017). Our tracing results are shown to be in a good qualitative agreement with the large-scale configuration of the optical corona, and lead to a more consistent reconstruction of the large-scale coronal magnetic field geometry, and potentially more accurate global heliospheric simulation results. Several upcoming data products for the space weather forecasting community will be also discussed.

SU-E-T-802: Verification of Implanted Cardiac Pacemaker Doses in Intensity-Modulated Radiation Therapy: Dose Prediction Accuracy and Reduction Effect of a Lead Sheet

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

Lee, J; Chung, J

2015-06-15

Purpose: To verify delivered doses on the implanted cardiac pacemaker, predicted doses with and without dose reduction method were verified using the MOSFET detectors in terms of beam delivery and dose calculation techniques in intensity-modulated radiation therapy (IMRT). Methods: The pacemaker doses for a patient with a tongue cancer were predicted according to the beam delivery methods [step-and-shoot (SS) and sliding window (SW)], intensity levels for dose optimization, and dose calculation algorithms. Dosimetric effects on the pacemaker were calculated three dose engines: pencil-beam convolution (PBC), analytical anisotropic algorithm (AAA), and Acuros-XB. A lead shield of 2 mm thickness was designedmore » for minimizing irradiated doses to the pacemaker. Dose variations affected by the heterogeneous material properties of the pacemaker and effectiveness of the lead shield were predicted by the Acuros-XB. Dose prediction accuracy and the feasibility of the dose reduction strategy were verified based on the measured skin doses right above the pacemaker using mosfet detectors during the radiation treatment. Results: The Acuros-XB showed underestimated skin doses and overestimated doses by the lead-shield effect, even though the lower dose disagreement was observed. It led to improved dose prediction with higher intensity level of dose optimization in IMRT. The dedicated tertiary lead sheet effectively achieved reduction of pacemaker dose up to 60%. Conclusion: The current SS technique could deliver lower scattered doses than recommendation criteria, however, use of the lead sheet contributed to reduce scattered doses.Thin lead plate can be a useful tertiary shielder and it could not acuse malfunction or electrical damage of the implanted pacemaker in IMRT. It is required to estimate more accurate scattered doses of the patient with medical device to design proper dose reduction strategy.« less

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

PubMed

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

2015-03-01

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

Improved perception of communication and compliance with a revised, intensive care unit-specific bedside communication sheet.

PubMed

Aponte-Patel, Linda; Sen, Anita

2015-01-01

Although many pediatric intensive care units (PICUs) use beside communication sheets (BCSs) to highlight daily goals, the optimal format is unknown. A site-specific BCS could improve both PICU communication and compliance completing the BCS. Via written survey, PICU staff at an academic children's hospital provided recommendations for improving and revising an existing BCS. Pre- and post-BCS revision, PICU staff were polled regarding PICU communication and BCS effectiveness, and daily compliance for completing the BCS was monitored. After implementation of the revised BCS, staff reporting "excellent" or "very good" day-to-day communication within the PICU increased from 57% to 77% (P = .02). Compliance for completing the BCS also increased significantly (75% vs 83%, P = .03). Introduction of a focused and concise BCS tailored to a specific PICU leads to improved perceptions of communication by PICU staff and increased compliance completing the daily BCS. © The Author(s) 2014.

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

PubMed

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

2009-07-01

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

Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors

NASA Astrophysics Data System (ADS)

Murumkar, Prashant Revan; Zambre, Vishal Prakash; Yadav, Mange Ram

2010-02-01

A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.

Water-Energy Nexus: Examining The Crucial Connection Through Simulation Based Optimization

NASA Astrophysics Data System (ADS)

Erfani, T.; Tan, C. C.

2014-12-01

With a growing urbanisation and the emergence of climate change, the world is facing a more water constrained future. This phenomenon will have direct impacts on the resilience and performance of energy sector as water is playing a key role in electricity generation processes. As energy is becoming a thirstier resource and the pressure on finite water sources is increasing, modelling and analysing this closely interlinked and interdependent loop, called 'water-energy nexus' is becoming an important cross-disciplinary challenge. Conflict often arises in transboundary river where several countries share the same source of water to be used in productive sectors for economic growth. From the perspective of the upstream users, it would be ideal to store the water for hydropower generation and protect the city against drought whereas the downstream users need the supply of water for growth. This research use the case study on the transboundary Blue Nile River basin located in the Middle East where the Ethiopian government decided to invest on building a new dam to store the water and generate hydropower. This leads to an opposition by downstream users as they believe that the introduction of the dam would reduce the amount of water available downstream. This calls for a compromise management where the reservoir operating rules need to be derived considering the interdependencies between the resources available and the requirements proposed by all users. For this, we link multiobjective optimization algorithm to water-energy use simulation model to achieve effective management of the transboundary reservoir operating strategies. The objective functions aim to attain social and economic welfare by minimizing the deficit of water supply and maximizing the hydropower generation. The study helps to improve the policies by understanding the value of water and energy in their alternative uses. The results show how different optimal reservoir release rules generate different trade-off solutions inherently involved in upstream and downstream users requirements and decisions. This study stimulates the research in this context by using simulation based optimization techniques to manage for security for food, water and energy generation, which leads to improve sustainability and long-term political stability.

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

Optimization of pelvic heating rate distributions with electromagnetic phased arrays.

PubMed

Paulsen, K D; Geimer, S; Tang, J; Boyse, W E

1999-01-01

Deep heating of pelvic tumours with electromagnetic phased arrays has recently been reported to improve local tumour control when combined with radiotherapy in a randomized clinical trial despite the fact that rather modest elevations in tumour temperatures were achieved. It is reasonable to surmise that improvements in temperature elevation could lead to even better tumour response rates, motivating studies which attempt to explore the parameter space associated with heating rate delivery in the pelvis. Computational models which are based on detailed three-dimensional patient anatomy are readily available and lend themselves to this type of investigation. In this paper, volume average SAR is optimized in a predefined target volume subject to a maximum allowable volume average SAR outside this zone. Variables under study include the position of the target zone, the number and distribution of radiators and the applicator operating frequency. The results show a clear preference for increasing frequency beyond 100 MHz, which is typically applied clinically, especially as the number of antennae increases. Increasing both the number of antennae per circumferential distance around the patient, as well as the number of independently functioning antenna bands along the patient length, is important in this regard, although improvements were found to be more significant with increasing circumferential antenna density. However, there is considerable site specific variation and cases occur where lower numbers of antennae spread out over multiple longitudinal bands are more advantageous. The results presented here have been normalized relative to an optimized set of antenna array amplitudes and phases operating at 100 MHz which is a common clinical configuration. The intent is to provide some indications of avenues for improving the heating rate distributions achievable with current technology.

Scoring of Side-Chain Packings: An Analysis of Weight Factors and Molecular Dynamics Structures.

PubMed

Colbes, Jose; Aguila, Sergio A; Brizuela, Carlos A

2018-02-26

The protein side-chain packing problem (PSCPP) is a central task in computational protein design. The problem is usually modeled as a combinatorial optimization problem, which consists of searching for a set of rotamers, from a given rotamer library, that minimizes a scoring function (SF). The SF is a weighted sum of terms, that can be decomposed in physics-based and knowledge-based terms. Although there are many methods to obtain approximate solutions for this problem, all of them have similar performances and there has not been a significant improvement in recent years. Studies on protein structure prediction and protein design revealed the limitations of current SFs to achieve further improvements for these two problems. In the same line, a recent work reported a similar result for the PSCPP. In this work, we ask whether or not this negative result regarding further improvements in performance is due to (i) an incorrect weighting of the SFs terms or (ii) the constrained conformation resulting from the protein crystallization process. To analyze these questions, we (i) model the PSCPP as a bi-objective combinatorial optimization problem, optimizing, at the same time, the two most important terms of two SFs of state-of-the-art algorithms and (ii) performed a preprocessing relaxation of the crystal structure through molecular dynamics to simulate the protein in the solvent and evaluated the performance of these two state-of-the-art SFs under these conditions. Our results indicate that (i) no matter what combination of weight factors we use the current SFs will not lead to better performances and (ii) the evaluated SFs will not be able to improve performance on relaxed structures. Furthermore, the experiments revealed that the SFs and the methods are biased toward crystallized structures.

Optimized scheduling of VLBI UT1 intensive sessions for twin telescopes employing impact factor analysis

NASA Astrophysics Data System (ADS)

Leek, Judith; Artz, Thomas; Nothnagel, Axel

2015-09-01

Daily Very Long Baseline Interferometry (VLBI) intensive measurements make an important contribution to the regular monitoring of Earth rotation variations. Since these variations are quite rapid, their knowledge is important for navigation with global navigation satellite system and for investigations in Earth sciences. Unfortunately, the precision of VLBI intensive observations is 2-3 times worse than the precision of regular 24h-VLBI measurements with networks of 5-10 radio telescopes. The major advancement of research in this paper is the improvement of VLBI intensive results by (a) using twin telescopes instead of single telescopes and (b) applying an entirely new scheduling concept for the individual observations. Preparatory investigations of standardintensive sessions suggest that the impact factors of the observations are well suited for the identification of the most influential observations which are needed for the determination of certain parameters within the entire design of a VLBI session. Based on this experience, the scheduling method is designed for optimizing the observations' geometry for a given network of radio telescopes and a predefined set of parameters to be estimated. The configuration of at least two twin telescopes, or one twin and two single telescopes, offers the possibility of building pairwise sub-nets that observe two different sources simultaneously. In addition to an optimized observing plan, a special parametrization for twin telescopes leads to an improved determination of Earth rotation variations, as it is shown by simulated observations. In general, an improvement of about 50 % in the formal errors can be realized using twin radio telescopes. This result is only due to geometric improvements as higher slew rates of the twin telescopes are not taken into account.

Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture

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

Panyala, Ajay; Chavarría-Miranda, Daniel; Manzano, Joseph B.

High performance, parallel applications with irregular data accesses are becoming a critical workload class for modern systems. In particular, the execution of such workloads on emerging many-core systems is expected to be a significant component of applications in data mining, machine learning, scientific computing and graph analytics. However, power and energy constraints limit the capabilities of individual cores, memory hierarchy and on-chip interconnect of such systems, thus leading to architectural and software trade-os that must be understood in the context of the intended application’s behavior. Irregular applications are notoriously hard to optimize given their data-dependent access patterns, lack of structuredmore » locality and complex data structures and code patterns. We have ported two irregular applications, graph community detection using the Louvain method (Grappolo) and high-performance conjugate gradient (HPCCG), to the Tilera many-core system and have conducted a detailed study of platform-independent and platform-specific optimizations that improve their performance as well as reduce their overall energy consumption. To conduct this study, we employ an auto-tuning based approach that explores the optimization design space along three dimensions - memory layout schemes, GCC compiler flag choices and OpenMP loop scheduling options. We leverage MIT’s OpenTuner auto-tuning framework to explore and recommend energy optimal choices for different combinations of parameters. We then conduct an in-depth architectural characterization to understand the memory behavior of the selected workloads. Finally, we perform a correlation study to demonstrate the interplay between the hardware behavior and application characteristics. Using auto-tuning, we demonstrate whole-node energy savings and performance improvements of up to 49:6% and 60% relative to a baseline instantiation, and up to 31% and 45:4% relative to manually optimized variants.« less

Helium: lifting high-performance stencil kernels from stripped x86 binaries to halide DSL code

DOE PAGES

Mendis, Charith; Bosboom, Jeffrey; Wu, Kevin; ...

2015-06-03

Highly optimized programs are prone to bit rot, where performance quickly becomes suboptimal in the face of new hardware and compiler techniques. In this paper we show how to automatically lift performance-critical stencil kernels from a stripped x86 binary and generate the corresponding code in the high-level domain-specific language Halide. Using Halide's state-of-the-art optimizations targeting current hardware, we show that new optimized versions of these kernels can replace the originals to rejuvenate the application for newer hardware. The original optimized code for kernels in stripped binaries is nearly impossible to analyze statically. Instead, we rely on dynamic traces to regeneratemore » the kernels. We perform buffer structure reconstruction to identify input, intermediate and output buffer shapes. Here, we abstract from a forest of concrete dependency trees which contain absolute memory addresses to symbolic trees suitable for high-level code generation. This is done by canonicalizing trees, clustering them based on structure, inferring higher-dimensional buffer accesses and finally by solving a set of linear equations based on buffer accesses to lift them up to simple, high-level expressions. Helium can handle highly optimized, complex stencil kernels with input-dependent conditionals. We lift seven kernels from Adobe Photoshop giving a 75 % performance improvement, four kernels from Irfan View, leading to 4.97 x performance, and one stencil from the mini GMG multigrid benchmark netting a 4.25 x improvement in performance. We manually rejuvenated Photoshop by replacing eleven of Photoshop's filters with our lifted implementations, giving 1.12 x speedup without affecting the user experience.« less

Optimizing Illumina next-generation sequencing library preparation for extremely AT-biased genomes.

PubMed

Oyola, Samuel O; Otto, Thomas D; Gu, Yong; Maslen, Gareth; Manske, Magnus; Campino, Susana; Turner, Daniel J; Macinnis, Bronwyn; Kwiatkowski, Dominic P; Swerdlow, Harold P; Quail, Michael A

2012-01-03

Massively parallel sequencing technology is revolutionizing approaches to genomic and genetic research. Since its advent, the scale and efficiency of Next-Generation Sequencing (NGS) has rapidly improved. In spite of this success, sequencing genomes or genomic regions with extremely biased base composition is still a great challenge to the currently available NGS platforms. The genomes of some important pathogenic organisms like Plasmodium falciparum (high AT content) and Mycobacterium tuberculosis (high GC content) display extremes of base composition. The standard library preparation procedures that employ PCR amplification have been shown to cause uneven read coverage particularly across AT and GC rich regions, leading to problems in genome assembly and variation analyses. Alternative library-preparation approaches that omit PCR amplification require large quantities of starting material and hence are not suitable for small amounts of DNA/RNA such as those from clinical isolates. We have developed and optimized library-preparation procedures suitable for low quantity starting material and tolerant to extremely high AT content sequences. We have used our optimized conditions in parallel with standard methods to prepare Illumina sequencing libraries from a non-clinical and a clinical isolate (containing ~53% host contamination). By analyzing and comparing the quality of sequence data generated, we show that our optimized conditions that involve a PCR additive (TMAC), produces amplified libraries with improved coverage of extremely AT-rich regions and reduced bias toward GC neutral templates. We have developed a robust and optimized Next-Generation Sequencing library amplification method suitable for extremely AT-rich genomes. The new amplification conditions significantly reduce bias and retain the complexity of either extremes of base composition. This development will greatly benefit sequencing clinical samples that often require amplification due to low mass of DNA starting material.

2D/ 3D Quantitative Ultrasound of the Breast

NASA Astrophysics Data System (ADS)

Nasief, Haidy Gerges

Breast cancer is the second leading cause of cancer death of women in the United States, so breast cancer screening for early detection is common. The purpose of this dissertation is to optimize quantitative ultrasound (QUS) methods to improve the specificity and objectivity of breast ultrasound. To pursue this goal, the dissertation is divided into two parts: 1) to optimize 2D QUS, and 2) to introduce and validate 3D QUS. Previous studies had validated these methods in phantoms. Applying our QUS analysis on subcutaneous breast fat demonstrated that QUS parameter estimates for subcutaneous fat were consistent among different human subjects. This validated our in vivo data acquisition methods and supported the use of breast fat as a clinical reference tissue for ultrasound BI-RADSRTM assessments. Although current QUS methods perform well for straightforward cases when assumptions of stationarity and diffuse scattering are well-founded, these conditions often are not present due to the complicated nature of in vivo breast tissue. Key improvements in QUS algorithms to address these challenges were: 1) applying a "modified least squares method (MLSM)" to account for the heterogeneous tissue path between the transducer and the region of interest, ROI; 2) detecting anisotropy in acoustic parameters; and 3) detecting and removing the echo sources that depart from diffuse and stationary scattering conditions. The results showed that a Bayesian classifier combining three QUS parameters in a biased pool of high-quality breast ultrasound data successfully differentiated all fibroadenomas from all carcinomas. Given promising initial results in 2D, extension to 3D acquisitions in QUS provided a unique capability to test QUS for the entire breast volume. QUS parameter estimates using 3D data were consistent with those found in 2D for phantoms and in vivo data. Extensions of QUS technology from 2D to 3D can improve the specificity of breast ultrasound, and thus, could lead to improved screening with this modality.

Efficient heuristics for maximum common substructure search.

PubMed

Englert, Péter; Kovács, Péter

2015-05-26

Maximum common substructure search is a computationally hard optimization problem with diverse applications in the field of cheminformatics, including similarity search, lead optimization, molecule alignment, and clustering. Most of these applications have strict constraints on running time, so heuristic methods are often preferred. However, the development of an algorithm that is both fast enough and accurate enough for most practical purposes is still a challenge. Moreover, in some applications, the quality of a common substructure depends not only on its size but also on various topological features of the one-to-one atom correspondence it defines. Two state-of-the-art heuristic algorithms for finding maximum common substructures have been implemented at ChemAxon Ltd., and effective heuristics have been developed to improve both their efficiency and the relevance of the atom mappings they provide. The implementations have been thoroughly evaluated and compared with existing solutions (KCOMBU and Indigo). The heuristics have been found to greatly improve the performance and applicability of the algorithms. The purpose of this paper is to introduce the applied methods and present the experimental results.

Introducing folding stability into the score function for computational design of RNA-binding peptides boosts the probability of success.

PubMed

Xiao, Xingqing; Agris, Paul F; Hall, Carol K

2016-05-01

A computational strategy that integrates our peptide search algorithm with atomistic molecular dynamics simulation was used to design rational peptide drugs that recognize and bind to the anticodon stem and loop domain (ASL(Lys3)) of human tRNAUUULys3 for the purpose of interrupting HIV replication. The score function of the search algorithm was improved by adding a peptide stability term weighted by an adjustable factor λ to the peptide binding free energy. The five best peptide sequences associated with five different values of λ were determined using the search algorithm and then input in atomistic simulations to examine the stability of the peptides' folded conformations and their ability to bind to ASL(Lys3). Simulation results demonstrated that setting an intermediate value of λ achieves a good balance between optimizing the peptide's binding ability and stabilizing its folded conformation during the sequence evolution process, and hence leads to optimal binding to the target ASL(Lys3). Thus, addition of a peptide stability term significantly improves the success rate for our peptide design search. © 2016 Wiley Periodicals, Inc.

Optimization of Uranium-Doped Americium Oxide Synthesis for Space Application.

PubMed

Vigier, Jean-François; Freis, Daniel; Pöml, Philipp; Prieur, Damien; Lajarge, Patrick; Gardeur, Sébastien; Guiot, Antony; Bouëxière, Daniel; Konings, Rudy J M

2018-04-16

Americium 241 is a potential alternative to plutonium 238 as an energy source for missions into deep space or to the dark side of planetary bodies. In order to use the 241 Am isotope for radioisotope thermoelectric generator or radioisotope heating unit (RHU) production, americium materials need to be developed. This study focuses on the stabilization of a cubic americium oxide phase using uranium as the dopant. After optimization of the material preparation, (Am 0.80 U 0.12 Np 0.06 Pu 0.02 )O 1.8 has been successfully synthesized to prepare a 2.96 g pellet containing 2.13 g of 241 Am for fabrication of a small scale RHU prototype. Compared to the use of pure americium oxide, the use of uranium-doped americium oxide leads to a number of improvements from a material properties and safety point of view, such as good behavior under sintering conditions or under alpha self-irradiation. The mixed oxide is a good host for neptunium (i.e., the 241 Am daughter element), and it has improved safety against radioactive material dispersion in the case of accidental conditions.

Virtual reality simulation for the optimization of endovascular procedures: current perspectives.

PubMed

Rudarakanchana, Nung; Van Herzeele, Isabelle; Desender, Liesbeth; Cheshire, Nicholas J W

2015-01-01

Endovascular technologies are rapidly evolving, often requiring coordination and cooperation between clinicians and technicians from diverse specialties. These multidisciplinary interactions lead to challenges that are reflected in the high rate of errors occurring during endovascular procedures. Endovascular virtual reality (VR) simulation has evolved from simple benchtop devices to full physic simulators with advanced haptics and dynamic imaging and physiological controls. The latest developments in this field include the use of fully immersive simulated hybrid angiosuites to train whole endovascular teams in crisis resource management and novel technologies that enable practitioners to build VR simulations based on patient-specific anatomy. As our understanding of the skills, both technical and nontechnical, required for optimal endovascular performance improves, the requisite tools for objective assessment of these skills are being developed and will further enable the use of VR simulation in the training and assessment of endovascular interventionalists and their entire teams. Simulation training that allows deliberate practice without danger to patients may be key to bridging the gap between new endovascular technology and improved patient outcomes.

Automated Spectroscopic Analysis Using the Particle Swarm Optimization Algorithm: Implementing a Guided Search Algorithm to Autofit

NASA Astrophysics Data System (ADS)

Ervin, Katherine; Shipman, Steven

2017-06-01

While rotational spectra can be rapidly collected, their analysis (especially for complex systems) is seldom straightforward, leading to a bottleneck. The AUTOFIT program was designed to serve that need by quickly matching rotational constants to spectra with little user input and supervision. This program can potentially be improved by incorporating an optimization algorithm in the search for a solution. The Particle Swarm Optimization Algorithm (PSO) was chosen for implementation. PSO is part of a family of optimization algorithms called heuristic algorithms, which seek approximate best answers. This is ideal for rotational spectra, where an exact match will not be found without incorporating distortion constants, etc., which would otherwise greatly increase the size of the search space. PSO was tested for robustness against five standard fitness functions and then applied to a custom fitness function created for rotational spectra. This talk will explain the Particle Swarm Optimization algorithm and how it works, describe how Autofit was modified to use PSO, discuss the fitness function developed to work with spectroscopic data, and show our current results. Seifert, N.A., Finneran, I.A., Perez, C., Zaleski, D.P., Neill, J.L., Steber, A.L., Suenram, R.D., Lesarri, A., Shipman, S.T., Pate, B.H., J. Mol. Spec. 312, 13-21 (2015)

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Experimental study of flow separation control on a low- Re airfoil using leading-edge protuberance method

NASA Astrophysics Data System (ADS)

Zhang, M. M.; Wang, G. F.; Xu, J. Z.

2014-04-01

An experimental study of flow separation control on a low- Re c airfoil was presently investigated using a newly developed leading-edge protuberance method, motivated by the improvement in the hydrodynamics of the giant humpback whale through its pectoral flippers. Deploying this method, the control effectiveness of the airfoil aerodynamics was fully evaluated using a three-component force balance, leading to an effectively impaired stall phenomenon and great improvement in the performances within the wide post-stall angle range (22°-80°). To understand the flow physics behind, the vorticity field, velocity field and boundary layer flow field over the airfoil suction side were examined using a particle image velocimetry and an oil-flow surface visualization system. It was found that the leading-edge protuberance method, more like low-profile vortex generator, effectively modified the flow pattern of the airfoil boundary layer through the chordwise and spanwise evolutions of the interacting streamwise vortices generated by protuberances, where the separation of the turbulent boundary layer dominated within the stall region and the rather strong attachment of the laminar boundary layer still existed within the post-stall region. The characteristics to manipulate the flow separation mode of the original airfoil indicated the possibility to further optimize the control performance by reasonably designing the layout of the protuberances.

Public-Private Partnerships in Lead Discovery: Overview and Case Studies.

PubMed

Gottwald, Matthias; Becker, Andreas; Bahr, Inke; Mueller-Fahrnow, Anke

2016-09-01

The pharmaceutical industry is faced with significant challenges in its efforts to discover new drugs that address unmet medical needs. Safety concerns and lack of efficacy are the two main technical reasons for attrition. Improved early research tools including predictive in silico, in vitro, and in vivo models, as well as a deeper understanding of the disease biology, therefore have the potential to improve success rates. The combination of internal activities with external collaborations in line with the interests and needs of all partners is a successful approach to foster innovation and to meet the challenges. Collaboration can take place in different ways, depending on the requirements of the participants. In this review, the value of public-private partnership approaches will be discussed, using examples from the Innovative Medicines Initiative (IMI). These examples describe consortia approaches to develop tools and processes for improving target identification and validation, as well as lead identification and optimization. The project "Kinetics for Drug Discovery" (K4DD), focusing on the adoption of drug-target binding kinetics analysis in the drug discovery decision-making process, is described in more detail. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Adaptive feature selection using v-shaped binary particle swarm optimization.

PubMed

Teng, Xuyang; Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers.

Adaptive feature selection using v-shaped binary particle swarm optimization

PubMed Central

Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers. PMID:28358850

A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters

PubMed Central

Wang, Zhihao; Yi, Jing

2016-01-01

For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result. PMID:28042291

Global Parameter Optimization of CLM4.5 Using Sparse-Grid Based Surrogates

NASA Astrophysics Data System (ADS)

Lu, D.; Ricciuto, D. M.; Gu, L.

2016-12-01

Calibration of the Community Land Model (CLM) is challenging because of its model complexity, large parameter sets, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time. The goal of this study is to calibrate some of the CLM parameters in order to improve model projection of carbon fluxes. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first use advanced sparse grid (SG) interpolation to construct a surrogate system of the actual CLM model, and then we calibrate the surrogate model in the optimization process. As the surrogate model is a polynomial whose evaluation is fast, it can be efficiently evaluated with sufficiently large number of times in the optimization, which facilitates the global search. We calibrate five parameters against 12 months of GPP, NEP, and TLAI data from the U.S. Missouri Ozark (US-MOz) tower. The results indicate that an accurate surrogate model can be created for the CLM4.5 with a relatively small number of SG points (i.e., CLM4.5 simulations), and the application of the optimized parameters leads to a higher predictive capacity than the default parameter values in the CLM4.5 for the US-MOz site.

Progress in navigation filter estimate fusion and its application to spacecraft rendezvous

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

1994-01-01

A new derivation of an algorithm which fuses the outputs of two Kalman filters is presented within the context of previous research in this field. Unlike other works, this derivation clearly shows the combination of estimates to be optimal, minimizing the trace of the fused covariance matrix. The algorithm assumes that the filters use identical models, and are stable and operating optimally with respect to their own local measurements. Evidence is presented which indicates that the error ellipsoid derived from the covariance of the optimally fused estimate is contained within the intersections of the error ellipsoids of the two filters being fused. Modifications which reduce the algorithm's data transmission requirements are also presented, including a scalar gain approximation, a cross-covariance update formula which employs only the two contributing filters' autocovariances, and a form of the algorithm which can be used to reinitialize the two Kalman filters. A sufficient condition for using the optimally fused estimates to periodically reinitialize the Kalman filters in this fashion is presented and proved as a theorem. When these results are applied to an optimal spacecraft rendezvous problem, simulated performance results indicate that the use of optimally fused data leads to significantly improved robustness to initial target vehicle state errors. The following applications of estimate fusion methods to spacecraft rendezvous are also described: state vector differencing, and redundancy management.

Formulation of a parametric systems design framework for disaster response planning

NASA Astrophysics Data System (ADS)

Mma, Stephanie Weiya

The occurrence of devastating natural disasters in the past several years have prompted communities, responding organizations, and governments to seek ways to improve disaster preparedness capabilities locally, regionally, nationally, and internationally. A holistic approach to design used in the aerospace and industrial engineering fields enables efficient allocation of resources through applied parametric changes within a particular design to improve performance metrics to selected standards. In this research, this methodology is applied to disaster preparedness, using a community's time to restoration after a disaster as the response metric. A review of the responses from Hurricane Katrina and the 2010 Haiti earthquake, among other prominent disasters, provides observations leading to some current capability benchmarking. A need for holistic assessment and planning exists for communities but the current response planning infrastructure lacks a standardized framework and standardized assessment metrics. Within the humanitarian logistics community, several different metrics exist, enabling quantification and measurement of a particular area's vulnerability. These metrics, combined with design and planning methodologies from related fields, such as engineering product design, military response planning, and business process redesign, provide insight and a framework from which to begin developing a methodology to enable holistic disaster response planning. The developed methodology was applied to the communities of Shelby County, TN and pre-Hurricane-Katrina Orleans Parish, LA. Available literature and reliable media sources provide information about the different values of system parameters within the decomposition of the community aspects and also about relationships among the parameters. The community was modeled as a system dynamics model and was tested in the implementation of two, five, and ten year improvement plans for Preparedness, Response, and Development capabilities, and combinations of these capabilities. For Shelby County and for Orleans Parish, the Response improvement plan reduced restoration time the most. For the combined capabilities, Shelby County experienced the greatest reduction in restoration time with the implementation of Development and Response capability improvements, and for Orleans Parish it was the Preparedness and Response capability improvements. Optimization of restoration time with community parameters was tested by using a Particle Swarm Optimization algorithm. Fifty different optimized restoration times were generated using the Particle Swarm Optimization algorithm and ranked using the Technique for Order Preference by Similarity to Ideal Solution. The optimization results indicate that the greatest reduction in restoration time for a community is achieved with a particular combination of different parameter values instead of the maximization of each parameter.

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

PubMed

Celik, Yuksel; Ulker, Erkan

2013-01-01

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

Efficiency Improvements to the Displacement Based Multilevel Structural Optimization Algorithm

NASA Technical Reports Server (NTRS)

Plunkett, C. L.; Striz, A. G.; Sobieszczanski-Sobieski, J.

2001-01-01

Multilevel Structural Optimization (MSO) continues to be an area of research interest in engineering optimization. In the present project, the weight optimization of beams and trusses using Displacement based Multilevel Structural Optimization (DMSO), a member of the MSO set of methodologies, is investigated. In the DMSO approach, the optimization task is subdivided into a single system and multiple subsystems level optimizations. The system level optimization minimizes the load unbalance resulting from the use of displacement functions to approximate the structural displacements. The function coefficients are then the design variables. Alternately, the system level optimization can be solved using the displacements themselves as design variables, as was shown in previous research. Both approaches ensure that the calculated loads match the applied loads. In the subsystems level, the weight of the structure is minimized using the element dimensions as design variables. The approach is expected to be very efficient for large structures, since parallel computing can be utilized in the different levels of the problem. In this paper, the method is applied to a one-dimensional beam and a large three-dimensional truss. The beam was tested to study possible simplifications to the system level optimization. In previous research, polynomials were used to approximate the global nodal displacements. The number of coefficients of the polynomials equally matched the number of degrees of freedom of the problem. Here it was desired to see if it is possible to only match a subset of the degrees of freedom in the system level. This would lead to a simplification of the system level, with a resulting increase in overall efficiency. However, the methods tested for this type of system level simplification did not yield positive results. The large truss was utilized to test further improvements in the efficiency of DMSO. In previous work, parallel processing was applied to the subsystems level, where the derivative verification feature of the optimizer NPSOL had been utilized in the optimizations. This resulted in large runtimes. In this paper, the optimizations were repeated without using the derivative verification, and the results are compared to those from the previous work. Also, the optimizations were run on both, a network of SUN workstations using the MPICH implementation of the Message Passing Interface (MPI) and on the faster Beowulf cluster at ICASE, NASA Langley Research Center, using the LAM implementation of UP]. The results on both systems were consistent and showed that it is not necessary to verify the derivatives and that this gives a large increase in efficiency of the DMSO algorithm.

A New Method for Setting Calculation Sequence of Directional Relay Protection in Multi-Loop Networks

NASA Astrophysics Data System (ADS)

Haijun, Xiong; Qi, Zhang

2016-08-01

Workload of relay protection setting calculation in multi-loop networks may be reduced effectively by optimization setting calculation sequences. A new method of setting calculation sequences of directional distance relay protection in multi-loop networks based on minimum broken nodes cost vector (MBNCV) was proposed to solve the problem experienced in current methods. Existing methods based on minimum breakpoint set (MBPS) lead to more break edges when untying the loops in dependent relationships of relays leading to possibly more iterative calculation workloads in setting calculations. A model driven approach based on behavior trees (BT) was presented to improve adaptability of similar problems. After extending the BT model by adding real-time system characters, timed BT was derived and the dependency relationship in multi-loop networks was then modeled. The model was translated into communication sequence process (CSP) models and an optimization setting calculation sequence in multi-loop networks was finally calculated by tools. A 5-nodes multi-loop network was applied as an example to demonstrate effectiveness of the modeling and calculation method. Several examples were then calculated with results indicating the method effectively reduces the number of forced broken edges for protection setting calculation in multi-loop networks.

Strategic targeting of advance care planning interventions: the Goldilocks phenomenon.

PubMed

Billings, J Andrew; Bernacki, Rachelle

2014-04-01

Strategically selecting patients for discussions and documentation about limiting life-sustaining treatments-choosing the right time along the end-of-life trajectory for such an intervention and identifying patients at high risk of facing end-of-life decisions-can have a profound impact on the value of advance care planning (ACP) efforts. Timing is important because the completion of an advance directive (AD) too far from or too close to the time of death can lead to end-of-life decisions that do not optimally reflect the patient's values, goals, and preferences: a poorly chosen target patient population that is unlikely to need an AD in the near future may lead to patients making unrealistic, hypothetical choices, while assessing preferences in the emergency department or hospital in the face of a calamity is notoriously inadequate. Because much of the currently studied ACP efforts have led to a disappointingly small proportion of patients eventually benefitting from an AD, careful targeting of the intervention should also improve the efficacy of such projects. A key to optimal timing and strategic selection of target patients for an ACP program is prognostication, and we briefly highlight prognostication tools and studies that may point us toward high-value AD interventions.

Fusion of magnetometer and gradiometer sensors of MEG in the presence of multiplicative error.

PubMed

Mohseni, Hamid R; Woolrich, Mark W; Kringelbach, Morten L; Luckhoo, Henry; Smith, Penny Probert; Aziz, Tipu Z

2012-07-01

Novel neuroimaging techniques have provided unprecedented information on the structure and function of the living human brain. Multimodal fusion of data from different sensors promises to radically improve this understanding, yet optimal methods have not been developed. Here, we demonstrate a novel method for combining multichannel signals. We show how this method can be used to fuse signals from the magnetometer and gradiometer sensors used in magnetoencephalography (MEG), and through extensive experiments using simulation, head phantom and real MEG data, show that it is both robust and accurate. This new approach works by assuming that the lead fields have multiplicative error. The criterion to estimate the error is given within a spatial filter framework such that the estimated power is minimized in the worst case scenario. The method is compared to, and found better than, existing approaches. The closed-form solution and the conditions under which the multiplicative error can be optimally estimated are provided. This novel approach can also be employed for multimodal fusion of other multichannel signals such as MEG and EEG. Although the multiplicative error is estimated based on beamforming, other methods for source analysis can equally be used after the lead-field modification.

Research on the Relationship between Water Diversion and Water Quality of Xuanwu Lake, China.

PubMed

Song, Weiwei; Xu, Qing; Fu, Xingqian; Zhang, Peng; Pang, Yong; Song, Dahao

2018-06-14

Water diversion is often used to improve water quality to reach the standard of China in the short term. However, this large amount of water diversion can not only improve the water quality, but also lead to a decline in the water quality (total phosphorus, total nitrogen) of Xuanwu Lake. Through theoretical analysis, the relationship between water quality and water diversion is established. We also found that the multiplication of the pollutant degradation coefficient ( K ) and the water residence time ( T ) is a constant ( N ), K⋅T=N. The water quality changed better at first, with the increase of inflow discharge, and then became worse, and the optimal water quality inflow discharge is 180,000 m³/day. By constructing two-dimensional hydrodynamic and water quality models, the optimal diversion water plan is calculated. Through model calculations, it can be seen that reducing the inflow discharge makes the water residence time longer (15.3 days changed to 23.8 days). Thereby, increasing the degradation of pollutants, and thus improving water quality. Compared with other wind directions, the southwest wind makes the water quality of Xuanwu Lake the most uniform. The concentration of water quality first became smaller and then became larger, as the wind speed increased, and eventually became constant. Implementing these results for water quality improvement in small and medium lakes will significantly reduce the cost of water diversion.

Improving Simulations of Fine Dust Surface Concentrations over the Western United States by Optimizing the Particle Size Distribution

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

Zhang, Li; Kok, Jasper F.; Henze, Daven

2013-06-28

To improve estimates of remote contributions of dust to fine particulate matter (PM2.5) in the western United States, new dust particle size distributions (PSDs) based upon scale-invariant fragmentation theory (Kok_PSD) with constraints from in situ measurements (IMP_PSD) are implemented in a chemical transport model (GEOS-Chem). Compared to initial simulations, this leads to reductions in the mass of emitted dust particles with radii <1.8 mm by 40%-60%. Consequently, the root-mean-square error in simulated fine dust concentrations compared to springtime surface observations in the western United States is reduced by 67%-81%. The ratio of simulated fine to coarse PM mass is alsomore » improved, which is not achievable by reductions in total dust emissions. The IMP_PSD best represents the PSD of dust transported from remote sources and reduces modeled PM2.5 concentrations up to 5 mg/m3 over the western United States, which is important when considering sources contributing to nonattainment of air quality standards. Citation: Zhang, L., J. F. Kok, D. K. Henze, Q. Li, and C. Zhao (2013), Improving simulations of fine dust surface concentrations over the western United States by optimizing the particle size distribution, Geophys. Res. Lett., 40, 3270-3275, doi:10.1002/grl.50591.« less

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

PubMed

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Double lead spiral platen parallel jaw end effector

NASA Technical Reports Server (NTRS)

Beals, David C.

1989-01-01

The double lead spiral platen parallel jaw end effector is an extremely powerful, compact, and highly controllable end effector that represents a significant improvement in gripping force and efficiency over the LaRC Puma (LP) end effector. The spiral end effector is very simple in its design and has relatively few parts. The jaw openings are highly predictable and linear, making it an ideal candidate for remote control. The finger speed is within acceptable working limits and can be modified to meet the user needs; for instance, greater finger speed could be obtained by increasing the pitch of the spiral. The force relaxation is comparable to the other tested units. Optimization of the end effector design would involve a compromise of force and speed for a given application.

Seebeck and figure of merit enhancement in nanostructured antimony telluride by antisite defect suppression through sulfur doping.

PubMed

Mehta, Rutvik J; Zhang, Yanliang; Zhu, Hong; Parker, David S; Belley, Matthew; Singh, David J; Ramprasad, Ramamurthy; Borca-Tasciuc, Theodorian; Ramanath, Ganpati

2012-09-12

Antimony telluride has a low thermoelectric figure of merit (ZT < ∼0.3) because of a low Seebeck coefficient α arising from high degenerate hole concentrations generated by antimony antisite defects. Here, we mitigate this key problem by suppressing antisite defect formation using subatomic percent sulfur doping. The resultant 10-25% higher α in bulk nanocrystalline antimony telluride leads to ZT ∼ 0.95 at 423 K, which is superior to the best non-nanostructured antimony telluride alloys. Density functional theory calculations indicate that sulfur increases the antisite formation activation energy and presage further improvements leading to ZT ∼ 2 through optimized doping. Our findings are promising for designing novel thermoelectric materials for refrigeration, waste heat recovery, and solar thermal applications.

ABLE project: Development of an advanced lead-acid storage system for autonomous PV installations

NASA Astrophysics Data System (ADS)

Lemaire-Potteau, Elisabeth; Vallvé, Xavier; Pavlov, Detchko; Papazov, G.; Borg, Nico Van der; Sarrau, Jean-François

In the advanced battery for low-cost renewable energy (ABLE) project, the partners have developed an advanced storage system for small and medium-size PV systems. It is composed of an innovative valve-regulated lead-acid (VRLA) battery, optimised for reliability and manufacturing cost, and an integrated regulator, for optimal battery management and anti-fraudulent use. The ABLE battery performances are comparable to flooded tubular batteries, which are the reference in medium-size PV systems. The ABLE regulator has several innovative features regarding energy management and modular series/parallel association. The storage system has been validated by indoor, outdoor and field tests, and it is expected that this concept could be a major improvement for large-scale implementation of PV within the framework of national rural electrification schemes.

Spectral gap optimization of order parameters for sampling complex molecular systems

PubMed Central

Tiwary, Pratyush; Berne, B. J.

2016-01-01

In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs. PMID:26929365

Multi-parameter geometrical scaledown study for energy optimization of MTJ and related spintronics nanodevices

NASA Astrophysics Data System (ADS)

Farhat, I. A. H.; Alpha, C.; Gale, E.; Atia, D. Y.; Stein, A.; Isakovic, A. F.

The scaledown of magnetic tunnel junctions (MTJ) and related nanoscale spintronics devices poses unique challenges for energy optimization of their performance. We demonstrate the dependence of the switching current on the scaledown variable, while considering the influence of geometric parameters of MTJ, such as the free layer thickness, tfree, lateral size of the MTJ, w, and the anisotropy parameter of the MTJ. At the same time, we point out which values of the saturation magnetization, Ms, and anisotropy field, Hk, can lead to lowering the switching current and overall decrease of the energy needed to operate an MTJ. It is demonstrated that scaledown via decreasing the lateral size of the MTJ, while allowing some other parameters to be unconstrained, can improve energy performance by a measurable factor, shown to be the function of both geometric and physical parameters above. Given the complex interdependencies among both families of parameters, we developed a particle swarm optimization (PSO) algorithm that can simultaneously lower energy of operation and the switching current density. Results we obtained in scaledown study and via PSO optimization are compared to experimental results. Support by Mubadala-SRC 2012-VJ-2335 is acknowledged, as are staff at Cornell-CNF and BNL-CFN.

Multi-objective/loading optimization for rotating composite flexbeams

NASA Technical Reports Server (NTRS)

Hamilton, Brian K.; Peters, James R.

1989-01-01

With the evolution of advanced composites, the feasibility of designing bearingless rotor systems for high speed, demanding maneuver envelopes, and high aircraft gross weights has become a reality. These systems eliminate the need for hinges and heavily loaded bearings by incorporating a composite flexbeam structure which accommodates flapping, lead-lag, and feathering motions by bending and twisting while reacting full blade centrifugal force. The flight characteristics of a bearingless rotor system are largely dependent on hub design, and the principal element in this type of system is the composite flexbeam. As in any hub design, trade off studies must be performed in order to optimize performance, dynamics (stability), handling qualities, and stresses. However, since the flexbeam structure is the primary component which will determine the balance of these characteristics, its design and fabrication are not straightforward. It was concluded that: pitchcase and snubber damper representations are required in the flexbeam model for proper sizing resulting from dynamic requirements; optimization is necessary for flexbeam design, since it reduces the design iteration time and results in an improved design; and inclusion of multiple flight conditions and their corresponding fatigue allowables is necessary for the optimization procedure.

History matching through dynamic decision-making

PubMed Central

Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson

2017-01-01

History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413

Identification of the optimal spectral region for plasmonic and nanoplasmonic sensing.

PubMed

Otte, Marinus A; Sepúlveda, Borja; Ni, Weihai; Juste, Jorge Pérez; Liz-Marzán, Luis M; Lechuga, Laura M

2010-01-26

We present a theoretical and experimental study involving the sensing characteristics of wavelength-interrogated plasmonic sensors based on surface plasmon polaritons (SPP) in planar gold films and on localized surface plasmon resonances (LSPR) of single gold nanorods. The tunability of both sensing platforms allowed us to analyze their bulk and surface sensing characteristics as a function of the plasmon resonance position. We demonstrate that a general figure of merit (FOM), which is equivalent in wavelength and energy scales, can be employed to mutually compare both sensing schemes. Most interestingly, this FOM has revealed a spectral region for which the surface sensitivity performance of both sensor types is optimized, which we attribute to the intrinsic dielectric properties of plasmonic materials. Additionally, in good agreement with theoretical predictions, we experimentally demonstrate that, although the SPP sensor offers a much better bulk sensitivity, the LSPR sensor shows an approximately 15% better performance for surface sensitivity measurements when its FOM is optimized. However, optimization of the substrate refractive index and the accessibility of the relevant molecules to the nanoparticles can lead to a total 3-fold improvement of the FOM in LSPR sensors.

A study of leading indicators for occupational health and safety management systems in healthcare.

PubMed

Almost, Joan M; VanDenKerkhof, Elizabeth G; Strahlendorf, Peter; Caicco Tett, Louise; Noonan, Joanna; Hayes, Thomas; Van Hulle, Henrietta; Adam, Ryan; Holden, Jeremy; Kent-Hillis, Tracy; McDonald, Mike; Paré, Geneviève C; Lachhar, Karanjit; Silva E Silva, Vanessa

2018-04-23

In Ontario, Canada, approximately $2.5 billion is spent yearly on occupational injuries in the healthcare sector. The healthcare sector has been ranked second highest for lost-time injury rates among 16 Ontario sectors since 2009 with female healthcare workers ranked the highest among all occupations for lost-time claims. There is a great deal of focus in Ontario's occupational health and safety system on compliance and fines, however despite this increased focus, the injury statistics are not significantly improving. One of the keys to changing this trend is the development of a culture of healthy and safe workplaces including the effective utilization of leading indicators within Occupational Health and Safety Management Systems (OHSMSs). In contrast to lagging indicators, which focus on outcomes retrospectively, a leading indicator is associated with proactive activities and consists of selected OHSMSs program elements. Using leading indicators to measure health and safety has been common practice in high-risk industries; however, this shift has not occurred in healthcare. The aim of this project is to conduct a longitudinal study implementing six elements of the Ontario Safety Association for Community and Healthcare (OSACH) system identified as leading indicators and evaluating the effectiveness of this intervention on improving selected health and safety workplace indicators. A quasi-experimental longitudinal research design will be used within two Ontario acute care hospitals. The first phase of the study will focus on assessing current OHSMSs using the leading indicators, determining potential facilitators and barriers to changing current OHSMSs, and identifying the leading indicators that could be added or changed to the existing OHSMS in place. Phase I will conclude with the development of an intervention designed to support optimizing current OHSMSs in participating hospitals based on identified gaps. Phase II will pilot test and evaluate the tailored intervention. By implementing specific elements to test leading indicators, this project will examine a novel approach to strengthening the occupational health and safety system. Results will guide healthcare organizations in setting priorities for their OHSMSs and thereby improve health and safety outcomes.

Mandala Networks: ultra-small-world and highly sparse graphs

PubMed Central

Sampaio Filho, Cesar I. N.; Moreira, André A.; Andrade, Roberto F. S.; Herrmann, Hans J.; Andrade, José S.

2015-01-01

The increasing demands in security and reliability of infrastructures call for the optimal design of their embedded complex networks topologies. The following question then arises: what is the optimal layout to fulfill best all the demands? Here we present a general solution for this problem with scale-free networks, like the Internet and airline networks. Precisely, we disclose a way to systematically construct networks which are robust against random failures. Furthermore, as the size of the network increases, its shortest path becomes asymptotically invariant and the density of links goes to zero, making it ultra-small world and highly sparse, respectively. The first property is ideal for communication and navigation purposes, while the second is interesting economically. Finally, we show that some simple changes on the original network formulation can lead to an improved topology against malicious attacks. PMID:25765450

Developing an Efficient and General Strategy for Immobilization of Small Molecules onto Microarrays Using Isocyanate Chemistry.

PubMed

Zhu, Chenggang; Zhu, Xiangdong; Landry, James P; Cui, Zhaomeng; Li, Quanfu; Dang, Yongjun; Mi, Lan; Zheng, Fengyun; Fei, Yiyan

2016-03-16

Small-molecule microarray (SMM) is an effective platform for identifying lead compounds from large collections of small molecules in drug discovery, and efficient immobilization of molecular compounds is a pre-requisite for the success of such a platform. On an isocyanate functionalized surface, we studied the dependence of immobilization efficiency on chemical residues on molecular compounds, terminal residues on isocyanate functionalized surface, lengths of spacer molecules, and post-printing treatment conditions, and we identified a set of optimized conditions that enable us to immobilize small molecules with significantly improved efficiencies, particularly for those molecules with carboxylic acid residues that are known to have low isocyanate reactivity. We fabricated microarrays of 3375 bioactive compounds on isocyanate functionalized glass slides under these optimized conditions and confirmed that immobilization percentage is over 73%.

Magnetic hyperthermia performance of magnetite nanoparticle assemblies under different driving fields

NASA Astrophysics Data System (ADS)

Wu, Kai; Wang, Jian-Ping

2017-05-01

The heating performance of magnetic nanoparticles (MNPs) under an alternating magnetic field (AMF) is dependent on several factors. Optimizing these factors improves the heating efficiency for cancer therapy and meanwhile lowers the MNP treatment dosage. AMF is one of the most easily controllable variables to enhance the efficiency of heat generation. This paper investigated the optimal magnetic field strength and frequency for an assembly of magnetite nanoparticles. For hyperthermia treatment in clinical applications, monodispersed NPs are forming nanoclusters in target regions where a strong magnetically interactive environment is anticipated, which leads to a completely different situation than MNPs in ferrofluids. Herein, the energy barrier model is revisited and Néel relaxation time is tailored for high MNP packing densities. AMF strength and frequency are customized for different magnetite NPs to achieve the highest power generation and the best hyperthermia performance.

MDTM: Optimizing Data Transfer using Multicore-Aware I/O Scheduling

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

Zhang, Liang; Demar, Phil; Wu, Wenji

2017-05-09

Bulk data transfer is facing significant challenges in the coming era of big data. There are multiple performance bottlenecks along the end-to-end path from the source to destination storage system. The limitations of current generation data transfer tools themselves can have a significant impact on end-to-end data transfer rates. In this paper, we identify the issues that lead to underperformance of these tools, and present a new data transfer tool with an innovative I/O scheduler called MDTM. The MDTM scheduler exploits underlying multicore layouts to optimize throughput by reducing delay and contention for I/O reading and writing operations. With ourmore » evaluations, we show how MDTM successfully avoids NUMA-based congestion and significantly improves end-to-end data transfer rates across high-speed wide area networks.« less

MDTM: Optimizing Data Transfer using Multicore-Aware I/O Scheduling

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

Zhang, Liang; Demar, Phil; Wu, Wenji

2017-01-01

Bulk data transfer is facing significant challenges in the coming era of big data. There are multiple performance bottlenecks along the end-to-end path from the source to destination storage system. The limitations of current generation data transfer tools themselves can have a significant impact on end-to-end data transfer rates. In this paper, we identify the issues that lead to underperformance of these tools, and present a new data transfer tool with an innovative I/O scheduler called MDTM. The MDTM scheduler exploits underlying multicore layouts to optimize throughput by reducing delay and contention for I/O reading and writing operations. With ourmore » evaluations, we show how MDTM successfully avoids NUMA-based congestion and significantly improves end-to-end data transfer rates across high-speed wide area networks.« less

Technology Readiness of Early Career Nurse Trainees: Utilization of the Technology Readiness Index (TRI).

PubMed

Odlum, Michelle

2016-01-01

Health Information Technology (HIT) adoption by clinicians, including nurses, will lead to reduction in healthcare costs and clinical errors and improve health outcomes. Understanding the importance of technology adoption, the current study utilized the Technology Readiness Index to explore technology perceptions of nursing students. Our analysis identifies factors that may influence perceptions of technology, including decreased optimism for students with clinical experience and increased discomfort of US born students. Our study provides insight to inform training programs to further meet the increasing demands of skilled nursing staff.

Financial advantages. Preventative measures ensure the health of your accounts receivable.

PubMed

Duda, Michelle

2009-11-01

Running a dental practice is no small task; from staying on the leading edge of new medical developments and products, to monitoring ever-changing dental insurance plans, to simply overseeing the fundamental day-to-day operations. But there is one area of your practice that can be streamlined to significantly improve your cash flow, minimize delinquencies and optimize fiscal operations. Your accounts receivable and collections can be economically and efficiently managed by a savvy combination of internal efforts and the partnership of a third party resource.

A temporal-spatial postprocessing model for probabilistic run-off forecast. With a case study from Ulla-Førre with five catchments and ten lead times

NASA Astrophysics Data System (ADS)

Engeland, K.; Steinsland, I.

2012-04-01

This work is driven by the needs of next generation short term optimization methodology for hydro power production. Stochastic optimization are about to be introduced; i.e. optimizing when available resources (water) and utility (prices) are uncertain. In this paper we focus on the available resources, i.e. water, where uncertainty mainly comes from uncertainty in future runoff. When optimizing a water system all catchments and several lead times have to be considered simultaneously. Depending on the system of hydropower reservoirs, it might be a set of headwater catchments, a system of upstream /downstream reservoirs where water used from one catchment /dam arrives in a lower catchment maybe days later, or a combination of both. The aim of this paper is therefore to construct a simultaneous probabilistic forecast for several catchments and lead times, i.e. to provide a predictive distribution for the forecasts. Stochastic optimization methods need samples/ensembles of run-off forecasts as input. Hence, it should also be possible to sample from our probabilistic forecast. A post-processing approach is taken, and an error model based on Box- Cox transformation, power transform and a temporal-spatial copula model is used. It accounts for both between catchment and between lead time dependencies. In operational use it is strait forward to sample run-off ensembles from this models that inherits the catchment and lead time dependencies. The methodology is tested and demonstrated in the Ulla-Førre river system, and simultaneous probabilistic forecasts for five catchments and ten lead times are constructed. The methodology has enough flexibility to model operationally important features in this case study such as hetroscadasety, lead-time varying temporal dependency and lead-time varying inter-catchment dependency. Our model is evaluated using CRPS for marginal predictive distributions and energy score for joint predictive distribution. It is tested against deterministic run-off forecast, climatology forecast and a persistent forecast, and is found to be the better probabilistic forecast for lead time grater then two. From an operational point of view the results are interesting as the between catchment dependency gets stronger with longer lead-times.

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

PubMed

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

2011-01-13

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

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

PubMed Central

2010-01-01

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

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

PubMed

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

2016-10-21

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

Outsourcing lead optimization: the eye of the storm.

PubMed

Clark, David E

2011-02-01

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

Design of the DIRECT-project: interventions to increase job resources and recovery opportunities to improve job-related health, well-being, and performance outcomes in nursing homes.

PubMed

Spoor, Ellen; de Jonge, Jan; Hamers, Jan P H

2010-05-28

Because of high demands at work, nurses are at high risk for occupational burnout and physical complaints. The presence of job resources (such as job autonomy or social support) and recovery opportunities could counteract the adverse effect of high job demands. However, it is still unclear how job resources and recovery opportunities can be translated into effective workplace interventions aiming to improve employee health, well-being, and performance-related outcomes. The aim of the current research project is developing and implementing interventions to optimize job resources and recovery opportunities, which may lead to improved health, well-being and performance of nurses. The DIRECT-project (DIsc Risk Evaluating Controlled Trial) is a longitudinal, quasi-experimental field study. Nursing home staff of 4 intervention wards and 4 comparison wards will be involved. Based on the results of a base-line survey, interventions will be implemented to optimize job resources and recovery opportunities. After 12 and 24 month the effect of the interventions will be investigated with follow-up surveys. Additionally, a process evaluation will be conducted to map factors that either stimulated or hindered successful implementation as well as the effectiveness of the interventions. The DIRECT-project fulfils a strong need for intervention research in the field of work, stress, performance, and health. The results could reveal (1) how interventions can be tailored to optimize job resources and recovery opportunities, in order to counteract job demands, and (2) what the effects of these interventions will be on health, well-being, and performance of nursing staff.

Improving Simulated Annealing by Recasting it as a Non-Cooperative Game

NASA Technical Reports Server (NTRS)

Wolpert, David; Bandari, Esfandiar; Tumer, Kagan

2001-01-01

The game-theoretic field of COllective INtelligence (COIN) concerns the design of computer-based players engaged in a non-cooperative game so that as those players pursue their self-interests, a pre-specified global goal for the collective computational system is achieved "as a side-effect". Previous implementations of COIN algorithms have outperformed conventional techniques by up to several orders of magnitude, on domains ranging from telecommunications control to optimization in congestion problems. Recent mathematical developments have revealed that these previously developed game-theory-motivated algorithms were based on only two of the three factors determining performance. Consideration of only the third factor would instead lead to conventional optimization techniques like simulated annealing that have little to do with non-cooperative games. In this paper we present an algorithm based on all three terms at once. This algorithm can be viewed as a way to modify simulated annealing by recasting it as a non-cooperative game, with each variable replaced by a player. This recasting allows us to leverage the intelligent behavior of the individual players to substantially improve the exploration step of the simulated annealing. Experiments are presented demonstrating that this recasting improves simulated annealing by several orders of magnitude for spin glass relaxation and bin-packing.

Flow field design and optimization based on the mass transport polarization regulation in a flow-through type vanadium flow battery

NASA Astrophysics Data System (ADS)

Zheng, Qiong; Xing, Feng; Li, Xianfeng; Ning, Guiling; Zhang, Huamin

2016-08-01

Vanadium flow battery holds great promise for use in large scale energy storage applications. However, the power density is relatively low, leading to significant increase in the system cost. Apart from the kinetic and electronic conductivity improvement, the mass transport enhancement is also necessary to further increase the power density and reduce the system cost. To better understand the mass transport limitations, in the research, the space-varying and time-varying characteristic of the mass transport polarization is investigated based on the analysis of the flow velocity and reactant concentration in the bulk electrolyte by modeling. The result demonstrates that the varying characteristic of mass transport polarization is more obvious at high SoC or high current densities. To soften the adverse impact of the mass transport polarization, a new rectangular plug flow battery with a plug flow and short flow path is designed and optimized based on the mass transport polarization regulation (reducing the mass transport polarization and improving its uniformity of distribution). The regulation strategy of mass transport polarization is practical for the performance improvement in VFBs, especially for high power density VFBs. The findings in the research are also applicable for other flow batteries and instructive for practical use.

Experimental analysis of a mobile health system for mood disorders.

PubMed

Massey, Tammara; Marfia, Gustavo; Potkonjak, Miodrag; Sarrafzadeh, Majid

2010-03-01

Depression is one of the leading causes of disability. Methods are needed to quantitatively classify emotions in order to better understand and treat mood disorders. This research proposes techniques to improve communication in body sensor network (BSN) that gathers data on the affective states of the patient. These BSNs can continuously monitor, discretely quantify, and classify a patient's depressive states. In addition, data on the patient's lifestyle can be correlated with his/her physiological conditions to identify how various stimuli trigger symptoms. This continuous stream of data is an improvement over a snapshot of localized symptoms that a doctor often collects during a medical examination. Our research first quantifies how the body interferes with communication in a BSN and detects a pattern between the line of sight of an embedded device and its reception rate. Then, a mathematical model of the data using linear programming techniques determines the optimal placement and number of sensors in a BSN to improve communication. Experimental results show that the optimal placement of embedded devices can reduce power cost up to 27% and reduce hardware costs up to 47%. This research brings researchers a step closer to continuous, real-time systemic monitoring that will allow one to analyze the dynamic human physiology and understand, diagnosis, and treat mood disorders.

Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modelling

NASA Astrophysics Data System (ADS)

Reniers, Jorn M.; Mulder, Grietus; Ober-Blöbaum, Sina; Howey, David A.

2018-03-01

The increased deployment of intermittent renewable energy generators opens up opportunities for grid-connected energy storage. Batteries offer significant flexibility but are relatively expensive at present. Battery lifetime is a key factor in the business case, and it depends on usage, but most techno-economic analyses do not account for this. For the first time, this paper quantifies the annual benefits of grid-connected batteries including realistic physical dynamics and nonlinear electrochemical degradation. Three lithium-ion battery models of increasing realism are formulated, and the predicted degradation of each is compared with a large-scale experimental degradation data set (Mat4Bat). A respective improvement in RMS capacity prediction error from 11% to 5% is found by increasing the model accuracy. The three models are then used within an optimal control algorithm to perform price arbitrage over one year, including degradation. Results show that the revenue can be increased substantially while degradation can be reduced by using more realistic models. The estimated best case profit using a sophisticated model is a 175% improvement compared with the simplest model. This illustrates that using a simplistic battery model in a techno-economic assessment of grid-connected batteries might substantially underestimate the business case and lead to erroneous conclusions.

Adaptive control schemes for improving dynamic performance of efficiency-optimized induction motor drives.

PubMed

Kumar, Navneet; Raj Chelliah, Thanga; Srivastava, S P

2015-07-01

Model Based Control (MBC) is one of the energy optimal controllers used in vector-controlled Induction Motor (IM) for controlling the excitation of motor in accordance with torque and speed. MBC offers energy conservation especially at part-load operation, but it creates ripples in torque and speed during load transition, leading to poor dynamic performance of the drive. This study investigates the opportunity for improving dynamic performance of a three-phase IM operating with MBC and proposes three control schemes: (i) MBC with a low pass filter (ii) torque producing current (iqs) injection in the output of speed controller (iii) Variable Structure Speed Controller (VSSC). The pre and post operation of MBC during load transition is also analyzed. The dynamic performance of a 1-hp, three-phase squirrel-cage IM with mine-hoist load diagram is tested. Test results are provided for the conventional field-oriented (constant flux) control and MBC (adjustable excitation) with proposed schemes. The effectiveness of proposed schemes is also illustrated for parametric variations. The test results and subsequent analysis confer that the motor dynamics improves significantly with all three proposed schemes in terms of overshoot/undershoot peak amplitude of torque and DC link power in addition to energy saving during load transitions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Mg2+ improves biomass production from soybean wastewater using purple non-sulfur bacteria.

PubMed

Wu, Pan; Zhang, Guangming; Li, Jianzheng

2015-02-01

Soybean wastewater was used to generate biomass resource by use of purple non-sulfur bacteria (PNSB). This study investigated the enhancement of PNSB cell accumulation in wastewater by Mg2+ under the light-anaerobic condition. Results showed that with the optimal Mg2+ dosage of 10 mg/L, biomass production was improved by 70% to 3630 mg/L, and biomass yield also was improved by 60%. Chemical Oxygen Demand (COD) removal reached above 86% and hydraulic retention time was shortened from 96 to 72 hr. The mechanism analysis indicated that Mg2+ could promote the content of bacteriochlorophyll in photosynthesis because Mg2+ is the bacteriochlorophyll active center, and thus improved adenosine triphosphate (ATP) production. An increase of ATP production enhanced the conversion of organic matter in wastewater into PNSB cell materials (biomass yield) and COD removal, leading to more biomass production. With 10 mg/L Mg2+, bacteriochlorophyll content and ATP production were improved by 60% and 33% respectively. Copyright © 2014. Published by Elsevier B.V.

Translational Medicine Guide transforms drug development processes: the recent Merck experience.

PubMed

Dolgos, Hugues; Trusheim, Mark; Gross, Dietmar; Halle, Joern-Peter; Ogden, Janet; Osterwalder, Bruno; Sedman, Ewen; Rossetti, Luciano

2016-03-01

Merck is implementing a question-based Translational Medicine Guide (TxM Guide) beginning as early as lead optimization into its stage-gate drug development process. Initial experiences with the TxM Guide, which is embedded into an integrated development plan tailored to each development program, demonstrated opportunities to improve target understanding, dose setting (i.e., therapeutic index), and patient subpopulation selection with more robust and relevant early human-based evidence, and increased use of biomarkers and simulations. The TxM Guide is also helping improve organizational learning, costs, and governance. It has also shown the need for stronger external resources for validating biomarkers, demonstrating clinical utility, tracking natural disease history, and biobanking. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Optical filtering in directly modulated/detected OOFDM systems.

PubMed

Sánchez, C; Ortega, B; Wei, J L; Capmany, J

2013-12-16

This work presents a theoretical investigation on the performance of directly modulated/detected (DM/DD) optical orthogonal frequency division multiplexed (OOFDM) systems subject to optical filtering. The impact of both linear and nonlinear distortion effects are taken into account to calculate the effective signal-to-noise ratio of each subcarrier. These results are then employed to optimize the design parameters of two simple optical filtering structures: a Mach Zehnder interferometer and a uniform fiber Bragg grating, leading to a significant optical power budget improvement given by 3.3 and 3dB, respectively. These can be further increased to 5.5 and 4.2dB respectively when balanced detection configurations are employed. We find as well that this improvement is highly dependent on the clipping ratio.

Albendazole nanocrystals with improved pharmacokinetic performance in mice.

PubMed

Paredes, Alejandro J; Bruni, Sergio Sánchez; Allemandi, Daniel; Lanusse, Carlos; Palma, Santiago D

2018-02-01

Albendazole (ABZ) is a broad-spectrum antiparasitic agent with poor aqueous solubility, which leads to poor/erratic bioavailability and therapeutic failures. Here, we aimed to produce a novel formulation of ABZ nanocrystals (ABZNC) and assess its pharmacokinetic performance in mice. Results/methodology: ABZNC were prepared by high-pressure homogenization and spray-drying processes. Redispersion capacity and solid yield were measured in order to obtain an optimized product. The final particle size was 415.69±7.40 nm and the solid yield was 72.32%. The pharmacokinetic parameters obtained in a mice model for ABZNC were enhanced (p < 0.05) with respect to the control formulation. ABZNC with improved pharmacokinetic behavior were produced by a simple, inexpensive and potentially scalable methodology.

Improvement of real-time seismic magnitude estimation by combining seismic and geodetic instrumentation

NASA Astrophysics Data System (ADS)

Goldberg, D.; Bock, Y.; Melgar, D.

2017-12-01

Rapid seismic magnitude assessment is a top priority for earthquake and tsunami early warning systems. For the largest earthquakes, seismic instrumentation tends to underestimate the magnitude, leading to an insufficient early warning, particularly in the case of tsunami evacuation orders. GPS instrumentation provides more accurate magnitude estimations using near-field stations, but isn't sensitive enough to detect the first seismic wave arrivals, thereby limiting solution speed. By optimally combining collocated seismic and GPS instruments, we demonstrate improved solution speed of earthquake magnitude for the largest seismic events. We present a real-time implementation of magnitude-scaling relations that adapts to consider the length of the recording, reflecting the observed evolution of ground motion with time.

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

NASA Astrophysics Data System (ADS)

Zhang, Jian; Gan, Yang

2018-04-01

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

Optimization and high-throughput screening of antimicrobial peptides.

PubMed

Blondelle, Sylvie E; Lohner, Karl

2010-01-01

While a well-established process for lead compound discovery in for-profit companies, high-throughput screening is becoming more popular in basic and applied research settings in academia. The development of combinatorial libraries combined with easy and less expensive access to new technologies have greatly contributed to the implementation of high-throughput screening in academic laboratories. While such techniques were earlier applied to simple assays involving single targets or based on binding affinity, they have now been extended to more complex systems such as whole cell-based assays. In particular, the urgent need for new antimicrobial compounds that would overcome the rapid rise of drug-resistant microorganisms, where multiple target assays or cell-based assays are often required, has forced scientists to focus onto high-throughput technologies. Based on their existence in natural host defense systems and their different mode of action relative to commercial antibiotics, antimicrobial peptides represent a new hope in discovering novel antibiotics against multi-resistant bacteria. The ease of generating peptide libraries in different formats has allowed a rapid adaptation of high-throughput assays to the search for novel antimicrobial peptides. Similarly, the availability nowadays of high-quantity and high-quality antimicrobial peptide data has permitted the development of predictive algorithms to facilitate the optimization process. This review summarizes the various library formats that lead to de novo antimicrobial peptide sequences as well as the latest structural knowledge and optimization processes aimed at improving the peptides selectivity.

Development of Miniaturized Optimized Smart Sensors (MOSS) for space plasmas

NASA Technical Reports Server (NTRS)

Young, D. T.

1993-01-01

The cost of space plasma sensors is high for several reasons: (1) Most are one-of-a-kind and state-of-the-art, (2) the cost of launch to orbit is high, (3) ruggedness and reliability requirements lead to costly development and test programs, and (4) overhead is added by overly elaborate or generalized spacecraft interface requirements. Possible approaches to reducing costs include development of small 'sensors' (defined as including all necessary optics, detectors, and related electronics) that will ultimately lead to cheaper missions by reducing (2), improving (3), and, through work with spacecraft designers, reducing (4). Despite this logical approach, there is no guarantee that smaller sensors are necessarily either better or cheaper. We have previously advocated applying analytical 'quality factors' to plasma sensors (and spacecraft) and have begun to develop miniaturized particle optical systems by applying quantitative optimization criteria. We are currently designing a Miniaturized Optimized Smart Sensor (MOSS) in which miniaturized electronics (e.g., employing new power supply topology and extensive us of gate arrays and hybrid circuits) are fully integrated with newly developed particle optics to give significant savings in volume and mass. The goal of the SwRI MOSS program is development of a fully self-contained and functional plasma sensor weighing 1 lb and requiring 1 W. MOSS will require only a typical spacecraft DC power source (e.g., 30 V) and command/data interfaces in order to be fully functional, and will provide measurement capabilities comparable in most ways to current sensors.

A Variational Approach to Video Registration with Subspace Constraints.

PubMed

Garg, Ravi; Roussos, Anastasios; Agapito, Lourdes

2013-01-01

This paper addresses the problem of non-rigid video registration, or the computation of optical flow from a reference frame to each of the subsequent images in a sequence, when the camera views deformable objects. We exploit the high correlation between 2D trajectories of different points on the same non-rigid surface by assuming that the displacement of any point throughout the sequence can be expressed in a compact way as a linear combination of a low-rank motion basis. This subspace constraint effectively acts as a trajectory regularization term leading to temporally consistent optical flow. We formulate it as a robust soft constraint within a variational framework by penalizing flow fields that lie outside the low-rank manifold. The resulting energy functional can be decoupled into the optimization of the brightness constancy and spatial regularization terms, leading to an efficient optimization scheme. Additionally, we propose a novel optimization scheme for the case of vector valued images, based on the dualization of the data term. This allows us to extend our approach to deal with colour images which results in significant improvements on the registration results. Finally, we provide a new benchmark dataset, based on motion capture data of a flag waving in the wind, with dense ground truth optical flow for evaluation of multi-frame optical flow algorithms for non-rigid surfaces. Our experiments show that our proposed approach outperforms state of the art optical flow and dense non-rigid registration algorithms.

Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

NASA Astrophysics Data System (ADS)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

Optimal use of tandem biotin and V5 tags in ChIP assays

PubMed Central

Kolodziej, Katarzyna E; Pourfarzad, Farzin; de Boer, Ernie; Krpic, Sanja; Grosveld, Frank; Strouboulis, John

2009-01-01

Background Chromatin immunoprecipitation (ChIP) assays coupled to genome arrays (Chip-on-chip) or massive parallel sequencing (ChIP-seq) lead to the genome wide identification of binding sites of chromatin associated proteins. However, the highly variable quality of antibodies and the availability of epitopes in crosslinked chromatin can compromise genomic ChIP outcomes. Epitope tags have often been used as more reliable alternatives. In addition, we have employed protein in vivo biotinylation tagging as a very high affinity alternative to antibodies. In this paper we describe the optimization of biotinylation tagging for ChIP and its coupling to a known epitope tag in providing a reliable and efficient alternative to antibodies. Results Using the biotin tagged erythroid transcription factor GATA-1 as example, we describe several optimization steps for the application of the high affinity biotin streptavidin system in ChIP. We find that the omission of SDS during sonication, the use of fish skin gelatin as blocking agent and choice of streptavidin beads can lead to significantly improved ChIP enrichments and lower background compared to antibodies. We also show that the V5 epitope tag performs equally well under the conditions worked out for streptavidin ChIP and that it may suffer less from the effects of formaldehyde crosslinking. Conclusion The combined use of the very high affinity biotin tag with the less sensitive to crosslinking V5 tag provides for a flexible ChIP platform with potential implications in ChIP sequencing outcomes. PMID:19196479

Interlead distance and left ventricular lead electrical delay predict reverse remodeling during cardiac resynchronization therapy.

PubMed

Merchant, Faisal M; Heist, E Kevin; Nandigam, K Veena; Mulligan, Lawrence J; Blendea, Dan; Riedl, Lindsay; McCarty, David; Orencole, Mary; Picard, Michael H; Ruskin, Jeremy N; Singh, Jagmeet P

2010-05-01

Both anatomic interlead separation and left ventricle lead electrical delay (LVLED) have been associated with outcomes following cardiac resynchronization therapy (CRT). However, the relationship between interlead distance and electrical delay in predicting CRT outcomes has not been defined. We studied 61 consecutive patients undergoing CRT for standard clinical indications. All patients underwent intraprocedural measurement of LVLED. Interlead distances in the horizontal (HD), vertical (VD), and direct (DD) dimensions were measured from postprocedure chest radiographs (CXR). Remodeling indices [percent change in left ventricle (LV) ejection fraction, end-diastolic, end-systolic dimensions] were assessed by transthoracic echocardiogram. There was a positive correlation between corrected LVLED and HD on lateral CXR (r = 0.361, P = 0.004) and a negative correlation between LVLED and VD on posteroanterior (PA) CXR (r =-0.281, P = 0.028). To account for this inverse relationship, we developed a composite anatomic distance (defined as: lateral HD-PA VD), which correlated most closely with LVLED (r = 0.404, P = 0.001). Follow-up was available for 48 patients. At a mean of 4.1 +/- 3.2 months, patients with optimal values for both corrected LVLED (>or=75%) and composite anatomic distance (>or=15 cm) demonstrated greater reverse LV remodeling than patients with either one or neither of these optimized values. We identified a significant correlation between LV-right ventricular interlead distance and LVLED; additionally, both parameters act synergistically in predicting LV anatomic reverse remodeling. Efforts to optimize both interlead distance and electrical delay may improve CRT outcomes.

Optimality study of a gust alleviation system for light wing-loading STOL aircraft

NASA Technical Reports Server (NTRS)

Komoda, M.

1976-01-01

An analytical study was made of an optimal gust alleviation system that employs a vertical gust sensor mounted forward of an aircraft's center of gravity. Frequency domain optimization techniques were employed to synthesize the optimal filters that process the corrective signals to the flaps and elevator actuators. Special attention was given to evaluating the effectiveness of lead time, that is, the time by which relative wind sensor information should lead the actual encounter of the gust. The resulting filter is expressed as an implicit function of the prescribed control cost. A numerical example for a light wing loading STOL aircraft is included in which the optimal trade-off between performance and control cost is systematically studied.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Waste management as an effort to improve urban area cleanliness and community income (journal review)

NASA Astrophysics Data System (ADS)

Kinantan, Bag; Rahim Matondang, A.; Hidayati, Juliza

2018-02-01

The problem of urban waste has reached a point of concern. Population and economic growth are thought to be the cause of increasing the waste generation. The major problem related to this condition is the increasing of waste production which is not balance with the increase of its management capacity. Based on the Law Number 18 of 2008 that waste management starts from the source by applying the 3R approach (Reduction, Reuse, Recycle). This regulation provides a way which expect the waste management can be better, so that, the level of waste service can be improved and load on landfills (TPA) can be reduced.The cost of garbage collection and transport are 85% of the total waste management cost, so if this is optimized, it will optimize the system as a whole. Subsequent research focuses on how to optimize the garbage collection and transport sub-systems by finding the shortest route of transportation to the landfill by developing a Vehicle Routing Problem (VRP) model. The development of an urban area leads to the preparation of the best route is no longer an optimal solution. The complexity of the waste problem is not only related to the technical matters, but also the social and economic problems of the community. So, it is necessary to develop a model of waste management which does not only pay attention to the technical aspects, but also the social and economic. Waste is expected to be no longer a burden, but can also be utilized economically to increase community income.

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

PubMed Central

Celik, Yuksel; Ulker, Erkan

2013-01-01

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

Bringing High-Rate, CO2-Based Microbial Electrosynthesis Closer to Practical Implementation through Improved Electrode Design and Operating Conditions.

PubMed

Jourdin, Ludovic; Freguia, Stefano; Flexer, Victoria; Keller, Jurg

2016-02-16

The enhancement of microbial electrosynthesis (MES) of acetate from CO2 to performance levels that could potentially support practical implementations of the technology must go through the optimization of key design and operating conditions. We report that higher proton availability drastically increases the acetate production rate, with pH 5.2 found to be optimal, which will likely suppress methanogenic activity without inhibitor addition. Applied cathode potential as low as -1.1 V versus SHE still achieved 99% of electron recovery in the form of acetate at a current density of around -200 A m(-2). These current densities are leading to an exceptional acetate production rate of up to 1330 g m(-2) day(-1) at pH 6.7. Using highly open macroporous reticulated vitreous carbon electrodes with macropore sizes of about 0.6 mm in diameter was found to be optimal for achieving a good balance between total surface area available for biofilm formation and effective mass transfer between the bulk liquid and the electrode and biofilm surface. Furthermore, we also successfully demonstrated the use of a synthetic biogas mixture as carbon dioxide source, yielding similarly high MES performance as pure CO2. This would allow this process to be used effectively for both biogas quality improvement and conversion of the available CO2 to acetate.

Formulation optimization, characterization, and evaluation of in vitro cytotoxic potential of curcumin loaded solid lipid nanoparticles for improved anticancer activity.

PubMed

Rompicharla, Sri Vishnu Kiran; Bhatt, Himanshu; Shah, Aashma; Komanduri, Neeraja; Vijayasarathy, Dhanya; Ghosh, Balaram; Biswas, Swati

2017-11-01

The aim of the present research was to develop a novel, biocompatible, amenable to industrial scale up and affordable solid lipid nanoparticles (SLN) preparation of curcumin and evaluate the therapeutic efficacy in vitro using cancer cells. We have incorporated cholesterol as the lipid to prepare SLN along with the Poloxamer-188 as stabilizer. High shear homogenization was used to prepare the SLN and formulation was optimized using Quality by Design The optimized Chol CUR SLN exhibited a narrow size distribution with a particle size of 166.4±3.5nm. Percentage encapsulation (%EE) was found to be 76.9±1.9%. The SLN were further characterized by DSC, FTIR, XRD and drug release. In vitro cell studies in MDA-MB-231 (Human Breast cancer) cell line revealed that the Chol CUR SLN showed superior cytotoxicity and uptake in comparison to the free curcumin. Furthermore, Chol CUR SLN induced a significantly higher apoptosis compared to free CUR treatment. These results indicated that the curcumin encapsulated in Chol SLN was able to significantly improve the cytotoxic potential and induction of apoptosis in MDA-MB-231 cells. The promising result from our study could lead a further exploration of this nanoparticle formulation to be utilized clinically for cancer treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal control of the orientation and alignment of an asymmetric-top molecule with terahertz and laser pulses

NASA Astrophysics Data System (ADS)

Coudert, L. H.

2018-03-01

Quantum optimal control theory is applied to determine numerically the terahertz and nonresonant laser pulses leading, respectively, to the highest degree of orientation and alignment of the asymmetric-top H2S molecule. The optimized terahertz pulses retrieved for temperatures of zero and 50 K lead after 50 ps to an orientation with ⟨ΦZx⟩ = 0.959 73 and ⟨⟨ΦZx⟩⟩ = 0.742 30, respectively. For the zero temperature, the orientation is close to its maximum theoretical value; for the higher temperature, it is below the maximum theoretical value. The mechanism by which the terahertz pulse populates high lying rotational levels is elucidated. The 5 ps long optimized laser pulse calculated for a zero temperature leads to an alignment with ⟨ΦZy 2 ⟩ =0.944 16 and consists of several kick pulses with a duration of ≈0.1 ps. It is found that the timing of these kick pulses is such that it leads to an increase of the rotational energy of the molecule. The optimized laser pulse retrieved for a temperature of 20 K is 6 ps long and yields a lower alignment with ⟨⟨ΦZy 2 ⟩ ⟩ =0.717 20 .